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Designing Assignments for Learning

The rapid shift to remote teaching and learning meant that many instructors reimagined their assessment practices. Whether adapting existing assignments or creatively designing new opportunities for their students to learn, instructors focused on helping students make meaning and demonstrate their learning outside of the traditional, face-to-face classroom setting. This resource distills the elements of assignment design that are important to carry forward as we continue to seek better ways of assessing learning and build on our innovative assignment designs.

On this page:

Rethinking traditional tests, quizzes, and exams.

  • Examples from the Columbia University Classroom
  • Tips for Designing Assignments for Learning

Reflect On Your Assignment Design

Connect with the ctl.

  • Resources and References

Cite this resource: Columbia Center for Teaching and Learning (2021). Designing Assignments for Learning. Columbia University. Retrieved [today’s date] from https://ctl.columbia.edu/resources-and-technology/teaching-with-technology/teaching-online/designing-assignments/

assignment design new model images

Traditional assessments tend to reveal whether students can recognize, recall, or replicate what was learned out of context, and tend to focus on students providing correct responses (Wiggins, 1990). In contrast, authentic assignments, which are course assessments, engage students in higher order thinking, as they grapple with real or simulated challenges that help them prepare for their professional lives, and draw on the course knowledge learned and the skills acquired to create justifiable answers, performances or products (Wiggins, 1990). An authentic assessment provides opportunities for students to practice, consult resources, learn from feedback, and refine their performances and products accordingly (Wiggins 1990, 1998, 2014). 

Authentic assignments ask students to “do” the subject with an audience in mind and apply their learning in a new situation. Examples of authentic assignments include asking students to: 

  • Write for a real audience (e.g., a memo, a policy brief, letter to the editor, a grant proposal, reports, building a website) and/or publication;
  • Solve problem sets that have real world application; 
  • Design projects that address a real world problem; 
  • Engage in a community-partnered research project;
  • Create an exhibit, performance, or conference presentation ;
  • Compile and reflect on their work through a portfolio/e-portfolio.

Noteworthy elements of authentic designs are that instructors scaffold the assignment, and play an active role in preparing students for the tasks assigned, while students are intentionally asked to reflect on the process and product of their work thus building their metacognitive skills (Herrington and Oliver, 2000; Ashford-Rowe, Herrington and Brown, 2013; Frey, Schmitt, and Allen, 2012). 

It’s worth noting here that authentic assessments can initially be time consuming to design, implement, and grade. They are critiqued for being challenging to use across course contexts and for grading reliability issues (Maclellan, 2004). Despite these challenges, authentic assessments are recognized as beneficial to student learning (Svinicki, 2004) as they are learner-centered (Weimer, 2013), promote academic integrity (McLaughlin, L. and Ricevuto, 2021; Sotiriadou et al., 2019; Schroeder, 2021) and motivate students to learn (Ambrose et al., 2010). The Columbia Center for Teaching and Learning is always available to consult with faculty who are considering authentic assessment designs and to discuss challenges and affordances.   

Examples from the Columbia University Classroom 

Columbia instructors have experimented with alternative ways of assessing student learning from oral exams to technology-enhanced assignments. Below are a few examples of authentic assignments in various teaching contexts across Columbia University. 

  • E-portfolios: Statia Cook shares her experiences with an ePorfolio assignment in her co-taught Frontiers of Science course (a submission to the Voices of Hybrid and Online Teaching and Learning initiative); CUIMC use of ePortfolios ;
  • Case studies: Columbia instructors have engaged their students in authentic ways through case studies drawing on the Case Consortium at Columbia University. Read and watch a faculty spotlight to learn how Professor Mary Ann Price uses the case method to place pre-med students in real-life scenarios;
  • Simulations: students at CUIMC engage in simulations to develop their professional skills in The Mary & Michael Jaharis Simulation Center in the Vagelos College of Physicians and Surgeons and the Helene Fuld Health Trust Simulation Center in the Columbia School of Nursing; 
  • Experiential learning: instructors have drawn on New York City as a learning laboratory such as Barnard’s NYC as Lab webpage which highlights courses that engage students in NYC;
  • Design projects that address real world problems: Yevgeniy Yesilevskiy on the Engineering design projects completed using lab kits during remote learning. Watch Dr. Yesilevskiy talk about his teaching and read the Columbia News article . 
  • Writing assignments: Lia Marshall and her teaching associate Aparna Balasundaram reflect on their “non-disposable or renewable assignments” to prepare social work students for their professional lives as they write for a real audience; and Hannah Weaver spoke about a sandbox assignment used in her Core Literature Humanities course at the 2021 Celebration of Teaching and Learning Symposium . Watch Dr. Weaver share her experiences.  

​Tips for Designing Assignments for Learning

While designing an effective authentic assignment may seem like a daunting task, the following tips can be used as a starting point. See the Resources section for frameworks and tools that may be useful in this effort.  

Align the assignment with your course learning objectives 

Identify the kind of thinking that is important in your course, the knowledge students will apply, and the skills they will practice using through the assignment. What kind of thinking will students be asked to do for the assignment? What will students learn by completing this assignment? How will the assignment help students achieve the desired course learning outcomes? For more information on course learning objectives, see the CTL’s Course Design Essentials self-paced course and watch the video on Articulating Learning Objectives .  

Identify an authentic meaning-making task

For meaning-making to occur, students need to understand the relevance of the assignment to the course and beyond (Ambrose et al., 2010). To Bean (2011) a “meaning-making” or “meaning-constructing” task has two dimensions: 1) it presents students with an authentic disciplinary problem or asks students to formulate their own problems, both of which engage them in active critical thinking, and 2) the problem is placed in “a context that gives students a role or purpose, a targeted audience, and a genre.” (Bean, 2011: 97-98). 

An authentic task gives students a realistic challenge to grapple with, a role to take on that allows them to “rehearse for the complex ambiguities” of life, provides resources and supports to draw on, and requires students to justify their work and the process they used to inform their solution (Wiggins, 1990). Note that if students find an assignment interesting or relevant, they will see value in completing it. 

Consider the kind of activities in the real world that use the knowledge and skills that are the focus of your course. How is this knowledge and these skills applied to answer real-world questions to solve real-world problems? (Herrington et al., 2010: 22). What do professionals or academics in your discipline do on a regular basis? What does it mean to think like a biologist, statistician, historian, social scientist? How might your assignment ask students to draw on current events, issues, or problems that relate to the course and are of interest to them? How might your assignment tap into student motivation and engage them in the kinds of thinking they can apply to better understand the world around them? (Ambrose et al., 2010). 

Determine the evaluation criteria and create a rubric

To ensure equitable and consistent grading of assignments across students, make transparent the criteria you will use to evaluate student work. The criteria should focus on the knowledge and skills that are central to the assignment. Build on the criteria identified, create a rubric that makes explicit the expectations of deliverables and share this rubric with your students so they can use it as they work on the assignment. For more information on rubrics, see the CTL’s resource Incorporating Rubrics into Your Grading and Feedback Practices , and explore the Association of American Colleges & Universities VALUE Rubrics (Valid Assessment of Learning in Undergraduate Education). 

Build in metacognition

Ask students to reflect on what and how they learned from the assignment. Help students uncover personal relevance of the assignment, find intrinsic value in their work, and deepen their motivation by asking them to reflect on their process and their assignment deliverable. Sample prompts might include: what did you learn from this assignment? How might you draw on the knowledge and skills you used on this assignment in the future? See Ambrose et al., 2010 for more strategies that support motivation and the CTL’s resource on Metacognition ). 

Provide students with opportunities to practice

Design your assignment to be a learning experience and prepare students for success on the assignment. If students can reasonably expect to be successful on an assignment when they put in the required effort ,with the support and guidance of the instructor, they are more likely to engage in the behaviors necessary for learning (Ambrose et al., 2010). Ensure student success by actively teaching the knowledge and skills of the course (e.g., how to problem solve, how to write for a particular audience), modeling the desired thinking, and creating learning activities that build up to a graded assignment. Provide opportunities for students to practice using the knowledge and skills they will need for the assignment, whether through low-stakes in-class activities or homework activities that include opportunities to receive and incorporate formative feedback. For more information on providing feedback, see the CTL resource Feedback for Learning . 

