essay on learning behaviour

Behavioral Learning Theory: Shaping Students’ Behavior and Learning

The Behavioral Learning Theory gives us insight into how to create a positive learning environment, influence our students’ behavior in class, and motivate them to develop good study habits.

• By Paul Holt
• Sep 20, 2023

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• The Behavioral Learning Theory is based on the premise that all human behavior is learned.
• According to this theory, our behaviors are simply reactions to external stimuli, and we can learn new behaviors through a process called conditioning.
• When applied correctly, Behaviorism can be an effective tool for helping students perform better in class and allow them to develop self-regulating skills.

We all know not to touch something hot because it can burn. This is a lesson that we’ve learned based on experience. It’s nothing new, right? Experience does teach us a lot of things. According to the Behavioral Learning Theory, this is, in fact, how all humans and animals learn.

The Behavioral Learning Theory , also known as Behaviorism, is based on the idea that we learn through our interaction with the environment. In fact, one of its assumptions is that all behavior can be learned. Moreover, behaviors can be replaced by new behaviors through a process called conditioning.

As teachers, understanding the Behavioral Learning Theory can teach you how to encourage your students to learn and create an environment that’s more stimulating and conducive to learning. In this article, we’ll discuss the Behavioral Learning Theory, its benefits, and how educators can use it in the classroom to help students achieve academic success.

Table of Contents

What is behavioral learning theory.

Behaviorism was first introduced in the 19th century as a reaction against mentalism . At the time, the study of the mind mostly relied on first-person accounts of people’s thoughts and feelings. Some psychologists didn’t think that unconscious thoughts and urges were objective or measurable. It was too subjective, which could lead to findings that were contradicting. Worse, they might not even be able to reproduce the same results.

Behavior, on the other hand, could be observed objectively, systematically studied, and empirically measured. Moreover, behaviorists believe that people can be trained to perform any task regardless of their genetic background or personality as long as you apply the right conditioning. In layman’s terms, we’re all blank slates when we’re born. And all our behavior is learned from our interaction with our environment.

Types of Behavioral Learning

Classical conditioning.

According to Classical Conditioning, a human or animal can learn new behavior by associating a neutral stimulus with another stimulus that causes a natural response. Once associated, the neutral stimulus can now trigger the learned response.

To explain this more clearly, let’s look at an experiment conducted by Russian physiologist Ivan Pavlov . You’ve heard of Pavlov’s dogs, right? In his experiments, he was able to teach dogs to associate the ringing of a bell (a neutral stimulus) with the arrival of food (the second stimulus). The smell of the food automatically triggers the dogs’ hunger, which includes physical signs such as salivation. Through conditioning, just hearing the ringing of the bell could cause the dogs to salivate, even if they no longer smelled the food.

Operant Conditioning

Most of us are very familiar with Operant Conditioning because this learning technique is based on the idea of reward and punishment. According to Operant Conditioning, consequences can control the behavior of an individual. A behavior is more likely to occur if the person knows that they’ll get something good out of it. It is less likely to occur if the person knows they’ll get punished.

Operant conditioning can be done using positive and negative reinforcement and positive and negative punishment:

Positive reinforcement: The presence of an added stimulus after you get the desired behavior can increase the likelihood of the individual repeating the behavior or, to put it more simply, giving a person something good to reinforce the behavior. For example, the teacher gives preschool kids a stamp if they are on good behavior in class at the end of the day. This makes them more likely to behave during class on the following days.

Negative reinforcement: Taking away something unpleasant after the desired behavior takes place. Over time, the desired behavior occurs more often with the expectation that the negative stimuli will be removed. For example, the beeping sound you hear when you don’t put on your seatbelt. We are motivated to put on our seatbelt quickly to stop the annoying beeps.

Positive punishment: Adding an undesirable stimulus after a behavior to discourage it from occurring in the future. For example, a student will get detention for misbehaving in class.

Negative punishment: Removing a positive stimulus after a behavior to discourage the person from doing it again. For example, removing a child’s internet privileges if he doesn’t do his homework.

Benefits of Behavioral Learning Theory in teaching

Understanding and harnessing the Behavioral Learning Theory can be an effective tool for influencing students to learn positive behaviors and discourage negative behaviors. Students can learn to work for rewards, including approval.

Benefits to using behaviorism in the classroom include:

• Behaviorism helps create a structured learning environment. Students are taught how to obey the rules inside the classroom, whether online or in person, through rewards and punishments. This helps create a more organized and disciplined environment that is conducive to learning.
• It can help give teachers a clear and objective structure for measuring a student’s performance.
• It provides students with immediate feedback, which can improve learning. For example, positive reinforcement has been shown to help students retain information better.
• Behaviorism can be used to shape a student’s study strategies.
• It can help teachers adapt their teaching techniques according to the abilities and needs of each student.
• It can teach students how to self-regulate. They gain an understanding of their behavior and motivations, allowing them to have more control over how they act. More importantly, it teaches them to become accountable for what they do.

How to apply the Behavioral Learning Theory in the online classroom

We’ve all experienced positive and negative reinforcement as well as positive and negative punishment in the classroom. These include:

• Getting praised by the teacher for a correct response to a question.
• Receiving a bonus to your grade if you have a perfect attendance record.
• Getting a grade of “0” for not submitting assignments.
• Getting your phone confiscated if you use it in class.
• Getting a free homework pass if you get a perfect grade on the exam.

In addition to the ideas mentioned above, below are several strategies that can be applied to the online and physical classrooms:

Set clear expectations . Students need to have a clear understanding of the goals they need to achieve and the rules they need to follow in the classroom. This is especially important for online classrooms. Many students might not take online classes as seriously as classes held face-to-face in school. Make sure that your students understand your expectations during the online class and enforce the rules consistently.

Provide regular reviews. Going over the same material while providing your students with positive reinforcement can enable them to retain information better.

Give quick feedback. It’s important that students are provided feedback in a timely manner so they will associate it with the work they did. This helps shape your student’s study habits more effectively.   

Reward good study habits. You need to help prevent students from cramming. Create a reward system that motivates them to regularly study the class materials. With the proper incentive, they’ll begin to associate regular study sessions with good feelings.

Provide guided practice. You can demonstrate the behavior that you want them to follow. For example, be directly involved in helping them solve a problem step-by-step and providing them reinforcement along the way.

Use negative reinforcement sparingly. Avoid too much negative reinforcement to prevent creating a negative atmosphere in the class.

Use game-based learning. Game-based learning can increase engagement and motivate students to learn. There are many online games that utilize the principles of Operant Conditioning to promote learning, such as FunBrain , Moose Math , and RoomRecess . Alternatively, you can create a token economy system. Students can earn tokens or points for certain behaviors or for accomplishing specific tasks. These tokens can be exchanged for rewards, which can incentivize them to follow the rules and stay on task.

The Behavioral Learning Theory teaches us how external stimuli can influence behavior and learning. As educators, we need to try to find different ways to elicit positive behaviors from our students and discourage negative responses. We need to be more aware of their needs and motivations so that we are able to create more positive learning environments and increase their motivation to learn.

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The Jigsaw Learning Method promotes inclusivity by valuing diverse perspectives and individual strengths. It deconstructs traditional classroom hierarchies to promote equality and respect and ensure that each learner plays an active role in everyone’s learning experiences.

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What are the key elements of a positive learning environment? Perspectives from students and faculty

Shayna a. rusticus.

Department of Psychology, Kwantlen Polytechnic University, 12666 72 Ave, Surrey, BC V3W 2M8 Canada

Tina Pashootan

The learning environment comprises the psychological, social, cultural and physical setting in which learning occurs and has an influence on student motivation and success. The purpose of the present study was to explore qualitatively, from the perspectives of both students and faculty, the key elements of the learning environment that supported and hindered student learning. We recruited a total of 22 students and 9 faculty to participate in either a focus group or an individual interview session about their perceptions of the learning environment at their university. We analyzed the data using a directed content analysis and organized the themes around the three key dimensions of personal development, relationships, and institutional culture. Within each of these dimensions, we identified subthemes that facilitated or impeded student learning and faculty work. We also identified and discussed similarities in subthemes identified by students and faculty.

Introduction

The learning environment (LE) comprises the psychological, social, cultural, and physical setting in which learning occurs and in which experiences and expectations are co-created among its participants (Rusticus et al., 2020 ; Shochet et al., 2013 ). These individuals, who are primarily students, faculty and staff, engage in this environment and the learning process as they navigate through their personal motivations and emotions and various interpersonal interactions. This all takes place within a physical setting that consists of various cultural and administrative norms (e.g. school policies).

While many studies of the LE have focused on student perspectives (e.g. Cayubit, 2021 ; Schussler et al., 2021 ; Tharani et al., 2017 ), few studies have jointly incorporated the perspectives of students and faculty. Both groups are key players within the educational learning environment. Some exceptions include researchers who have used both instructor and student informants to examine features of the LE in elementary schools (Fraser & O’Brien, 1985 ; Monsen et al., 2014 ) and in virtual learning and technology engaged environments in college (Annansingh, 2019 ; Downie et al., 2021 ) Other researchers have examined perceptions of both groups, but in ways that are not focused on understanding the LE (e.g. Bolliger & Martin, 2018 ; Gorham & Millette, 1997 ; Midgly et al., 1989 ).

In past work, LEs have been evaluated on the basis of a variety of factors, such as students’ perceptions of the LE have been operationalized as their course experiences and evaluations of teaching (Guo et al., 2021 ); level of academic engagement, skill development, and satisfaction with learning experience (Lu et al., 2014 ); teacher–student and student–peer interactions and curriculum (Bolliger & Martin, 2018 ; Vermeulen & Schmidt, 2008 ); perceptions of classroom personalization, involvement, opportunities for and quality of interactions with classmates, organization of the course, and how much instructors make use of more unique methods of teaching and working (Cayubit, 2021 ). In general, high-quality learning environments are associated with positive outcomes for students at all levels. For example, ratings of high-quality LEs have been correlated with outcomes such as increased satisfaction and motivation (Lin et al., 2018 ; Rusticus et al., 2014 ; Vermeulen & Schmidt, 2008 ), higher academic performance (Lizzio et al., 2002 ; Rusticus et al., 2014 ), emotional well-being (Tharani et al., 2017 ), better career outcomes such as satisfaction, job competencies, and retention (Vermeulen & Schmidt, 2008 ) and less stress and burnout (Dyrbye et al., 2009 ). From teacher perspectives, high-quality LEs have been defined in terms of the same concepts and features as those used to evaluate student perspective and outcomes. For example, in one quantitative study, LEs were rated as better by students and teachers when they were seen as more inclusive (Monsen et al., 2014 ).

However, LEs are diverse and can vary depending on context and, although many elements of the LE that have been identified, there has been neither a consistent nor clear use of theory in assessing those key elements (Schönrock-Adema et al., 2012 ). One theory that has been recommended by Schönrock-Adema et al. ( 2012 ) to understand the LE is Moos’ framework of human environments (Insel & Moos, 1974 ; Moos, 1973 , 1991 ). Through his study of a variety of human environments (e.g. classrooms, psychiatric wards, correctional institutions, military organizations, families), Moos proposed that all environments have three key dimensions: (1) personal development/goal direction, (2) relationships, and (3) system maintenance/change. The personal development dimension encompasses the potential in the environment for personal growth, as well as reflecting the emotional climate of the environment and contributing to the development of self-esteem. The relationship dimension encompasses the types and quality of social interactions that occur within the environment, and it reflects the extent to which individuals are involved in the environment and the degree to which they interact with, and support, each other. The system maintenance/change dimension encompasses the degree of structure, clarity and openness to change that characterizes the environment, as well as reflecting physical aspects of the environment.

We used this framework to guide our research question: What do post-secondary students and faculty identify as the positive and negative aspects of the learning environment? Through the use of a qualitative methodology to explore the LE, over the more-typical survey-based approaches, we were able to explore this topic in greater depth, to understand not only the what, but also the how and the why of what impacts the LE. Furthermore, in exploring the LE from both the student and faculty perspectives, we highlight similarities and differences across these two groups and garner an understanding of how both student and faculty experience the LE.

Participants

All participants were recruited from a single Canadian university with three main campuses where students can attend classes to obtain credentials, ranging from a one-year certificate to a four-year undergraduate degree. Approximately 20,000 students attend each year. The student sample was recruited through the university’s subject pool within the psychology department. The faculty sample was recruited through emails sent out through the arts faculty list-serve and through direct recruitment from the first author.

The student sample was comprised of 22 participants, with the majority being psychology majors ( n  = 10), followed by science majors ( n  = 4) and criminology majors ( n  = 3). Students spanned all years of study with seven in their first year, three in second year, five in third year, six in fourth year, and one unclassified. The faculty sample consisted of nine participants (6 male, 3 female). Seven of these participants were from the psychology department, one was from the criminology department and one was from educational studies. The teaching experience of faculty ranged from 6 to 20 years.

Interview schedule and procedure

We collected student data through five focus groups and two individual interviews. The focus groups ranged in size from two to six participants. All sessions occurred in a private meeting room on campus and participants were provided with food and beverages, as well as bonus credit. Each focus group/interview ranged from 30 to 60 min. We collected all faculty data through individual interviews ranging from 30 to 75 min. Faculty did not receive any incentives for their participation. All sessions were conducted by the first author, with the second author assisting with each of the student focus groups.

With the consent of each participant, we audio-recorded each session and transcribed them verbatim. For both samples, we used a semi-structured interview format involving a set of eight open-ended questions about participants’ overall perceptions of the LE at their institution (see Appendix for interview guide). These questions were adapted from a previous study conducted by the first author (Rusticus et al., 2020 ) and focused on how participants defined the LE, what they considered to be important elements of the LE, and their positive and negative experiences within their environment. Example questions were: “Can you describe a [negative/positive] learning [students]/teaching [faculty] experience that you have had?”.

