research paper science education

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• Published: 10 March 2020

Research and trends in STEM education: a systematic review of journal publications

• Yeping Li 1 ,
• Ke Wang 2 ,
• Yu Xiao 1 &
• Jeffrey E. Froyd 3  

International Journal of STEM Education volume  7 , Article number:  11 ( 2020 ) Cite this article

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With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments in STEM education scholarship. We examined those selected journal publications both quantitatively and qualitatively, including the number of articles published, journals in which the articles were published, authorship nationality, and research topic and methods over the years. The results show that research in STEM education is increasing in importance internationally and that the identity of STEM education journals is becoming clearer over time.

Introduction

A recent review of 144 publications in the International Journal of STEM Education ( IJ - STEM ) showed how scholarship in science, technology, engineering, and mathematics (STEM) education developed between August 2014 and the end of 2018 through the lens of one journal (Li, Froyd, & Wang, 2019 ). The review of articles published in only one journal over a short period of time prompted the need to review the status and trends in STEM education research internationally by analyzing articles published in a wider range of journals over a longer period of time.

With global recognition of the growing importance of STEM education, we have witnessed the urgent need to support research and scholarship in STEM education (Li, 2014 , 2018a ). Researchers and educators have responded to this on-going call and published their scholarly work through many different publication outlets including journals, books, and conference proceedings. A simple Google search with the term “STEM,” “STEM education,” or “STEM education research” all returned more than 450,000,000 items. Such voluminous information shows the rapidly evolving and vibrant field of STEM education and sheds light on the volume of STEM education research. In any field, it is important to know and understand the status and trends in scholarship for the field to develop and be appropriately supported. This applies to STEM education.

Conducting systematic reviews to explore the status and trends in specific disciplines is common in educational research. For example, researchers surveyed the historical development of research in mathematics education (Kilpatrick, 1992 ) and studied patterns in technology usage in mathematics education (Bray & Tangney, 2017 ; Sokolowski, Li, & Willson, 2015 ). In science education, Tsai and his colleagues have conducted a sequence of reviews of journal articles to synthesize research trends in every 5 years since 1998 (i.e., 1998–2002, 2003–2007, 2008–2012, and 2013–2017), based on publications in three main science education journals including, Science Education , the International Journal of Science Education , and the Journal of Research in Science Teaching (e.g., Lin, Lin, Potvin, & Tsai, 2019 ; Tsai & Wen, 2005 ). Erduran, Ozdem, and Park ( 2015 ) reviewed argumentation in science education research from 1998 to 2014 and Minner, Levy, and Century ( 2010 ) reviewed inquiry-based science instruction between 1984 and 2002. There are also many literature reviews and syntheses in engineering and technology education (e.g., Borrego, Foster, & Froyd, 2015 ; Xu, Williams, Gu, & Zhang, 2019 ). All of these reviews have been well received in different fields of traditional disciplinary education as they critically appraise and summarize the state-of-art of relevant research in a field in general or with a specific focus. Both types of reviews have been conducted with different methods for identifying, collecting, and analyzing relevant publications, and they differ in terms of review aim and topic scope, time period, and ways of literature selection. In this review, we systematically analyze journal publications in STEM education research to overview STEM education scholarship development broadly and globally.

The complexity and ambiguity of examining the status and trends in STEM education research

A review of research development in a field is relatively straight forward, when the field is mature and its scope can be well defined. Unlike discipline-based education research (DBER, National Research Council, 2012 ), STEM education is not a well-defined field. Conducting a comprehensive literature review of STEM education research require careful thought and clearly specified scope to tackle the complexity naturally associated with STEM education. In the following sub-sections, we provide some further discussion.

Diverse perspectives about STEM and STEM education

STEM education as explicated by the term does not have a long history. The interest in helping students learn across STEM fields can be traced back to the 1990s when the US National Science Foundation (NSF) formally included engineering and technology with science and mathematics in undergraduate and K-12 school education (e.g., National Science Foundation, 1998 ). It coined the acronym SMET (science, mathematics, engineering, and technology) that was subsequently used by other agencies including the US Congress (e.g., United States Congress House Committee on Science, 1998 ). NSF also coined the acronym STEM to replace SMET (e.g., Christenson, 2011 ; Chute, 2009 ) and it has become the acronym of choice. However, a consensus has not been reached on the disciplines included within STEM.

To clarify its intent, NSF published a list of approved fields it considered under the umbrella of STEM (see http://bit.ly/2Bk1Yp5 ). The list not only includes disciplines widely considered under the STEM tent (called “core” disciplines, such as physics, chemistry, and materials research), but also includes disciplines in psychology and social sciences (e.g., political science, economics). However, NSF’s list of STEM fields is inconsistent with other federal agencies. Gonzalez and Kuenzi ( 2012 ) noted that at least two US agencies, the Department of Homeland Security and Immigration and Customs Enforcement, use a narrower definition that excludes social sciences. Researchers also view integration across different disciplines of STEM differently using various terms such as, multidisciplinary, interdisciplinary, and transdisciplinary (Vasquez, Sneider, & Comer, 2013 ). These are only two examples of the ambiguity and complexity in describing and specifying what constitutes STEM.

Multiple perspectives about the meaning of STEM education adds further complexity to determining the extent to which scholarly activity can be categorized as STEM education. For example, STEM education can be viewed with a broad and inclusive perspective to include education in the individual disciplines of STEM, i.e., science education, technology education, engineering education, and mathematics education, as well as interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (English, 2016 ; Li, 2014 ). On the other hand, STEM education can be viewed by others as referring only to interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (Honey, Pearson, & Schweingruber, 2014 ; Johnson, Peters-Burton, & Moore, 2015 ; Kelley & Knowles, 2016 ; Li, 2018a ). These multiple perspectives allow scholars to publish articles in a vast array and diverse journals, as long as journals are willing to take the position as connected with STEM education. At the same time, however, the situation presents considerable challenges for researchers intending to locate, identify, and classify publications as STEM education research. To tackle such challenges, we tried to find out what we can learn from prior reviews related to STEM education.

Guidance from prior reviews related to STEM education

A search for reviews of STEM education research found multiple reviews that could suggest approaches for identifying publications (e.g., Brown, 2012 ; Henderson, Beach, & Finkelstein, 2011 ; Kim, Sinatra, & Seyranian, 2018 ; Margot & Kettler, 2019 ; Minichiello, Hood, & Harkness, 2018 ; Mizell & Brown, 2016 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). The review conducted by Brown ( 2012 ) examined the research base of STEM education. He addressed the complexity and ambiguity by confining the review with publications in eight journals, two in each individual discipline, one academic research journal (e.g., the Journal of Research in Science Teaching ) and one practitioner journal (e.g., Science Teacher ). Journals were selected based on suggestions from some faculty members and K-12 teachers. Out of 1100 articles published in these eight journals from January 1, 2007, to October 1, 2010, Brown located 60 articles that authors self-identified as connected to STEM education. He found that the vast majority of these 60 articles focused on issues beyond an individual discipline and there was a research base forming for STEM education. In a follow-up study, Mizell and Brown ( 2016 ) reviewed articles published from January 2013 to October 2015 in the same eight journals plus two additional journals. Mizell and Brown used the same criteria to identify and include articles that authors self-identified as connected to STEM education, i.e., if the authors included STEM in the title or author-supplied keywords. In comparison to Brown’s findings, they found that many more STEM articles were published in a shorter time period and by scholars from many more different academic institutions. Taking together, both Brown ( 2012 ) and Mizell and Brown ( 2016 ) tended to suggest that STEM education mainly consists of interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines, but their approach consisted of selecting a limited number of individual discipline-based journals and then selecting articles that authors self-identified as connected to STEM education.

In contrast to reviews on STEM education, in general, other reviews focused on specific issues in STEM education (e.g., Henderson et al., 2011 ; Kim et al., 2018 ; Margot & Kettler, 2019 ; Minichiello et al., 2018 ; Schreffler, Vasquez III, Chini, & James, 2019 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). For example, the review by Henderson et al. ( 2011 ) focused on instructional change in undergraduate STEM courses based on 191 conceptual and empirical journal articles published between 1995 and 2008. Margot and Kettler ( 2019 ) focused on what is known about teachers’ values, beliefs, perceived barriers, and needed support related to STEM education based on 25 empirical journal articles published between 2000 and 2016. The focus of these reviews allowed the researchers to limit the number of articles considered, and they typically used keyword searches of selected databases to identify articles on STEM education. Some researchers used this approach to identify publications from journals only (e.g., Henderson et al., 2011 ; Margot & Kettler, 2019 ; Schreffler et al., 2019 ), and others selected and reviewed publications beyond journals (e.g., Minichiello et al., 2018 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ).

The discussion in this section suggests possible reasons contributing to the absence of a general literature review of STEM education research and development: (1) diverse perspectives in existence about STEM and STEM education that contribute to the difficulty of specifying a scope of literature review, (2) its short but rapid development history in comparison to other discipline-based education (e.g., science education), and (3) difficulties in deciding how to establish the scope of the literature review. With respect to the third reason, prior reviews have used one of two approaches to identify and select articles: (a) identifying specific journals first and then searching and selecting specific articles from these journals (e.g., Brown, 2012 ; Erduran et al., 2015 ; Mizell & Brown, 2016 ) and (b) conducting selected database searches with keywords based on a specific focus (e.g., Margot & Kettler, 2019 ; Thibaut et al., 2018 ). However, neither the first approach of selecting a limited number of individual discipline-based journals nor the second approach of selecting a specific focus for the review leads to an approach that provides a general overview of STEM education scholarship development based on existing journal publications.

Current review

Two issues were identified in setting the scope for this review.

What time period should be considered?

What publications will be selected for review?

Time period

We start with the easy one first. As discussed above, the acronym STEM did exist until the early 2000s. Although the existence of the acronym does not generate scholarship on student learning in STEM disciplines, it is symbolic and helps focus attention to efforts in STEM education. Since we want to examine the status and trends in STEM education, it is reasonable to start with the year 2000. Then, we can use the acronym of STEM as an identifier in locating specific research articles in a way as done by others (e.g., Brown, 2012 ; Mizell & Brown, 2016 ). We chose the end of 2018 as the end of the time period for our review that began during 2019.

Focusing on publications beyond individual discipline-based journals

As mentioned before, scholars responded to the call for scholarship development in STEM education with publications that appeared in various outlets and diverse languages, including journals, books, and conference proceedings. However, journal publications are typically credited and valued as one of the most important outlets for research exchange (e.g., Erduran et al., 2015 ; Henderson et al., 2011 ; Lin et al., 2019 ; Xu et al., 2019 ). Thus, in this review, we will also focus on articles published in journals in English.

The discourse above on the complexity and ambiguity regarding STEM education suggests that scholars may publish their research in a wide range of journals beyond individual discipline-based journals. To search and select articles from a wide range of journals, we thought about the approach of searching selected databases with keywords as other scholars used in reviewing STEM education with a specific focus. However, existing journals in STEM education do not have a long history. In fact, IJ-STEM is the first journal in STEM education that has just been accepted into the Social Sciences Citation Index (SSCI) (Li, 2019a ). Publications in many STEM education journals are practically not available in several important and popular databases, such as the Web of Science and Scopus. Moreover, some journals in STEM education were not normalized due to a journal’s name change or irregular publication schedule. For example, the Journal of STEM Education was named as Journal of SMET Education when it started in 2000 in a print format, and the journal’s name was not changed until 2003, Vol 4 (3 and 4), and also went fully on-line starting 2004 (Raju & Sankar, 2003 ). A simple Google Scholar search with keywords will not be able to provide accurate information, unless you visit the journal’s website to check all publications over the years. Those added complexities prevented us from taking the database search as a viable approach. Thus, we decided to identify journals first and then search and select articles from these journals. Further details about the approach are provided in the “ Method ” section.

Research questions

Given a broader range of journals and a longer period of time to be covered in this review, we can examine some of the same questions as the IJ-STEM review (Li, Froyd, & Wang, 2019 ), but we do not have access to data on readership, articles accessed, or articles cited for the other journals selected for this review. Specifically, we are interested in addressing the following six research questions:

What were the status and trends in STEM education research from 2000 to the end of 2018 based on journal publications?

What were the patterns of publications in STEM education research across different journals?

Which countries or regions, based on the countries or regions in which authors were located, contributed to journal publications in STEM education?

What were the patterns of single-author and multiple-author publications in STEM education?

What main topics had emerged in STEM education research based on the journal publications?

What research methods did authors tend to use in conducting STEM education research?

Based on the above discussion, we developed the methods for this literature review to follow careful sequential steps to identify journals first and then identify and select STEM education research articles published in these journals from January 2000 to the end of 2018. The methods should allow us to obtain a comprehensive overview about the status and trends of STEM education research based on a systematic analysis of related publications from a broad range of journals and over a longer period of time.

Identifying journals

We used the following three steps to search and identify journals for inclusion:

We assumed articles on research in STEM education have been published in journals that involve more than one traditional discipline. Thus, we used Google to search and identify all education journals with their titles containing either two, three, or all four disciplines of STEM. For example, we did Google search of all the different combinations of three areas of science, mathematics, technology Footnote 1 , and engineering as contained in a journal’s title. In addition, we also searched possible journals containing the word STEAM in the title.

Since STEM education may be viewed as encompassing discipline-based education research, articles on STEM education research may have been published in traditional discipline-based education journals, such as the Journal of Research in Science Teaching . However, there are too many such journals. Yale’s Poorvu Center for Teaching and Learning has listed 16 journals that publish articles spanning across undergraduate STEM education disciplines (see https://poorvucenter.yale.edu/FacultyResources/STEMjournals ). Thus, we selected from the list some individual discipline-based education research journals, and also added a few more common ones such as the Journal of Engineering Education .

Since articles on research in STEM education have appeared in some general education research journals, especially those well-established ones. Thus, we identified and selected a few of those journals that we noticed some publications in STEM education research.

Following the above three steps, we identified 45 journals (see Table  1 ).

Identifying articles

In this review, we will not discuss or define the meaning of STEM education. We used the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) as a term in our search of publication titles and/or abstracts. To identify and select articles for review, we searched all items published in those 45 journals and selected only those articles that author(s) self-identified with the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) in the title and/or abstract. We excluded publications in the sections of practices, letters to editors, corrections, and (guest) editorials. Our search found 798 publications that authors self-identified as in STEM education, identified from 36 journals. The remaining 9 journals either did not have publications that met our search terms or published in another language other than English (see the two separate lists in Table 1 ).