Communicate about the assignment 

Share the purpose, task, audience, expectations, and criteria for the assignment. Students may have expectations about assessments and how they will be graded that is informed by their prior experiences completing high-stakes assessments, so be transparent. Tell your students why you are asking them to do this assignment, what skills they will be using, how it aligns with the course learning outcomes, and why it is relevant to their learning and their professional lives (i.e., how practitioners / professionals use the knowledge and skills in your course in real world contexts and for what purposes). Finally, verify that students understand what they need to do to complete the assignment. This can be done by asking students to respond to poll questions about different parts of the assignment, a “scavenger hunt” of the assignment instructions–giving students questions to answer about the assignment and having them work in small groups to answer the questions, or by having students share back what they think is expected of them.

Plan to iterate and to keep the focus on learning 

Draw on multiple sources of data to help make decisions about what changes are needed to the assignment, the assignment instructions, and/or rubric to ensure that it contributes to student learning. Explore assignment performance data. As Deandra Little reminds us: “a really good assignment, which is a really good assessment, also teaches you something or tells the instructor something. As much as it tells you what students are learning, it’s also telling you what they aren’t learning.” ( Teaching in Higher Ed podcast episode 337 ). Assignment bottlenecks–where students get stuck or struggle–can be good indicators that students need further support or opportunities to practice prior to completing an assignment. This awareness can inform teaching decisions. 

Triangulate the performance data by collecting student feedback, and noting your own reflections about what worked well and what did not. Revise the assignment instructions, rubric, and teaching practices accordingly. Consider how you might better align your assignment with your course objectives and/or provide more opportunities for students to practice using the knowledge and skills that they will rely on for the assignment. Additionally, keep in mind societal, disciplinary, and technological changes as you tweak your assignments for future use. 

Now is a great time to reflect on your practices and experiences with assignment design and think critically about your approach. Take a closer look at an existing assignment. Questions to consider include: What is this assignment meant to do? What purpose does it serve? Why do you ask students to do this assignment? How are they prepared to complete the assignment? Does the assignment assess the kind of learning that you really want? What would help students learn from this assignment? 

Using the tips in the previous section: How can the assignment be tweaked to be more authentic and meaningful to students? 

As you plan forward for post-pandemic teaching and reflect on your practices and reimagine your course design, you may find the following CTL resources helpful: Reflecting On Your Experiences with Remote Teaching , Transition to In-Person Teaching , and Course Design Support .

The Columbia Center for Teaching and Learning (CTL) is here to help!

For assistance with assignment design, rubric design, or any other teaching and learning need, please request a consultation by emailing [email protected]

Transparency in Learning and Teaching (TILT) framework for assignments. The TILT Examples and Resources page ( https://tilthighered.com/tiltexamplesandresources ) includes example assignments from across disciplines, as well as a transparent assignment template and a checklist for designing transparent assignments . Each emphasizes the importance of articulating to students the purpose of the assignment or activity, the what and how of the task, and specifying the criteria that will be used to assess students. 

Association of American Colleges & Universities (AAC&U) offers VALUE ADD (Assignment Design and Diagnostic) tools ( https://www.aacu.org/value-add-tools ) to help with the creation of clear and effective assignments that align with the desired learning outcomes and associated VALUE rubrics (Valid Assessment of Learning in Undergraduate Education). VALUE ADD encourages instructors to explicitly state assignment information such as the purpose of the assignment, what skills students will be using, how it aligns with course learning outcomes, the assignment type, the audience and context for the assignment, clear evaluation criteria, desired formatting, and expectations for completion whether individual or in a group.

Villarroel et al. (2017) propose a blueprint for building authentic assessments which includes four steps: 1) consider the workplace context, 2) design the authentic assessment; 3) learn and apply standards for judgement; and 4) give feedback. 

References 

Ambrose, S. A., Bridges, M. W., & DiPietro, M. (2010). Chapter 3: What Factors Motivate Students to Learn? In How Learning Works: Seven Research-Based Principles for Smart Teaching . Jossey-Bass. 

Ashford-Rowe, K., Herrington, J., and Brown, C. (2013). Establishing the critical elements that determine authentic assessment. Assessment & Evaluation in Higher Education. 39(2), 205-222, http://dx.doi.org/10.1080/02602938.2013.819566 .  

Bean, J.C. (2011). Engaging Ideas: The Professor’s Guide to Integrating Writing, Critical Thinking, and Active Learning in the Classroom . Second Edition. Jossey-Bass. 

Frey, B. B, Schmitt, V. L., and Allen, J. P. (2012). Defining Authentic Classroom Assessment. Practical Assessment, Research, and Evaluation. 17(2). DOI: https://doi.org/10.7275/sxbs-0829  

Herrington, J., Reeves, T. C., and Oliver, R. (2010). A Guide to Authentic e-Learning . Routledge. 

Herrington, J. and Oliver, R. (2000). An instructional design framework for authentic learning environments. Educational Technology Research and Development, 48(3), 23-48. 

Litchfield, B. C. and Dempsey, J. V. (2015). Authentic Assessment of Knowledge, Skills, and Attitudes. New Directions for Teaching and Learning. 142 (Summer 2015), 65-80. 

Maclellan, E. (2004). How convincing is alternative assessment for use in higher education. Assessment & Evaluation in Higher Education. 29(3), June 2004. DOI: 10.1080/0260293042000188267

McLaughlin, L. and Ricevuto, J. (2021). Assessments in a Virtual Environment: You Won’t Need that Lockdown Browser! Faculty Focus. June 2, 2021. 

Mueller, J. (2005). The Authentic Assessment Toolbox: Enhancing Student Learning through Online Faculty Development . MERLOT Journal of Online Learning and Teaching. 1(1). July 2005. Mueller’s Authentic Assessment Toolbox is available online. 

Schroeder, R. (2021). Vaccinate Against Cheating With Authentic Assessment . Inside Higher Ed. (February 26, 2021).  

Sotiriadou, P., Logan, D., Daly, A., and Guest, R. (2019). The role of authentic assessment to preserve academic integrity and promote skills development and employability. Studies in Higher Education. 45(111), 2132-2148. https://doi.org/10.1080/03075079.2019.1582015    

Stachowiak, B. (Host). (November 25, 2020). Authentic Assignments with Deandra Little. (Episode 337). In Teaching in Higher Ed . https://teachinginhighered.com/podcast/authentic-assignments/  

Svinicki, M. D. (2004). Authentic Assessment: Testing in Reality. New Directions for Teaching and Learning. 100 (Winter 2004): 23-29. 

Villarroel, V., Bloxham, S, Bruna, D., Bruna, C., and Herrera-Seda, C. (2017). Authentic assessment: creating a blueprint for course design. Assessment & Evaluation in Higher Education. 43(5), 840-854. https://doi.org/10.1080/02602938.2017.1412396    

Weimer, M. (2013). Learner-Centered Teaching: Five Key Changes to Practice . Second Edition. San Francisco: Jossey-Bass. 

Wiggins, G. (2014). Authenticity in assessment, (re-)defined and explained. Retrieved from https://grantwiggins.wordpress.com/2014/01/26/authenticity-in-assessment-re-defined-and-explained/

Wiggins, G. (1998). Teaching to the (Authentic) Test. Educational Leadership . April 1989. 41-47. 

Wiggins, Grant (1990). The Case for Authentic Assessment . Practical Assessment, Research & Evaluation , 2(2). 

Wondering how AI tools might play a role in your course assignments?

See the CTL’s resource “Considerations for AI Tools in the Classroom.”

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Center for Teaching Innovation

Ai in assignment design.