We analyzed the data using a directed content analysis approach (Hsieh & Shannon, 2005 ) that used existing theory to develop the initial coding scheme. We used Moos’s (Insel & Moos, 1974 ; Moos, 1973 , 1991 ) framework and its three dimensions of personal development, relationships, and system maintenance/change to guide our analysis. During the analysis phase, we renamed the system maintenance/change dimension to ‘institutional setting’ as we felt it was more descriptive of, and better represented, the content of this theme.

We analyzed student and faculty data separately, starting with the student data, but used the same process for both. First, we randomly selected two transcripts. We each independently coded the first transcript using the broad themes of personal development, relationships and institutional setting, and developed subcodes within each of these themes, as needed. We then reviewed and discussed our codes, reaching consensus on any differences in coding. We then repeated this process for the second transcript and, through group discussions, created a codebook. The first author then coded the remaining transcripts.

When coding the faculty data, we aimed to maintain subcodes similar to the student data while allowing for flexibility when needed. For instance, within the personal development theme, a subcode for the student data was ‘engagement with learning’, whereas a parallel subcode for the faculty data was ‘engagement with teaching’.

We present the results of the student and faculty data separately. For both, we have organized our analysis around the three overarching themes of personal development, relationships and institutional setting.

Student perspectives of the learning environment

Personal development.

Personal development was defined as any motivation either within or outside the LE that provide students with encouragement, drive, and direction for their personal growth and achievement. Within this theme, there were two subthemes: engaging with learning and work-life balance.

Engagement with learning reflected a student’s desire and ability to participate in their learning, as opposed to a passive-learning approach. Students felt more engaged when they were active learners, as well as when they perceived the material to be relevant to their career goals or real-world applications. Students also said that having opportunities to apply their learning helped them to better understand their own career paths:

I had two different instructors and both of them were just so open and engaging and they shared so many personal stories and they just seemed so interested in what they were doing and what I was like. Wow, I want to be that. I want to be interested in what I’m learning. (G6P1)

A common complaint that negatively impacted student motivation was that instructors would lecture for the entire class without supporting materials or opportunities for students to participate.

I’ve had a couple professors who just don’t have any visuals at all. All he does is talk. So, for the whole three hours, we would just be scrambling to write down the notes. It’s brutal...(G7P2)

Trying to establish a healthy work-life balance and managing the demands of their courses, often in parallel with managing work and family demands, were key challenges for students and were often sources of stress and anxiety. For instance, one student spoke about her struggles in meeting expectations:

It was a tough semester. For the expectations that I had placed on myself, I wasn’t meeting them and it took a toll on me. But now I know that I can exceed my expectations, but you really have to try and work hard for it. (G6P1)

Achieving a good work-life balance and adjusting to university life takes time. Many students commented that, as they reached their third year of study, they felt more comfortable in the school environment. Unfortunately, students also noted that the mental and emotional toll of university life can lead to doubt about the future and a desire to leave. One student suggested more support for students to help with this adjustment:

I think school should give students more service to help them to overcome the pressure and make integration into the first year and second year quicker and faster. Maybe it’s very helpful for the new students. (G7P4)

Relationships

Relationships was the second dimension of the LE. Subthemes within this dimension included: faculty support, peer interaction, and group work. Most students commented on the impact that faculty had on their learning. Faculty support included creating a safe or unsafe space in the classroom (i.e. ability to ask questions without judgement, fostering a respectful atmosphere), providing additional learning material, accommodating requests, or simply listening to students. Students generally indicated that faculty at this university were very willing to offer extra support and genuinely cared for them and their education. Faculty were described as friendly and approachable, and their relationships with students were perceived as “egalitarian”.

I think feeling that you’re safe in that environment, that anything you pose or any questions that you may have, you’re free to ask. And without being judged. And you’ll get an answer that actually helps you. (G1P4)

While most students felt welcome and comfortable in their classes, a few students spoke about negative experiences that they had because of lack of faculty support. Students cited examples of professors “shutting down” questions, saying that a question was “stupid”, refusing requests for additional help, or interrupting them while speaking. Another student felt that the inaction of faculty sometimes contributed to a negative atmosphere:

I’ve had bad professors that just don't listen to any comment or, if you suggest something to improve it which may seem empirically better, they still shut you down! That’s insane. (G2P2)

The peer interactions subtheme referred to any instances when students could interact with other students; this occurred both in and out of the classroom. Most often, students interacted with their peers during a class or because of an assignment:

I think the way the class is structured really helps you build relationships with your peers. For example, I met S, we had several classes with each other. Those classes were more proactive and so it allowed us to build a relationship… I think that’s very important because we’re going to be in the same facility for a long time and to have somebody to back you up, or to have someone to study with…”. (G1P4)

However, other students felt that they lacked opportunities to interact with peers in class. Although a few participants stated that they felt the purpose of going to school was to get a degree, rather than to socialize with others, students wanted more opportunities to interact with peers.

The final subtheme, group work, was a very common activity at this school. The types of group work in which students engaged included classroom discussions, assignments/projects, and presentations. Many students had enjoyable experiences working in groups, noting that working together helped them to solve problems and create something that was better than one individual’s work. Even though sometimes doing the work itself was a negative experience, people still saw value in group work:

Some of the best memories I’ve ever had was group work and the struggles we've had. (G2P2) I don’t like group work but it taught me a lot, I’ve been able to stay friends and be able to connect with people that I’ve had a class with in 2nd year psych all the way up till now. I think that’s very valuable. (G6P1)

Almost all students who spoke about group work also talked about negative aspects or experiences they had. When the work of a group made up a large proportion of the final grade, students sometimes would have preferred to be evaluated individually. Students disliked when they worked in groups when members were irresponsible or work was not shared equally, and they were forced to undertake work that other students were not completing.

A lot of people don’t really care, or they don’t take as much responsibility as you. I think people have different goals and different ways of working, so sometimes I find that challenging. (G7P2)

Institutional setting

The third overarching theme was the institutional setting. Broadly, this theme refers to the physical structure, expectations, and the overall culture of the environment and was composed of two key subthemes: importance of small class sizes; and the lack of a sense of community.

Small class sizes, with a maximum of 35 students, were a key reason why many students chose to come to this institution. The small classes created an environment in which students and faculty were able to get to know one another more personally; students felt that they were known as individuals, not just as numbers. They also noted that this promoted greater feelings of connectedness to the class environment, more personalized attention, and opportunities to request reference letters in the future:

My professors know my name. Not all of them that I’m having for the first time ever, but they try… That means a lot to me. (G6P4)

Several students also said that having smaller class sizes helped them to do well in their courses. The extra attention encouraged them to perform better academically, increased their engagement with their material, and made them feel more comfortable in asking for help.

Having a sense of belonging was a key feature of the environment and discussions around a sense of community (or lack thereof) was a prominent theme among the students. Students generally agreed that the overall climate of the school is warm and friendly. However, many students referred to the institution as a “commuter school”, because there are no residencies on campus and students must commute to the school. This often resulted in students attending their classes and then leaving immediately after, contributing to a lack of community life on campus.

What [other schools] have is that people live on campus. I think that plays a huge role. We can’t ignore that we are a commuter school… They have these events and people go because they’re already there and you look at that and it seems to be fun and engaging. (G4P1)

Furthermore, students commented on a lack of campus areas that supported socialization and encouraged students to remain on campus. While there were events and activities that were regularly hosted at the school, students had mixed opinions about them. Some students attended the events and found them personally beneficial. Other students stated that, although many events and activities were available, turnout was often low:

There isn’t any hanging out after campus and you can even see in-events and in-event turnout for different events… It is like pulling teeth to get people to come out to an event… There are free food and fun music and really cool stuff. But, no one’s going to go. It’s sad. (G5P1)

Faculty perspectives on the learning environment

Similar to the student findings, faculty data were coded within the three overarching themes of personal development, relationships, and institutional setting.

Personal development reflected any motivation either within or outside the LE that provided faculty with the encouragement, drive, and direction for their personal growth and engagement with teaching. Within this dimension, there were two main subthemes: motivation to teach and emotional well-being.

As with any career, there are many positive and negative motivating factors that contribute to one’s involvement in their work. Faculty generally reported feeling passionate about their work, and recounted positive experiences they have had while teaching, both personally and professionally. While recollecting positive drives throughout their career, one instructor shared:

It’s [teaching in a speciality program] allowed me to teach in a very different way than the traditional classroom… I’ve been able to translate those experiences into conferences, into papers, into connections, conversations with others that have opened up really interesting dialogues…. (8M)

Faculty also reported that receiving positive feedback from students or getting to see their students grow over time was highly motivating:

I take my teaching evaluations very seriously and I keep hearing that feedback time and time again they feel safe. They feel connected, they feel listened too, they feel like I'm there for them. I think, you know, those are the things that let me know what I'm doing is achieving the goals that I have as an educator. (1F) Being able to watch [students] grow over time is very important to me… I always try to have a few people I work with and see over the course of their degree. So, when they graduate, you know I have a reason to be all misty-eyed. (2M)

Emotional well-being related to how different interactions, primarily with students, affected instructors’ mental states. Sometimes the emotional well-being of faculty was negatively affected by the behaviour of students. One instructor spoke about being concerned when students drop out of a class:

A student just this last semester was doing so well, but then dropped off the face of the earth… I felt such a disappointing loss… So, when that happens, I'm always left with those questions about what I could have done differently. Maybe, at the end of the day, there is nothing I could've done, nothing. It's a tragedy or something's happened in their life or I don't know. But those unanswered questions do concern-- they cause me some stress or concern. (1F)

Another instructor said that, while initially they had let the students’ behaviour negatively affect their well-being, over time, they had eventually become more apathetic.

There are some who come, leave after the break. Or they do not come, right, or come off and on. Previously I was motivated to ask them ‘what is your problem?’ Now I do not care. That is the difference which has happened. I do not care. (4M)

This dimension included comments related to interactions with other faculty and with students and consisted of three subthemes: faculty supporting faculty; faculty supporting students; and creating meaningful experiences for students.

Most faculty felt that it was important to be supported by, and supportive to, their colleagues. For instance, one instructor reported that their colleagues’ helpfulness inspired them to be supportive of others:

If I was teaching a new course, without me having to go and beg for resources or just plead and hope that someone might be willing to share, my experience was that the person who last taught the course messaged me and said let me know if anything I have will be useful to you… When people are willing to do that for you, then you’re willing to do that for someone else….(7M)

Many faculty members also spoke about the importance of having supportive relationships with students, and that this would lead to better learning outcomes:

If you don't connect with your students, you're not going to get them learning much. They're not; they're just going to tune out. So, I think, I think connection is critical to having a student not only trust in the learning environment, but also want to learn from the learning environment. (3M)

Facilitating an open, inviting space in the classroom and during their office hours, where students were comfortable asking questions, was one way that faculty tried to help students succeed. Faculty also spoke about the value of having close mentorship relationships with students:

I work with them a lot and intensively…and their growth into publishing, presenting, and seeing them get recognized and get jobs on their way out and so forth are extraordinary. So, being able to watch them grow over time is very important to me. (2M)

Faculty also noted that occasionally there were instances when students wanted exceptions to be made for them which can create tensions in the environment. One instructor spoke about the unfairness of those requests arguing that students need to be accountable to themselves:

The failure rate, …it was 43%. I do not know if there is any other course in which there is a 43% failure rate. So, I do not want to fail these students, why? Instructors want these students to pass, these are my efforts […], and there are also the efforts of these students and their money, right? But, if a student doesn’t want to pass himself or herself, I cannot pass this student, that’s it. (4M)

Faculty were generally motivated to provide memorable and engaging experiences for students. These included providing practical knowledge and opportunities to apply knowledge in real-world settings, field schools, laboratory activities, group discussions, guest speakers, field trips, videos and group activities. They were often willing to put in extra effort if it meant that students would have a better educational experience.

Creating meaningful experiences for students was also meaningful for faculty. One faculty member said that faculty felt amazing when the methods that they used in their courses were appreciated by students. Another faculty member noted:

This student who was in my social psychology class, who was really bright and kind of quirky, would come to my office, twice a week, and just want to talk about psychology … That was like a really satisfying experience for me to see someone get so sparked by the content. (9F)

This third theme refers to the physical structure, expectation, and overall culture of the environment and it consisted of two subthemes: the importance of small class sizes, and the lack of a sense of community.

The majority of the faculty indicated that the small class sizes are an integral feature of the LE. The key advantage of the small classes was that they allowed greater connection with students.

Your professor knows your name. That’s a huge difference from other schools. It’s a small classroom benefit. (6F)

Similar to the students, nearly all the faculty indicated that a sense of community at the institution was an important part of the environment, and something that was desired, but it currently was lacking. They spoke about various barriers which prevent a sense of community, such as the lack of residences, a dearth of events and activities at the university, the busy schedules of faculty and students, the commuter nature of the school, and characteristics of the student population:

When I complain about the commuter campus feeling that occurs with students, we suffer from that too at a faculty level… People are just not in their offices because we work from home… And that really also affects the culture… We come in. We do our thing. We meet with students. And then we leave… I encounter so many students in the hallway who are looking for instructors and they can’t find them. (9F)

These findings have provided insight into the perspectives of both students and faculty on the LE of a Canadian undergraduate university. We found that framing our analysis and results within Moos’ framework of human environments (Insel & Moos, 1974 ; Moos, 1973 , 1991 ) was an appropriate lens for the data and that the data fit well within these three themes. This provides support for the use of this theory to characterize the educational LE. Within each of these dimensions, we discuss subthemes that both facilitated and hindered student learning and commonalities among student and faculty perspectives.