Data analysis

To address research question 3, we analyzed authorship to examine which countries/regions contributed to STEM education research over the years. Because each publication may have either one or multiple authors, we used two different methods to analyze authorship nationality that have been recognized as valuable from our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). The first method considers only the corresponding author’s (or the first author, if no specific indication is given about the corresponding author) nationality and his/her first institution affiliation, if multiple institution affiliations are listed. Method 2 considers every author of a publication, using the following formula (Howard, Cole, & Maxwell, 1987 ) to quantitatively assign and estimate each author’s contribution to a publication (and thus associated institution’s productivity), when multiple authors are included in a publication. As an example, each publication is given one credit point. For the publication co-authored by two, the first author would be given 0.6 and the second author 0.4 credit point. For an article contributed jointly by three authors, the three authors would be credited with scores of 0.47, 0.32, and 0.21, respectively.

After calculating all the scores for each author of each paper, we added all the credit scores together in terms of each author’s country/region. For brevity, we present only the top 10 countries/regions in terms of their total credit scores calculated using these two different methods, respectively.

To address research question 5, we used the same seven topic categories identified and used in our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). We tested coding 100 articles first to ensure the feasibility. Through test-coding and discussions, we found seven topic categories could be used to examine and classify all 798 items.

K-12 teaching, teacher, and teacher education in STEM (including both pre-service and in-service teacher education)

Post-secondary teacher and teaching in STEM (including faculty development, etc.)

K-12 STEM learner, learning, and learning environment

Post-secondary STEM learner, learning, and learning environments (excluding pre-service teacher education)

Policy, curriculum, evaluation, and assessment in STEM (including literature review about a field in general)

Culture and social and gender issues in STEM education

History, epistemology, and perspectives about STEM and STEM education

To address research question 6, we coded all 798 publications in terms of (1) qualitative methods, (2) quantitative methods, (3) mixed methods, and (4) non-empirical studies (including theoretical or conceptual papers, and literature reviews). We assigned each publication to only one research topic and one method, following the process used in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). When there was more than one topic or method that could have been used for a publication, a decision was made in choosing and assigning a topic or a method. The agreement between two coders for all 798 publications was 89.5%. When topic and method coding discrepancies occurred, a final decision was reached after discussion.

Results and discussion

In the following sections, we report findings as corresponding to each of the six research questions.

The status and trends of journal publications in STEM education research from 2000 to 2018

Figure  1 shows the number of publications per year. As Fig.  1 shows, the number of publications increased each year beginning in 2010. There are noticeable jumps from 2015 to 2016 and from 2017 to 2018. The result shows that research in STEM education had grown significantly since 2010, and the most recent large number of STEM education publications also suggests that STEM education research gained its own recognition by many different journals for publication as a hot and important topic area.

The distribution of STEM education publications over the years

Among the 798 articles, there were 549 articles with the word “STEM” (or STEAM, or written with the phrase of “science, technology, engineering, and mathematics”) included in the article’s title or both title and abstract and 249 articles without such identifiers included in the title but abstract only. The results suggest that many scholars tended to include STEM in the publications’ titles to highlight their research in or about STEM education. Figure  2 shows the number of publications per year where publications are distinguished depending on whether they used the term STEM in the title or only in the abstract. The number of publications in both categories had significant increases since 2010. Use of the acronym STEM in the title was growing at a faster rate than using the acronym only in the abstract.

The trends of STEM education publications with vs. without STEM included in the title

Not all the publications that used the acronym STEM in the title and/or abstract reported on a study involving all four STEM areas. For each publication, we further examined the number of the four areas involved in the reported study.

Figure  3 presents the number of publications categorized by the number of the four areas involved in the study, breaking down the distribution of these 798 publications in terms of the content scope being focused on. Studies involving all four STEM areas are the most numerous with 488 (61.2%) publications, followed by involving one area (141, 17.7%), then studies involving both STEM and non-STEM (84, 10.5%), and finally studies involving two or three areas of STEM (72, 9%; 13, 1.6%; respectively). Publications that used the acronym STEAM in either the title or abstract were classified as involving both STEM and non-STEM. For example, both of the following publications were included in this category.

Dika and D’Amico ( 2016 ). “Early experiences and integration in the persistence of first-generation college students in STEM and non-STEM majors.” Journal of Research in Science Teaching , 53 (3), 368–383. (Note: this article focused on early experience in both STEM and Non-STEM majors.)

Sochacka, Guyotte, and Walther ( 2016 ). “Learning together: A collaborative autoethnographic exploration of STEAM (STEM+ the Arts) education.” Journal of Engineering Education , 105 (1), 15–42. (Note: this article focused on STEAM (both STEM and Arts).)

Publication distribution in terms of content scope being focused on. (Note: 1=single subject of STEM, 2=two subjects of STEM, 3=three subjects of STEM, 4=four subjects of STEM, 5=topics related to both STEM and non-STEM)

Figure  4 presents the number of publications per year in each of the five categories described earlier (category 1, one area of STEM; category 2, two areas of STEM; category 3, three areas of STEM; category 4, four areas of STEM; category 5, STEM and non-STEM). The category that had grown most rapidly since 2010 is the one involving all four areas. Recent growth in the number of publications in category 1 likely reflected growing interest of traditional individual disciplinary based educators in developing and sharing multidisciplinary and interdisciplinary scholarship in STEM education, as what was noted recently by Li and Schoenfeld ( 2019 ) with publications in IJ-STEM.

Publication distribution in terms of content scope being focused on over the years

Patterns of publications across different journals

Among the 36 journals that published STEM education articles, two are general education research journals (referred to as “subject-0”), 12 with their titles containing one discipline of STEM (“subject-1”), eight with journal’s titles covering two disciplines of STEM (“subject-2”), six covering three disciplines of STEM (“subject-3”), seven containing the word STEM (“subject-4”), and one in STEAM education (“subject-5”).

Table  2 shows that both subject-0 and subject-1 journals were usually mature journals with a long history, and they were all traditional subscription-based journals, except the Journal of Pre - College Engineering Education Research , a subject-1 journal established in 2011 that provided open access (OA). In comparison to subject-0 and subject-1 journals, subject-2 and subject-3 journals were relatively newer but still had quite many years of history on average. There are also some more journals in these two categories that provided OA. Subject-4 and subject-5 journals had a short history, and most provided OA. The results show that well-established journals had tended to focus on individual disciplines or education research in general. Multidisciplinary and interdisciplinary education journals were started some years later, followed by the recent establishment of several STEM or STEAM journals.

Table 2 also shows that subject-1, subject-2, and subject-4 journals published approximately a quarter each of the publications. The number of publications in subject-1 journals is interested, because we selected a relatively limited number of journals in this category. There are many other journals in the subject-1 category (as well as subject-0 journals) that we did not select, and thus it is very likely that we did not include some STEM education articles published in subject-0 or subject-1 journals that we did not include in our study.

Figure  5 shows the number of publications per year in each of the five categories described earlier (subject-0 through subject-5). The number of publications per year in subject-5 and subject-0 journals did not change much over the time period of the study. On the other hand, the number of publications per year in subject-4 (all 4 areas), subject-1 (single area), and subject-2 journals were all over 40 by the end of the study period. The number of publications per year in subject-3 journals increased but remained less than 30. At first sight, it may be a bit surprising that the number of publications in STEM education per year in subject-1 journals increased much faster than those in subject-2 journals over the past few years. However, as Table 2 indicates these journals had long been established with great reputations, and scholars would like to publish their research in such journals. In contrast to the trend in subject-1 journals, the trend in subject-4 journals suggests that STEM education journals collectively started to gain its own identity for publishing and sharing STEM education research.

STEM education publication distribution across different journal categories over the years. (Note: 0=subject-0; 1=subject-1; 2=subject-2; 3=subject-3; 4=subject-4; 5=subject-5)

Figure  6 shows the number of STEM education publications in each journal where the bars are color-coded (yellow, subject-0; light blue, subject-1; green, subject-2; purple, subject-3; dark blue, subject-4; and black, subject-5). There is no clear pattern shown in terms of the overall number of STEM education publications across categories or journals, but very much individual journal-based performance. The result indicates that the number of STEM education publications might heavily rely on the individual journal’s willingness and capability of attracting STEM education research work and thus suggests the potential value of examining individual journal’s performance.

Publication distribution across all 36 individual journals across different categories with the same color-coded for journals in the same subject category

The top five journals in terms of the number of STEM education publications are Journal of Science Education and Technology (80 publications, journal number 25 in Fig.  6 ), Journal of STEM Education (65 publications, journal number 26), International Journal of STEM Education (64 publications, journal number 17), International Journal of Engineering Education (54 publications, journal number 12), and School Science and Mathematics (41 publications, journal number 31). Among these five journals, two journals are specifically on STEM education (J26, J17), two on two subjects of STEM (J25, J31), and one on one subject of STEM (J12).

Figure  7 shows the number of STEM education publications per year in each of these top five journals. As expected, based on earlier trends, the number of publications per year increased over the study period. The largest increase was in the International Journal of STEM Education (J17) that was established in 2014. As the other four journals were all established in or before 2000, J17’s short history further suggests its outstanding performance in attracting and publishing STEM education articles since 2014 (Li, 2018b ; Li, Froyd, & Wang, 2019 ). The increase was consistent with the journal’s recognition as the first STEM education journal for inclusion in SSCI starting in 2019 (Li, 2019a ).

Publication distribution of selected five journals over the years. (Note: J12: International Journal of Engineering Education; J17: International Journal of STEM Education; J25: Journal of Science Education and Technology; J26: Journal of STEM Education; J31: School Science and Mathematics)

Top 10 countries/regions where scholars contributed journal publications in STEM education

Table  3 shows top countries/regions in terms of the number of publications, where the country/region was established by the authorship using the two different methods presented above. About 75% (depending on the method) of contributions were made by authors from the USA, followed by Australia, Canada, Taiwan, and UK. Only Africa as a continent was not represented among the top 10 countries/regions. The results are relatively consistent with patterns reported in the IJ-STEM study (Li, Froyd, & Wang, 2019 )

Further examination of Table 3 reveals that the two methods provide not only fairly consistent results but also yield some differences. For example, Israel and Germany had more publication credit if only the corresponding author was considered, but South Korea and Turkey had more publication credit when co-authors were considered. The results in Table 3 show that each method has value when analyzing and comparing publications by country/region or institution based on authorship.

Recognizing that, as shown in Fig. 1 , the number of publications per year increased rapidly since 2010, Table  4 shows the number of publications by country/region over a 10-year period (2009–2018) and Table 5 shows the number of publications by country/region over a 5-year period (2014–2018). The ranks in Tables  3 , 4 , and 5 are fairly consistent, but that would be expected since the larger numbers of publications in STEM education had occurred in recent years. At the same time, it is interesting to note in Table 5 some changes over the recent several years with Malaysia, but not Israel, entering the top 10 list when either method was used to calculate author's credit.

Patterns of single-author and multiple-author publications in STEM education

Since STEM education differs from traditional individual disciplinary education, we are interested in determining how common joint co-authorship with collaborations was in STEM education articles. Figure  8 shows that joint co-authorship was very common among these 798 STEM education publications, with 83.7% publications with two or more co-authors. Publications with two, three, or at least five co-authors were highest, with 204, 181, and 157 publications, respectively.

Number of publications with single or different joint authorship. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors)

Figure  9 shows the number of publications per year using the joint authorship categories in Fig.  8 . Each category shows an increase consistent with the increase shown in Fig. 1 for all 798 publications. By the end of the time period, the number of publications with two, three, or at least five co-authors was the largest, which might suggest an increase in collaborations in STEM education research.

Publication distribution with single or different joint authorship over the years. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors)

Co-authors can be from the same or different countries/regions. Figure  10 shows the number of publications per year by single authors (no collaboration), co-authors from the same country (collaboration in a country/region), and co-authors from different countries (collaboration across countries/regions). Each year the largest number of publications was by co-authors from the same country, and the number increased dramatically during the period of the study. Although the number of publications in the other two categories increased, the numbers of publications were noticeably fewer than the number of publications by co-authors from the same country.

Publication distribution in authorship across different categories in terms of collaboration over the years

Published articles by research topics

Figure  11 shows the number of publications in each of the seven topic categories. The topic category of goals, policy, curriculum, evaluation, and assessment had almost half of publications (375, 47%). Literature reviews were included in this topic category, as providing an overview assessment of education and research development in a topic area or a field. Sample publications included in this category are listed as follows:

DeCoito ( 2016 ). “STEM education in Canada: A knowledge synthesis.” Canadian Journal of Science , Mathematics and Technology Education , 16 (2), 114–128. (Note: this article provides a national overview of STEM initiatives and programs, including success, criteria for effective programs and current research in STEM education.)

Ring-Whalen, Dare, Roehrig, Titu, and Crotty ( 2018 ). “From conception to curricula: The role of science, technology, engineering, and mathematics in integrated STEM units.” International Journal of Education in Mathematics Science and Technology , 6 (4), 343–362. (Note: this article investigates the conceptions of integrated STEM education held by in-service science teachers through the use of photo-elicitation interviews and examines how those conceptions were reflected in teacher-created integrated STEM curricula.)

Schwab et al. ( 2018 ). “A summer STEM outreach program run by graduate students: Successes, challenges, and recommendations for implementation.” Journal of Research in STEM Education , 4 (2), 117–129. (Note: the article details the organization and scope of the Foundation in Science and Mathematics Program and evaluates this program.)

Frequencies of publications’ research topic distributions. (Note: 1=K-12 teaching, teacher and teacher education; 2=Post-secondary teacher and teaching; 3=K-12 STEM learner, learning, and learning environment; 4=Post-secondary STEM learner, learning, and learning environments; 5=Goals and policy, curriculum, evaluation, and assessment (including literature review); 6=Culture, social, and gender issues; 7=History, philosophy, Epistemology, and nature of STEM and STEM education)

The topic with the second most publications was “K-12 teaching, teacher and teacher education” (103, 12.9%), followed closely by “K-12 learner, learning, and learning environment” (97, 12.2%). The results likely suggest the research community had a broad interest in both teaching and learning in K-12 STEM education. The top three topics were the same in the IJ-STEM review (Li, Froyd, & Wang, 2019 ).

Figure  11 also shows there was a virtual tie between two topics with the fourth most cumulative publications, “post-secondary STEM learner & learning” (76, 9.5%) and “culture, social, and gender issues in STEM” (78, 9.8%), such as STEM identity, students’ career choices in STEM, and inclusion. This result is different from the IJ-STEM review (Li, Froyd, & Wang, 2019 ), where “post-secondary STEM teacher & teaching” and “post-secondary STEM learner & learning” were tied as the fourth most common topics. This difference is likely due to the scope of journals and the length of the time period being reviewed.