Using generative artificial intelligence (AI) can be both productive and limiting—it can help students to create and revise content, yet it also has the potential to undermine the process by which students create. When incorporated effectively into assignments, generative AI can be leveraged to stimulate students' ability to apply essential knowledge and develop critical thinking skills. 

As you explore the possible uses of generative AI in your course, note that establishing a general familiarity with generative AI and being mindful of accessibility and ethical concerns will be helpful. 

The following process may help you determine how to best incorporate generative AI into your course assignments.

Affirm What You Actually Want to Assess

As you decide how you might incorporate AI into your course, it’s important to revisit your current course assessment plan, most importantly your course learning outcomes —that is, the skills and knowledge you want students to learn and demonstrate by the end of your course. Once you have a clear idea of the specific skills/knowledge you want to assess, the following questions can help determine whether or not your current assignments are effective and assessing what you want them to assess:

  • Does my assignment call for the same type of thinking skills that are articulated in my class outcomes? For example, if my course learning outcome calls for students to analyze major themes in a work, is there risk of my final assignment prompting students to do more (e.g., synthesize multiple themes across multiple works) or to do less (e.g., merely identify a theme) than this outcome? If so, there may be a misalignment that can easily be addressed.
  • Does my assignment call for the same type of thinking skills that students have actually practiced in class? For example, if I am asking students to generate a research prospectus, have I given them adequate opportunity to develop—and receive feedback on—this skill in class?
  • Depending on your discipline, is there a need for an additional course outcome that honors what students now need to know about the use of generative AI in your course/field?

Explore When & How Generative AI Can Facilitate Student Learning

Once you have affirmed your learning outcomes and ensured that your assignments are properly aligned with those outcomes, think about if, when, and how it might make sense to incorporate generative AI. Is there a way to leverage generative AI to engage students in deeper learning, provide meaningful practice, or help scaffold your assignments?

Consider the usefulness of generative AI to serve as:

  • Have students analyze AI-generated texts to articulate what constitutes “good” (and not so good) responses to prompts.
  • Have students analyze AI-generated texts and engage in error analysis to develop more nuanced and discipline-specific writing skills.
  • Leverage the use of generative AI platforms to help students become more discerning. This can help students develop the critical thinking and information literacy skills required to effectively and responsibly use such platforms.
  • Have students revise AI-generated texts to develop critical thinking skills.
  • Have students engage with a generative AI platform as a tutor. 
  • Facilitate students’ responsible, self-guided use of generative AI to develop select discipline specific skills (e.g., coding in computer science courses)
  • Have students use generative AI to off-load repetitive tasks.
  • Have students use generative AI to conduct preliminary analysis of data sets to confirm broad takeaways and affirm that their more nuanced analysis is heading in the right direction.

Identify When Generative AI Cannot Facilitate Student Learning

It is often the case that students cannot—or should not—leverage generative AI to promote or demonstrate their own learning. To help ensure that your assignment design highlights students’ unique perspectives and underscores the importance of a (non-generative AI informed) discipline-specific process, consider how to emphasize metacognition, authentic application, thematic connection, or personal reflection.  

Even if another part of an assignment calls for the use of generative AI, the following strategies may supplement the uses of AI highlighted above and foster deep and meaningful learning:

  • Have students identify the successes and challenges they experienced throughout the completion of a project.
  • Have students set incremental goals throughout a project, highlighting next steps of a discipline-specific process, resources they used, and the steps about which they are enthusiastic/nervous.
  • Have students self-assess their work, identifying strengths and weaknesses of their product/effort.
  • Have students engage in problem-based learning projects, ideally in authentic settings (e.g., problems that focus on our local community, real-world challenges, real-world industries, etc.).
  • Have students present projects (and engage with) authentic audiences (e.g., real stakeholders, discipline-specific research partners, native-speaking language partners, etc.)
  • Have students connect select reading(s) to course experiences (e.g., labs, field experiences, class discussions). 
  • Leverage Canvas-based tools that promote student-to-student interactions (e.g., Hypothesis for social annotation or FeedbackFruits for peer review and feedback).
  • Have students provide a reflective rationale for choices made throughout the completion of a class project (e.g., an artist statement, response to a reflection prompt about personal relevance of source selections)
  • Have students connect course experiences/motivations to their own lived experiences.

Create Transparent Assignment Materials

Once you have thought about whether or not generative AI can be effectively incorporated into your assignments, it is important to create assignment materials that are transparent (Winkelmes, et al., 2019). Specifically, this means creating ways to communicate to students the task you are are requiring, along with its purpose and evaluative criteria:

  • Task. Students will benefit from having a clear and accessible set of directions for the project or assignment you are asking them to complete. 
  • Purpose. Students are often more motivated when they understand why a particular task is worth doing and what specific knowledge or skills they will develop by completing the assigned task.
  • Evaluative Criteria. Students benefit from having a clear sense of how their work will be evaluated and a full understanding of what good work looks like.

Communicate Your Expectations for Generative AI Use 

Regardless of the extent to which you incorporate the use of generative AI into your assignment design, it is essential to communicate your expectations to students. Sharing clear directions for assignments, communicating how students can be successful in your class, and promoting academic integrity serves both you and your students well. 

Example Assignment Policy Language for Generative AI Use

The following language on the use of generative AI may be helpful as you create directions for specific assignments. Please note that the following sample language does not reflect general, course-level perspectives on the use of generative AI tools. For sample course-level statements, see AI & Academic Integrity .

Prohibiting AI Use for a Specific Assignment

Allowing the use of generative ai for a specific assignment with attribution.

For full details on how to properly cite AI-generated work, please see the APA Style article, How to Cite ChatGPT . "

Encouraging the Use of Generative AI for a Specific Assignment with Attribution

For full details on how to properly cite AI- generated work, please see the APA Style article, How to Cite ChatGPT ."

Confer with Colleagues

There is almost always a benefit to discussing an assessment plan with colleagues, either within or beyond your department. Remember, too, that CTI offers consultations on any topic related to teaching and learning, and we are delighted to collaboratively review your course assessment plan. Visit our Consultations page to learn more, or contact us to set up a consultation.

2023 EducaUse Horizon Report | Teaching and Learning Edition. (2023, May 8). EDUCAUSE Library. https://library.educause.edu/resources/2023/5/2023-educause-horizon-report-teaching-and-learning-edition

Antoniak, M. (2023, June 22). Using large language models with care - AI2 blog. Medium. https://blog.allenai.org/using-large-language-models-with-care-eeb17b0aed27

Dinnar, S. M., Dede, C., Johnson, E., Straub, C. and Korjus, K. (2021), Artificial Intelligence and Technology in Teaching Negotiation. Negotiation Journal, 37: 65-82. https://doi.org/10.1111/nejo.12351

Jensen, T., Dede, C., Tsiwah, F., & Thompson, K. (2023, July 27). Who Does the Thinking: The Role of Generative AI in Higher Education. YouTube. International Association of Universities. Retrieved July 27, 2023.

OpenAI. (2023, February 16.). How should AI systems behave, and who should decide? https://openai.com/blog/how-should-ai-systems-behave

Winkelmes, M. A., Boye, A., & Tapp, S. (2019). Transparent design in higher education 

teaching and leadership: A guide to implementing the transparency framework institution-wide to improve learning and retention. Sterling, VA: Stylus Publishing .

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Teaching Commons > Teaching Guides > Assignment Design

Assignment Design

Strategies

Here's a short list of some general assignment design strategies that apply to a wide variety of disciplines.

Aligning with Learning Goals

A number of strategies for deterring plagiarism are discussed, including asking your students to write about current topics relevant to your course and staging essay assignments throughout the quarter.