Within the personal development dimension, both students and faculty discussed the importance of engagement and/or motivation as a facilitator of a positive LE. When students were engaged with their learning, most often by being an active participant or seeing the relevance of what they were learning, they saw it as a key strength. Other studies have also identified engagement as a feature of positive LEs for populations such as high-school students (Seidel, 2006 ), nursing students (D’Souza et al., 2013 ) and college students taking online courses (e.g. Holley & Dobson, 2008 ; O’Shea et al., 2015 ). Faculty who reported being motivated to teach, often felt that this motivation was fueled by the reactions of their students; when students were engaged, they felt more motivated. This creates a positive cyclic pattern in which one group feeds into the motivation and engagement levels of the other. However, this can also hinder the LE when a lack of engagement in one group can bring down the motivation of the other group (such as students paying more attention to their phones than to a lecture or faculty lecturing for the entire class period).

Emotional climate was another subtheme within the personal development dimension that was shared by both students and faculty although, for students, this was focused more on the stress and anxiety that they felt trying to manage their school workloads with their work and family commitments. The overall emotional climate of the school was generally considered to be positive, which was largely driven by the supportive and welcoming environment provided by the faculty. However, it was the negative emotions of stress and anxiety that often surfaced as a challenging aspect in the environment for students. Past research suggests that some types of stress, such as from a challenge, can improve learning and motivation, but negative stress, such as that reported by our participants, is associated with worsened performance and greater fatigue (LePine et al., 2004 ).

For faculty, their emotional state was often influenced by their students. When things were going well for their students, faculty often shared in the joy; however, when students would disappear without notice from a class, it was a source of disappointment and self-doubt. For other faculty, the accumulation of negative experiences resulted in them being more distant and less affected emotionally than they had been earlier in their career. This diminishing concern could have implications for how engaged faculty are in their teaching, which could in turn influence student engagement and harm the LE.

The relationships dimension was the most influential aspect of the environment for both students and faculty. While both groups felt that the relationships that they formed were generally positive, they also reported a desire for more peer connections (i.e. students with other students and faculty with other faculty). Students commented that it was a typical experience for them to come to campus to attend their classes and then leave afterwards, often to work or study at home. Many of the students at this school attend on a part-time basis while they work part- or full-time and/or attend to family commitments. While this is a benefit to these students to have the flexibility to work and further their education, it comes at loss of the social aspect of post-secondary education.

The one way in which student–peer relationships were fostered was through group work. However, students held both positive and negative views on this: the positive aspect was the opportunity to get to know other students and being able to share the burden of the workload, and the negative aspect was being unfair workloads among team members. When group dynamics are poor, such as unfair work distribution, having different goals and motivations, or not communicating effectively with their groups, it has been shown to lead to negative experiences (Rusticus & Justus, 2019 ).

Faculty also commented that it was typical for them and other faculty to come up to campus only to teach their classes and then leave afterwards. They noted that their office block was often empty and noted instances when students have come looking for faculty only to find a locked office. Overall, faculty did report feeling congenial with, and supported by, their peers. They also desired a greater connection with their peers, but noted that it would require effort to build, which many were not willing to make.

Finally, student–faculty relationships were the most-rewarding experience for both groups. Students saw these experiences as highly encouraging and felt that they created a safe and welcoming environment where they could approach faculty to ask questions and get extra support. However, in some cases, students had negative experiences with faculty and these had an impact on their self-esteem, motivation and willingness to participate in class. Students’ negative experiences and feedback have been shown to result in declined levels of intrinsic motivation, even if their performance ability is not low (Weidinger et al., 2016 ).

Within the third dimension, institutional setting, a key strength was the small class sizes. With a maximum class size of 35 students, this created a more personal and welcoming environment for students. Students felt that their instructors got to know their names and this promoted more opportunities for interactions. Faculty concurred with this, indicating that the small classes provided greater opportunities for interactions with their students. This enabled more class discussions and grouped-based activities which contributed to a more engaging and interactive educational experience for students and faculty. For students, not being able to hide in the crowd of a large lecture hall, as is common in other university settings, encouraged them to work harder on their studies and to seek help from their instructor if needed.

Finally, both students and faculty commented that the lack of a sense of community was a negative aspect of the LE. This institution is known as a commuter school and both groups reported that they would often attend campus only for school/work and would leave as soon as their commitments were done. This limits opportunities to interact with others and could also potentially impact one’s identity as a member of this community. While both groups expressed a desire for more of a community life, neither group was willing to put in much effort to make this happen. Others have also found that sense of community, including opportunities to engage and interact with others, is important in LEs (e.g. Sadera et al., 2009 ). Schools with more activities and opportunities for student involvement have reports of higher satisfaction for both academic and social experiences (Charles et al., 2016 ).

Limitations

Because this study is based on a relatively small sample at a single university, there is a question of whether the findings can be applied to other departments, universities or contexts. However, it is a strength of this study that both student and faculty perceptions were included, because few past studies have jointly looked at these two groups together using qualitative methods. The use of focus groups among the student groups might have limited the openness of some participants. We also acknowledge that the analysis of qualitative data is inevitably influenced by our roles, life experiences and backgrounds. (The first author is a faculty member and the second and third authors were fourth year students at the time of the study.) This might have impacted our approach to the interpretation of the data compared with how others might approach the data and analysis (Denzin & Lincoln, 2008 ). However, the analysis involved consultation among the research team to identify and refine the themes, and the findings are presented with quotes to support the interpretation. Finally, because experiences were self-reported in this study, they have the associated limitations of self-report data. Despite these limitations, we believe that our findings add to what is known about LEs by capturing multiple perspectives within the same environment.

Future directions

Because our sample was comprised of students across multiple years of their program, some of our findings suggest that upper-level students might have different perceptions of the LE from lower-level students (e.g. work/life balance, access to resources, and overall familiarity with the environment and resources available). However, because the small sample sizes within these subgroups prevent any strong conclusions being made, future researchers might want to explore year-of-study differences in the LE. Additionally, the data collected for this study occurred prior to the COVID-19 pandemic and the mandatory switch to online teaching and learning. Future researchers might want to consider how this has impacted student and faculty perceptions of the LE regarding their personal motivation, the nature and quality of the relationships that have formed with peers and faculty, and the culture and norms of their institution.

This study increases our understanding of LEs by incorporating data collected from both students and faculty working in the same context. Across both groups, we identified important aspects of the LE as being high levels of engagement and motivation, a positive emotional climate, support among peers, strong faculty–student relationships, meaningful experiences, and small class sizes. Students identified negative aspects of the LE, such as certain characteristics of group work and struggles with work–life balance. Both faculty and students identified a lack of a sense of community as something that could detract from the LE. These findings identify important elements that educators and researchers might want to consider as they strive to promote more-positive LEs and learning experiences for students.

Appendix: Interview guide

[Faculty] Tell me a little bit about yourself. For instance, what department you are in, how long you have been teaching at KPU, what courses you teach, why you were interested in this study

• When I say the word learning environment, what does that mean to you?
• Probe for specific examples
• Relate to goal development, relationships, KPU culture
• Probe for factors that made it a positive environment
• Probe for factors that made it a negative environment
• How would you describe an ideal environment?
• Probe for reasons why
• Probe for how KPU could be made more ideal
• What recommendations would you give to the Dean of Arts regarding the learning environment? This could be changes you would recommend or things you recommend should stay the same.
• Do you have any final comments? Or feel there is anything about the learning environment that we have not addressed?

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Learning can be defined as the process leading to relatively permanent behavioral change or potential behavioral change. In other words, as we learn, we alter the way we perceive our environment, the way we interpret the incoming stimuli, and therefore the way we interact, or behave. John B. Watson (1878-1958) was the first to study how the process of learning affects our behavior, and he formed the school of thought known as Behaviorism. The central idea behind behaviorism is that only observable behaviors are worthy of research since other abstraction such as a person’s mood or thoughts are too subjective. This belief was dominant in psychological research in the United Stated for a good 50 years.

Perhaps the most well known Behaviorist is B. F. Skinner (1904-1990). Skinner followed much of Watson’s research and findings, but believed that internal states could influence behavior just as external stimuli. He is considered to be a Radical Behaviorist because of this belief, although nowadays it is believed that both internal and external stimuli influence our behavior.

Behavioral Psychology is basically interested in how our behavior results from the stimuli both in the environment and within ourselves. They study, often in minute detail, the behaviors we exhibit while controlling for as many other variables as possible. Often a grueling process, but results have helped us learn a great deal about our behaviors, the effect our environment has on us, how we learn new behaviors, and what motivates us to change or remain the same.

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What Is the Psychology of Learning?

Learning in psychology is based on a person's experiences

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

 James Lacy, MLS, is a fact-checker and researcher.

The psychology of learning focuses on a range of topics related to how people learn and interact with their environments.

Are you preparing for a big test in your psychology of learning class? Or are you just interested in a review of learning and behavioral psychology topics? This learning study guide offers a brief overview of some of the major learning issues including behaviorism, classical, and operant conditioning .

Let's learn a bit more about the psychology of learning.

Definition of Learning in Psychology

Learning can be defined in many ways, but most psychologists would agree that it is a relatively permanent change in behavior that results from experience. During the first half of the 20th century, the school of thought known as behaviorism rose to dominate psychology and sought to explain the learning process. Behaviorism sought to measure only observable behaviors.

3 Types of Learning in Psychology

Behavioral learning falls into three general categories.

Classical Conditioning

Classical conditioning is a learning process in which an association is made between a previously neutral stimulus and a stimulus that naturally evokes a response.

For example, in Pavlov's classic experiment , the smell of food was the naturally occurring stimulus that was paired with the previously neutral ringing of the bell. Once an association had been made between the two, the sound of the bell alone could lead to a response.

For example, if you don't know how to swim and were to fall into a pool, you'd take actions to avoid the pool.

Operant Conditioning

Operant conditioning is a learning process in which the probability of a response occurring is increased or decreased due to reinforcement or punishment. First studied by Edward Thorndike and later by B.F. Skinner , the underlying idea behind operant conditioning is that the consequences of our actions shape voluntary behavior.

Skinner described how reinforcement could lead to increases in behaviors where punishment would result in decreases. He also found that the timing of when reinforcements were delivered influenced how quickly a behavior was learned and how strong the response would be. The timing and rate of reinforcement are known as schedules of reinforcement .

For example, your child might learn to complete their homework because you reward them with treats and/or praise.

Observational Learning

Observational learning is a process in which learning occurs through observing and imitating others. Albert Bandura's social learning theory suggests that in addition to learning through conditioning, people also learn through observing and imitating the actions of others.

Basic Principles of Social Learning Theory

As demonstrated in his classic Bobo Doll experiments, people will imitate the actions of others without direct reinforcement. Four important elements are essential for effective observational learning: attention, motor skills, motivation, and memory.

For example, a teen's older sibling gets a speeding ticket, with the unpleasant results of fines and restrictions. The teen then learns not to speed when they take up driving.

The three types of learning in psychology are classical conditioning, operant conditioning, and observational learning.

History of the Psychology of Learning

One of the first thinkers to study how learning influences behavior was psychologist John B. Watson , who suggested in his seminal 1913 paper Psychology as the Behaviorist Views It that all behaviors are a result of the learning process. Psychology, the behaviorists believed, should be the scientific study of observable, measurable behavior. Watson's work included the famous Little Albert experiment in which he conditioned a small child to fear a white rat.

Behaviorism dominated psychology for much of the early 20th century. Although behavioral approaches remain important today, the latter part of the century was marked by the emergence of humanistic psychology, biological psychology, and cognitive psychology .

Other important figures in the psychology of learning include:

• Edward Thorndike
• Ivan Pavlov
• B.F. Skinner
• Albert Bandura

A Word From Verywell

The psychology of learning encompasses a vast body of research that generally focuses on classical conditioning, operant conditioning, and observational learning. As the field evolves, it continues to have important implications for explaining and motivating human behavior.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Learning Is a Learned Behavior. Here’s How to Get Better at It.

• Ulrich Boser

It’s effectively a type of project management.

Many people mistakenly believe that people are born learners, or they’re not. However, a growing body of research shows that learning is a learned behavior. Through the deliberate use of dedicated strategies, we can all develop expertise faster and more effectively. There are three practical strategies for this, starting with organization. Effective learning often boils down to a type of project management. In order to develop an area of expertise, we first have to set achievable goals about what we want to learn and then develop strategies to reach those goals. Another practical method is thinking about thinking. Also known as metacognition, this is akin to asking yourself questions like “Do I really get this idea? Could I explain it to a friend?” Finally, reflection is a third practical way to improve your ability to learn. In short, we can all learn to become a better study.

Many people mistakenly believe that the ability to learn is a matter of intelligence. For them, learning is an immutable trait like eye color, simply luck of the genetic draw. People are born learners, or they’re not, the thinking goes. So why bother getting better at it?

• UB Ulrich Boser is a Senior Fellow at the Center for American Progress, where he also founded and runs the science of learning initiative. He’s the author of Learn Better: Mastering the Skills for Success in Life, Business, and School, or, How to Become an Expert in Just About Anything .

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Behavior Change: Cognitive Processes in Learning Essay

Introduction, learning and cognition, reference list.

According to Kimble (1961), learning is taken as the process that brings in a relatively permanent alteration in behavior or potentiality in behavior as a result of reinforcement. For leaning to take place there must be a permanent change in the behavior. Therefore learning omits those behavior changes that are not permanent such as sleeping, eating and so on. In addition the term learning also do not consider the permanent changes that result due to maturation as learning process.