Figure  12 shows the number of publications per year in each topic category. As expected from the results in Fig.  11 the number of publications in topic category 5 (goals, policy, curriculum, evaluation, and assessment) was the largest each year. The numbers of publications in topic category 3 (K-12 learner, learning, and learning environment), 1 (K-12 teaching, teacher, and teacher education), 6 (culture, social, and gender issues in STEM), and 4 (post-secondary STEM learner and learning) were also increasing. Although Fig.  11 shows the number of publications in topic category 1 was slightly more than the number of publications in topic category 3 (see Fig.  11 ), the number of publications in topic category 3 was increasing more rapidly in recent years than its counterpart in topic category 1. This may suggest a more rapidly growing interest in K-12 STEM learner, learning, and learning environment. The numbers of publications in topic categories 2 and 7 were not increasing, but the number of publications in IJ-STEM in topic category 2 was notable (Li, Froyd, & Wang, 2019 ). It will be interesting to follow trends in the seven topic categories in the future.

Publication distributions in terms of research topics over the years

Published articles by research methods

Figure  13 shows the number of publications per year by research methods in empirical studies. Publications with non-empirical studies are shown in a separate category. Although the number of publications in each of the four categories increased during the study period, there were many more publications presenting empirical studies than those without. For those with empirical studies, the number of publications using quantitative methods increased most rapidly in recent years, followed by qualitative and then mixed methods. Although there were quite many publications with non-empirical studies (e.g., theoretical or conceptual papers, literature reviews) during the study period, the increase of the number of publications in this category was noticeably less than empirical studies.

Publication distributions in terms of research methods over the years. (Note: 1=qualitative, 2=quantitative, 3=mixed, 4=Non-empirical)

Concluding remarks

The systematic analysis of publications that were considered to be in STEM education in 36 selected journals shows tremendous growth in scholarship in this field from 2000 to 2018, especially over the past 10 years. Our analysis indicates that STEM education research has been increasingly recognized as an important topic area and studies were being published across many different journals. Scholars still hold diverse perspectives about how research is designated as STEM education; however, authors have been increasingly distinguishing their articles with STEM, STEAM, or related words in the titles, abstracts, and lists of keywords during the past 10 years. Moreover, our systematic analysis shows a dramatic increase in the number of publications in STEM education journals in recent years, which indicates that these journals have been collectively developing their own professional identity. In addition, the International Journal of STEM Education has become the first STEM education journal to be accepted in SSCI in 2019 (Li, 2019a ). The achievement may mark an important milestone as STEM education journals develop their own identity for publishing and sharing STEM education research.

Consistent with our previous reviews (Li, Froyd, & Wang, 2019 ; Li, Wang, & Xiao, 2019 ), the vast majority of publications in STEM education research were contributed by authors from the USA, where STEM and STEAM education originated, followed by Australia, Canada, and Taiwan. At the same time, authors in some countries/regions in Asia were becoming very active in the field over the past several years. This trend is consistent with findings from the IJ-STEM review (Li, Froyd, & Wang, 2019 ). We certainly hope that STEM education scholarship continues its development across all five continents to support educational initiatives and programs in STEM worldwide.

Our analysis has shown that collaboration, as indicated by publications with multiple authors, has been very common among STEM education scholars, as that is often how STEM education distinguishes itself from the traditional individual disciplinary based education. Currently, most collaborations occurred among authors from the same country/region, although collaborations across cross-countries/regions were slowly increasing.

With the rapid changes in STEM education internationally (Li, 2019b ), it is often difficult for researchers to get an overall sense about possible hot topics in STEM education especially when STEM education publications appeared in a vast array of journals across different fields. Our systematic analysis of publications has shown that studies in the topic category of goals, policy, curriculum, evaluation, and assessment have been the most prevalent, by far. Our analysis also suggests that the research community had a broad interest in both teaching and learning in K-12 STEM education. These top three topic categories are the same as in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). Work in STEM education will continue to evolve and it will be interesting to review the trends in another 5 years.

Encouraged by our recent IJ-STEM review, we began this review with an ambitious goal to provide an overview of the status and trends of STEM education research. In a way, this systematic review allowed us to achieve our initial goal with a larger scope of journal selection over a much longer period of publication time. At the same time, there are still limitations, such as the decision to limit the number of journals from which we would identify publications for analysis. We understand that there are many publications on STEM education research that were not included in our review. Also, we only identified publications in journals. Although this is one of the most important outlets for scholars to share their research work, future reviews could examine publications on STEM education research in other venues such as books, conference proceedings, and grant proposals.

Availability of data and materials

The data and materials used and analyzed for the report are publicly available at the various journal websites.

Journals containing the word "computers" or "ICT" appeared automatically when searching with the word "technology". Thus, the word of "computers" or "ICT" was taken as equivalent to "technology" if appeared in a journal's name.

Abbreviations

Information and Communications Technology

International Journal of STEM Education

Kindergarten–Grade 12

Science, Mathematics, Engineering, and Technology

Science, Technology, Engineering, Arts, and Mathematics

Science, Technology, Engineering, and Mathematics

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Physics education research for 21 st century learning

• Lei Bao   ORCID: orcid.org/0000-0003-3348-4198 1 &
• Kathleen Koenig 2  

Disciplinary and Interdisciplinary Science Education Research volume  1 , Article number:  2 ( 2019 ) Cite this article

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Education goals have evolved to emphasize student acquisition of the knowledge and attributes necessary to successfully contribute to the workforce and global economy of the twenty-first Century. The new education standards emphasize higher end skills including reasoning, creativity, and open problem solving. Although there is substantial research evidence and consensus around identifying essential twenty-first Century skills, there is a lack of research that focuses on how the related subskills interact and develop over time. This paper provides a brief review of physics education research as a means for providing a context towards future work in promoting deep learning and fostering abilities in high-end reasoning. Through a synthesis of the literature around twenty-first Century skills and physics education, a set of concretely defined education and research goals are suggested for future research, along with how these may impact the next generation physics courses and how physics should be taught in the future.

Introduction

Education is the primary service offered by society to prepare its future generation workforce. The goals of education should therefore meet the demands of the changing world. The concept of learner-centered, active learning has broad, growing support in the research literature as an empirically validated teaching practice that best promotes learning for modern day students (Freeman et al., 2014 ). It stems out of the constructivist view of learning, which emphasizes that it is the learner who needs to actively construct knowledge and the teacher should assume the role of a facilitator rather than the source of knowledge. As implied by the constructivist view, learner-centered education usually emphasizes active-engagement and inquiry style teaching-learning methods, in which the learners can effectively construct their understanding under the guidance of instruction. The learner-centered education also requires educators and researchers to focus their efforts on the learners’ needs, not only to deliver effective teaching-learning approaches, but also to continuously align instructional practices to the education goals of the times. The goals of introductory college courses in science, technology, engineering, and mathematics (STEM) disciplines have constantly evolved from some notion of weed-out courses that emphasize content drilling, to the current constructivist active-engagement type of learning that promotes interest in STEM careers and fosters high-end cognitive abilities.

Following the conceptually defined framework of twenty-first Century teaching and learning, this paper aims to provide contextualized operational definitions of the goals for twenty-first Century learning in physics (and STEM in general) as well as the rationale for the importance of these outcomes for current students. Aligning to the twenty-first Century learning goals, research in physics education is briefly reviewed to provide a context towards future work in promoting deep learning and fostering abilities in high-end reasoning in parallel. Through a synthesis of the literature around twenty-first Century skills and physics education, a set of concretely defined education and research goals are suggested for future research. These goals include: domain-specific research in physics learning; fostering scientific reasoning abilities that are transferable across the STEM disciplines; and dissemination of research-validated curriculum and approaches to teaching and learning. Although this review has a focus on physics education research (PER), it is beneficial to expand the perspective to view physics education in the broader context of STEM learning. Therefore, much of the discussion will blend PER with STEM education as a continuum body of work on teaching and learning.

Education goals for twenty-first century learning

Education goals have evolved to emphasize student acquisition of essential “21 st Century skills”, which define the knowledge and attributes necessary to successfully contribute to the workforce and global economy of the 21st Century (National Research Council, 2011 , 2012a ). In general, these standards seek to transition from emphasizing content-based drilling and memorization towards fostering higher-end skills including reasoning, creativity, and open problem solving (United States Chamber of Commerce, 2017 ). Initiatives on advancing twenty-first Century education focus on skills that converge on three broad clusters: cognitive, interpersonal, and intrapersonal, all of which include a rich set of sub-dimensions.

Within the cognitive domain, multiple competencies have been proposed, including deep learning, non-routine problem solving, systems thinking, critical thinking, computational and information literacy, reasoning and argumentation, and innovation (National Research Council, 2012b ; National Science and Technology Council, 2018 ). Interpersonal skills are those necessary for relating to others, including the ability to work creatively and collaboratively as well as communicate clearly. Intrapersonal skills, on the other hand, reside within the individual and include metacognitive thinking, adaptability, and self-management. These involve the ability to adjust one’s strategy or approach along with the ability to work towards important goals without significant distraction, both essential for sustained success in long-term problem solving and career development.

Although many descriptions exist for what qualifies as twenty-first Century skills, student abilities in scientific reasoning and critical thinking are the most commonly noted and widely studied. They are highly connected with the other cognitive skills of problem solving, decision making, and creative thinking (Bailin, 1996 ; Facione, 1990 ; Fisher, 2001 ; Lipman, 2003 ; Marzano et al., 1988 ), and have been important educational goals since the 1980s (Binkley et al., 2010 ; NCET, 1987 ). As a result, they play a foundational role in defining, assessing, and developing twenty-first Century skills.

The literature for critical thinking is extensive (Bangert-Drowns & Bankert, 1990 ; Facione, 1990 ; Glaser, 1941 ). Various definitions exist with common underlying principles. Broadly defined, critical thinking is the application of the cognitive skills and strategies that aim for and support evidence-based decision making. It is the thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions (Halpern, 1999 ). It is the “reasonable reflective thinking focused on deciding what to believe or do” (Ennis, 1993 ). Critical thinking is recognized as a way to understand and evaluate subject matter; producing reliable knowledge and improving thinking itself (Paul, 1990 ; Siegel, 1988 ).

The notion of scientific reasoning is often used to label the set of skills that support critical thinking, problem solving, and creativity in STEM. Broadly defined, scientific reasoning includes the thinking and reasoning skills involved in inquiry, experimentation, evidence evaluation, inference and argument that support the formation and modification of concepts and theories about the natural world; such as the ability to systematically explore a problem, formulate and test hypotheses, manipulate and isolate variables, and observe and evaluate consequences (Bao et al., 2009 ; Zimmerman, 2000 ). Critical thinking and scientific reasoning share many features, where both emphasize evidence-based decision making in multivariable causal conditions. Critical thinking can be promoted through the development of scientific reasoning, which includes student ability to reach a reliable conclusion after identifying a question, formulating hypotheses, gathering relevant data, and logically testing and evaluating the hypothesis. In this way, scientific reasoning can be viewed as a scientific domain instantiation of critical thinking in the context of STEM learning.

In STEM learning, cognitive aspects of the twenty-first Century skills aim to develop reasoning skills, critical thinking skills, and deep understanding, all of which allow students to develop well connected expert-like knowledge structures and engage in meaningful scientific inquiry and problem solving. Within physics education, a core component of STEM education, the learning of conceptual understanding and problem solving remains a current emphasis. However, the fast-changing work environment and technology-driven world require a new set of core knowledge, skills, and habits of mind to solve complex interdisciplinary problems, gather and evaluate evidence, and make sense of information from a variety of sources (Tanenbaum, 2016 ). The education goals in physics are transitioning towards ability fostering as well as extension and integration with other STEM disciplines. Although curriculum that supports these goals is limited, there are a number of attempts, particularly in developing active learning classrooms and inquiry-based laboratory activities, which have demonstrated success. Some of these are described later in this paper as they provide a foundation for future work in physics education.

Interpersonal skills, such as communication and collaboration, are also essential for twenty-first Century problem-solving tasks, which are often open-ended, complex, and team-based. As the world becomes more connected in a multitude of dimensions, tackling significant problems involving complex systems often goes beyond the individual and requires working with others who are increasingly from culturally diverse backgrounds. Due to the rise of communication technologies, being able to articulate thoughts and ideas in a variety of formats and contexts is crucial, as well as the ability to effectively listen or observe to decipher meaning. Interpersonal skills can be promoted by integrating group-learning experiences into the classroom setting, while providing students with the opportunity to engage in open-ended tasks with a team of peer learners who may propose more than one plausible solution. These experiences should be designed such that students must work collaboratively and responsibly in teams to develop creative solutions, which are later disseminated through informative presentations and clearly written scientific reports. Although educational settings in general have moved to providing students with more and more opportunities for collaborative learning, a lack of effective assessments for these important skills has been a limiting factor for producing informative research and widespread implementation. See Liu ( 2010 ) for an overview of measurement instruments reported in the research literature.

Intrapersonal skills are based on the individual and include the ability to manage one’s behavior and emotions to achieve goals. These are especially important for adapting in the fast-evolving collaborative modern work environment and for learning new tasks to solve increasingly challenging interdisciplinary problems, both of which require intellectual openness, work ethic, initiative, and metacognition, to name a few. These skills can be promoted using instruction which, for example, includes metacognitive learning strategies, provides opportunities to make choices and set goals for learning, and explicitly connects to everyday life events. However, like interpersonal skills, the availability of relevant assessments challenges advancement in this area. In this review, the vast amount of studies on interpersonal and intrapersonal skills will not be discussed in order to keep the main focus on the cognitive side of skills and reasoning.

The purpose behind discussing twenty-first Century skills is that this set of skills provides important guidance for establishing essential education goals for modern society and learners. However, although there is substantial research evidence and consensus around identifying necessary twenty-first Century skills, there is a lack of research that focuses on how the related subskills interact and develop over time (Reimers & Chung, 2016 ), with much of the existing research residing in academic literature that is focused on psychology rather than education systems (National Research Council, 2012a ). Therefore, a major and challenging task for discipline-based education researchers and educators is to operationally define discipline-specific goals that align with the twenty-first Century skills for each of the STEM fields. In the following sections, this paper will provide a limited vision of the research endeavors in physics education that can translate the past and current success into sustained impact for twenty-first Century teaching and learning.

Proposed education and research goals

Physics education research (PER) is often considered an early pioneer in discipline-based education research (National Research Council, 2012c ), with well-established, broad, and influential outcomes (e.g., Hake, 1998 ; Hsu, Brewe, Foster, & Harper, 2004 ; McDermott & Redish, 1999 ; Meltzer & Thornton, 2012 ). Through the integration of twenty-first Century skills with the PER literature, a set of broadly defined education and research goals is proposed for future PER work:

Discipline-specific deep learning: Cognitive and education research involving physics learning has established a rich literature on student learning behaviors along with a number of frameworks. Some of the popular frameworks include conceptual understanding and concept change, problem solving, knowledge structure, deep learning, and knowledge integration. Aligned with twenty-first Century skills, future research in physics learning should aim to integrate the multiple areas of existing work, such that they help students develop well integrated knowledge structures in order to achieve deep leaning in physics.