Integrative Learning

​Integrative learning occurs when students make connections among ideas and experiences in order to transfer learning to new contexts.​

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Creative Assignments: Teaching with Images – Part 1

by Cosette Bruhns | Dec 17, 2019 | Instructional design , Services | 1 comment

assignment design new model images

Photo by Christopher Flynn on Unsplash

Images (e.g. photographs, illustrations, and visual metaphors) can facilitate student engagement and understanding in classroom assignments by making abstract concepts tangible and providing a different way of illustrating arguments to students. Instructors can assign images as submission requirements in order to encourage students to draw connections across boundaries and disciplines through a visual lens. Used with care, images can also support inclusive teaching practices by inviting students to engage with course content through different points of view, facilitating student access to remote objects or collections, and increasing opportunities for students who excel at visual learning to participate fully in assignments. In these cases, images serve as a portal for engaging with course material through a different framework (i.e., not text- or audio-based). Finally, using images in assignments can invite students to exercise different aspects of critical thinking skills, like visual literacy and lateral thinking, by encouraging students to develop an argument about or relating to some aspect of an image.

A Few Examples

Here are some examples of how images can be incorporated into student assignments to help you get started. The assignment types are listed in order of shallow to steep learning curve.

Image Discussion Board Posts

Discussion board posts are often assigned by instructors in order to invite students to expand their thoughts on a course reading or discussion. One way instructors can continue to broaden student learning about a topic outside of the classroom creatively is by assigning an image submission in a discussion board. By assigning an image as a submission requirement instead of text, instructors can stimulate student imagination and facilitate student ability to make visual connections between different ideas.

For example, in a literature course on Ovid’s Metamorphoses , an instructor could assign an image submission as a way to invite students to think about how to visualize an allegorical theme or passage from the text. Students could submit images in response to the selected theme or passage, along with a short one- to two-sentence explanation for why the image is related to the original theme. When the class next meets, instructors can draw on their image responses to engage students visually and creatively by asking students to further explain their reasons for submitting their image and why they think it is related to the original theme or passage.

For this type of assignment, Canvas-supported tools like Discussion Board can help achieve this goal. Follow the instructions on the Canvas resource page for more on how to create assignments using Canvas Discussion Board.

Example of an image post in a Canvas discussion board

Tip: When creating a discussion post, remember to select “Allow threaded replies” under Options, in order to let students respond to each other’s comments.

Image Annotation

Image annotation is the ability to mark up an image with text or visual symbols in order to highlight some aspect within the image. Applied to an assignment, instructors can use the idea of image annotation to introduce skills like visual literacy or visual analysis, by asking students to annotate images in order to make an argument about or pertaining to an image based on close analysis of an object or aspect of the original image. By emphasizing a specific aspect of an image, instructors can encourage students to think critically about the relationship between the image and concepts or themes addressed in class.

For example, in a class addressing early modern Italian art, an instructor could ask students to individually or collaboratively annotate an image of Duccio’s Maestà in order to analyze different historical, political, and theological themes represented in the painting. The instructor could create an assignment asking students to isolate specific elements of the painting, using annotation methods, in order to identify main themes to explore further through individual projects or in-class discussion, strengthening the relationship between the assignment and the course. It might be a useful exercise to create a working list of objects, ideas, or concepts identified through the image annotation assignment that students can build on during the course. In a course that examines multiple images, instructors could return to that set of student-produced themes to see how they are represented in other images representing the Madonna. By drawing connections between concepts and images, instructors can begin to introduce students to skills like visual literacy, which is important for interpreting, understanding, and making meaning from images.

There are a number of easy-to-use tools for image annotation that are readily available. Google Jamboard is an interactive whiteboard that can be shared with multiple students. Features of Google Jamboard include real-time collaboration and a number of creative drawing tools for visualizing ideas. In an image annotation assignment, students could share a Google Jamboard file with the class that creatively isolates an aspect of the original image in order to share an observation or build an argument about that image.

Duccio's Maesta annotated with Google Jamboard

Ex. Duccio di Buoninsegna, Maestà , c. 1308-1311. Google Jamboard can be used to add simple mark-ups to an image as an assignment or in real-time. The bottom tool in the tool bar is a digital laser pointer that can be used during a presentation to highlight an aspect of an image. As part of the Google Suite, Google Jamboard files can be easily shared with multiple collaborators.

Where to To Find Image Resources

A number of images are available for use in teaching and student assignments through fair use laws. There is a list of resources for finding fair use images on the UChicago wiki tools page . Many images are also easily searchable on databases such as LUNA , the University of Chicago’s image collections database, the Getty Search Gateway , and the Met Collection , to name a few. Several museums participate in open access policies, allowing their public domain images to be downloaded, used, and reproduced for scholarly and educational purposes. For further information on fair use policies, reach out to the University of Chicago’s Copyright Information Center , or the Visual Resource Center , which provides support in researching images or digitizing and developing a collection of images for research and teaching.

Getting Help and Next Steps

If you are interested in using image exercises in your classroom or as assignments, contact Academic Technology Solutions for help. ATS instructional designers can help you create exercises that support your broader learning objectives and select the appropriate software tools to use in your class.

Stay tuned for Part 2, in which we will discuss digital exhibitions!

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Thanks, Cosette, this is great. Take a look at WeVu for this too. Images and pdfs, with group annotation, with private and public replies to annotations. Can be used for whole-class dialogue about parts of images, or for assignments where students’ annotations are only seen by instructors.

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Assignment Design

Related links.

Designing Quantitative Reasoning Assignments

Ivan working with the Town of Arlington

To speed your work, check out the Discipline- and method-specific activity collections or browse activities that emphasize teaching with data in a variety of disciplines

Begin with explicitly articulated student learning outcomes for your course

What are the 4 to 7 key learning goals for this course? And how does teaching with data support students' achievement of those goals? It is easy to become excited by a new pedagogy when the research suggests it can notably enhance student learning. And when we are excited we want to dive right in. But before jumping in to revising assignments or course modules it is important to step back and identify the ways the new activities will connect with the primary objectives for the course.

This is true for at least two reasons. First, syllabi are very tight. Most faculty have never met a colleague who concluded a term saying, "With two weeks left in the term I had covered everything I felt I needed to cover. The rest of the term was just filler." Across all fields, faculty are keenly aware of disciplinary expectations of content coverage for courses. This sense of obligation is particularly sharp in courses which are pre-requisites for other courses in the curriculum. With so much external pressure, any aspect of a course that doesn't align with primary learning goals must be quickly tossed aside, no matter how much excitement surrounded its initial addition to the syllabus.

Second (and more importantly), innovations in teaching should never be done for the sake of "change." The goal is to teach students more effectively. While teaching with data often achieves that end, it is very time intensive (for both the faculty member and students) and so needs to be used deliberately when and where it is aligned with course goals.

Read more about course design

Consider having students work in teams to mitigate skills gaps

Sometimes teams can allow an instructor to work around variations in student experience with tools or methods. If you survey your class at the beginning of the term to find out who is comfortable with what, you can assign students to teams designed to ensure that each team has an "expert" in each tool and/or method required in the assignment.

If you choose to proceed in this direction, make sure to ask yourself whether you want all of the students to end up equally well-prepared with the required methods and tools. Is it okay if the one student who has experience with this instrument collects the data while others look on (and never learn to do it themselves)? If not, then be sure to build in time for peer instruction.

Read more about cooperative learning Read more about peer-led team learning

Consider "scaffolding" your teach-with-data assignment

students using the mouse

Scaffolding allows you to correct fundamental errors before they are inserted into the larger, final product. This serves two purposes. First, it helps students organize their work. Research shows that when students are asked to take on new tasks, they may experience regression in previously mastered skills. This predictably follows from having their attention devoted to the new task at hand. Scaffolding helps students see their work as a series of more manageable pieces.

The second purpose for scaffolding is more pragmatic. Teaching-with-data assignments often involve a complex interaction of tasks. (Indeed, that is often the point!) When students make a fundamental mistake in the first step, the resulting final product can be incredibly difficult to grade. While much of what the students did after making the early error "made sense," the final product may be irreparably damaged. The tension between "what follows makes sense given the error" and "the error leads to a ridiculous end point" can be very difficult to resolve.

Scaffolding also allows you to increase the complexity of assignments over the course of the term. For example, if some skills are not consistently taught in prior classes, then you can use assignments early in the term to teach students the methods you want them to use in the final project.