Whenever learning occurs, it is manifested as a change in behavior. The change though does not result immediately after learning, but occurs after some time span. Since learning cannot be studied directly, learning of behavior change is an important aspect because gives an inference to the process that preside behavior change and hence making the study of learning possible.

Except for B.F. Skinner who considers reinforcement and punishment as the most important aspects of learning behavior, majority of the learning theorist consider that learning compose of a superseding variable between experience and behavior (Olson & Hergenhahn, 2009). This helps to differentiate performance and learning where performance exhibit the real learning as a behavior, although learning is regarded to take place before the exhibition of the learned behavior through performance.

Thus it should be taken to represent potential for future behavior. Thus in summary, learning can be taken to represent behavior in potential that signify a superseding variable between experience and behavior; that ultimately gets expressed through the tool of performance.

Conditioning is one process through which learning takes place. This type of learning was initially formulated by Pavlov and later augmented by Skinner. Conditioning can further be split into two groups.

These are classical conditioning and Instrumental conditioning. In the former conditioning, learning occurs when animals master how to associate neutral stimulus with natural stimulus they are familiar with. For instance classical conditioning results when a dog salivates when a man with a lab coat passes. This can happen only if the man that feeds the dog wears a lab coat every time he does it. Therefore the dog learns to associate the lab coat with food. Thus every time it sees a lab coat it associates it with food.

On the other hand, the latter conditioning is also known as operant conditioning and it occurs when a behavior that already exists is reinforced in order to increases its chances of reoccurrences (Olson & Hergenhahn 2009). Similarly it occurs when an animal masters to act in a certain manner in order to receive an intrinsically rewarding stimulus. This can be inferred by jumping of a trained dolphin from a pool of water so that to get a fish.

This results if the dolphin is given a fish every time it reaps. These forms of learning are very important in the day to day lives since Classical conditioning is used to differentiate between those objects that are essential for survival and those that are not, while on the other hand, operant conditioning is used for avoidance of unwanted objects.

Almost every theory of learning includes cognitive association into the general stimulus-response relationship advocated by operant and classical conditioning. The said cognitive association can occur between an occurrence of two stimuli (S-O), depiction of a stimulus and response (S-R) or finally a representation of a response and an outcome (R-O).

The most important factor in all these associations is that anticipation of the results acts as the mediator between learning and performance. Therefore the S-R association can result from preconditioning events (Kimble, 1961).

For instance introducing of a pairing related stimuli and do away with any reinforcement which will result into the expectation that future representation of one of the stimulus will lead to the occurrence of the other one. On the other hand, reducing the frequency of representation of a set of stimuli will reduce the future expectancy of the representation of the desired stimuli or response.

For example when a dog is conditioned that every time it sees a man with a lab coat it gets its food will salivate every moment it sees any man wearing a lab coat. Therefore there is a general expectancy that when the dog sees a man with a lab coat it will definitely salivate since it associates the lab coat with the stimulus it is familiar with food. If this procedure is altered and the dog does not get its food every time it sees a man with a lab coat, its expectation that it will salivate every time it sees a man with a lab coat decreases.

Behavior change can be regarded as the ultimate result of learning that is represented through the instrument of performance. Classical conditioning and instrumental conditioning are considered as the two forms of learning through which other form of learning can be linked to. It is from this learning paradigm that forms the basis of cognitive association which tries to explain the expectancy of future happenings as a mediating variable that helps to build a framework to enable comprehend cognitive processes so that to assist in.

Kimble, G. (1961). Hilgard, Ernest R. and Marquis, Donald G. Hilgard and Marquis’ Conditioning and learning. New York: Appleton-Century-Crofts.

Olson, Mathew., & Hergenhahn, B. (2009). An Introduction to Theories of Learning. (Eighth Edition). New York: Prentice Hall.

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IvyPanda. (2018, December 27). Behavior Change: Cognitive Processes in Learning. https://ivypanda.com/essays/learning-and-cognition/

"Behavior Change: Cognitive Processes in Learning." IvyPanda , 27 Dec. 2018, ivypanda.com/essays/learning-and-cognition/.

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IvyPanda . 2018. "Behavior Change: Cognitive Processes in Learning." December 27, 2018. https://ivypanda.com/essays/learning-and-cognition/.

1. IvyPanda . "Behavior Change: Cognitive Processes in Learning." December 27, 2018. https://ivypanda.com/essays/learning-and-cognition/.

Bibliography

IvyPanda . "Behavior Change: Cognitive Processes in Learning." December 27, 2018. https://ivypanda.com/essays/learning-and-cognition/.

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Behavior for Learning Strategies in Education

Introduction

Teachers, to ensure that students are behaving well in class to learn, use behaviour for Learning (B4L) strategies (Adams, 2009). The relationships are the crucial influences upon children’s learning behaviours (Adams, 2009). Such relationships are with themselves, others and the curriculum (East Sussex Primary GTP, 2009). If these relationships are approached positively by a teacher, the students can “increase opportunities for learning” (ESP GTP, 2009, p.1). Focusing on the lessons from year 6 class, this essay will show the two key strategies, which are supporting pupil’s emotional well being, which caters the relationship with themselves and others, and utilizing simple, clear and well paced lessons with stimulating activities, which caters the relationship with the curriculum (ESP GTP, 2009; Elton Report, 1989). These strategies can be used to create an effective and purposeful classroom environment.

To support student’s emotional wellbeing, the teacher needs to attempt to make a positive relationship with the students. According to Haydn (2007), students preferred friendly teachers who praised and encourage them through learning process. Positive reinforcement can support students to feel valued and emotionally secure, which impacts positively and neurologically on their learning behavior (NHSS, 2004). On the other hand, if the students don’t feel valued and feel insecure, they will more likely have low self-esteem (NHS, 2004). Low-self esteem is the major barrier to effective learning and motivation (Cohen et al, 2010). Hence, motivation is a crucial element of learning and success in school and helps students achieve and maintain good behavior (Wentzel, 2012; Wentzel & Wigfield, 2009; Wigfield et al., 2006). Unlike the punishment, positive reinforcement lasts for long term and lasts effectiveness over time (Kohn, 2006). This was clearly seen in the observation of most of the lessons as the teacher precisely praised (Lemov, 2010) most students during the discussion although they were not exactly correct but related. Students who have given wrong answers were also praised for participating in the discussion and this encouraged the normalizing of errors when trying (Lemov, 2010). The students looked more confident and frequently had their hands up more ever since, showing the effect of praise and encouragement.

Student well being has been stated by Awang, Ahmad, Wahab and Mamat (2013) as the major determinant of the behavior the student exhibits and therefore, how he/she engages in the classroom and class related activities. One of the challenges in supporting student wellbeing is when the student exhibits negative behavior. According to Awang et al. (2013), it is important that the teacher deals with negative behavior in a way that doesn’t dent the student’s emotional wellbeing. Some of the ways suggested by Awang et al. (2013) and witnessed in the classroom include privately approaching the students and promise. Under private approach to the student, the teacher approaches the student and points out the negative behaviour and how it is interfering with class work or interrupting instruction. The teacher then reminds the students of his/her academic obligations and the specific tasks he/she should be engaged. The student is then given an opportunity to explain his/her behavior and then the teacher offers him/her an opportunity to improve on the negative behavior. This method doesn’t embarrass the student and it has been shown to reduce the likelihood of a student involvement in negative behavior (Gotzens, Badia, Genovard & Dezcallar, 2010). Promise involves the teacher approaching the misbehaving student and informing him/her of the negative behavior. The teacher then asks the student to state the appropriate alternative behavior and then asks the student to make a promise either verbally or in writing not to engage in the negative behaviour again. This method saves the students face, it helps to hold the students accountable to his/her action, and reduces likelihood of misbehaving in the future (Gotzens et al., 2010).

In terms of pedagogical characteristics, teachers can achieve good relationship with the students if the teacher’s professional. Explicitly, the students are more likely to respect their teachers if they are knowledgeable and can explain things clearly (Hydn, 2007). Moyles (2001) supported that children showed unacceptable behavior when they are unsure of their work based on observations. Students are more likely to be engaged in class if the lesson is dynamic and stimulating yet clear and easy enough to understand. Teaching Agency and Rogers (2006) point out that well prepared lesson plans are one of the strategies for good teaching. Hence “good teaching is the most effective way to get good behavior” (TA, 2012). If the lesson is not simple and clear enough, the students are most likely become disengaged and misbehave since they are not provided with the direction to their own learning (East Sussex Primary GTP, 2009; Moyles, 2001). However on the other hand, making the lessons too easy can affect high-ability students negatively since the lessons are not challenging enough (Paton, 2012). Wiliam (2014) argued that the smartest child can be overtaken academically by the slowest child if the smartest child is not over stimulated with challenges. Therefore, differentiated lesson can be effective for classes with mixed abilities (Grimes and Stevens 2009; Tomlinson, 2010). The class demonstrated the use of differentiated instruction especially during the mathematics lesson especially during the independent activity phase. The students with high ability were given the challenging exercise whereas other students (regular and the low ability) worked on the medium leveled exercise. The teacher gave the low ability students, extra scaffolding/support. Thus children were focused and engaged without any low level disruptions, which demonstrates the success of applying differentiated (dynamic, stimulating yet clear and simple) lesson in the class. According to Wheatley, West, Charlton, Sanders and Taylor (2009), differential instruction helps in reaching to the students regardless of their abilities and serves to build confidence in them. This method of instruction is important and relevant because it makes the students fell in control, builds confidence, and makes the students less dependent on the teacher (Wheatley et al., 2009). As argued by James and Coolier (2011), the starting point of each learning session is vital, and inclusion of warm-up activities is important for boosting students’ participation and understanding. In the mathematics class, it was observed that warm-up included a revision of the previous class work for the first five minutes of the current class.

Student behavior management is still rated the most stressful aspect of teaching among the teachers (Chaplain, 1995b, 2008; Mastilli and Sadro-Brown, 2002). If the teacher is unable to manage the misbehaviours, students are unable to learn properly (Adams, 2009). To prevent that from happening and cater the positive learning environment, based on the observation from the year 6 class, the two key strategies are by engaging with pupils positively and making the lesson fun yet explicit. These strategies can ensure the students to create the positive relationship with themselves, others and the curriculum, which overall encourages effective learning.

• Awang, M.M., Ahmad, A.R., Wahab, J.L.A. & Mamat, N. (2013).Effective teaching strategies to encourage learning behavior. IOSR Journal Of Humanities And Social Science (IOSR-JHSS) Volume 8, Issue 2, 35-40
• Gotzens, C., Badia, M., Genovard, C., & Dezcallar, T. A. (2010). Comparative Study of the Seriousness Attributed to Disruptive Classroom Behaviours. Electronic Journal of Research in Educational Psychology , 8(1), 33-58.
• James, A. R., & Coolier, D. H. (2011). Warm-Ups: The Key to the Beginning of a Great Lesson. Strategies , 14- 15
• Wheatley, R. K., West, R. P., Charlton, C. T., Sanders, R. B., & Taylor, T. G. S. M. J. (2009). Improving behaviour through differential reinforcement: A praise note system for elementary school students. Education and Treatment of Children , 32(4), 551-557.

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Behaviour in schools: is it really getting worse?

In classrooms across the UK, Europe, the US and Australia, teachers and school leaders say that student behaviour is a growing problem. Even in places with little in-class violence, more schools report higher rates of students being disruptive, off-task, disrespectful and chronically absent. More students are also reported to be “internally truant” - ie, in school buildings, but not in class.

In some cases, the occurrences are extreme. In Dundee, Scotland, a 17-year-old was charged with assaulting a teacher , allegedly knocking her unconscious. Parents in Washington DC report that their Reception-age students are repeatedly coming home with black eyes given to them by other five-year-olds. In Baltimore, Maryland, teachers and principals report being threatened and assaulted by students and their parents.

There are several theories about why poor behaviour is on the rise. Approaches to curbing student disruption and undesirable behaviour have also become politicised and polarised around ideas of what discipline and behaviour codes should look like in schools.

But do we know if behaviour is really getting worse? And if it is, do we understand why?

Is behaviour getting worse in schools?

When it comes to behavioural incidents, anecdotes abound, especially following the rocky reopening of schools after the pandemic. But experts say official government data is limited.

That’s partly because behaviour is subjective - classifying types of behaviour is usually down to individual teachers’ judgements in the moment in classrooms. Agreeing terms and specifications to frame what constitutes poor behaviour across a school is hard enough, let alone across a wider geographical area. This makes the data that is captured problematic.

Official data also tends to lag by up to a year or longer, which makes a real-time viewpoint impossible.

And in terms of low-level disruption in particular - the behaviour that doesn’t require the use of sanctions such as suspensions and exclusions - there are few governments that have the time or capacity to collect and process that kind of data systematically at a national level.

Lack of behaviour data

Tom Bennett, a long-time behaviour adviser for the Department for Education, says the English government is attempting to conduct a comparable year-by-year analysis - but it is only in its second year and is survey-based data. What it does suggest, though, is that schools are reporting increasing disruption from behaviour .

Away from the government, there is a patchwork of other sources. So what do they tell us?

One source is teacher experience, a valid measure when considered in the wider context. Visits to hundreds of schools over the past few years have provided Bennett with some “anecdata” that points to a rising problem.

“Every school I go to, they say behaviour has gotten worse, and truancy has gotten worse,” he says.

Recent survey data supports that.

The Tes Wellbeing Report 2024 , based on survey data, found an increase in the number of schools turning to behaviour management software to reduce the workload of a rise in behaviour incidents in schools.