Fostering scientific reasoning for transfer across STEM disciplines: The broad literature in physics learning and scientific reasoning can provide a solid foundation to further develop effective physics education approaches, such as active engagement instruction and inquiry labs, specifically targeting scientific inquiry abilities and reasoning skills. Since scientific reasoning is a more domain-general cognitive ability, success in physics can also more readily inform research and education practices in other STEM fields.

Research, development, assessment, and dissemination of effective education approaches: Developing and maintaining a supportive infrastructure of education research and implementation has always been a challenge, not only in physics but in all STEM areas. The twenty-first Century education requires researchers and instructors across STEM to work together as an extended community in order to construct a sustainable integrated STEM education environment. Through this new infrastructure, effective team-based inquiry learning and meaningful assessment can be delivered to help students develop a comprehensive skills set including deep understanding and scientific reasoning, as well as communication and other non-cognitive abilities.

The suggested research will generate understanding and resources to support education practices that meet the requirements of the Next Generation Science Standards (NGSS), which explicitly emphasize three areas of learning including disciplinary core ideas, crosscutting concepts, and practices (National Research Council, 2012b ). The first goal for promoting deep learning of disciplinary knowledge corresponds well to the NGSS emphasis on disciplinary core ideas, which play a central role in helping students develop well integrated knowledge structures to achieve deep understanding. The second goal on fostering transferable scientific reasoning skills supports the NGSS emphasis on crosscutting concepts and practices. Scientific reasoning skills are crosscutting cognitive abilities that are essential to the development of domain-general concepts and modeling strategies. In addition, the development of scientific reasoning requires inquiry-based learning and practices. Therefore, research on scientific reasoning can produce a valuable knowledge base on education means that are effective for developing crosscutting concepts and promoting meaningful practices in STEM. The third research goal addresses the challenge in the assessment of high-end skills and the dissemination of effective educational approaches, which supports all NGSS initiatives to ensure sustainable development and lasting impact. The following sections will discuss the research literature that provides the foundation for these three research goals and identify the specific challenges that will need to be addressed in future work.

Promoting deep learning in physics education

Physics education for the twenty-first Century aims to foster high-end reasoning skills and promote deep conceptual understanding. However, many traditional education systems place strong emphasis on only problem solving with the expectation that students obtain deep conceptual understanding through repetitive problem-solving practices, which often doesn’t occur (Alonso, 1992 ). This focus on problem solving has been shown to have limitations as a number of studies have revealed disconnections between learning conceptual understanding and problem-solving skills (Chiu, 2001 ; Chiu, Guo, & Treagust, 2007 ; Hoellwarth, Moelter, & Knight, 2005 ; Kim & Pak, 2002 ; Nakhleh, 1993 ; Nakhleh & Mitchell, 1993 ; Nurrenbern & Pickering, 1987 ; Stamovlasis, Tsaparlis, Kamilatos, Papaoikonomou, & Zarotiadou, 2005 ). In fact, drilling in problem solving may actually promote memorization of context-specific solutions with minimal generalization rather than transitioning students from novices to experts.

Towards conceptual understanding and learning, many models and definitions have been established to study and describe student conceptual knowledge states and development. For example, students coming into a physics classroom often hold deeply rooted, stable understandings that differ from expert conceptions. These are commonly referred to as misconceptions or alternative conceptions (Clement, 1982 ; Duit & Treagust, 2003 ; Dykstra Jr, Boyle, & Monarch, 1992 ; Halloun & Hestenes, 1985a , 1985b ). Such students’ conceptions are context dependent and exist as disconnected knowledge fragments, which are strongly situated within specific contexts (Bao & Redish, 2001 , 2006 ; Minstrell, 1992 ).

In modeling students’ knowledge structures, DiSessa’s proposed phenomenological primitives (p-prim) describe a learner’s implicit thinking, cued from specific contexts, as an underpinning cognitive construct for a learner’s expressed conception (DiSessa, 1993 ; Smith III, DiSessa, & Roschelle, 1994 ). Facets, on the other hand, map between the implicit p-prim and concrete statements of beliefs and are developed as discrete and independent units of thought, knowledge, or strategies used by individuals to address specific situations (Minstrell, 1992 ). Ontological categories, defined by Chi, describe student reasoning in the most general sense. Chi believed that these are distinct, stable, and constraining, and that a core reason behind novices’ difficulties in physics is that they think of physics within the category of matter instead of processes (Chi, 1992 ; Chi & Slotta, 1993 ; Chi, Slotta, & De Leeuw, 1994 ; Slotta, Chi, & Joram, 1995 ). More details on conceptual learning and problem solving are well summarized in the literature (Hsu et al., 2004 ; McDermott & Redish, 1999 ), from which a common theme emerges from the models and definitions. That is, learning is context dependent and students with poor conceptual understanding typically have locally connected knowledge structures with isolated conceptual constructs that are unable to establish similarities and contrasts between contexts.

Additionally, this idea of fragmentation is demonstrated through many studies on student problem solving in physics and other fields. It has been shown that a student’s knowledge organization is a key aspect for distinguishing experts from novices (Bagno, Eylon, & Ganiel, 2000 ; Chi, Feltovich, & Glaser, 1981 ; De Jong & Ferguson-Hesler, 1986 ; Eylon & Reif, 1984 ; Ferguson-Hesler & De Jong, 1990 ; Heller & Reif, 1984 ; Larkin, McDermott, Simon, & Simon, 1980 ; Smith, 1992 ; Veldhuis, 1990 ; Wexler, 1982 ). Expert’s knowledge is organized around core principles of physics, which are applied to guide problem solving and develop connections between different domains as well as new, unfamiliar situations (Brown, 1989 ; Perkins & Salomon, 1989 ; Salomon & Perkins, 1989 ). Novices, on the other hand, lack a well-organized knowledge structure and often solve problems by relying on surface features that are directly mapped to certain problem-solving outcomes through memorization (Chi, Bassok, Lewis, Reimann, & Glaser, 1989 ; Hardiman, Dufresne, & Mestre, 1989 ; Schoenfeld & Herrmann, 1982 ).

This lack of organization creates many difficulties in the comprehension of basic concepts and in solving complex problems. This leads to the common complaint that students’ knowledge of physics is reduced to formulas and vague labels of the concepts, which are unable to substantively contribute to meaningful reasoning processes. A novice’s fragmented knowledge structure severely limits the learner’s conceptual understanding. In essence, these students are able to memorize how to approach a problem given specific information but lack the understanding of the underlying concept of the approach, limiting their ability to apply this approach to a novel situation. In order to achieve expert-like understanding, a student’s knowledge structure must integrate all of the fragmented ideas around the core principle to form a coherent and fully connected conceptual framework.

Towards a more general theoretical consideration, students’ alternative conceptions and fragmentation in knowledge structures can be viewed through both the “naïve theory” framework (e.g., Posner, Strike, Hewson, & Gertzog, 1982 ; Vosniadou, Vamvakoussi, & Skopeliti, 2008 ) and the “knowledge in pieces” (DiSessa, 1993 ) perspective. The “naïve theory” framework considers students entering the classroom with stable and coherent ideas (naïve theories) about the natural world that differ from those presented by experts. In the “knowledge in pieces” perspective, student knowledge is constructed in real-time and incorporates context features with the p-prims to form the observed conceptual expressions. Although there exists an ongoing debate between these two views (Kalman & Lattery, 2018 ), it is more productive to focus on their instructional implications for promoting meaningful conceptual change in students’ knowledge structures.

In the process of learning, students may enter the classroom with a range of initial states depending on the population and content. For topics with well-established empirical experiences, students often have developed their own ideas and understanding, while on topics without prior exposure, students may create their initial understanding in real-time based on related prior knowledge and given contextual features (Bao & Redish, 2006 ). These initial states of understanding, regardless of their origin, are usually different from those of experts. Therefore, the main function of teaching and learning is to guide students to modify their initial understanding towards the experts’ views. Although students’ initial understanding may exist as a body of coherent ideas within limited contexts, as students start to change their knowledge structures throughout the learning process, they may evolve into a wide range of transitional states with varying levels of knowledge integration and coherence. The discussion in this brief review on students’ knowledge structures regarding fragmentation and integration are primarily focused on the transitional stages emerged through learning.

The corresponding instructional goal is then to help students more effectively develop an integrated knowledge structure so as to achieve a deep conceptual understanding. From an educator’s perspective, Bloom’s taxonomy of education objectives establishes a hierarchy of six levels of cognitive skills based on their specificity and complexity: Remember (lowest and most specific), Understand, Apply, Analyze, Evaluate, and Create (highest and most general and complex) (Anderson et al., 2001 ; Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956 ). This hierarchy of skills exemplifies the transition of a learner’s cognitive development from a fragmented and contextually situated knowledge structure (novice with low level cognitive skills) to a well-integrated and globally networked expert-like structure (with high level cognitive skills).

As a student’s learning progresses from lower to higher cognitive levels, the student’s knowledge structure becomes more integrated and is easier to transfer across contexts (less context specific). For example, beginning stage students may only be able to memorize and perform limited applications of the features of certain contexts and their conditional variations, with which the students were specifically taught. This leads to the establishment of a locally connected knowledge construct. When a student’s learning progresses from the level of Remember to Understand, the student begins to develop connections among some of the fragmented pieces to form a more fully connected network linking a larger set of contexts, thus advancing into a higher level of understanding. These connections and the ability to transfer between different situations form the basis of deep conceptual understanding. This growth of connections leads to a more complete and integrated cognitive structure, which can be mapped to a higher level on Bloom’s taxonomy. This occurs when students are able to relate a larger number of different contextual and conditional aspects of a concept for analyzing and evaluating to a wider variety of problem situations.

Promoting the growth of connections would appear to aid in student learning. Exactly which teaching methods best facilitate this are dependent on the concepts and skills being learned and should be determined through research. However, it has been well recognized that traditional instruction often fails to help students obtain expert-like conceptual understanding, with many misconceptions still existing after instruction, indicating weak integration within a student’s knowledge structure (McKeachie, 1986 ).

Recognizing the failures of traditional teaching, various research-informed teaching methods have been developed to enhance student conceptual learning along with diagnostic tests, which aim to measure the existence of misconceptions. Most advances in teaching methods focus on the inclusion of inquiry-based interactive-engagement elements in lecture, recitations, and labs. In physics education, these methods were popularized after Hake’s landmark study demonstrated the effectiveness of interactive-engagement over traditional lectures (Hake, 1998 ). Some of these methods include the use of peer instruction (Mazur, 1997 ), personal response systems (e.g., Reay, Bao, Li, Warnakulasooriya, & Baugh, 2005 ), studio-style instruction (Beichner et al., 2007 ), and inquiry-based learning (Etkina & Van Heuvelen, 2001 ; Laws, 2004 ; McDermott, 1996 ; Thornton & Sokoloff, 1998 ). The key approach of these methods aims to improve student learning by carefully targeting deficits in student knowledge and actively encouraging students to explore and discuss. Rather than rote memorization, these approaches help promote generalization and deeper conceptual understanding by building connections between knowledge elements.

Based on the literature, including Bloom’s taxonomy and the new education standards that emphasize twenty-first Century skills, a common focus on teaching and learning can be identified. This focus emphasizes helping students develop connections among fragmented segments of their knowledge pieces and is aligned with the knowledge integration perspective, which focuses on helping students develop and refine their knowledge structure toward a more coherently organized and extensively connected network of ideas (Lee, Liu, & Linn, 2011 ; Linn, 2005 ; Nordine, Krajcik, & Fortus, 2011 ; Shen, Liu, & Chang, 2017 ). For meaningful learning to occur, new concepts must be integrated into a learner’s existing knowledge structure by linking the new knowledge to already understood concepts.

Forming an integrated knowledge structure is therefore essential to achieving deep learning, not only in physics but also in all STEM fields. However, defining what connections must occur at different stages of learning, as well as understanding the instructional methods necessary for effectively developing such connections within each STEM disciplinary context, are necessary for current and future research. Together these will provide the much needed foundational knowledge base to guide the development of the next generation of curriculum and classroom environment designed around twenty-first Century learning.

Developing scientific reasoning with inquiry labs

Scientific reasoning is part of the widely emphasized cognitive strand of twenty-first Century skills. Through development of scientific reasoning skills, students’ critical thinking, open-ended problem-solving abilities, and decision-making skills can be improved. In this way, targeting scientific reasoning as a curricular objective is aligned with the goals emphasized in twenty-first Century education. Also, there is a growing body of research on the importance of student development of scientific reasoning, which have been found to positively correlate with course achievement (Cavallo, Rozman, Blickenstaff, & Walker, 2003 ; Johnson & Lawson, 1998 ), improvement on concept tests (Coletta & Phillips, 2005 ; She & Liao, 2010 ), engagement in higher levels of problem solving (Cracolice, Deming, & Ehlert, 2008 ; Fabby & Koenig, 2013 ); and success on transfer (Ates & Cataloglu, 2007 ; Jensen & Lawson, 2011 ).

Unfortunately, research has shown that college students are lacking in scientific reasoning. Lawson ( 1992 ) found that ~ 50% of intro biology students are not capable of applying scientific reasoning in learning, including the ability to develop hypotheses, control variables, and design experiments; all necessary for meaningful scientific inquiry. Research has also found that traditional courses do not significantly develop these abilities, with pre-to-post-test gains of 1%–2%, while inquiry-based courses have gains around 7% (Koenig, Schen, & Bao, 2012 ; Koenig, Schen, Edwards, & Bao, 2012 ). Others found that undergraduates have difficulty developing evidence-based decisions and differentiating between and linking evidence with claims (Kuhn, 1992 ; Shaw, 1996 ; Zeineddin & Abd-El-Khalick, 2010 ). A large scale international study suggested that learning of physics content knowledge with traditional teaching practices does not improve students’ scientific reasoning skills (Bao et al., 2009 ).

Aligned to twenty-first Century learning, it is important to implement curriculum that is specifically designed for developing scientific reasoning abilities within current education settings. Although traditional lectures may continue for decades due to infrastructure constraints, a unique opportunity can be found in the lab curriculum, which may be more readily transformed to include hands-on minds-on group learning activities that are ideal for developing students’ abilities in scientific inquiry and reasoning.

For well over a century, the laboratory has held a distinctive role in student learning (Meltzer & Otero, 2015 ). However, many existing labs, which haven’t changed much since the late 1980s, have received criticism for their outdated cookbook style that lacks effectiveness in developing high-end skills. In addition, labs have been primarily used as a means for verifying the physical principles presented in lecture, and unfortunately, Hofstein and Lunetta ( 1982 ) found in an early review of the literature that research was unable to demonstrate the impact of the lab on student content learning.