Of course, scaffolding need not be an either/or proposition. You may choose to scaffold assignments at the beginning of the term and then eliminate this guardrail as students gain confidence and competence. The main point is that instructors must equip students with the skills they need before they take on any new task.

Read more about scaffolding and sequencing

Provide instruction for the methods/tools students will need

Sometimes this principle can go without saying because the goal of the teaching-with-data activity is to teach students the new method or tool. But often our goal is to get students to wrestle with the data or the ideas behind the data. The analysis tool is just a vehicle. For example, you may ask students to explore the correlations between several variables using Excel. Despite fluently mastering hundreds of apps for the smart phones, a large fraction of students have never used a spreadsheet. Even a "simple" task like plotting the data in a scatter plot can pose significant challenges. Without instruction, students can waste time that was intended for data exploration.

While students often require instruction, this does not necessarily mean you need to provide it personally during class time. Most information technology departments can provide introductions to software tools. And many such tools have online tutorials which can be assigned to students who lack experience. However, the more specific the tool or method is to your discipline the more likely you will have to teach it yourself. Two areas that commonly require teaching: the use of statistical tools and understanding and creating graphs .

You get what you teach: Provide explicit instruction on data analysis and presentation

spring 2012 hackNY student hackathon presentations

Providing examples of high quality work will help some students. Better yet, provide a set of examples that demonstrates a range of quality. But most will need you to "walk them through" those examples to help them see what makes good work good. If you have a grading rubric, strongly consider sharing it with your students. As one colleague of mine said about her early (and bumpy) experience as a scholar, "I wasn't producing C work because I wanted to. It was just that no one had shown me how to produce A work!"

  • The literature on learning shows that students need two or more examples to distinguish surface characteristics from underlying principles--and you probably want them to focus on the principles! See Gick and Holyoak 1983 for the seminal research on the importance of multiple examples.
  • Jane Miller's Chicago Guide to Writing about Numbers provides a great model for showing students a set of examples of varying quality.)

Model the behaviors you want your students to adopt

Let your students see you engage data. Sometimes this may be staged. For example, when presenting a lecture you might show students a plot of the raw data and then "work through" the process of analysis in front of them. But don't be afraid to occasionally let them see you take on real, open-ended problems. Many students find it very powerful to see their teacher in the process, generating hypotheses in "real time." While it may feel risky to teach from material for which we don't know the answers, it teaches students the important lesson (particularly in the sciences) that scholarship is not about mastering a canon. Rather, it is about generating and exploring important new questions for which we do not have clear answers.

Either way, as you model the practices you value, be sure to call students' attention to the moves you are making (and that you wish them to copy).

Gick, M. L. and Holyoak, K. J. 1983. "Schema induction and analogical transfer," Cognitive Psychology , 15(1): 1-38.

Miller, J. E. 2004. The Chicago Guide to Writing about Numbers: The Effective Presentation of Quantitative Information. Chicago: University of Chicago Press.

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Generative AI in the Classroom

  • Developing Your AI Policy
  • Effective Use of AI for Teaching and Learning

Integrating AI into Assignments

Making assignments ai resistant, openai's guide to teaching with ai, student use cases for ai, assigning ai: seven approaches for students, with prompts, 80 ways to use chatgpt in the classroom.

  • How Does AI Think?
  • The Scholarly Conversation
  • US Government and UN Publications
  • TextGenEd: An Introduction to Teaching with Text Generation Technologies : an open access collection of ready-to-implement writing assignments integrating student use of technologies like ChatGPT; all have been taught at least once (see the table of contents to quickly view all of the assignments)  
  • “ What Does Learning Look Like ” according to AI?: a ready-to-implement discussion activity in which students discuss AI responses to the question, “what does learning look like?”

Handout from “Teaching & Learning in a ChatGPT World,” Nancy Chick’s presentation from rFLA Faculty meeting on March 2, 2023

Focus: thinking about the purpose of your writing assignments, capturing process (“the cutting room floor”) & not just product, alternatives to writing assignments

ChatGPT: students could use AI to cheat, but it’s a chance to rethink assessment altogether

Illingworth, Sam. “ChatGPT: Students Could Use AI to Cheat, but It’s a Chance to Rethink Assessment Altogether.” The Conversation , 19 Jan. 2023, http://theconversation.com/chatgpt-students-could-use-ai-to-cheat-but-its-a-chance-to-rethink-assessment-altogether-198019.

Focus: finding opportunities to make assignments, activities, and assessments more authentic

  • Teaching with AI by OpenAI a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias.

An Inspiring Minds series from Harvard Business Publishing: Education

This series addresses in depth specific ways to integrate students' use of AI into your teaching and learning. 

  • Prologue: Student Guidelines for AI Use  
  • Part 1: AI as Feedback Generator
  • Part 2: AI as Personal Tutor
  • Part 3: AI as Team Coach
  • Part 4: AI as Learner

For each of these roles, [the authors] offer practical recommendations—and a detailed, shareable prompt—for how exactly you can guide students in wielding AI to achieve these ends.

Abstract [Access Full Text]

This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks. Prompts are included for each of these approaches. The aim is to help students learn with and about AI, with practical strategies designed to mitigate risks such as complacency about the AI’s output, errors, and biases. These strategies promote active oversight, critical assessment of AI outputs, and complementarity of AI's capabilities with the students' unique insights. By challenging students to remain the "human in the loop," the authors aim to enhance learning outcomes while ensuring that AI serves as a supportive tool rather than a replacement. The proposed framework offers a guide for educators navigating the integration of AI-assisted learning in classrooms. 

[Access Full Text]   https://dx.doi.org/10.2139/ssrn.4475995  

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  • Last Updated: Jan 22, 2024 4:46 PM
  • URL: https://libguides.rollins.edu/generative_ai_in_the_classroom

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Designing assignments.

Making a few revisions to your writing assignments can make a big difference in the writing your students will produce. The most effective changes involve specifying what you would like students to do in the assignment and suggesting concrete steps students can take to achieve that goal.

Clarify what you want your students to do…and why they’re doing it

Kerry Walk, former director of the Princeton Writing Program, offers these principles to consider when designing a writing assignment (condensed and adapted from the original): “At least one sentence on your assignment sheet should explicitly state what you want students to do. The assignment is usually signaled by a verb, such as “analyze,” “assess,” “explain,” or “discuss.” For example, in a history course, after reading a model biography, students were directed as follows: ‘Your assignment is to write your own biographical essay on Mao, using Mao’s reminiscences (as told to a Western journalist), speeches, encyclopedia articles, a medical account from Mao’s physician, and two contradictory obituaries.’ In addition, including a purpose for the assignment can provide crucial focus and guidance. Explaining to students why they’re doing a particular assignment can help them grasp the big picture—what you’re trying to teach them and why learning it is worthwhile. For example, ‘This assignment has three goals: for you to (1) see how the concepts we’ve learned thus far can be used in a different field from economics, (2) learn how to write about a model, and (3) learn to critique a model or how to defend one.’”

Link course writing goals to assignments

Students are more likely to understand what you are asking them to do if the assignment re-uses language that you’ve already introduced in class discussions, in writing activities, or in your Writing Guide. In the assignment below, Yale professor Dorlores Hayden uses writing terms that have been introduced in class:

Choose your home town or any other town or city you have lived in for at least a year. Based upon the readings on the history of transportation, discuss how well or how poorly pedestrian, horse-drawn, steam- powered, and electric transportation might have served your town or city before the gasoline automobile. (If you live in a twentieth-century automobile-oriented suburb, consider rural transportation patterns before the car and the suburban houses.) How did topography affect transportation choices? How did transportation choices affect the local economy and the built environment? Length, 1000 words (4 typed pages plus a plan of the place and/or a photograph). Be sure to argue a strong thesis and back it up with quotations from the readings as well as your own analysis of the plan or photograph.