Meanwhile, in a Teacher Tapp survey commissioned by the BBC earlier this year, a third of UK teachers reported that they’d witnessed a student fight that week, and 40 per cent had witnessed violence that needed adult intervention. A fifth of teachers reported online or verbal abuse from a parent or guardian.

Low-level disruption

In a different Teacher Tapp survey this year, about 43 per cent of teachers said the last lesson they taught was disrupted owing to poor behaviour. This was significantly more than the number who had responded the same in previous surveys over the past five years, except for a period in 2019 when the figure was 41 per cent. Overall - particularly in primary - teachers report worse behaviour now than in the period since 2018.

A similar evidence base exists in the US. A new survey , conducted by Pew Research Center, reveals that nearly half of teachers consider student behaviour at their school “fair or poor”, and a vast majority, 79 per cent, say parents don’t do enough to hold children accountable for misbehaviour at school. Teacher responses varied widely according to the poverty level at their school, with teachers in schools with higher poverty responding more negatively about student behaviour and their perceived stress levels.

“Eight in ten teachers say the lasting impact of the pandemic on students’ behaviour, academic performance and emotional wellbeing has been very or somewhat negative,” write the Pew researchers.

Meanwhile, in Australia, a Senate committee looking into worsening behaviour in the country’s schools found disruptive behaviour was among the worst in the world. In France, a perceived worsening of behaviour is prompting trials of school uniforms in an effort to improve behaviour standards.

Attendance in schools

Chronic absenteeism, officially defined as missing 10 per cent of school days, has also substantially increased. Persistent absenteeism in England has doubled since before the pandemic, according to government data, to include more than a quarter of students. In the US, 26 per cent of students are chronically absent. Even within schools, students have gone missing owing to “ internal truancy ”, when students are in the building but not in class.

And the exclusions and suspensions data we have in England does suggest a growing need for these sanctions since the pandemic.

Reasons for challenging behaviour

So the data that we do have points to a worsening problem, as does the testimony of those working in schools. For many, the pandemic has been cited as the driver of that deterioration.

The National Center of Educational Statistics reported last year that 80 per cent of US schools blamed the pandemic for impacting student behaviour and socio-emotional development. Increased classroom disruptions, misconduct and incidents of disrespect, schools agreed, were due “to the Covid-19 pandemic and its lingering effects”.

But some believe it is more a “perfect storm” of challenges that are contributing to the increase in bad behaviour and absences - including teacher and support-staff shortages, lack of clear guidance on how to handle misbehaviour and a change in how families view the importance of coming to school after pandemic school closures.

“The habits children had of being at school and following structure have been lost,” Bennett says. “Children most affected by this are in the most chaotic environments. It’s a perfect storm and it’s had an impact.”

Missed social learning

Others argue that schools aren’t only responsible for academic learning, they also help many students to develop crucial socio-emotional skills, such as controlling their emotions and learning how to get along with others.

That learning was interrupted when schools were closed, putting some of the most vulnerable children behind, and there is perhaps less focus on these skills than in previous generations, owing to a greater emphasis on academic skills, partly because of efforts to catch up on missed learning.

Leanne Forde-Nassey, headteacher of the Key Education Centre pupil referral unit in Hampshire, says she is seeing more students with behavioural challenges, and it might be that lockdowns and closures prevented many students from learning important behaviour-related skills.

“We’ve got a number of children that will be developmentally more delayed,” Forde-Nassey says. “We expect them to plan, self-motivate and have executive functioning skills, but they are incapable of doing all these things. There is no way [the pandemic] hasn’t had an impact on how their brain has developed. Then they can’t engage in learning.”

Mental health in schools

Forde-Nassey also mentions the backlog of students who need mental health evaluations and diagnoses, which the pandemic worsened but were already problematic before the pandemic. In the US and the UK, mental health challenges for children and teens have surged significantly - the effects of which may play out in classrooms in the form of disruption and disobedience.

Some argue that schools may also not be paying enough attention to how a lack of academic skills can give rise to behaviour issues - skills that were also delayed because of the pandemic. Research suggests that students with poor reading skills, for example, often register more behaviour incidents, such as office referrals.

“The number of kids who missed crucial periods of instruction during the pandemic is higher,” says the behavioural analyst Matthew Cicoria. In his work consulting with US schools on behaviour issues and supporting individual students, he has found that when foundational skills are missing, students are more frustrated and less likely to cooperate with classroom norms.

Reasons to act out make sense and may even become beneficial for an academically frustrated student, Cicoria says. Getting into trouble might mean they get to stop doing the hard things they are struggling with, like writing an essay or doing long division, and they may get to leave class and spend time with an attentive adult.

“If even a five per cent increase of kids are having frustration-related academic issues, by the law of large numbers, that is a significant number” of students disrupting class, Cicoria says.

Mobile phones and education

Yet another influence may be pupils using digital technology. Research has shown how the widespread use of phones in classrooms causes distraction and academic disruption. But it’s not just phones, experts say - many students may have spent the majority of time at home during the school closures playing video games and watching YouTube.

Returning to an environment that requires paying attention for long periods may be more challenging. After focusing is disrupted, it’s often harder to get back on track.

Considering all of the facets to this problem, it’s perhaps unsurprising that teachers feel under pressure around students’ behaviour: the challenges are clearly greater and more complex than in the past.

Teachers interviewed for this piece say that we have failed to properly prepare teachers to face these challenges. Indeed, anonymously, some argue that a lack of proper behaviour training is a contributor to the behaviour challenges being seen in schools.

Teachers say that classroom management is the hardest part of their job, yet in one study, 40 per cent reported that they felt unprepared to handle classroom behaviour challenges. Experts say many new teachers didn’t receive any training on how to handle bad behaviour and disruptions in their training programmes.

Training for teachers

The US Department of Education’s Institute for Education Sciences indicates five top practices, based on research, that teachers should master for effective classroom management.

These include how to establish rules and routines, and set expectations for behaviour; how to manage time and engage students; and how to reinforce positive behaviour and redirect off-task behaviour. However, teachers aren’t often taught it - a 2020 report from the National Council on Teacher Quality shows that only about 30 per cent of US teachers receive pre-service training in those practices.

Getting that training to teachers and leaders in the UK has been crucial, Bennett says, through initiatives such as the Behaviour Hubs project that provides schools with training for teachers and leaders, and helps schools to develop a plan.

Training on what defines good behaviour extends to the students as well - an important step that schools often skip. “Lots of studies in the UK show that the best schools teach the behaviours to succeed,” Bennett says. “‘This is how we want you to behave’ - and they have clear consequences, some of which won’t be punitive.”

Bennett says that explicitly teaching behaviour expectations to students has seen some success, along with changes in leadership and other school-specific factors, in the more than 750 schools in the Behaviour Hubs programme, according to school reports and individual school case studies. (Interim data hasn’t yet been published.) But Bennett admits that the programme, which is at capacity, takes in a fraction of the 30,000 schools across the UK.

“We can’t pretend that it has changed the whole system,” Bennett said. But he hopes that they are setting an example of what’s possible by “shining a light on some of the schools that are doing exceptional work in the area of behaviour, and networking them with other schools on their own journeys”.

Yet while training is clearly needed, what complicates its delivery is the lack of agreement on what good behaviour management should look like.

Behaviour war

In the US and the UK, there are big disagreements about what might be called the philosophy of behaviour management in schools. Like the “reading wars”, a polarising kind of “behaviour war” has pitted one “side” against the other, with one group of educators believing that behaviour improves more efficiently through addressing children’s emotional needs, while others opt for a more structured approach, centred on rules, norms and consequences.

Take two of the popular approaches at opposite ends of the spectrum in the US: restorative justice and zero tolerance. Restorative justice focuses on repairing harms and relationships - ”making things right” with offending parties - instead of just handing out punishment for poor behaviour, with the aim of improving students’ socio-emotional skills and reducing suspensions. However, rigorous studies of restorative practices have found serious flaws in improving student behaviour and academic performance. Yet the same can be said for zero-tolerance policies, which focus more on doling out punishments, often for minor infractions.

On the ground, those schools that provide consistently safe environments with fewer behaviour incidents and disruptions may be coming from different philosophies but seem to have much in common. Both kinds appear to have detailed behaviour plans, good communication with educators and staff and - importantly - parents, and focus on building relationships with students and having high, specific expectations.

Kulvarn Atwal, who runs two Unicef rights-respecting primary schools - Highlands and Uphall - in Redbridge, London, said the schools’ values are kindness, respect and responsibility, and their expectations for behaviour follow those values.

Students have a right to an education, he says, but that includes respecting others’ right to the same. Children learn early to move through the school on their own without adult supervision and have a voice in decision-making. Adults have been trained to model the calm behaviour they expect from students.

Restorative approaches

Highlands and Uphall use the restorative approach to help students reflect on poor choices and make amends with someone they’ve offended, whether that’s a teacher or another student. Atwal calls more structured approaches with clear adult authority “low-trust environments”, which often just remove unwanted behaviours instead of working to improve them - whereas rights-respecting schools, such as his, hope to change unwanted behaviours.

But he said practices such as restorative justice only really work if the underlying culture supports it. “If a child is hitting the same child again and again, then it’s not working,” he says. “We aren’t a school that has no sanctions.”

Meanwhile, Barry Smith, a former headteacher who is now a behaviour consultant, is renowned in the English school system for his orderly, some might say militaristic, adults-are-in-charge ideas around managing behaviour. In relation to schools where he has worked, such as Michaela Academy and Great Yarmouth Charter Academy, he says similar things to Atwal about the need to foster a safe, positive environment, it’s just that the ideas are coming from a different place.

“My basic premise is that relationships are really important. Schools should be built on relationships and school culture is built on mutual genuine respect,” Smith says. “The adults are the boss. I’m the boss, and I’m going to tell you what to do - but I’m a very kind boss.”

Respect is shown mutually, from student to teacher and back again. For Smith, that often looks like what he calls “over-polite”, a kind of exaggerated kindness that extends from word choice to body language to facial expression, and which is supposed to convey a “warm, welcoming and friendly” attitude.

Influence of Covid-19

So might part of the solution to poor behaviour involve bringing these camps closer together to see what they have in common, rather than how they differ, to provide better training for teachers?

Like so much of this debate, it’s not that straightforward. To improve behaviour system-wide, Smith says, educators, parents and leaders would need to be more honest about the size of the challenges schools are facing - and that not just behaviour plans, but instruction and leadership, would need to improve.

We need better data (something that is increasing owing to digital behaviour monitoring tools), better research, better training and better alignment. And to a degree, that’s not a pandemic problem, Smith says, it’s a system problem that we are avoiding talking about - and until we do, these challenges will remain.

“I think we delude ourselves on lots of levels,” Smith says. “We say it’s post-Covid. I think that’s a convenient excuse.”

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• Open access
• Published: 13 May 2024

The big five factors as differential predictors of self-regulation, achievement emotions, coping and health behavior in undergraduate students

• Jesús de la Fuente 1 , 2 ,
• Paul Sander 3 ,
• Angélica Garzón Umerenkova 4 ,
• Begoña Urien 1 ,
• Mónica Pachón-Basallo 1 &
• Elkin O Luis 1  

BMC Psychology volume  12 , Article number:  267 ( 2024 ) Cite this article

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1 Altmetric

Metrics details

The aim of this research was to analyze whether the personality factors included in the Big Five model differentially predict the self-regulation and affective states of university students and health.

A total of 637 students completed validated self-report questionnaires. Using an ex post facto design, we conducted linear regression and structural prediction analyses.

The findings showed that model factors were differential predictors of both self-regulation and affective states. Self-regulation and affective states, in turn, jointly predict emotional performance while learning and even student health. These results allow us to understand, through a holistic predictive model, the differential predictive relationships of all the factors: conscientiousness and extraversion were predictors regulating positive emotionality and health; the openness to experience factor was non-regulating; nonregulating; and agreeableness and neuroticism were dysregulating, hence precursors of negative emotionality and poorer student health.

Conclusions

These results are important because they allow us to infer implications for guidance and psychological health at university.

Peer Review reports

Introduction

The personality characteristics of students have proven to be essential explanatory and predictive factors of learning behavior and performance at universities [ 1 , 2 , 3 , 4 ]. However, our knowledge about such factors does not exhaust further questions, such as which personality factors tend toward the regulation of learning behavior and which do not? Or can personality factors be arranged on a continuum to understand student differences in their emotions when learning? Consequently, the aim of this study was to analyze whether students’ personality traits differentially predict the regulation of behavior and emotionality. These variables align as different motivational-affective profiles of students, through the type of achievement emotions they experience during study, as well as their coping strategies, motivational state, and ultimately health.

Five-factor model

Previous research has shown the value and consistency of the five-factor model for analyzing students’ personality traits. Pervin, Cervone, and John [ 5 ] defined five factors as follows: (1) Conscientiousness includes a sense of duty, persistence, and behavior that is self-disciplined and goal-directed. The descriptors organized, responsible, and efficient are typically used to describe conscientious persons. (2) Extraversion is characterized by the quantity and intensity of interpersonal relationships, as well as sensation seeking. The descriptors sociable, assertive, and energetic are typically used to describe extraverted persons. (3) Openness to experience incorporates autonomous thinking and willingness to examine unfamiliar ideas and try new things. The descriptors inquisitive, philosophical, and innovative are typically used to describe persons open to experience. (4) Agreeableness is quantified along a continuum from social antagonism to compassion in one’s quality of interpersonal interactions. The descriptors inquisitive, kind, considerate, and generous are often used to describe persons characterized by agreeableness. (5) Finally, neuroticism tends to indicate negative emotions . Persons showing neuroticism are often described as moody, nervous, or touchy.