About this same time, a shift towards a constructivist view of learning gained popularity and influenced lab curriculum development towards engaging students in the process of constructing knowledge through science inquiry. Curricula, such as Physics by Inquiry (McDermott, 1996 ), Real-Time Physics (Sokoloff, Thornton, & Laws, 2011 ), and Workshop Physics (Laws, 2004 ), were developed with a primary focus on engaging students in cognitive conflict to address misconceptions. Although these approaches have been shown to be highly successful in improving deep learning of physics concepts (McDermott & Redish, 1999 ), the emphasis on conceptual learning does not sufficiently impact the domain general scientific reasoning skills necessitated in the goals of twenty-first Century learning.

Reform in science education, both in terms of targeted content and skills, along with the emergence of knowledge regarding human cognition and learning (Bransford, Brown, & Cocking, 2000 ), have generated renewed interest in the potential of inquiry-based lab settings for skill development. In these types of hands-on minds-on learning, students apply the methods and procedures of science inquiry to investigate phenomena and construct scientific claims, solve problems, and communicate outcomes, which holds promise for developing both conceptual understanding and scientific reasoning skills in parallel (Trowbridge, Bybee, & Powell, 2000 ). In addition, the availability of technology to enhance inquiry-based learning has seen exponential growth, along with the emergence of more appropriate research methodologies to support research on student learning.

Although inquiry-based labs hold promise for developing students’ high-end reasoning, analytic, and scientific inquiry abilities, these educational endeavors have not become widespread, with many existing physics laboratory courses still viewed merely as a place to illustrate the physical principles from the lecture course (Meltzer & Otero, 2015 ). Developing scientific ideas from practical experiences, however, is a complex process. Students need sufficient time and opportunity for interaction and reflection on complex, investigative tasks. Blended learning, which merges lecture and lab (such as studio style courses), addresses this issue to some extent, but has experienced limited adoption, likely due to the demanding infrastructure resources, including dedicated technology-intensive classroom space, equipment and maintenance costs, and fully committed trained staff.

Therefore, there is an immediate need to transform the existing standalone lab courses, within the constraints of the existing education infrastructure, into more inquiry-based designs, with one of its primary goals dedicated to developing scientific reasoning skills. These labs should center on constructing knowledge, along with hands-on minds-on practical skills and scientific reasoning, to support modeling a problem, designing and implementing experiments, analyzing and interpreting data, drawing and evaluating conclusions, and effective communication. In particular, training on scientific reasoning needs to be explicitly addressed in the lab curriculum, which should contain components specifically targeting a set of operationally-defined scientific reasoning skills, such as ability to control variables or engage in multivariate causal reasoning. Although effective inquiry may also implicitly develop some aspects of scientific reasoning skills, such development is far less efficient and varies with context when the primary focus is on conceptual learning.

Several recent efforts to enhance the standalone lab course have shown promise in supporting education goals that better align with twenty-first Century learning. For example, the Investigative Science Learning Environment (ISLE) labs involve a series of tasks designed to help students develop the “habits of mind” of scientists and engineers (Etkina et al., 2006 ). The curriculum targets reasoning as well as the lab learning outcomes published by the American Association of Physics Teachers (Kozminski et al., 2014 ). Operationally, ISLE methods focus on scaffolding students’ developing conceptual understanding using inquiry learning without a heavy emphasis on cognitive conflict, making it more appropriate and effective for entry level students and K-12 teachers.

Likewise, Koenig, Wood, Bortner, and Bao ( 2019 ) have developed a lab curriculum that is intentionally designed around the twenty-first Century learning goals for developing cognitive, interpersonal, and intrapersonal abilities. In terms of the cognitive domain, the lab learning outcomes center on critical thinking and scientific reasoning but do so through operationally defined sub-skills, all of which are transferrable across STEM. These selected sub-skills are found in the research literature, and include the ability to control variables and engage in data analytics and causal reasoning. For each targeted sub-skill, a series of pre-lab and in-class activities provide students with repeated, deliberate practice within multiple hypothetical science-based scenarios followed by real inquiry-based lab contexts. This explicit instructional strategy has been shown to be essential for the development of scientific reasoning (Chen & Klahr, 1999 ). In addition, the Karplus Learning Cycle (Karplus, 1964 ) provides the foundation for the structure of the lab activities and involves cycles of exploration, concept introduction, and concept application. The curricular framework is such that as the course progresses, the students engage in increasingly complex tasks, which allow students the opportunity to learn gradually through a progression from simple to complex skills.

As part of this same curriculum, students’ interpersonal skills are developed, in part, through teamwork, as students work in groups of 3 or 4 to address open-ended research questions, such as, What impacts the period of a pendulum? In addition, due to time constraints, students learn early on about the importance of working together in an efficient manor towards a common goal, with one set of written lab records per team submitted after each lab. Checkpoints built into all in-class activities involve Socratic dialogue between the instructor and students and promote oral communication. This use of directed questioning guides students in articulating their reasoning behind decisions and claims made, while supporting the development of scientific reasoning and conceptual understanding in parallel (Hake, 1992 ). Students’ intrapersonal skills, as well as communication skills, are promoted through the submission of individual lab reports. These reports require students to reflect upon their learning over each of four multi-week experiments and synthesize their ideas into evidence-based arguments, which support a claim. Due to the length of several weeks over which students collect data for each of these reports, the ability to organize the data and manage their time becomes essential.

Despite the growing emphasis on research and development of curriculum that targets twenty-first Century learning, converting a traditionally taught lab course into a meaningful inquiry-based learning environment is challenging in current reform efforts. Typically, the biggest challenge is a lack of resources; including faculty time to create or adapt inquiry-based materials for the local setting, training faculty and graduate student instructors who are likely unfamiliar with this approach, and the potential cost of new equipment. Koenig et al. ( 2019 ) addressed these potential implementation barriers by designing curriculum with these challenges in mind. That is, the curriculum was designed as a flexible set of modules that target specific sub-skills, with each module consisting of pre-lab (hypothetical) and in-lab (real) activities. Each module was designed around a curricular framework such that an adopting institution can use the materials as written, or can incorporate their existing equipment and experiments into the framework with minimal effort. Other non-traditional approaches have also been experimented with, such as the work by Sobhanzadeh, Kalman, and Thompson ( 2017 ), which targets typical misconceptions by using conceptual questions to engage students in making a prediction, designing and conducting a related experiment, and determining whether or not the results support the hypothesis.

Another challenge for inquiry labs is the assessment of skills-based learning outcomes. For assessment of scientific reasoning, a new instrument on inquiry in scientific thinking analytics and reasoning (iSTAR) has been developed, which can be easily implemented across large numbers of students as both a pre- and post-test to assess gains. iSTAR assesses reasoning skills necessary in the systematical conduct of scientific inquiry, which includes the ability to explore a problem, formulate and test hypotheses, manipulate and isolate variables, and observe and evaluate the consequences (see www.istarassessment.org ). The new instrument expands upon the commonly used classroom test of scientific reasoning (Lawson, 1978 , 2000 ), which has been identified with a number of validity weaknesses and a ceiling effect for college students (Bao, Xiao, Koenig, & Han, 2018 ).

Many education innovations need supporting infrastructures that can ensure adoption and lasting impact. However, making large-scale changes to current education settings can be risky, if not impossible. New education approaches, therefore, need to be designed to adapt to current environmental constraints. Since higher-end skills are a primary focus of twenty-first Century learning, which are most effectively developed in inquiry-based group settings, transforming current lecture and lab courses into this new format is critical. Although this transformation presents great challenges, promising solutions have already emerged from various research efforts. Perhaps the biggest challenge is for STEM educators and researchers to form an alliance to work together to re-engineer many details of the current education infrastructure in order to overcome the multitude of implementation obstacles.

This paper attempts to identify a few central ideas to provide a broad picture for future research and development in physics education, or STEM education in general, to promote twenty-first Century learning. Through a synthesis of the existing literature within the authors’ limited scope, a number of views surface.

Education is a service to prepare (not to select) the future workforce and should be designed as learner-centered, with the education goals and teaching-learning methods tailored to the needs and characteristics of the learners themselves. Given space constraints, the reader is referred to the meta-analysis conducted by Freeman et al. ( 2014 ), which provides strong support for learner-centered instruction. The changing world of the twenty-first Century informs the establishment of new education goals, which should be used to guide research and development of teaching and learning for present day students. Aligned to twenty-first Century learning, the new science standards have set the goals for STEM education to transition towards promoting deep learning of disciplinary knowledge, thereby building upon decades of research in PER, while fostering a wide range of general high-end cognitive and non-cognitive abilities that are transferable across all disciplines.

Following these education goals, more research is needed to operationally define and assess the desired high-end reasoning abilities. Building on a clear definition with effective assessments, a large number of empirical studies are needed to investigate how high-end abilities can be developed in parallel with deep learning of concepts, such that what is learned can be generalized to impact the development of curriculum and teaching methods which promote skills-based learning across all STEM fields. Specifically for PER, future research should emphasize knowledge integration to promote deep conceptual understanding in physics along with inquiry learning to foster scientific reasoning. Integration of physics learning in contexts that connect to other STEM disciplines is also an area for more research. Cross-cutting, interdisciplinary connections are becoming important features of the future generation physics curriculum and defines how physics should be taught collaboratively with other STEM courses.

This paper proposed meaningful areas for future research that are aligned with clearly defined education goals for twenty-first Century learning. Based on the existing literature, a number of challenges are noted for future directions of research, including the need for:

clear and operational definitions of goals to guide research and practice

concrete operational definitions of high-end abilities for which students are expected to develop

effective assessment methods and instruments to measure high-end abilities and other components of twenty-first Century learning

a knowledge base of the curriculum and teaching and learning environments that effectively support the development of advanced skills

integration of knowledge and ability development regarding within-discipline and cross-discipline learning in STEM

effective means to disseminate successful education practices

The list is by no means exhaustive, but these themes emerge above others. In addition, the high-end abilities discussed in this paper focus primarily on scientific reasoning, which is highly connected to other skills, such as critical thinking, systems thinking, multivariable modeling, computational thinking, design thinking, etc. These abilities are expected to develop in STEM learning, although some may be emphasized more within certain disciplines than others. Due to the limited scope of this paper, not all of these abilities were discussed in detail but should be considered an integral part of STEM learning.

Finally, a metacognitive position on education research is worth reflection. One important understanding is that the fundamental learning mechanism hasn’t changed, although the context in which learning occurs has evolved rapidly as a manifestation of the fast-forwarding technology world. Since learning is a process at the interface between a learner’s mind and the environment, the main focus of educators should always be on the learner’s interaction with the environment, not just the environment. In recent education developments, many new learning platforms have emerged at an exponential rate, such as the massive open online courses (MOOCs), STEM creative labs, and other online learning resources, to name a few. As attractive as these may be, it is risky to indiscriminately follow trends in education technology and commercially-incentivized initiatives before such interventions are shown to be effective by research. Trends come and go but educators foster students who have only a limited time to experience education. Therefore, delivering effective education is a high-stakes task and needs to be carefully and ethically planned and implemented. When game-changing opportunities emerge, one needs to not only consider the winners (and what they can win), but also the impact on all that is involved.

Based on a century of education research, consensus has settled on a fundamental mechanism of teaching and learning, which suggests that knowledge is developed within a learner through constructive processes and that team-based guided scientific inquiry is an effective method for promoting deep learning of content knowledge as well as developing high-end cognitive abilities, such as scientific reasoning. Emerging technology and methods should serve to facilitate (not to replace) such learning by providing more effective education settings and conveniently accessible resources. This is an important relationship that should survive many generations of technological and societal changes in the future to come. From a physicist’s point of view, a fundamental relation like this can be considered the “mechanics” of teaching and learning. Therefore, educators and researchers should hold on to these few fundamental principles without being distracted by the surfacing ripples of the world’s motion forward.

Availability of data and materials

Not applicable.

Abbreviations

American Association of Physics Teachers

Investigative Science Learning Environment

Inquiry in Scientific Thinking Analytics and Reasoning

Massive open online course

New Generation Science Standards

• Physics education research

Science Technology Engineering and Math

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The research is supported in part by NSF Awards DUE-1431908 and DUE-1712238. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

The research is supported in part by NSF Awards DUE-1431908 and DUE-1712238.

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Bao, L., Koenig, K. Physics education research for 21 st century learning. Discip Interdscip Sci Educ Res 1 , 2 (2019). https://doi.org/10.1186/s43031-019-0007-8

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Among Keith's publications are a number of research reports and other papers:

Taber, K. S. (2024). Understanding the octet framework : Comment on 'What resources do high school students activate to link energetic and structural changes in chemical reactions? – A qualitative study ' [10.1039/D3RP00232B]. Chemistry Education Research and Practice . https://doi.org/10.1039/D3RP00232B [ Download the paper ]

Brock, R., Taber, K. S., & Watts, D. M. (2023). Assembly required: a microgenetic multiple case study of four students' assemblages when learning about force. International Journal of Science Education , 1-21. https://doi.org/10.1080/09500693.2023.2269616 [ Download paper ]

Izquierdo-Acebes, E., & Taber, K. S. (2023). Secondary Science Teachers' Instructional Strategies for Promoting the Construction of Scientific Explanations . Science & Education . https://doi.org/10.1007/s11191-022-00412-5

Taber, K. S. (2021). The Challenge to Educational Reforms during a Global Emergency: The Case of Progressive Science Education . C.E.P.S. Journal , 11 (Special issue), 1-21. doi:doi: 10.26529/cepsj.1109

Billingsley, B., Taber, K. S., & Nassaji, M. (2021). Secondary school students' perceptions of scientific and religious positions on miracles. Science & Christian Belief , 33(2), 99.