Give students methods for approaching their work

Strong writing assignments not only identify a clear writing task, they often provide suggestions for how students might begin to accomplish the task. In order to avoid overloading students with information and suggestions, it is often useful to separate the assignment prompt and the advice for approaching the assignment. Below is an example of this strategy from one of Yale’s English 114 sections:

Assignment: In the essays we have read so far, a debate has emerged over what constitutes cosmopolitan practice , loosely defined as concrete actions motivated by a cosmopolitan philosophy or perspective. Using these readings as evidence, write a 5-6-page essay in which you make an argument for your own definition of effective cosmopolitan practice.

Method: In order to develop this essay, you must engage in a critical conversation with the essays we have read in class. In creating your definition of cosmopolitan practice, you will necessarily draw upon the ideas of these authors. You must show how you are building upon, altering, or working in opposition to their ideas and definitions through your quotation and analysis of their concepts and evidence.

Questions to consider:  These questions are designed to prompt your thinking. You do not need to address all these questions in the body of your essay; instead, refer to any of these issues only as they support your ideas.

  • How would you define cosmopolitan practice? How does your definition draw upon or conflict with the definitions offered by the authors we have read so far?
  • What are the strengths of your definition of cosmopolitan practice? What problems does it address? How do the essays we have read support those strengths? How do those strengths address weaknesses in other writers’ arguments?
  • What are the limitations or problems with your definition? How would the authors we have read critique your definition? How would you respond to those critiques?

Case Study: A Sample Writing Assignment and Revision

A student responding to the following assignment felt totally at sea, with good reason:

Write an essay describing the various conceptions of property found in your readings and the different arguments for and against the distribution of property and the various justifications of, and attacks on, ownership. Which of these arguments has any merits? What is the role of property in the various political systems discussed? The essay should concentrate on Hobbes, Locke, and Marx.

“How am I supposed to structure the essay?” the student asked. “Address the first question, comparing the three guys? Address the second question, doing the same, etc.? … Do I talk about each author separately in terms of their conceptions of the nation, and then have a section that compares their arguments, or do I have a 4 part essay which is really 4 essays (two pages each) answering each question? What am I going to put in the intro, and the conclusion?” Given the tangle of ideas presented in the assignment, the student’s panic and confusion are understandable.

A better-formulated assignment poses significant challenges, but one of them is not wondering what the instructor secretly wants. Here’s a possible revision, which follows the guidelines suggested above:

[Course Name and Title]

[Instructor’s Name]

Due date: Thursday, February 24, at 11:10am in section

Length: 5-6pp. double-spaced

Limiting your reading to the sourcebook, write a comparative analysis of Hobbes’s, Locke’s, and Marx’s conceptions of property.

The purpose of this assignment is to help you synthesize some difficult political theory and identify the profound differences among some key theorists.

The best papers will focus on a single shared aspect of the theorists’ respective political ideologies, such as how property is distributed, whether it should be owned, or what role it serves politically. The best papers will not only focus on a specific topic, but will state a clear and arguable thesis about it (“the three authors have differing conceptions of property” is neither) and go on to describe and assess the authors’ viewpoints clearly and concisely.

Note that this revised assignment is now not only clearer than the original; it also requires less regurgitation and more sustained thought.

For more information about crafting and staging your assignments, see “ The Papers We Want to Read ” by Linda Simon, Social Studies; Jan/Feb90, Vol. 81 Issue 1, p37, 3p. (The link to Simon’s article will only work if your computer is on the Yale campus.) See also the discussion of Revising Assignments in the section of this website on Addressing Plagiarism .

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Writing Consultations

For graduate students looking for expert advice on planning, drafting, and revising their research paper, dissertation, presentation, or any other writing project.

Assignment Design Basics

Here are some introductory materials to get you started with writing assignment design:

Designing and Responding to Writing Assignments: this slide deck, developed by the WAC Director for the new faculty seminar, (lightly) covers some of the core concepts in designing effective writing assignments, including scaffolding, connecting assignments to course goals, developing rubrics, and providing effective feedback.

Designing Rubrics : this handout provides a bit more detail on how to develop effective rubrics and includes a few examples of different types.

Questions for Low- and High-Stakes Assignments: this handout provides a list of questions to consider as you design low and high-stakes writing assignments for your courses.

The LTC Archive on Course Design addresses far more than writing assignments, but the general principles of transparency and accessibility that their materials emphasize are certainly applicable to writing assignment design.

For additional help…

Carleton faculty, keep in mind that George Cusack, the WAC Director is happy (and contractually obligated) to help you develop writing assignments in your courses. If you have questions or simply want some feedback on assignments in process, please feel free to email George!

The Teaching and Learning Center

The Teaching and Learning Center

Creative assignment design.

This workshop explores how to design problem-based learning (PBL) assignments that tie the practice of skills or course objectives with a direct engagement with a student’s environment. We will discuss strategies for incorporating, across the disciplines, the vast range of resources NYC offers, including archives, museums, site exploration, and field visits, etc., into assignment design.

The Creative Assignment Design workshop was offered as as an in-person workshop at the Graduate Center, CUNY in Spring 2016. The workshop and materials were developed by Elizabeth Decker.

Workshop Materials

All materials on this page and in the linked google folder are licensed under a Creative Commons Attribution-ShareAlike ( CC-BY-SA ) 4.0 International Public License.

This folder contains outreach materials, workshop plans and slides, and a handout about ethical tech lingo used in the workshop. Materials are licensed under a Creative Commons Attribution-ShareAlike ( CC-BY-SA ) 4.0 International Public License.

Materials Folder: Creative Assignment Design Materials

Workshop Plan

I. Introductions

II. Scaffolding and Example

I’d like to start by talking about scaffolding assignments and cover:

  • what it means to scaffold assignments
  • why people use it
  • building skills
  • building levels of thinking/processing
  • how it works

III. Activity I

Coming up collaboratively with a list of skills we’d want to hit, then pair participants, and using the constraint of a smartphone as the material for the assignment, I’d ask them to think of ways to hit those skills (come up with a loose assignment design/a general idea)

IV. Discussion (discussion/recap of activity)→ Writing the assignment→ (broader)PBL, resources + example

After the activity and chatting about what we came up with, I’d like to talk about how we’d go about writing up those ideas as assignments for students. I’d cover:

  • tips on writing an effective assignment
  • how to situate information / too much text v. too little
  • what modeling can the assignment perform?

Shift to talking about the assignment design/scaffolding on a larger scale

Example of PBL + incorporating readings (specifically theory readings) into ‘active learning’

V. Group Activity

Similar to the first activity. Make two or three groups and give them (the same?) a site/resource in nyc-area and a list of skills/objectives and ask them to sketch a quick design of an assignment that would make use of that site. Present ideas to each other / general discussion in groups and together of other site assignments they’ve done etc

VI. Questions and survey

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Assignment Design

There’s a fine line between assignment design and assessment strategies . In short, designing good assignments is one means of assessing your students’ learning on a larger scale.

Assignments help measure student learning in your course. Effective assignment design in your course involves aligning your assignments with learning outcomes. When assignments and outcomes are aligned, good grades and good learning go hand in hand ( https://www.cmu.edu/teaching/designteach/design/assessments.html ).

Assessments fall into one of two categories, formative or summative .

Formative assessments are typically low-stakes and help students identify their strengths and weaknesses so that they can improve their learning. Routine formative assessments also help instructors identify the areas where students are struggling and adapt their teaching accordingly.

Summative assessments evaluate student learning (such as at the end of a unit of instruction). Summative assessments are generally higher stakes (like midterm exams and final projects).

Assignments are what students actually ‘do’ as part of those assessments.

Incorporating a mix of assignment activities in your course can help students practice and demonstrate their mastery of outcomes in multiple ways. Consider ways you can design your assignments so that they better mirror the application of knowledge in real-world scenarios. Assignments designed in this way are often referred to as Authentic Assessments ( Authentic-assessment.pdf (uwex.edu)). One type of highly authentic assessment is the long-term project which challenges students to solve a problem or complete a challenge requiring the application of course concepts ( Project_Based_Learning.pdf (uwex.edu) ).