This construct has appeared to consistently predict individual differences between university students. Prior research has documented its essential role in explaining differences in achievement [ 6 , 7 ], motivational states [ 8 ], students’ learning approaches [ 9 ], self-regulated learning [ 10 ].

Five-factor model, self-regulation, achievement emotions and health

The relationship between the Big Five factors and self-regulation has been analyzed historically with much interest [ 11 , 12 , 13 , 14 , 15 ]. The dimensions of the five-factor model describe fundamental ways in which people differ from one another [ 16 , 17 ]. Of the five factors, conscientiousness may be the best reflection of self-regulation capacity. More recent research has shown consistent evidence of the relationship between these two constructs, especially conscientiousness, which has a positive relationship, and neuroticism, which has a negative relationship with self-regulation [ 18 , 19 ]. The Big Five factors are also related to coping strategies [ 20 ].

The evidence on the role of the five-factor model in self-regulation, achievement emotions, and health has been fairly consistent. On the one hand, self-regulation has a confirmed role as a meta-cognitive variable that is present in students’ mental health problems [ 21 ]. Similarly, personality factors and types of perfectionism have been associated with mental health in university students [ 22 ]. In a complementary fashion, one longitudinal study has shown that personality factors have a persistent effect on self-regulation and health. Sirois and Hirsch [ 23 ] confirmed that the Big Five traits affect balance and health behaviors.

Self-regulation, achievement emotions and health

Self-regulation has recently been considered a significant behavioral meta-ability that regulates other skills in the university environment. It has consistently appeared to be a predictor of achievement emotions [ 24 ], coping strategies [ 25 ], and health behavior [ 26 ]. In the context of university learning, the level of self-regulation is a determining factor in learning approaches, motivation and achievement [ 27 ]. Similarly, the self- vs. externally regulated behavior theory [ 27 , 28 ] assumes that the continuum of self-regulation can be divided into three types: (1) self-regulation behavior, which is the meta-behavior or meta-skill of planning and executing control over one’s behavior; (2) nonregulation behavior (deregulation) , where consistent self-regulating behavior is absent; and (3) nonregulation behavior, when regulatory behavior is maladaptive or contrary to what is expected. Some example behaviors are presented below, and these have already been documented (see Table  1 ). Recently, Beaulieu and collaborators [ 29 ] proposed a self-dysregulation latent profile for describing subjects with lower scores on subscales regarding extraversion, agreeableness and conscientiousness and higher scores concerning negative emotional facets.

Table  1 here.

Consequently, the question that we pose - as yet unresolved - is whether the different personality factors predict a determined type of regulation on the continuum of regulatory behavior, nonregulatory (deregulatory) behavior and dysregulatory behavior, based on evidence.

Aims and hypotheses

Based on the existing evidence, the aim of this study was to establish a structural predictive model that would order personality factors along a continuum as predictors of university students’ regulatory behavior. The following hypotheses were proposed for this purpose: (1) personality factors differentially predict students’ regulatory, nonregulatory and dysregulatory behavior during academic learning; they also differentially determine students’ type of emotional states (positive vs. negative affect); (2) the preceding factors differentially predict achievement emotions (positive vs. negative) during learning, coping strategies (problem-focused vs. emotion-focused) and motivational state (engagement vs. burnout); and (3) all these factors ultimately predict student health, either positively or negatively, depending on their regulatory or dysregulatory nature.

Participants

Data were gathered from 2019 to 2022, encompassing a total of 626 undergraduate students enrolled in Psychology, Primary Education, and Educational Psychology programs across two Spanish universities. Within this cohort, 85.5% were female, and 14.5% were male, with ages ranging from 19 to 24 years and a mean age of 21.33 years. The student distribution was equal between the two universities, with 324 attending one and 318 attending the other. The study employed an incidental, nonrandomized design. The guidance departments at both universities extended invitations for teacher participation, and teachers, in turn, invited their students to partake voluntarily, ensuring anonymity. Questionnaires were completed online for each academic subject, corresponding to the specific teaching-learning process.

Instruments

Five personality factors.

The Big Five Questionnaire [ 30 ], based on the version by Barbaranelli et al. [ 31 ], assessed scores for five personality factors. Confirmatory factor analysis (CFA) of the 67 scale items resulted in a five-factor structure aligned with the Big Five Model. The outcomes demonstrated satisfactory psychometric properties and acceptable fit indices. The second-order confirmatory model exhibited a good fit (chi-square = 38.273; degrees of freedom (20–15) = 5; p  > 0.10; chi/df = 7.64; RMR = 0.0425; NFI = 0.939; RFI = 0.917; IFI = 0.947; TLI = 0.937; CFI = 0.946; RMSEA = 0.065; HoeLength index = 2453 ( p  < 0.05) and 617 ( p  < 0.01)). Internal consistency of the total scale was also strong (alpha = 0.956; Part 1 = 0.932 and Part 2 = 0.832; Spearman-Brown = 0.962 and Guttman = 0.932).

Self-Regulation : The Short Self-Regulation Questionnaire (SSRQ) [ 32 ] gauged self-regulation. The Spanish adaptation, previously validated in Spanish samples [ 33 ], encompassed four factors measured by a total of 17 items. Confirmatory factor analysis confirmed a consistent factor structure (chi-square = 845.593; df = 113; chi/df = 7.483; RMSM = 0.0299; CFI = 0.959, GFI = 0.94, AGFI = 0.96, RMSEA = 0.059). Validity and reliability values (Cronbach’s alpha) were deemed acceptable (total (α = 0.86; Omega = 0.843); goal-setting planning (α = 0.79; Omega = 0.784); perseverance (α = 0.78; Omega = 0.779); decision-making (α = 0.72; Omega = 0.718); and learning from mistakes (α = 0.72; Omega = 0.722)), comparable to those of the English version. Example statements include: “I usually keep track of my progress toward my goals,” “In regard to deciding about a change, I feel overwhelmed by the choice,” and “I learn from my mistakes.”

Positive-negative affect

The Positive and Negative Affect Scale (PANAS-N) [ 34 ], validated with university students, assessed positive and negative affect. The PANAS comprises two factors and 20 items, demonstrating a consistent confirmatory factor structure (chi-square = 1111.147; df = 169; chi/df = 6.518; RMSM = 0.0346; CFI = 0.955, GFI = 0.963, AGFI = 0.96, RMSEA = 0.058). Validity and reliability values (Cronbach’s alpha) were acceptable (total (α = 0.891; Omega = 0.857); positive affect (α = 0.8199; Omega = 0.784); and negative affect (α = 0.795; Omega = 0.776), comparable to those of the English version. Sample items include “I am a lively person, I usually get excited; I have bad moods (I get upset or irritated).”

Learning Achievement Emotion : The variable was measured using the Spanish version [ 35 ] of the Achievement Emotions Questionnaire (AEQ-Learning) [ 36 ], encompassing nine emotions (enjoyment, hope, pride, relief, anger, anxiety, hopelessness, shame, and boredom). Emotions were classified based on valence (positive or negative) and activation (activating or deactivating), resulting in four quadrants. Another classification considered the source or trigger: the ongoing activity, prospective outcome, or retrospective outcome. Psychometric properties were adequate, and the confirmatory model displayed a good fit (chi-square = 529.890; degrees of freedom = 79; chi/df = 6.70; SRMR = 0.053; p  > 0.08; NFI = 0.964; RFI = 0.957; IFI = 0.973; TLI = 0.978, CFI = 0.971; RMSEA = 0.080; HOELTER = 165 ( p  < 0.05) and 178 ( p  < 0.01)). Good internal consistency was found for the total scale (Alpha = 0.939; Part 1 = 0.880, Part 2 = 0.864; Spearman-Brown = 0.913 and 884; Guttman = 0.903). Example items include Item 90: “I am angry when I have to study”; Item 113: “My sense of confidence motivates me”; and Item 144: “I am proud of myself”.

Engagement-Burnout : Engagement was assessed using a validated Spanish version of the Utrecht Work Engagement Scale for Students [ 37 ], demonstrating satisfactory psychometric properties for Spanish students. The model displayed good fit indices, with a second-order structure comprising three factors: vigor, dedication, and absorption. Scale unidimensionality and metric invariance were verified in the samples assessed (chi-square = 592.526, p  > 0.09; df = 84, chi/df = 7.05; SRMR = 0.034; TLI = 0.976, IFI = 0.954, and CFI = 0.923; RMSEA = 0.083; HOELTER = 153, p  < 0.05; 170 p  < 0.01). Cronbach’s alpha for this sample was 0.900 (14 items); the two parts of the scale produced values of 0.856 (7 items) and 0.786 (7 items).

Burnout : The Maslach Burnout Inventory (MBI) [ 38 ], in its validated Spanish version, was employed to assess burnout. This version exhibited adequate psychometric properties for Spanish students. Good fit indices were obtained, with a second-order structure comprising three factors: exhaustion or depletion, cynicism, and lack of effectiveness. Scale unidimensionality and metric invariance were confirmed in the samples assessed (chi-square = 567.885, p  > 0.010, df = 87, chi/df = 6.52; SRMR = 0.054; CFI = 0.956, IFI = 0.951, TLI = 0.951; RMSEA = 0.071; HOELTER = 224, p  < 0.05; 246 p  < 0.01). Cronbach’s alpha for this sample was 0.874 (15 items); the two parts of the scale were 0.853 (8 items) and 0.793 (7 items).

Strategies for coping with academic stress : The Coping Strategies Scale (Escala Estrategias de Coping - EEC) [ 39 ] was utilized in its original version. Constructed based on the Lazarus and Folkman questionnaire [ 40 ] using theoretical-rational criteria, the original 90-item instrument resulted in a 64-item first-order structure. The second-order structure comprised 10 factors and two significant dimensions. A satisfactory fit was observed in the second-order structure (chi-square = 478.750; degrees of freedom = 73, p  > 0.09; chi/df = 6.55; RMSR = 0.052; NFI = 0.901; RFI = 0.945; IFI = 0.903, TLI = 0.951, CFI = 0.903). Reliability was confirmed with Cronbach’s alpha values of 0.93 (complete scale), 0.93 (first half), and 0.90 (second half); Spearman-Brown coefficient of 0.84; and Guttman coefficient of 0.80. Two dimensions and 11 factors were identified: (1) Dimension: emotion-focused coping—F1. Fantasy distraction; F6. Help for action; F8. Preparing for the worst; F9. Venting and emotional isolation; F11. Resigned acceptance. (2) Dimension: problem-focused coping—F2. Help seeking and family counsel; F10. Self-instructions; F10. Positive reappraisal and firmness; F12. Communicating feelings and social support; F13. Seeking alternative reinforcement.

Student Health Behavior : The Physical and Psychosocial Health Inventory [ 41 ] measured this variable, summarizing the World Health Organization (WHO) definition of health: “Health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” The inventory focused on the impact of studies, with questions such as “I feel anxious about my studies.” Students responded on a Likert scale from 1 (strongly disagree) to 5 (strongly agree). In the Spanish sample, the model displayed good fit indices (CFI = 0.95, GFI = 0.96, NFI = 0.94; RMSEA = 0.064), with a Cronbach’s alpha of 0.82.

All participants provided informed consent before engaging in the study. The completion of scales was voluntary and conducted through an online platform. Over two academic years, students reported on five distinct teaching-learning processes, each corresponding to a different university subject they were enrolled in during this period. Students took their time to answer the questionnaires gradually throughout the academic year. The assessment for Presage variables took place in September-October of 2018 and 2019, Process variables were assessed in the subsequent February-March, and Product variables were evaluated in May-June. The procedural steps were ethically approved by the Ethics Committee under reference 2018.170, within the broader context of an R&D Project spanning 2018 to 2021.

Data analysis

The ex post facto design [ 42 ] of this cross-sectional study involved bivariate association analyses, multiple regression, and structural predictions (SEMs). Preliminary analyses were executed to ensure the appropriateness of the parameters used in the analyses, including tests for normality (Kolmogorov-Smirnov), skewness, and kurtosis (+-0.05).

Multiple regression

Hypothesis 1 was evaluated using multiple regression analysis through SPSS (v. 26).

Confirmatory factor analysis

To test Hypotheses 2 and 3, a structural equation model (SEM) was employed in this sample. Model fit was assessed by examining the chi-square to degrees of freedom ratio, along with RMSEA (root mean square error of approximation), NFI (normed fit index), CFI (comparative fit index), GFI (goodness-of-fit index), and AGFI (adjusted goodness-of-fit index) [ 43 ]. Ideally, all these values should surpass 0.90. The adequacy of the sample size was confirmed using the Hoelter index [ 44 ]. These analyses were conducted using AMOS (v.22).

Prediction results

The predictive relationships exhibited a continuum along two extremes. On the one hand, conscientiousness, extraversion and openness were significant, graded, and positive predictors of self-regulation. On the other hand, Agreeableness and Neuroticism were negative, graded predictors of self-regulation. A considerable percentage of explained variance was observed ( r 2  = 0.499). The most meaningful finding, however, is that this predictive differential grading is maintained for the rest of the variables analyzed: positive affect ( r 2  = 0.571) and negative affect ( r 2  = 0.524), achievement emotions during study, engagement burnout, problem- and emotion-focused coping strategies, and student health. See Table  2 .

Structural prediction results

Structural prediction model.

Three models were tested. Model 1 proposes the exclusive prediction of personality factors on the rest of the factors, not including self-regulation. Model 2 evaluated the predictive potential of self-regulation on the factors of the Big Five model. Model 3 tested the ability of the Big Five personality traits to predict self-regulation and the other factors. The latter model presented adequate statistical values. These models are shown in Table  3 .