Billingsley, B., Taber, K. S., & Nassaji, M. (2021). Scientism, creationism or category error? A cross-age survey of secondary school students' perceptions of the relationships between science and religion . The Curriculum Journal , 32(2), 334-358. doi:https://doi.org/10.1002/curj.83 ( Download this open access paper )

Taber, K. S., Billingsley, B., & Riga, F. (2021). Secondary students' values and perceptions of science-related careers: responses to vignette-based scenarios . SN Social Sciences , 1 (Art. 104). doi:10.1007/s43545-021-00130-9 (Download the accepted manuscript version of the paper )

Taber, K. S. (2020). Comment on "Increasing chemistry students' knowledge, confidence, and conceptual understanding of pH using a collaborative computer pH simulation" by S. W. Watson, A. V. Dubrovskiy and M. L. Peters, Chem. Educ. Res. Pract., 2020, 21, 528 . Chemistry Education Research and Practice , 21: 1218 – 1221. doi:10.1039/D0RP00131G. Open access at: https://pubs.rsc.org/en/content/articlepdf/2020/rp/d0rp00131g

Brock, R., & Taber, K. S. (2020). Making claims about learning: a microgenetic multiple case study of temporal patterns of conceptual change in learners' activation of force conceptions . International Journal of Science Education , 42(8), 1388-1407. doi:10.1080/09500693.2020.1764657

Taber, K. S. (2020). Conceptual confusion in the chemistry curriculum: exemplifying the problematic nature of representing chemical concepts as target knowledge . Foundations of Chemistry , 22: 309-334. https://doi.org/10.1007/s10698-019-09346-3 [ Open Access ]

Taber, K. S. (2019). Progressing chemistry education research as a disciplinary field . Disciplinary and Interdisciplinary Science Education Research , 1(1), 5. doi:10.1186/s43031-019-0011-z [ Open Access ]

Taber, K. S. (2019). Experimental research into teaching innovations: responding to methodological and ethical challenges . Studies in Scienc e Education , 55(1), 69-119. doi:10.1080/03057267.2019.1658058 [ Download manuscript version ]

Taber, K. S. (2019) Alternative Conceptions and the Learning of Chemistry . Israel Journal of Chemistry , 59(6-7), 450-469. doi:10.1002/ijch.201800046

Tan, K. C. D., Taber, K. S., Liew, Y. Q., & Teo, K. L. A. (2019). A web-based ionisation energy diagnostic instrument : exploiting the affordances of technology . Chemistry Education Research and Practice , 20(2), 412-427. doi:10.1039/C8RP00215K [ Free access ]

Taber, K. S. (2018). The Use of Cronbach's Alpha When Developing and Reporting Research Instruments in Science Education . Research in Science Education , 48, 1273-1296. doi:10.1007/s11165-016-9602-2 [ Open access ]

Taber, K. S. (2017). Knowledge, beliefs and pedagogy: how the nature of science should inform the aims of science education (and not just when teaching evolution) . Cultural Studies of Science Education , 12(1), 81-91. doi:10.1007/s11422-016-9750-8 [ Open access ]

Taber, K. S. (2017). Identifying research foci to progress chemistry education as a field . Educación Química , 28 (2) pp.66-73. [ Open access ]

Billingsley, B., Brock, R., Taber, K. S., & Riga, F. (2016). How Students View the Boundaries Between Their Science and Religious Education Concerning the Origins of Life and the Universe . Science Education , 100(3), 459-482. doi:10.1002/sce.21213 [ Open Access ]

Kılıç, D., Taber, K. S., & Winterbottom, M. (2016). A Cross-National Study of Students' Understanding of Genetics Concepts : Implications from Similarities and Differences in England and Turkey . Educational Research International , 2016 (Article ID 653962). doi:10.1155/2016/6539626 [ Open Access ]

Ruthven, K., Mercer, N., Taber, K. S., Guardia, P., Hofmann, R., Ilie, S., Luthman, S., Riga, F. (2016). A research-informed dialogic-teaching approach to early secondary-school mathematics and science: the pedagogical design and field trial of the epiSTEMe intervention . Research Papers in Education . doi:10.1080/02671522.2015.1129642

Philip, J. M. D. & Taber, K. S. (2015). Separating 'Inquiry Questions' and 'Techniques' to Help Learners Move between the How and the Why of Biology Practical Work . Journal of Biological Education , 1-20. doi:10.1080/00219266.2015.1058840.

Taber, K. S., Billingsley, B., Riga, F., & Newdick, H. (2015). English secondary students' thinking about the status of scientific theories: consistent, comprehensive, coherent and extensively evidenced explanations of aspects of the natural world – or just 'an idea someone has' . The Curriculum Journal , 1-34. doi: 10.1080/09585176.2015.1043926

Taber, K. S. (2014). The significance of implicit knowledge in teaching and learning chemistry . Chemistry Education Research and Practice . 15, 447-461. doi: 10.1039/C4RP00124A [ Free access ] [ Download the author's manuscript version ]

Billingsley, B., Riga, F., Taber, K. S., & Newdick, H. (2014). Secondary school teachers' perspectives on teaching about topics that bridge science and religion . The Curriculum Journal , 25(3), 372-395. doi: 10.1080/09585176.2014.920264.

Adbo, K., & Taber, K. S. (2014). Developing an Understanding of Chemistry: A case study of one Swedish student's rich conceptualisation for making sense of upper secondary school chemistry . International Journal of Science Education , 36(7), 1107-1136. doi: 10.1080/09500693.2013.844869

Taber, K. S. (2013). Revisiting the chemistry triplet: drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education . Chemistry Education Research and Practice , 14(2), 156-168..doi: 10.1039/C3RP00012E [ Free access ]

Taber, K. S. (2013). Upper Secondary Students' Understanding of the Basic Physical Interactions in Analogous Atomic and Solar Systems . Research in Science Education, 43(4), 1377-1406. doi:10.1007/s11165-012-9312-3 [ Download manuscript version ]

Billingsley, B., Taber, K. S., Riga, F., & Newdick, H. (2013). Secondary school students' epistemic insight into the relationships between science and religion – a preliminary enquiry. Research in Science Education , 43, 1715-1732. https://doi.org/DOI 10.1007/s11165-012-9317-y

Taber, K. S. (2012). Vive la différence? Comparing 'like with like' in studies of learners' ideas in diverse educational contexts . Educational Research International , 2012 (Article 168741), 1-12. Retrieved from http://www.hindawi.com/journals/edu/2012/168741/ doi:10.1155/2012/168741 (Open access: available for free download). [ Download paper ]

Taber, K. S. (2012). Meeting the needs of gifted science learners in the context of England's system of comprehensive secondary education: the ASCEND project . Journal of Science Education in Japan , 36(2), 101-112. (Invited research article) [ Download paper ]

Taber, K. S., Tsaparlis, G., & Nakiboğlu, C. (2012). Student Conceptions of Ionic Bonding: Patterns of thinking across three European contexts . I nternational Journal of Science Education ,34(18), 2843-2873. doi: 10.1080/09500693.2012.656150. [ Download article ]

Taber, K. S., & Tan, K. C. D. (2011). The insidious nature of 'hard core' alternative conceptions: Implications for the constructivist research programme of patterns in high school students' and pre-service teachers' thinking about ionisation energy . International Journal of Science Education , 33(2), 259-297 [ Download this paper ]

Taber, K. S., Billingsley, B., Riga, F., & Newdick, H. (2011). Secondary students' responses to perceptions of the relationship between science and religion: stances identified from an interview study . Science Education , 95(6), 1000-1025.

Taber, K. S., Billingsley, B., Riga, F., & Newdick, H. (2011). To what extent do pupils perceive science to be inconsistent with religious faith? An exploratory survey of 13-14 year-old English pupils. S cience Education International , 22(2), 99-118.

Taber, K. S., Riga, F., Brindley, S., Winterbottom, M., Finey, J., & Fisher, L. (2011). Formative conceptions of assessment: trainee teachers' thinking about assessment issues in English secondary schools . Teacher Development , 15(2), 171-186.

Taber, K. S. (2011). Models, molecules and misconceptions : a commentary on "Secondary School Students' Misconceptions of Covalent Bonding" . Journal of Turkish Science Education , 8(1), 3-18.

Levy Nahum, T., Mamlok-Naaman, R., Hofstein, A., & Taber, K. S. (2010). Teaching and learning the concept of chemical bonding . Studies in Science Education , 46(2), 179-207.

Taber, K. S., & García Franco, A. (2010). Learning processes in chemistry: Drawing upon cognitive resources to learn about the particulate structure of matter . Journal of the Learning Sciences , 19(1), 99-142. ( Download the author's manuscript version of the paper .)

Taber, K. S. (2010). Straw men and false dichotomies: Overcoming philosophical confusion in chemical education . Journal of Chemical Education , 87(5), 552-558.

Taber, K. S. (2010). Paying lip-service to research?: The adoption of a constructivist perspective to inform science teaching in the English curriculum context . The Curriculum Journal , 21(1), 25 – 45. [ Download the article ]

Bektas, O., & Taber, K. S. (2009). Can science pedagogy in English schools inform educational reform in Turkey? Exploring the extent of constructivist teaching in a curriculum context informed by constructivist principles . Journal of Turkish Science Education , 6(3), 66-80.

Taber, K. S., & Bricheno, P. A. (2009). Coordinating Procedural and Conceptual Knowledge to Make Sense of Word Equations: Understanding the complexity of a 'simple' completion task at the learner's resolution . International Journal of Science Education , 31(15), 2021-2055.

Tan, K.-C. D., & Taber, K. S. (2009). I onization Energy: Implications of Pre-service Teachers' Conceptions . Journal of Chemical Education , 86(5), 623-629.

Garcia Franco, A. & Taber, K. S. (2009) Secondary Students' Thinking about Familiar Phenomena: Learners' explanations from a curriculum context where 'particles' is a key idea for organising teaching and learning . International Journal of Science Education , 31(14), 1917-1952. (DOI: 10.1080/09500690802307730.)

Taber, K. S. (2009). Learning from experience and teaching by example: reflecting upon personal learning experience to inform teaching practice . Journal of Cambridge Studies , 4(1), 82-91. (Invited opinion piece) [ Download the article ]

Winterbottom, M., Brindley, S., Taber, K. S., Fisher, L. G., Finney, J., & Riga, F. (2008). Conceptions of assessment: trainee teachers' practice and values . The Curriculum Journal , 19(3), 193-213.

Taber, K. S. (2009) College students' conceptions of chemical stability: The widespread adoption of a heuristic rule out of context and beyond its range of application . International Journal of Science Education , 31(10), 1333-1358. doi: 10.1080/09500690801975594. ( Download the author's manuscript version of the paper )

Winterbottom, M., Taber, K. S., Brindley, S., Fisher, L., Finney, J., & Riga, F. (2008). Understanding differences in trainee teachers' values and practice in relation to assessment . Teacher Development , 12 (1), pp.15 – 35.

Taber, K. S. (2008) Exploring student learning from a constructivist perspective in diverse educational contexts , Journal of Turkish Science Education , 5 (1), 2-21. (Invited contribution).

Adbo, K. & Taber, K. S. (2009). Learners' mental models of the particle nature of matter: a study of 16 year-old Swedish science students . International Journal of Science Education . 31(6), 757-786. doi: 10.1080/09500690701799383. [ Download ]

Taber, K. S. (2008). Conceptual Resources for Learning Science: Issues of transience and grain-size in cognition and cognitive structure . International Journal of Science Education . 30 (8), pp.1027-1053. doi: 10.1080/09500690701485082 [ Download this article ]

Taber, K. S. (2008). Exploring Conceptual Integration in Student Thinking: Evidence from a case study . International Journal of Science Education , 30 (14), 1915-1943. (Published on-line, 9th October, 2007, DOI: 10.1080/09500690701589404.)

Tan, K. C. D., Taber, K. S., Liu, X., Coll, R. K., Lorenzo, M., Li, J., Goh, N.K. & Chia, L.S. (2008). Students' conceptions of ionisation energy: A cross-cultural study . International Journal of Science Education , 30 (2), pp.263-283. (DOI: 10.1080/09500690701385258.)

Cokelez, A., Dumon, A, & Taber, K. S. (2008) Upper secondary French students, chemical transformations and the "register of models": a cross-sectional study . International Journal of Science Education , 30 (6), pp.807-836. (DOI: 10.1080/09500690701308458.)

Taber, K. S. & Tan, K. C. D. (2007) Exploring learners' conceptual resources: Singapore A level students' explanations in the topic of ionisation energy , International Journal of Science and Mathematics Educatio n, 5, pp.375-392 (DOI: 10.1007/s10763-006-9044-9)

Taber, K. S. (2006) Towards a curricular model of the nature of science , Science & Education . 17(2-3), 179-218. (DOI: 10.1007/s11191-006-9056-4.) [ Download this article ]

Taber, K. S. (2006) Constructivism's new clothes: the trivial, the contingent, and a progressive research programme into the learning of science , Foundations of Chemistry , 8 (2), pp. 189-219. [ Download the paper fro m the journal website]

Taber, K. S. (2006) Beyond Constructivism: the Progressive Research Programme into Learning Science , Studies in Science Education , 42, pp.125-184. [ Download this article ]

Tan, K. C. D. & Taber, K. S. (2005) What comes after stable octet? Stable sub-shell! , Journal of Science and Mathematics Education in Southeast Asia , 28 (1), pp.81-102.

Taber, K. S. (2005) Developing Teachers as Learning Doctors , Teacher Development , 9 (2), pp.219-235.

Tan, K-C. D., Taber, K. S., Goh, N-K & Chia, L-S. (2005) The ionisation energy diagnostic instrument : a two-tier multiple choice instrument to determine high school students' understanding of ionisation energy , Chemistry Education Research & Practice , 6 (4), pp.180-197. [ Free access ]

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Taber, K. S. (2003) Mediating mental models of metals: acknowledging the priority of the learner's prior learning , Science Education , 87, pp.732-758. [ Download the author's manuscript version or the paper ]

Taber, K. S. & Student, T. A. (2003) How was it for you?: the dialogue between researcher and colearner , Westminster Studies in Education , 26 (1), pp.33-44.

Taber, K. S. (2003) Facilitating science learning in the inter-disciplinary matrix – some perspectives on teaching chemistry and physic s , Chemistry Education: Research and Practice , 4 (2), pp.103-114. [ Download this article ]

Taber, K. S. (2003) Understanding ionisation energy: physical, chemical and alternative conceptions , Chemistry Education: Research and Practice , 4 (2), pp.149-169. [ Free access ]

Taber, K. S. (2003) Lost without trace or not brought to mind? – a case study of remembering and forgetting of college science , Chemistry Education: Research and Practice , 4 (3), pp.249-277. doi:10.1039/B3RP90016A [ Free access ]

Taber, K. S. (2003) The atom in the chemistry curriculum: fundamental concept, teaching model or epistemological obstacle ? , Foundations of Chemistry , 5 (1), pp.43-84. ( Download the author's manuscript version of the paper )

Taber, K. S. (2002) "Intense, but it's all worth it in the end": the colearner's experience of the research process , British Educational Research Journal , 28 (3), 435-457.