More details and examples can be found in the tabbed content box below. Please also consider signing up for a CATL consultation with one of our instructional designers for some personalized assistance in developing your ideas for assignments and ensuring that they align with your course outcomes .

(Adapted from Carnegie Mellon's:  Design and Teach a Course )

Assessments should provide instructors and students with evidence of how well students have mastered the course outcomes.

There are two major reasons for aligning assessments with learning outcomes.

  • Alignment increases the probability that we will provide students with the opportunities to learn and practice knowledge and skills that instructors will require students know in the objectives and in the assessments. (Teaching to the assessment is a  good  thing.)
  • When instructors align assessments with outcomes, students are more likely to translate "good grades" into "good learning." Conversely, when instructors misalign assessments with objectives, students will focus on getting good grades on the assessments, rather than focusing on mastering the material that the instructor finds important.

Instructors may use different types of assessments to measure student proficiency in a learning objective. Moreover, instructors may use the same activity to measure different objectives. To ensure a more accurate assessment of student proficiency, many instructional designers recommend that you use different kinds of activities so that students have multiple ways to practice and demonstrate their knowledge and skills.

Formative assessment

The goal of formative assessment is to  monitor student learning  to provide ongoing feedback that can be used by instructors to improve their teaching and by students to improve their learning. More specifically, formative assessments:

  • help students identify their strengths and weaknesses and target areas that need work
  • help faculty recognize where students are struggling and address problems immediately

Formative assessments are generally  low stakes , which means that they have low or no point value. Examples of formative assessments include asking students to:

  • draw a concept map in class to represent their understanding of a topic
  • submit one or two sentences identifying the main point of a lecture
  • turn in a research proposal for early feedback

Summative assessment

The goal of summative assessment is to  evaluate student learning  at the end of an instructional unit by comparing it against some standard or benchmark.

Summative assessments are often  high stakes , which means that they have a high point value. Examples of summative assessments include:

  • a midterm exam
  • a final project
  • a senior recital

Information from summative assessments can be used formatively when students or faculty use it to guide their efforts and activities in subsequent courses.

Formative Assessments:

  • Reading quizzes
  • Concept map
  • Muddiest point
  • Pro/con grid
  • Focused paraphrasing
  • Reflective journal
  • Virtual lab/game
  • Webconference
  • Debate (synchronous or asynchronous)
  • Participant research
  • Peer review

Summative Assessments:

  • Presentation
  • Portfolio project

Carnegie Mellon University on Aligning Assessments with Objectives with examples.

Items to consider when weighing your assessment options:

If you are thinking about using discussions, be sure to think about the following:.

  • What kind of questions/situations do you want the students to discuss? Is it complex enough to allow students to build knowledge beyond the textbook? Will the discussion help students meet your objectives (and develop an answer for your essential questions)?
  • What are your expectations for discussions? Should students participate (post) a certain number of times, with a certain number of words, and reply to a certain number of people?
  • What is your role in the discussion (traffic cop, the person who clarifies issues, will you respond to every post)?

If you are thinking about using quizzes, be sure to think about the following:

  • What type of questions will help your students meet the objectives of the course? Are you going to grade essay questions or just let the computer grade multiple choice questions?
  • What is the place for academic integrity? Are you going to randomize questions, randomize answers, restrict time, restrict the answers that students can see after completing the exam?
  • How are you going to populate your quiz? Are you going to write the questions or use questions that come from a textbook publisher?

If you are thinking of using essays, be sure to think about the following:

  • Will these essays/papers help students to meet the course objectives, which ones? Is the length of the essay appropriate?
  • What do you think about plagiarism checkers such as TurnItIn?
  • To what extent will you allow students to submit drafts, and will you provide feedback on drafts, or will you use a peer review system?

Other items to consider:

  • Are you thinking about using an alternative assignment? If so, you may want to talk with an instructional technologist or designer.
  • Consider the type of feedback you will provide for each assignment. What should students expect from you; how will you communicate those expectations; and how soon will you provide feedback (realistically)?

Further resources

Small teaching online.

This book (requires UWGB login) contains many tips that are easy to integrate into your distance education class. The chapter on “ surfacing backward design” contains many tips for assessment for online classes, many of which are adaptable to all distance modalities.

CATL Resources

  • Collaborative Learning Assignments  (Toolbox article)
  • Administering Tests and Quizzes (including alternatives) (Toolbox article)
  • Writing Good Multiple Choice Questions ( TeAch Tuesday , YouTube)

Tip sheets from UW-System

UW-System put together some tip sheets for common sticking points in assessment for distance education.

  • Writing effective multiple choice questions
  • Authentic assessments
  • Unproctored online assessments
  • Project-based learning

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Creating Your Assignment Sheets

Main navigation.

In order to help our students best engage with the writing tasks we assign them, we need as a program  to scaffold the assignments with not only effectively designed activities, but equally effectively designed assignment sheets that clearly explain the learning objectives, purpose, and logistics for the assignment.

Checklist for Assignment Sheet Design

As a program, instructors should compose assignment sheets that contain the following elements.

A  clear description of the assignment and its purpose . How does this assignment contribute to their development as writers in this class, and perhaps beyond? What is the genre of the assignment? (e.g., some students will be familiar with rhetorical analysis, some will not).

Learning objectives for the assignment .  The learning objectives for each assignment are available on the TeachingWriting website. While you might include others objectives, or tweak the language of these a bit to fit with how you teach rhetoric, these objectives should appear in some form on the assignment sheet and should be echoed in your rubric.

Due dates or timeline, including dates for drafts .  This should include specific times and procedures for turning in drafts. You should also indicate dates for process assignments and peer review if they are different from the main assignment due dates.

Details about format (including word count, documentation form) .  This might also be a good place to remind them of any technical specifications (even if you noted them on the syllabus).

Discussion of steps of the process.  These might be “suggested” to avoid the implication that there is one best way to achieve a rhetorical analysis.

Evaluation criteria / grading rubric that is in alignment with learning objectives .  While the general  PWR evaluation criteria  is a good starting place, it is best to customize your rubric to the specific purposes of your assignment, ideally incorporating some of the language from the learning goals. In keeping with PWR’s elevation of rhetoric over rules, it’s generally best to avoid rubrics that assign specific numbers of points to specific features of the text since that suggests a fairly narrow range of good choices for students’ rhetorical goals. (This is not to say that points shouldn’t be used: it’s just more in the spirit of PWR’s rhetorical commitments to use them holistically.)

Canvas Versions of Assignment Sheets

Canvas offers an "assignment" function you can use to share assignment sheet information with students.  It provides you with the opportunity to upload a rubric in conjunction with assignment details; to create an upload space for student work (so they can upload assignments directly to Canvas); to link the assignment submissions to Speedgrader, Canvas's internal grading platform; and to sync your assigned grades with the gradebook.  While these are very helpful features, don't hesitate to reach out to the Canvas Help team or our ATS for support when you set them up for the first time. In addition, you should always provide students with access to a separate PDF assignment sheet. Don't just embed the information in the Canvas assignment field; if students have trouble accessing Canvas for any reason (Canvas outage; tech issues), they won't be able to access that information.

In addition, you might creating video mini-overviews or "talk-throughs" of your assignments.  These should serve as supplements to the assignment sheets, not as a replacement for them.

Sample Assignment Sheets

Check out some examples of Stanford instructors' assignment sheets via the links below. Note that these links will route you to our Canvas PWR Program Materials site, so you must have access to the Canvas page in order to view these files: 

See examples of rhetorical analysis assignment sheets

See examples of texts in conversation assignment sheets

See examples of research-based argument assignment sheets

Further reading on assignment sheets

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Our next-generation model: Gemini 1.5

Feb 15, 2024

The model delivers dramatically enhanced performance, with a breakthrough in long-context understanding across modalities.