Models of the linear structural results of the variables

Direct effects.

The statistical effects showed a direct, significant, positive predictive effect of the personality factors C (Conscientiousness) and E (Extraversion) on self-regulation. The result for factor O (openness to experience) was not significant. Factors A (agreeableness) and N (neuroticism) were negatively related, especially the latter. In a complementary fashion, factors C and E showed significant, positive predictions of positive affect, while O and A had less strength. Factor N most strongly predicted negative affect.

Moreover, self-regulation positively predicted positive achievement emotions during study and negatively predicted negative achievement emotions. Positive affect predicted positive emotions during study, engagement, and problem-focused coping strategies; negative affect predicted negative emotions during study, burnout, and emotion-focused strategies. Positive emotions during study negatively predict negative emotions and burnout. Engagement positively predicted problem-focused coping and negatively predicted burnout. Finally, problem-focused coping also predicted emotion-focused coping. Emotion-focused coping negatively predicts health and well-being.

Indirect effects

The Big Five factors exhibited consistent directionality. Factors C and E positively predicted positive emotions, engagement, problem-focused coping, and health and negatively predicted negative emotions and burnout. Factor O had low prediction values in both negative and positive cases. Factors A and N were positive predictors of negative emotions during study, burnout, emotion-focused coping and health, while the opposite was true for factors C and E. These factors had positive predictive effects on self-regulation, positive affect, positive emotions during study, engagement, problem-focused strategies and health; in contrast, the other factors had negative effects on negative affect, negative emotions during study, burnout, emotion-focused strategies and health. See Table  4 ; Fig.  1 .

SEM of prediction in the variables Note. C = Conscientiousness; E = Extraversion; O = Openness to experience; A = Agreeableness; N = Neuroticism; SR = Self-Regulation; Pos.A = Positive Affect; Neg.A = Negative Affect; Pe.S = Positive emotions during study; Ne.S = Negative emotions during study; ENG = Engagement; BURN = Burnout; EFCS = Emotion-focused coping strategies; PFCS = Problem-focused coping strategies: HEALTH: Health behavior.

Based on the Self- vs. External-Regulation theory [ 27 , 28 ], the aim of this study was to show, differentially, the regulatory, nonregulatory or dysregulatory power of the Big Five personality factors with respect to study behaviors, associated emotionality during study, motivational states, and ultimately, student health behavior.

Regarding Hypothesis 1 , the results showed a differential, graded prediction of the Big Five personality factors affecting both self-regulation and affective states. The results from the logistic and structural regression analyses showed a clear, graded pattern from the positive predictive relationship of C to the negative predictive relationship of N. On the one hand, they showed the regulatory effect (direct and indirect) of factors C and E, the nonregulatory effect of O, and the dysregulatory effect of factors A and especially N. This evidence offers a differential categorization of the five factors in an integrated manner. On the other hand, their effects on affective tone (direct and indirect) take the same positive direction in C and E, intermediate in the case of O, and negative in A and N. There is plentiful prior evidence that has shown this relationship, though only in part, not in the integrated manner of the model presented here [ 29 , 45 , 46 , 47 ].

Regarding Hypothesis 2 , the evidence shows that self-regulation directly and indirectly predicts affective states in achievement emotions during study. Directionality can be positive or negative according to the influence of C and E and of positive emotionality or of A and N with negative affect. This finding agrees with prior research [ 29 , 48 , 49 , 50 , 51 ].

Regarding Hypothesis 3 , the results have shown clear bidirectionality. Subsequent to the prior influence of personality factors and self-regulation, achievement emotions bring about the resulting motivational states of engagement-burnout and the use of different coping strategies (problem-focused vs. emotion-focused). Positive achievement emotions during study predicted a motivational state of engagement and problem-focused coping strategies and were positive predictors of health; however, negative emotions predicted burnout and emotion-focused coping strategies and were negative predictors of health. These results are in line with prior evidence [ 49 , 52 , 53 ]. Finally, we unequivocally showed a double, sequenced path of emotional variables and affective motivations in a process that ultimately and differentially predicts student health [ 54 , 55 ].

In conclusion, these results allow us to understand the predictive relationships involving these multiple variables in a holistic predictive model, while previous research has addressed this topic only in part [ 56 ]. We believe that these results lend empirical support to the sequence proposed by the SR vs. ER model [ 27 ]: the factors of conscientiousness and extraversion appear to be regulators of positive emotionality, engagement and health; openness to experience is considered to be nonregulating; and agreeableness and neuroticism are dysregulators of the learning process and precursors of negative emotionality and poorer student health [ 57 ]. New levels of detail—in a graded heuristic—have been added to our understanding of the relationships among the five-factor model, self-regulation, achievement emotions and health [ 23 ].

Limitations and research prospects

A primary limitation of this study was that the analysis focused exclusively on the student. The role of the teaching context, therefore, was not considered. Previous research has reported the role of the teaching process, in interaction with student characteristics, in predicting positive or negative emotionality in students [ 49 , 58 ]. However, such results do not undercut the value of the results presented here. Future research should further analyze potential personality types derived from the present categorization according to heuristic values.

Practical implications

The relationships presented may be considered a mental map that orders the constituent factors of the Five-Factor Model on a continuum, from the most adaptive (or regulatory) and deregulatory to the most maladaptive or dysregulatory. This information is very important for carrying out preventive intervention programs for students and for designing programs for those who could benefit from training in self-regulation and positivity. Such intervention could improve how students experience the difficulties inherent in university studies [ 47 , 59 ], another indicator of the need for active Psychology and Counseling Centers at universities.

Data availability

No datasets were generated or analysed during the current study.

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Silverman M, Wilson S, Ramsay I, Hunt R, Thomas K, Krueger R, Iacono W. Trait neuroticism and emotion neurocircuitry: functional magnetic resonance imaging evidence for a failure in emotion regulation. Dev Psychopathol. 2019;31(3):1085–99. https://doi.org/10.1017/S0954579419000610 .

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Harward DW. Well-being and higher education: a strategy for change and the realization of education’s greater purposes. Bringing Theory to Practice; 2016.

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Acknowledgements

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This research was funded by the R&D Project PID2022-136466NB-I00 and the R&D Project PGC2018-094672-B-I00. University of Navarra (Ministry of Science and Education, Spain), R&D Project UAL18-SEJ-DO31-A-FEDER (University of Almería, Spain), and the European Social Fund.

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Jesús de la Fuente, Begoña Urien, Mónica Pachón-Basallo & Elkin O Luis

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Conceptualization, J.d.l.F and ELG; formal analysis and methodology, J.d.l.F and ELG.; project administration, J.d.l.F.; writing—original draft, J.d.l.F, PS, AG, BU, MP, and ELG; writing—review & editing, J.d.l.F, PS, AG, BU, MP and ELG. All authors have read and agreed to the published version of the manuscript.

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Fuente, J.d.l., Sander, P., Garzón Umerenkova, A. et al. The big five factors as differential predictors of self-regulation, achievement emotions, coping and health behavior in undergraduate students. BMC Psychol 12 , 267 (2024). https://doi.org/10.1186/s40359-024-01768-9

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Expelling students for bad behaviour seems like the obvious solution, but is it really a good idea?

Professor and Director of the Centre for Inclusive Education, Queensland University of Technology

Disclosure statement

Linda J. Graham receives funding from the Australian Research Council. She chaired the 2020 inquiry into suspension, exclusion and expulsion processes in South Australian government schools, and was a member of the 2023 National School Reform Agreement Ministerial Reference Group.

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Two male students have been expelled from a Melbourne private school for their involvement in a list ranking female students.

The two were part of a group of four high school students suspended from Yarra Valley Grammar last Friday, after sharing a spreadsheet of photos of female classmates, ranking them with terms including “wifeys”, “cuties” and “unrapable”.

As principal Mark Merry said in a letter to parents on Tuesday, he had “formed the view” the position of two of the students had “become untenable”. The two other students who played a “lesser role” will face “disciplinary action”. The school is offering wellbeing support to the girls who were targeted.

Earlier this week, the suspensions were met with approval from Education Minister Jason Clare who told the ABC , “I’m glad the school’s fronting up. I think that they’ve taken the sort of action that the community would expect”.

Expelling or suspending students for this kind of behaviour seems like the obvious course of action. But is it a good idea?

Why do schools suspend or expel students?

Suspending or expelling a student is meant to be a last resort for serious problem behaviour. It is either supposed to allow space for a reset or as a consequence for behaviour which threatens other students’ safety or learning.

In the case of Yarra Valley Grammar, the suspensions and expulsions send a message to the girls in the school, other students, parents and the broader public this behaviour is not tolerated.

With so much media and public attention on the spreadsheet, the suspensions and expulsions also help protect the reputation of the school.

Clearly there has been some horrendous behaviour and it does need to have a stern response. But without condoning the behaviour in any way, kicking these students out of school is not the best way to handle this situation, which is a symptom of a much bigger problem.

What does the research say about suspensions and expulsions?

Typically, when a student is expelled, the outcomes are not positive for that child.

This is because expulsion is a punitive action, not an educative one.

Research shows suspending and expelling students can also simply build resentment and anger. If students feel like they are rejected from society , there is a risk they become more extreme in their views or behaviours.

Research also shows it can impact a young person’s learning and lead to leaving school early. We also know there is an association between suspension and expulsion and increased delinquency , including contact with the police .

The most protective thing to do is to keep young people in schools where they can be exposed to the influence of positive peers, under adult supervision, with a chance to keep up with their learning.

What could happen instead?

This is not to say students should just be told to go back to class as if nothing has happened.

With the help of experts like psychologists, schools can engage in a restorative justice process . This is about helping young people understand the real impact of their actions.

There can often be an assumption young people act with full knowledge of the consequences of what they are doing. But parts of their brain involving control and self regulation are still developing into adulthood.

Experts can work with students so they can learn their actions were not harmless fun with their mates but something that hurts others.

An example of how this can be done is through giving those students “ inquiry projects ” where they investigate similar incidents and present their findings to their peers. The emphasis is on an educative response that builds empathy and understanding in that young person.

The school could also ask the female students included in the spreadsheet to express through their choice of medium how it made them feel.

One criticism of this process is it requires the victims to engage in emotional labour when they have already experienced harm. But when a restorative justice process is done well , it can give the victims a voice and public acknowledgement of the wrong they have experienced.

Those victims can also receive an apology if they want it. That apology is likely to be more meaningful if the perpetrator has learnt something of the effect of their behaviour.

Importantly, the aim of a restorative justice process is not to dispense “justice”. It is to restore peace, to heal harms done and to prevent future harms from occurring through better understanding.

Given the Yarra Valley Grammar “list” is the latest episode in a string of incidents involving misogynistic behaviour by male students , it is time we tried something different.

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Do good lessons promote students' attention and behavior?

by Anke Wilde, Leibniz-Institut für Bildungsforschung und Bildungsinformation

Students are better able to regulate themselves in lessons that they consider to be particularly well implemented. This is the conclusion drawn from a study by the DIPF | Leibniz Institute for Research and Information in Education, published in the journal Learning and Instruction .

The link between teaching quality and self-regulation tends to be particularly true for pupils who have problems controlling their behavior and following lessons, for example due to ADHD symptoms.

Good teaching is characterized by the teacher leading the class through the lesson without disruption, encouraging the students to think, taking an interest in them and supporting them individually. The better the teacher is at this, the better the students will be able to regulate their behavior, for example by paying attention, cooperating and adhering to the class rules.

As a result, they learn better. This link, which has already been established in research, has now been examined in more detail in this daily diary study and evaluated with the help of multilevel analyses.

It became clear that the quality of teaching has an impact not only on self-regulation overall, but also in each individual lesson, as Dr. Friederike Blume, lead author of the now published study, summarizes the results.

"When teachers are particularly good at classroom management and providing student support in a lesson, students are better able to regulate their behavior. When these two characteristics of good teaching are not working well in a lesson, students also reported that they were less able to concentrate and engage."

Cognitive activation, the third characteristic of good teaching, was hardly relevant for self-regulation. Therefore, the personal relationship between teacher and student is particularly important, emphasizes Dr. Blume.

This is especially true for students who have difficulties with self-regulation, such as those with attention deficit hyperactivity disorder (ADHD).

"Many teachers find it difficult to establish a positive relationship with children with ADHD symptoms," says the educational researcher. "However, our study showed that in lessons where children with self-regulation difficulties felt particularly supported by their teacher, they were more likely to report being able to concentrate better and follow class rules.

"It is therefore worth taking a positive approach to these children in the classroom and showing a genuine interest in them, as this can reduce the pressure on teachers in the long term and bring more calm to the classroom."

The DIPF researcher also recommends that teachers ask their students for feedback on their teaching from time to time. Although this is still a taboo for many, it can provide valuable information on how to better tailor their teaching to the needs of individual students.

A total of 64 pupils in years 5 and 6 took part in the study. They did not necessarily belong to the same school or class, but were recruited through an email appeal to music schools, sports and leisure centers, for example.

At the start of the study, the children completed a questionnaire about general information such as their grade level and type of school, as well as how they rated their self-regulation skills. Over the next three school weeks, the children answered daily questions about the last lesson of each day.

The questions related to the quality of teaching (e.g., support from the teacher, disruptions in lessons, stimulation of reflection), as well as their ability to regulate themselves in that lesson (e.g., attention, impulse control, motor activity).

The links between the individual lessons and the corresponding daily entries were evaluated using multilevel analysis. Among other things, the results were analyzed on an intrapersonal level, which allows conclusions to be drawn at the level of the individual child. In addition, interpersonal associations were examined, which allows conclusions to be drawn about all participants together.