Taber, K. S. (2002) Conceptualizing quanta – illuminating the ground state of student understanding of atomic orbitals , Chemistry Education: Research and Practice in Europe , 3 (2), pp.145-158. [ Download paper ]

Taber, K. S. (2002) Compounding quanta – probing the frontiers of student understanding of molecular orbitals , Chemistry Education: Research and Practice in Europe , 3 (2), pp.159-173. [ Free access ]

Taber, K. S. (2001) Building the structural concepts of chemistry: some considerations from educational research , Chemistry Education: Research and Practice in Europe , 2 (2), pp.123-158. [ Free access ]

Taber, K. S. (2001) Constructing chemical concepts in the classroom?: using research to inform practice , Chemistry Education: Research and Practice in Europe , 2 (1), pp.43-51. doi:10.1039/B1RP90014E [ Download this article ]

Taber, K. S. (2001) The mismatch between assumed prior knowledge and the learner's conceptions: a typology of learning impediments , Educational Studies , 27 (2), 159-171. [ Download article ]

Taber, K. S. (2001) Shifting sands: a case study of conceptual development as competition between alternative conceptions , International Journal of Science Education , 23 (7), 731-753.

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Taber, K. S. (2000) Chemistry lessons for universities?: a review of constructivist ideas , University Chemistry Education , 4 (2), pp.26-35. [ Download article ]

Taber, K. S. (2000) Case studies and generalisability – grounded theory and research in science education , International Journal of Science Education , 22 (5), pp.469-487.

Taber, K. S. (2000) Multiple frameworks?: Evidence of manifold conceptions in individual cognitive structure , International Journal of Science Education , 22 (4), pp.399-417. https://doi.org/10.1080/095006900289813 [ Download this paper ]

Taber, K. S. (1998) The sharing-out of nuclear attraction: or I can't think about Physics in Chemistry , International Journal of Science Education , 20 (8), pp.1001-1014. [ Download the paper ]

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Taber, K. S. and Watts, M. (1996) The secret life of the chemical bond: students' anthropomorphic and animistic references to bondin g , International Journal of Science Education , 18 (5), pp.557-568.

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Recent Research in Science Teaching and Learning

• Sarah L. Eddy

*Address correspondence to: Sarah L. Eddy ( E-mail Address: [email protected] ).

Department of Biological Sciences, STEM Transformation Institute, Florida International University, Miami, FL 33199

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The Current Insights feature is designed to introduce life science educators and researchers to current articles of interest in other social science and education journals. In this installment, I highlight three diverse research studies: one addresses the relationships between active learning and teaching evaluations; one presents an observation tool for documenting metacognition in the classroom; and the last explores things teachers can say to encourage students to employ scientific reasoning during class discussions.

STUDENT EVALUATIONS AND ACTIVE LEARNING

Henderson, C., Khan, R., & Dancy, M. (2018). Will my student evaluations decrease if I adopt an active learning instructional strategy? American Journal of Physics , 86 (12), 934–942. https://doi.org/10.1119/1.5065907

Student evaluations are widely used and are often the sole source for the evaluation of faculty teaching. As described in the Introduction, fear that one’s student evaluations may decrease is one of the oft-cited reasons for faculty not adopting active-learning techniques. Yet this phenomenon has not been studied on a large scale. Henderson and colleagues test the hypothesis that active learning lowers student evaluations in a population of physics and astronomy instructors who participated in a long-running faculty development workshop. Forty percent (40%) of new physics and astronomy faculty attended this workshop. Of the more than 1300 workshop participants, 431 responded to a follow-up survey. Participants were asked about their use of active-learning methods in their most recent quantitative physics class; whether their student evaluations were impacted by the use of active learning; and whether students complained about the inclusion of active learning. If a faculty member reported a change in student evaluations, he or she was given an opportunity to provide an explanation for that change.

The majority of respondents saw either an increase (48%) or no change in their student evaluations (32%). The subset of instructors who reported receiving lower teaching evaluations also reported substantially less time lecturing than instructors who reported better evaluations. This pattern seemed driven by people using interactive methods for more than 80% of a class period, as this population was more likely to report reduced evaluations. Student complaints followed a similar pattern, with an increase in complaints becoming the most common outcome for instructors using active methods more than 80% of class time.

The reasons shared by instructors for why their evaluations changed were varied. For those who reported their evaluations improving, more than 20% of the instructors thought this increase was due to each of the following: students believing they were learning more, students enjoying class more, students enjoying interacting with one another, or students enjoying using technology. For those who reported lower evaluations, 40% reported that the students felt that the instructor was not teaching. Interestingly, many of these instructors also confessed as part of this comment that they were not good at “selling” the active learning. They next most common explanation given for lower evaluations was that students did not like working during class time; they would rather be listeners.

The results of this study suggest that, for the majority of faculty, adopting active learning will not negatively impact student evaluations. The study also suggests that those instructors concerned about student evaluations could incorporate active-learning activities for as much as 80% of class time and still not be likely to see a negative impact on their evaluations. This could be useful information to share with departmental colleagues and anyone mentoring new faculty who are deciding how to teach. As always, though, some caution should be taken in applying these results in a new context. Specifically, the authors acknowledge that they did not account for what types of active learning instructors implemented. It may be that some methods are more accepted by students than others.

TEACHERS TALKING METACOGNITION

Zepeda, C. D., Hlutkowsky, C. O., Partika, A. C., & Nokes-­Malach, T. J. (2018, October 29). Identifying teachers’ supports of metacognition through classroom talk and its relation to growth in conceptual learning. Journal of Educational Psychology (advance online publication). https://doi.org/10.1037/edu0000300

Metacognition refers to one’s knowledge and awareness of one’s own thought processes. As reviewed in the Introduction, metacognition is considered highly desirable for students, because it has been linked to many positive outcomes in experimental and classroom studies, including achievement, transfer of knowledge from one context to another, and motivation. Although many studies have focused on the use of planned interventions for metacognition, few have looked at what teachers are saying and doing spontaneously in the classroom that might influence student metacognition.

Zepeda and colleagues developed an observation protocol to detect classroom talk directed toward metacognitive growth in middle school students in math classrooms. They identified both the metacognitive content of the talk and the delivery method by documenting four dimensions, each with three possible states: the type of metacognitive knowledge being promoted; the metacognitive skill being worked on; the manner in which the teacher delivered this content; and how specific the metacognitive skill is frame d (from specific to the question being worked on to a more global approach to problem solving). For example, a teacher might say, “Alright, so explain to us what you are doing right now.” This would be coded as personal knowledge, because the student is asked about his or her own process. The skill being worked on would be monitoring, (i.e., being aware of why they are doing what they are doing). The manner in which the teacher delivers the content would be directive, because the teacher is telling the student to do something. The framing could be domain general, because the prompt could be used with any type of problem. I am not going to go further into the individual states for each dimension due to space, but there are lengthy descriptions of them within the original paper.

The authors use this observation tool with one class session from 39 middle school math instructors. The classes were selected from a larger national data set of middle school classrooms. Every class included in this larger data set had math knowledge assessments. The current authors created a smaller data set that included instructors who had the most student growth on the math assessment over a year and a set of instructors who had the least growth after accounting for various student- and instructor-level factors. Each video was transcribed and each teacher statement was examined for metacognitive talk. Any instance of metacognitive talk was coded for the four dimensions in the observation tool.

Overall, there were very few metacognitive statements made by teachers (∼7% of teacher statements), but even with this low overall percentage, there were some interesting patterns. The odds of teachers engaging in metacognitive talk were 4.75 times greater during whole-class activities than during activities done individually by students. In addition, in high math growth classes, the odds of instructors engaging in metacognitive talk were 1.5 times higher than in low math growth classes.

The content of the metacognitive talk differed between these two class types as well. In terms of the knowledge dimension, teachers in the high math growth classes elicited more personal knowledge statements in which students shared their own understanding of what they were doing in class than teachers in the low math growth classes. The high math growth class also had more statements focused on the skills of monitoring and evaluating their own work. In terms of how the metacognitive content was delivered (manner), the high math growth class had more directive statements. Finally, the high math growth classes had more domain-general framing of the metacognitive statements.

This study demonstrates that classroom observations can be used to explore metacognition and that the same methods that work most effectively in interventions designed to promote metacognition may also work more informally during teach talk in class. Although the authors cannot rule out that teachers who are more effective in other ways are also more likely to engage in metacognitive talk, the results do suggest that certain ways and certain content of metacognitive talk is more effective than others.

BUILDING STUDENT’S SCIENTIFIC REASONING IN CONVERSATIONS

Grinath, A. S., & Southerland, S. A. (2018). Applying the ambitious science teaching framework in undergraduate biology: Responsive talk moves that support explanatory rigor. Science Education ,  103 (1), 92–122. https://doi.org/10.1002/sce.21484

Active learning is centered around the idea that it encourages students to engage in their own learning, often through conversations about course content. Yet the quality of these conversations can vary. In this paper, Grinath and Southerland explore how instructors can influence in-class student discussions.

To explore the question of facilitation effects without confounding variables of differences between lessons, content, and students, the authors chose to work with 26 teaching assistants (TAs) instructing sections of the same introductory biology lab for nonmajors at the same university. This controlled both the content being presented to students across instructors and the structure of the lessons, as each TA was provided the same slides and the same training in how to conduct the lab. The laboratory lessons were designed around the Ambitious Science Teaching framework described in the Introduction, which is meant to help students engage in the meaningful practices of their discipline, including scientific dialogue. One aspect of this framework is helping students connect their everyday explanations of their experiences to the scientific principles underlying them, that is, bridging their everyday way of talking and science talk. This initial conversation is thought to help them meaningfully engage in the subsequent lesson. This study focuses on these initial conversations.

Grinath and Southerland recorded the 8- to 22-minute–long class discussions that opened a lab class exploring how organisms respond to stimuli. At the start of class, students were asked to describe how they experience stress and explain what is driving this response. The authors transcribed the recordings and characterized each TA discourse “move,” a statement made by a TA that served a specific communication function. These moves were coded as conservative or ambitious . Conservative patterns follow the traditional classroom pattern, in which the expertise lies with the instructor only. These moves include the instructor asking questions that only have one correct answer, usually about recalling facts or procedures; evaluating a student response as right or wrong; and explaining the connection between the student response and the scientific concept rather than having students make the connection. Ambitious patterns of discourse allow students to be experts, and the instructor is the facilitator. These instructor moves include asking questions with many possible reasonable answers, probing student responses, and pressing students to supply explanations for their answers. Finally, observers also coded TA moves as inclusive or not inclusive . Inclusive moves could include providing opportunities for multiple students to respond to a question, acknowledging a contribution without indicating correctness, and repeating student responses out loud.

The discourse moves were correlated with student talk. Grinath and Southerland used a framework for explanatory rigor of scientific talk to code student responses in the initial class discussion. There were three codes for student answers: fact , observation , and explanation . A turn of student talk was coded as fact if it was short and a vocabulary word or scientific definition not grounded in personal experience. Observations were what a student thought was happening based on personal experience. Finally, explanations were students’ ideas of why something was happening. The goal of ambitious science teaching is to help students start making their own explanations of phenomena grounded in science and their own experiences. Thus, TA discourse moves that promoted student explanations were considered the most important in this study.

Using linear regressions with a Bonferroni correction for multiple comparisons, Grinath and Southerland found that conservative discourse moves by TAs were related to an increase in student responses being simply fact statements. Ambitious questions (with multiple possible answers) did not predict student responses, but ambitious responses in which TAs deliberately probed student response and pressed students to expand on their answers did relate to increased explanations. Finally, inclusive moves together related to increased observations given by students.

This work highlights several interesting principles that could be expanded beyond labs. First, it seems that, without deliberately pressing for it (and removing the instructor’s explanations), students are not making explanations themselves. They offer facts or observations and wait for the instructor to put them together. Yet explaining phenomena is a key scientific practice and one students should develop. Second, how instructors respond to student answers is critical for creating meaningful conversations in the classroom, maybe even more critical than the qualities of the initial question itself.

• A Critical Feminist Approach for Equity and Inclusion in Undergraduate Biology Education 22 April 2021

© 2019 S. L. Eddy. CBE—Life Sciences Education © 2019 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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• Published: 26 April 2024

A guide to science communication training for doctoral students

• Christina Maher 1   na1 ,
• Trevonn Gyles   ORCID: orcid.org/0000-0003-4635-5985 1   na1 ,
• Eric J. Nestler   ORCID: orcid.org/0000-0002-7905-2000 1 , 2 &
• Daniela Schiller   ORCID: orcid.org/0000-0002-0357-7724 1 , 2  

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Effective science communication is necessary for engaging the public in scientific discourse and ensuring equitable access to knowledge. Training doctoral students in science communication will instill principles of accessibility, accountability, and adaptability in the next generation of scientific leaders, who are poised to expand science’s reach, generate public support for research funding, and counter misinformation. To this aim, we provide a guide for implementing formal science communication training for doctoral students.

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Acknowledgements

The authors thank P. Croxson for her involvement as co-founder of the effective science communication course. We also thank the various teaching assistants over the years, who were actively involved in shaping the course: T. Fehr, C. Lardner, C. Guevara and M. O’Brien.

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Title: teaching algorithm design: a literature review.

Abstract: Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both related to algorithm design and evaluated on undergraduate-level students. Across all papers in the ACM Digital Library prior to August 2023, we only find 94 such papers. We first classify these papers by topic, evaluation metric, evaluation methods, and intervention target. Through our classification, we find a broad sparsity of papers which indicates that many open questions remain about teaching algorithm design, with each algorithm topic only being discussed in between 0 and 10 papers. We also note the need for papers using rigorous research methods, as only 38 out of 88 papers presenting quantitative data use statistical tests, and only 15 out of 45 papers presenting qualitative data use a coding scheme. Only 17 papers report controlled trials. We then synthesize the results of the existing literature to give insights into what the corpus reveals about how we should teach algorithms. Much of the literature explores implementing well-established practices, such as active learning or automated assessment, in the algorithms classroom. However, there are algorithms-specific results as well: a number of papers find that students may under-utilize certain algorithmic design techniques, and studies describe a variety of ways to select algorithms problems that increase student engagement and learning. The results we present, along with the publicly available set of papers collected, provide a detailed representation of the current corpus of CS Education work related to algorithm design and can orient further research in the area.

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Science has an AI problem. This group says they can fix it.

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AI holds the potential to help doctors find early markers of disease and accelerate research on other important scientific advances. But a growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.

Now an interdisciplinary team of 19 researchers that includes Marta Serra-Garcia of the University of California San Diego’s Rady School of Management has published guidelines for the responsible use of machine learning in science.

“When we graduate from traditional statistical methods to machine learning methods, there are a vastly greater number of ways to shoot oneself in the foot,” said Arvind Narayanan , director of Princeton University’s   Center for Information Technology Policy , who led the research team along with Princeton computer scientist Sayash Kapoor. “If we don’t have an intervention to improve our scientific standards and reporting standards when it comes to machine learning-based science, we risk not just one discipline but many different scientific disciplines rediscovering these crises one after another.”

Because machine learning methods are new and used by many different disciplines, it is important to develop guidelines that can ensure the credibility of these methods as their use expands. A paper detailing their guidelines was recently published in the journal Science Advances.