SundarPichai_2x.jpg

A note from Google and Alphabet CEO Sundar Pichai:

Last week, we rolled out our most capable model, Gemini 1.0 Ultra, and took a significant step forward in making Google products more helpful, starting with Gemini Advanced . Today, developers and Cloud customers can begin building with 1.0 Ultra too — with our Gemini API in AI Studio and in Vertex AI .

Our teams continue pushing the frontiers of our latest models with safety at the core. They are making rapid progress. In fact, we’re ready to introduce the next generation: Gemini 1.5. It shows dramatic improvements across a number of dimensions and 1.5 Pro achieves comparable quality to 1.0 Ultra, while using less compute.

This new generation also delivers a breakthrough in long-context understanding. We’ve been able to significantly increase the amount of information our models can process — running up to 1 million tokens consistently, achieving the longest context window of any large-scale foundation model yet.

Longer context windows show us the promise of what is possible. They will enable entirely new capabilities and help developers build much more useful models and applications. We’re excited to offer a limited preview of this experimental feature to developers and enterprise customers. Demis shares more on capabilities, safety and availability below.

Introducing Gemini 1.5

By Demis Hassabis, CEO of Google DeepMind, on behalf of the Gemini team

This is an exciting time for AI. New advances in the field have the potential to make AI more helpful for billions of people over the coming years. Since introducing Gemini 1.0 , we’ve been testing, refining and enhancing its capabilities.

Today, we’re announcing our next-generation model: Gemini 1.5.

Gemini 1.5 delivers dramatically enhanced performance. It represents a step change in our approach, building upon research and engineering innovations across nearly every part of our foundation model development and infrastructure. This includes making Gemini 1.5 more efficient to train and serve, with a new Mixture-of-Experts (MoE) architecture.

The first Gemini 1.5 model we’re releasing for early testing is Gemini 1.5 Pro. It’s a mid-size multimodal model, optimized for scaling across a wide-range of tasks, and performs at a similar level to 1.0 Ultra , our largest model to date. It also introduces a breakthrough experimental feature in long-context understanding.

Gemini 1.5 Pro comes with a standard 128,000 token context window. But starting today, a limited group of developers and enterprise customers can try it with a context window of up to 1 million tokens via AI Studio and Vertex AI in private preview.

As we roll out the full 1 million token context window, we’re actively working on optimizations to improve latency, reduce computational requirements and enhance the user experience. We’re excited for people to try this breakthrough capability, and we share more details on future availability below.

These continued advances in our next-generation models will open up new possibilities for people, developers and enterprises to create, discover and build using AI.

Context lengths of leading foundation models

Highly efficient architecture

Gemini 1.5 is built upon our leading research on Transformer and MoE architecture. While a traditional Transformer functions as one large neural network, MoE models are divided into smaller "expert” neural networks.

Depending on the type of input given, MoE models learn to selectively activate only the most relevant expert pathways in its neural network. This specialization massively enhances the model’s efficiency. Google has been an early adopter and pioneer of the MoE technique for deep learning through research such as Sparsely-Gated MoE , GShard-Transformer , Switch-Transformer, M4 and more.

Our latest innovations in model architecture allow Gemini 1.5 to learn complex tasks more quickly and maintain quality, while being more efficient to train and serve. These efficiencies are helping our teams iterate, train and deliver more advanced versions of Gemini faster than ever before, and we’re working on further optimizations.

Greater context, more helpful capabilities

An AI model’s “context window” is made up of tokens, which are the building blocks used for processing information. Tokens can be entire parts or subsections of words, images, videos, audio or code. The bigger a model’s context window, the more information it can take in and process in a given prompt — making its output more consistent, relevant and useful.

Through a series of machine learning innovations, we’ve increased 1.5 Pro’s context window capacity far beyond the original 32,000 tokens for Gemini 1.0. We can now run up to 1 million tokens in production.

This means 1.5 Pro can process vast amounts of information in one go — including 1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words. In our research, we’ve also successfully tested up to 10 million tokens.

Complex reasoning about vast amounts of information

1.5 Pro can seamlessly analyze, classify and summarize large amounts of content within a given prompt. For example, when given the 402-page transcripts from Apollo 11’s mission to the moon, it can reason about conversations, events and details found across the document.

Reasoning across a 402-page transcript: Gemini 1.5 Pro Demo

Gemini 1.5 Pro can understand, reason about and identify curious details in the 402-page transcripts from Apollo 11’s mission to the moon.

Better understanding and reasoning across modalities

1.5 Pro can perform highly-sophisticated understanding and reasoning tasks for different modalities, including video. For instance, when given a 44-minute silent Buster Keaton movie , the model can accurately analyze various plot points and events, and even reason about small details in the movie that could easily be missed.

Multimodal prompting with a 44-minute movie: Gemini 1.5 Pro Demo

Gemini 1.5 Pro can identify a scene in a 44-minute silent Buster Keaton movie when given a simple line drawing as reference material for a real-life object.

Relevant problem-solving with longer blocks of code

1.5 Pro can perform more relevant problem-solving tasks across longer blocks of code. When given a prompt with more than 100,000 lines of code, it can better reason across examples, suggest helpful modifications and give explanations about how different parts of the code works.

Problem solving across 100,633 lines of code | Gemini 1.5 Pro Demo

Gemini 1.5 Pro can reason across 100,000 lines of code giving helpful solutions, modifications and explanations.

Enhanced performance

When tested on a comprehensive panel of text, code, image, audio and video evaluations, 1.5 Pro outperforms 1.0 Pro on 87% of the benchmarks used for developing our large language models (LLMs). And when compared to 1.0 Ultra on the same benchmarks, it performs at a broadly similar level.

Gemini 1.5 Pro maintains high levels of performance even as its context window increases. In the Needle In A Haystack (NIAH) evaluation, where a small piece of text containing a particular fact or statement is purposely placed within a long block of text, 1.5 Pro found the embedded text 99% of the time, in blocks of data as long as 1 million tokens.

Gemini 1.5 Pro also shows impressive “in-context learning” skills, meaning that it can learn a new skill from information given in a long prompt, without needing additional fine-tuning. We tested this skill on the Machine Translation from One Book (MTOB) benchmark, which shows how well the model learns from information it’s never seen before. When given a grammar manual for Kalamang , a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person learning from the same content.

As 1.5 Pro’s long context window is the first of its kind among large-scale models, we’re continuously developing new evaluations and benchmarks for testing its novel capabilities.

For more details, see our Gemini 1.5 Pro technical report .

Extensive ethics and safety testing

In line with our AI Principles and robust safety policies, we’re ensuring our models undergo extensive ethics and safety tests. We then integrate these research learnings into our governance processes and model development and evaluations to continuously improve our AI systems.

Since introducing 1.0 Ultra in December, our teams have continued refining the model, making it safer for a wider release. We’ve also conducted novel research on safety risks and developed red-teaming techniques to test for a range of potential harms.

In advance of releasing 1.5 Pro, we've taken the same approach to responsible deployment as we did for our Gemini 1.0 models, conducting extensive evaluations across areas including content safety and representational harms, and will continue to expand this testing. Beyond this, we’re developing further tests that account for the novel long-context capabilities of 1.5 Pro.

Build and experiment with Gemini models

We’re committed to bringing each new generation of Gemini models to billions of people, developers and enterprises around the world responsibly.

Starting today, we’re offering a limited preview of 1.5 Pro to developers and enterprise customers via AI Studio and Vertex AI . Read more about this on our Google for Developers blog and Google Cloud blog .

We’ll introduce 1.5 Pro with a standard 128,000 token context window when the model is ready for a wider release. Coming soon, we plan to introduce pricing tiers that start at the standard 128,000 context window and scale up to 1 million tokens, as we improve the model.

Early testers can try the 1 million token context window at no cost during the testing period, though they should expect longer latency times with this experimental feature. Significant improvements in speed are also on the horizon.

Developers interested in testing 1.5 Pro can sign up now in AI Studio, while enterprise customers can reach out to their Vertex AI account team.

Learn more about Gemini’s capabilities and see how it works .

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