“Many researchers are concerned with the emerging reproducibility crisis in the use of these methods, which could be as serious as the replication crisis that emerged in social psychology more than a decade ago,” Serra-Garcia said, an associate professor of economics and strategy at the Rady School.

The good news is that a simple set of best practices can help resolve this newer crisis before it gets out of hand, according to the authors, who come from computer science, mathematics, social science and health research.

“This is a systematic problem with systematic solutions,” said Kapoor , a graduate student who works with Narayanan and who organized the effort to produce the new consensus-based checklist.

The checklist focuses on ensuring the integrity of research that uses machine learning. Science depends on the ability to independently reproduce results and validate claims. Otherwise, new work cannot be reliably built atop old work, and the entire enterprise collapses. While other researchers have developed checklists that apply to discipline-specific problems, notably in medicine, the new guidelines start with the underlying methods and apply them to any quantitative discipline.

{/exp:typographee}

Marta Serra-Garcia Associate Professor of Economics and Strategy

One of the main takeaways is transparency. The checklist calls on researchers to provide detailed descriptions of each machine learning model, including the code, the data used to train and test the model, the hardware specifications used to produce the results, the experimental design, the project’s goals and any limitations of the study’s findings. The standards are flexible enough to accommodate a wide range of nuance, including private datasets and complex hardware configurations, according to the authors.

While the increased rigor of these new standards might slow the publication of any given study, the authors believe wide adoption of these standards would increase the overall rate of discovery and innovation, potentially by a significant amount.

“What we ultimately care about is the pace of scientific progress,” said sociologist Emily Cantrell , one of the lead authors, who is pursuing her Ph.D. at Princeton. “By making sure the papers that get published are of high quality and that they’re a solid base for future papers to build on, that potentially then speeds up the pace of scientific progress. Focusing on scientific progress itself and not just getting papers out the door is really where our emphasis should be.”

Kapoor concurred. The errors hurt. “At the collective level, it’s just a major time sink,” he said. That time costs money. And that money, once wasted, could have catastrophic downstream effects, limiting the kinds of science that attract funding and investment, tanking ventures that are inadvertently built on faulty science and discouraging countless numbers of young researchers.

In working toward a consensus about what should be included in the guidelines, the authors said they aimed to strike a balance: simple enough to be widely adopted, comprehensive enough to catch as many common mistakes as possible.

They say researchers could adopt the standards to improve their own work; peer reviewers could use the checklist to assess papers; and journals could adopt the standards as a requirement for publication.

“The scientific literature, especially in applied machine learning research, is full of avoidable errors,” Narayanan said. “And we want to help people. We want to keep honest people honest.”

The paper, “ Consensus-based recommendations for machine-learning-based science ,” published on May 1 in Science Advances, included the following authors: Sayash Kapoor, Princeton University; Emily Cantrell, Princeton University; Kenny Peng, Cornell University; Thanh Hien (Hien) Pham, Princeton University; Christopher A. Bail, Duke University; Odd Erik Gundersen, Norwegian University of Science and Technology; Jake M. Hofman, Microsoft Research; Jessica Hullman, Northwestern University; Michael A. Lones, Heriot-Watt University; Momin M. Malik, Center for Digital Health, Mayo Clinic; Priyanka Nanayakkara, Northwestern; Russell A. Poldrack, Stanford University; Inioluwa Deborah Raji, University of California-Berkeley; Michael Roberts, University of Cambridge; Matthew J. Salganik, Princeton University; Marta Serra-Garcia, University of California-San Diego; Brandon M. Stewart, Princeton University; Gilles Vandewiele, Ghent University; and Arvind Narayanan, Princeton University.

— Adapted from a Princeton University release

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Princeton University

Princeton engineering, the science of static shock jolted into the 21st century.

By Scott Lyon

April 9, 2024

Static electricity has puzzled scientists for thousands of years. Above, water ions carry charge between two electrically insulating materials. The blue mesh represents the flow of charge that could be felt as a spark. Image courtesy of the researchers

Shuffling across the carpet to zap a friend may be the oldest trick in the book, but on a deep level that prank still mystifies scientists, even after thousands of years of study.

Now Princeton researchers have sparked new life into static. Using millions of hours of computational time to run detailed simulations, the researchers found a way to describe static charge atom-by-atom with the mathematics of heat and work. Their paper appeared in Nature Communications on March 23.

The study looked specifically at how charge moves between materials that do not allow the free flow of electrons, called insulating materials, such as vinyl and acrylic. The researchers said there is no established view on what mechanisms drive these jolts, despite the ubiquity of static: the crackle and pop of clothes pulled from a dryer, packing peanuts that cling to a box.

“We know it’s not electrons,” said Mike Webb , assistant professor of chemical and biological engineering , who led the study. “What is it?”

Webb first asked himself that question as a postdoctoral researcher at the University of Chicago. He puzzled over it with colleagues, baffled that such a common phenomenon could be so poorly understood. But the more they looked, the more insurmountable the questions became. “It just seemed out of reach,” he said.

It had been out of reach since Thales of Miletus first rubbed amber with fur and watched the amber (Greek: elektron ) collect feathers and dust — 26 centuries ago. Thales was one of the first people to explain nature through reason rather than supernatural forces. He played a critical role in the development of philosophy and eventually science. Despite the depth and breadth of knowledge accumulated over subsequent millennia, despite the myriad technologies born of that knowledge, science, in all that time, never cracked static. Maybe it never would.

At Princeton Webb got to talking to his colleague Sankaran Sundaresan , a leading expert in chemical reaction engineering who specializes in the flow of materials in gaseous chambers. In those environments, loaded with volatile chemicals, a stray spark could be deadly. Sundaresan had worked with static charge for decades, using reliable experimental data to predict but not fully fathom how charge moved in these systems.

“I treat that like a black box,” said Sundaresan, the Norman John Sollenberger Professor in Engineering. “We do some experiments and the experiments tell me: This is what happens. This is the charge.” He works down to the limit and carefully notes what he sees. What happens inside the black box remains a mystery.

One thing you find no matter where you look, though, according to Sundaresan, is trace amounts of water. Charged water molecules are everywhere, in nearly everything, clinging to virtually every surface on Earth. Even in extremely arid conditions, under intense heat, stray water ions pool into microscopic oases that harbor electrical charge.

Incidentally, Thales is best known not for his work on electricity but for an even grander project. He proposed that the entirety of nature was made of water, that water was the ur-substance, the essential stuff. It was the first attempt at a unified theory of everything. Aristotle wrote it all down.

Over the arc of Sundaresan’s career, he and his colleagues shrunk that black box so that the mysteries have been pushed ever deeper. But mysteries they remain.

The conversation between him and Webb led to a mutual realization: Sundaresan had decades of insight into data from reactors, and Webb could apply sophisticated atom-scale computational techniques to look at these water ions from the perspective of thermodynamics. How much energy would it take for a water ion to bolt from surface to surface? Maybe that would explain what was happening inside Sundaresan’s black box. The unresolved puzzle from Webb’s postdoc days came unlocked.

By modeling the relationship between charged water molecules and the amount of energy those molecules have available to propel them between surfaces, Webb and graduate student Hang Zhang demonstrated a very precise mathematical approximation of how electrical charge moves between two insulating materials.

In other words, they used math to simulate the movement of around 80,000 atoms. Those simulations matched real-life observations with a very high degree of precision. It turns out, in all likelihood, static shock is a function of water, and more specifically, the free energy of stray water ions. With that framework, Webb and Zhang revealed the molecular underpinnings of those familiar shocks in infinitesimal detail. They blew Sundaresan’s black box wide open. If only Thales could see.

The paper “Thermodynamic driving forces in contact electrification between polymeric materials” was published March 23 in the journal Nature Communications. Support for this work was provided by the Princeton Innovation Project X Fund and the U.S. Department of Energy. The simulations and analyses were performed using the resources of Princeton Research Computing.

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Research in Science Education (RISE): A Review (and Story) of Research in RISE Articles (1994–2018)

• Published: 01 June 2020
• Volume 52 , pages 205–237, ( 2022 )

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To celebrate the 50th anniversary of the Australasian Science Education Research Association’s annual conference, this paper reviews the last 25 years of the Association’s journal Research in Science Education ( RISE ). All RISE papers, at 4-year intervals (1994–2018; seven volumes), were reviewed: a total of 262/970 (27%) papers. Abstracts, together with the methodology/methods sections, were the main source of data, although theoretical/conceptual frameworks were also identified. Using a range of research indicators (e.g., research theme; paradigm and research design/methodology choice; methods used; sample characteristics; authors’ nationality), various trends emerged. Other data and trends were accessed using the Scopus database (e.g., research areas, most cited papers). Comparisons are made with similar reviews of the leading international science education journals ( JRST, Science Education and IJSE ), as well as White’s review for the first 25 years of ASERA ( RISE, 27 (2)). Findings indicate the increasing diversity of areas investigated, the mix of research approaches used, and a plurality of research designs. Trends are interpreted and overlooked areas identified. Future research possibilities are proffered and the direction that RISE appears to be heading.

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Trends in Science Education Research in Taiwan: A Content Analysis of the Chinese Journal of Science Education from 1993 to 2012

A bibliometric analysis of Research on Education 4.0 during the 2017–2021 period

A decade revisited and a step toward the future: incremental but quintessential progress

To celebrate the 50th anniversary of ASERA, this paper was presented at the 2019 conference in Queenstown, New Zealand.

There were no conference proceedings in 1969. Early conference volumes were titled Research 1971 and Science Education Research 1973. From 1974, RISE was the adopted title. For an early history of RISE , see Gardner ( 1994 , pp.vi–vii) and https://www.asera.org.au/about/history .

SJR (Scimago Journal and Country Rank) rankings (across “Education” journals) and 2016 and 2017 impact factors were: JRST (17; 3.007 & 2.708); SE (31; 2.151 & 2.240); RISE (120; 1.328 & 1.019), and IJSE (143; 1.223 & 0.906) (SJR: https://www.scimagojr.com accessed May 7, 2019; sources for the 2017 impact factors are from the journals’ websites).

It is acknowledged that some argue that “research design” is more inclusive in that it embraces the whole research enterprise (e.g., research questions etc.) (e.g., see Babbie 2016 ).

The WoS database did not include RISE issues from 1995 to 2001. Hence, Chang et al.’s RISE analyses are therefore incomplete and their conclusions may not hold.

This was mainly due to a Special Issue on “Science and technology studies and science education” (1998).

Recall that RISE (1994) was only conference proceedings, while in 1995 RISE was an international refereed journal.

Tippet et al.‘s (2019) RISE analysis (1971–2019) found ECE teachers were the focus of some papers.

There were five autobiographical studies by university lecturers (in Special issue ‘Autobiography and science education’ (2000)).

As completing a degree was not a requirement in the pre-service education of Australian primary and secondary teachers during the early years of RISE , White’s undergraduate figures may have included more non-teacher education undergraduates.

As the 7V analyses were completed, an informal determination of the dominant theoretical/conceptual bases of the RISE papers was recorded. It was consistent with the Scopus analyses. Main 7V themes and their dominant years were constructivism/conceptual change/conceptions (23%; 1994), classroom processes (12%; 2010), pedagogical content knowledge (9%; 2018), nature of science (6%; 2018), and student views and attributes (e.g., reasoning) (6%; 2010).

Interestingly, a very common component of PCK, “explaining scientific concepts,” has received scant attention in RISE with only seven papers exploring this issue since 1983 (Geelan 2019 ).

Some papers revolving around socio-scientific issues did use environmental contexts (e.g., climate change).

Data from O’Toole et al. ( 2018 ) were not used for comparison purposes as they stated that the “type” of research (as defined in this paper) could only be identified in 56% of abstracts.

Other researchers are also “stakeholders.” Chang et al. ( 2010 ), for example, pose an interesting question: does an increase in published papers in an area mean that they are impacting other researchers? The example of an increase in published Turkish papers (in earth science) was investigated, and it was found that they were not accompanied by an increase in citation frequency; this type of investigation warrants such an analysis for RISE papers.

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Acknowledgments

The ASERA board for providing the opportunity to undertake this review of RISE ; it was a privilege and a pleasure. Reviewers: their critiques and insights improved the final version of this paper.

Former editors of RISE (Campbell McRobbie, Stephen Ritchie, and David Geelan) provided feedback on a draft version of this paper; their input was appreciated.

Marty Williams, Liaison Librarian, Southern Cross University, was extremely helpful in negotiating the use of Scopus and WoS databases.

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Typical topics in the NARST research themes (Lee et al. 2009 , p.2003) and Chang et al.’s ( 2010 , pp. 315–23) areas

Teacher education: Pre-service and continuing professional development of teachers; teacher education programs and policy; field experience; issues related to teacher education reform.

Teaching: Teacher cognition; pedagogical knowledge and pedagogical content knowledge; forms of knowledge representation; exemplary teachers; teacher thinking; teaching behaviors and strategies.

Learning—students’ conceptions and conceptual change (Learning—conception): Methods for investigating student understanding; students’ alternative conceptions; instructional approaches for conceptual change; conceptual change in learners; conceptual development.

Learning—classroom contexts and learner characteristics (Learning—context): Student motivation; learning environment; individual differences; reasoning; learning approaches; exceptionality; teacher–student interactions; peer interactions; laboratory environments; affective dimensions of science learning; cooperative learning; language, writing, and discourse in learning; social, political, and economic factors.

Goals and policy, curriculum, evaluation, and assessment: Curriculum development, change, implementation, dissemination and evaluation; social analysis of curriculum; alternative forms of assessment; teacher evaluation; educational measurement; identifying effective schools; curriculum policy and reform.

Cultural, social and gender issues: Multicultural and bilingual issues; ethnic issues; gender issues; comparative studies; issues of diversity related to science teaching and learning.

History, philosophy, epistemology, and nature of science: Historical issues; philosophical issues; epistemological issues; ethical and moral issues; nature of science.

Educational technology: Computers; interactive multimedia; video; integration of technology into teaching; learning and assessment involving the use of technology.

Informal Learning: Science learning in informal contexts (e.g., museums, outdoor settings, etc.); public awareness of science.

Chang et al.’s areas: Scientific concept, Instructional practice, Conceptual change and concept mapping, Professional development; Conceptual change and analogy; Nature of science and socio-scientific issues; Reasoning skill and problem solving; Attitude and gender; and Design-based and urban education.

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Skamp, K. Research in Science Education (RISE): A Review (and Story) of Research in RISE Articles (1994–2018). Res Sci Educ 52 , 205–237 (2022). https://doi.org/10.1007/s11165-020-09934-w

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Published : 01 June 2020

Issue Date : February 2022

DOI : https://doi.org/10.1007/s11165-020-09934-w

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