Limitations of the study

Studies with such an elaborate design, involving daily diaries, always aim to collect data in as short time as possible. As a result, teaching quality was only measured here on the basis of only few statements, which certainly do not cover all the characteristics of good teaching.

Future studies should therefore take a closer look at classroom interaction processes to explore which features of teaching are particularly beneficial, especially for children with stronger ADHD symptoms.

Furthermore, future studies must show whether the results found here apply to all subjects or only to certain subjects, and the role of different teaching methods.

Journal information: Learning and Instruction

Provided by Leibniz-Institut für Bildungsforschung und Bildungsinformation

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Operant Versus Classical Conditioning: Real-World Applications and Outcomes

This essay about behavioral psychology explores the fundamental concepts of classical and operant conditioning, illustrating their profound impact on human behavior across various contexts. It discusses how classical conditioning underlies the mechanisms of advertising and therapeutic interventions, while operant conditioning shapes educational methods and parenting strategies. The essay also highlights the integration of both conditioning types in clinical settings and animal training, emphasizing their importance in understanding and molding behavior in a diverse range of environments.

How it works

Delving into the intricate realms of behavioral psychology, one inevitably encounters the twin pillars of learning: classical and operant conditioning. These fundamental principles, while distinct in their mechanisms, intertwine in the intricate tapestry of behavior shaping. Their applications extend far beyond laboratory experiments, permeating everyday life in ways both subtle and profound.

Classical conditioning, famously demonstrated by Ivan Pavlov’s salivating dogs, revolves around the formation of associations between stimuli and responses. Through repeated pairings, a neutral stimulus becomes imbued with the power to evoke reflexive reactions.

Consider the pervasive realm of advertising, where classical conditioning operates in full force. Brands deftly weave their products into narratives brimming with allure and desire, strategically associating them with symbols of pleasure and fulfillment. As consumers encounter these stimuli repeatedly, their subconscious forms connections, paving the path for brand loyalty and purchasing decisions.

Yet, classical conditioning extends its tendrils far beyond the realm of consumerism. In the domain of therapy, it emerges as a potent tool for dismantling phobias brick by brick. Therapists orchestrate systematic desensitization rituals, gradually exposing individuals to feared stimuli while coupling them with relaxation techniques. Through this meticulous process, the once-terrifying triggers lose their grip, replaced by associations of tranquility and empowerment.

In stark contrast, operant conditioning, crafted by the ingenious mind of B.F. Skinner, revolves around the consequences of behavior. Actions are not mere reactions to external stimuli but rather strategic maneuvers shaped by their outcomes. Education, a domain ripe for behavioral sculpting, witnesses operant conditioning in action. Teachers wield the twin swords of reinforcement and punishment, molding students’ behaviors through a delicate dance of consequences. Positive reinforcement showers accolades upon diligent learners, fueling their thirst for knowledge, while negative reinforcement lifts the burden of undesirable tasks, paving the path for academic excellence.

Parenting, too, emerges as a crucible where operant conditioning finds its canvas. Through a symphony of rewards and consequences, caregivers sculpt the moral compasses of their offspring. Each chore completed heralds a chorus of praise and privileges, while missteps invite corrective measures. In this intricate dance, children learn the ropes of cause and effect, navigating the labyrinth of behavioral expectations with growing adeptness.

Venturing into the animal kingdom, operant conditioning emerges as a cornerstone of training methodologies. Trainers harness the power of rewards and punishments to shape the behaviors of their charges, be they majestic dolphins or playful pups. Through a symphony of treats and cues, animals learn to perform intricate tasks with precision and grace, showcasing the remarkable synergy between cognition and conditioning.

Yet, in the theater of life, classical and operant conditioning seldom operate in isolation. They intertwine, forming a dynamic tapestry of behavior shaping. Consider the humble clicker, initially a neutral stimulus in the classical realm, transformed into a beacon of guidance in the operant domain. With a click and a treat, trainers communicate their expectations, seamlessly blending the principles of association and consequence to sculpt behaviors with finesse.

In the crucible of clinical interventions, this marriage of paradigms bears fruit, offering a nuanced approach to behavior modification. Therapists weave classical cues into operant frameworks, leveraging the power of association to reinforce desired behaviors. Through this holistic approach, they navigate the labyrinth of the human psyche, unraveling the knots of maladaptive behaviors with precision and compassion.

In summation, the realms of classical and operant conditioning stand as bastions of insight into the mysteries of behavior. From the hallowed halls of academia to the bustling streets of consumerism, their influence reverberates, shaping the contours of human experience. As we navigate this labyrinth of learning, let us heed the lessons of the past and embrace the symbiotic dance of association and consequence, forging pathways to growth and transformation in the ever-evolving tapestry of life.

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Why writing by hand beats typing for thinking and learning

Jonathan Lambert

If you're like many digitally savvy Americans, it has likely been a while since you've spent much time writing by hand.

The laborious process of tracing out our thoughts, letter by letter, on the page is becoming a relic of the past in our screen-dominated world, where text messages and thumb-typed grocery lists have replaced handwritten letters and sticky notes. Electronic keyboards offer obvious efficiency benefits that have undoubtedly boosted our productivity — imagine having to write all your emails longhand.

To keep up, many schools are introducing computers as early as preschool, meaning some kids may learn the basics of typing before writing by hand.

But giving up this slower, more tactile way of expressing ourselves may come at a significant cost, according to a growing body of research that's uncovering the surprising cognitive benefits of taking pen to paper, or even stylus to iPad — for both children and adults.

Is this some kind of joke? A school facing shortages starts teaching standup comedy

In kids, studies show that tracing out ABCs, as opposed to typing them, leads to better and longer-lasting recognition and understanding of letters. Writing by hand also improves memory and recall of words, laying down the foundations of literacy and learning. In adults, taking notes by hand during a lecture, instead of typing, can lead to better conceptual understanding of material.

"There's actually some very important things going on during the embodied experience of writing by hand," says Ramesh Balasubramaniam , a neuroscientist at the University of California, Merced. "It has important cognitive benefits."

While those benefits have long been recognized by some (for instance, many authors, including Jennifer Egan and Neil Gaiman , draft their stories by hand to stoke creativity), scientists have only recently started investigating why writing by hand has these effects.

A slew of recent brain imaging research suggests handwriting's power stems from the relative complexity of the process and how it forces different brain systems to work together to reproduce the shapes of letters in our heads onto the page.

Your brain on handwriting

Both handwriting and typing involve moving our hands and fingers to create words on a page. But handwriting, it turns out, requires a lot more fine-tuned coordination between the motor and visual systems. This seems to more deeply engage the brain in ways that support learning.

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Feeling artsy here's how making art helps your brain.

"Handwriting is probably among the most complex motor skills that the brain is capable of," says Marieke Longcamp , a cognitive neuroscientist at Aix-Marseille Université.

Gripping a pen nimbly enough to write is a complicated task, as it requires your brain to continuously monitor the pressure that each finger exerts on the pen. Then, your motor system has to delicately modify that pressure to re-create each letter of the words in your head on the page.

"Your fingers have to each do something different to produce a recognizable letter," says Sophia Vinci-Booher , an educational neuroscientist at Vanderbilt University. Adding to the complexity, your visual system must continuously process that letter as it's formed. With each stroke, your brain compares the unfolding script with mental models of the letters and words, making adjustments to fingers in real time to create the letters' shapes, says Vinci-Booher.

That's not true for typing.

To type "tap" your fingers don't have to trace out the form of the letters — they just make three relatively simple and uniform movements. In comparison, it takes a lot more brainpower, as well as cross-talk between brain areas, to write than type.

Recent brain imaging studies bolster this idea. A study published in January found that when students write by hand, brain areas involved in motor and visual information processing " sync up " with areas crucial to memory formation, firing at frequencies associated with learning.

"We don't see that [synchronized activity] in typewriting at all," says Audrey van der Meer , a psychologist and study co-author at the Norwegian University of Science and Technology. She suggests that writing by hand is a neurobiologically richer process and that this richness may confer some cognitive benefits.

Other experts agree. "There seems to be something fundamental about engaging your body to produce these shapes," says Robert Wiley , a cognitive psychologist at the University of North Carolina, Greensboro. "It lets you make associations between your body and what you're seeing and hearing," he says, which might give the mind more footholds for accessing a given concept or idea.

Those extra footholds are especially important for learning in kids, but they may give adults a leg up too. Wiley and others worry that ditching handwriting for typing could have serious consequences for how we all learn and think.

What might be lost as handwriting wanes

The clearest consequence of screens and keyboards replacing pen and paper might be on kids' ability to learn the building blocks of literacy — letters.

"Letter recognition in early childhood is actually one of the best predictors of later reading and math attainment," says Vinci-Booher. Her work suggests the process of learning to write letters by hand is crucial for learning to read them.

"When kids write letters, they're just messy," she says. As kids practice writing "A," each iteration is different, and that variability helps solidify their conceptual understanding of the letter.

Research suggests kids learn to recognize letters better when seeing variable handwritten examples, compared with uniform typed examples.

This helps develop areas of the brain used during reading in older children and adults, Vinci-Booher found.

"This could be one of the ways that early experiences actually translate to long-term life outcomes," she says. "These visually demanding, fine motor actions bake in neural communication patterns that are really important for learning later on."

Ditching handwriting instruction could mean that those skills don't get developed as well, which could impair kids' ability to learn down the road.

"If young children are not receiving any handwriting training, which is very good brain stimulation, then their brains simply won't reach their full potential," says van der Meer. "It's scary to think of the potential consequences."

Many states are trying to avoid these risks by mandating cursive instruction. This year, California started requiring elementary school students to learn cursive , and similar bills are moving through state legislatures in several states, including Indiana, Kentucky, South Carolina and Wisconsin. (So far, evidence suggests that it's the writing by hand that matters, not whether it's print or cursive.)

Slowing down and processing information

For adults, one of the main benefits of writing by hand is that it simply forces us to slow down.

During a meeting or lecture, it's possible to type what you're hearing verbatim. But often, "you're not actually processing that information — you're just typing in the blind," says van der Meer. "If you take notes by hand, you can't write everything down," she says.

The relative slowness of the medium forces you to process the information, writing key words or phrases and using drawing or arrows to work through ideas, she says. "You make the information your own," she says, which helps it stick in the brain.

Such connections and integration are still possible when typing, but they need to be made more intentionally. And sometimes, efficiency wins out. "When you're writing a long essay, it's obviously much more practical to use a keyboard," says van der Meer.

Still, given our long history of using our hands to mark meaning in the world, some scientists worry about the more diffuse consequences of offloading our thinking to computers.

"We're foisting a lot of our knowledge, extending our cognition, to other devices, so it's only natural that we've started using these other agents to do our writing for us," says Balasubramaniam.

It's possible that this might free up our minds to do other kinds of hard thinking, he says. Or we might be sacrificing a fundamental process that's crucial for the kinds of immersive cognitive experiences that enable us to learn and think at our full potential.

Balasubramaniam stresses, however, that we don't have to ditch digital tools to harness the power of handwriting. So far, research suggests that scribbling with a stylus on a screen activates the same brain pathways as etching ink on paper. It's the movement that counts, he says, not its final form.

Jonathan Lambert is a Washington, D.C.-based freelance journalist who covers science, health and policy.

• handwriting

Living With and Learning From Inconsistent Behavior in ADHD

Variability can feel confusing and frustrating but is an expected part of adhd..

Posted May 13, 2024 | Reviewed by Devon Frye

• What Is ADHD?
• Find a therapist to help with ADHD
• Inconsistency in ADHD can feel befuddling and lead to conflict.
• Inconsistent performance is a marker for any of us of a skill that isn't fully formed yet.
• When a child with ADHD seems unusually inconsistent, that frequently reveals a skill that needs building.
• If inconsistency is persistently disruptive, consider an objective review of possible ADHD interventions.

What surprises me is there is so much variability, I don’t know what to expect day to day, cooperation or resistance.

I don’t get it. We don’t have any problems at all at home. How come he struggles so much to behave in school?

With ADHD , inconsistency can feel like a puzzle to solve, as the quotes throughout this article reflect. It can seem confusing—and can be misleading.

Variability in behavior gets misinterpreted, for example, as meaning a child doesn’t actually need support. If you are capable sometimes why wouldn’t you be capable always ? It feels like a befuddling contradiction when life looks so up and down.

Another common example is focus . If you can pay attention in your favorite class, why not your hardest? That pattern suggests either, you don’t need help, or, you need to care more . Yet that kind of uneven focus is routine ADHD—it’s frustrating but expected.

What Accounts for the Variability in ADHD Behavior?

The underlying cause of that unevenness in academics or behavior or mood is often straight-forward with ADHD. ADHD impacts executive function, which includes skills such as focus, impulse control, time management , and emotional regulation . As with any new skill in life, a child will remain inconsistent until their underlying abilities improve. Their inconsistency represents an accurate reflection—difficult as it is to live with—of various ADHD symptoms to address.

When someone has been diagnosed with ADHD, it’s not only that they are imperfect (like us all!) but that some aspect of ADHD significantly impacts their well-being. Their symptoms must reach that level to consider a diagnosis.

It’s not a total absence of skill, however. By nature, in some moments, things come together—and then with ADHD, there are likely too many moments where they do not.

Inconsistency as a Measure of Skill

It’s so simple—why can’t you remember to hand in your homework every day?

I don’t understand—you treat your friends nicely, why not your sister?

I’m a decidedly average tennis player. On any random day, if my serve happens to go in a bunch, I’ll beat a better player. If I play that same person several times, my maddeningly unreliable serve undermines me. More consistency makes my opponent better at tennis. My game will remain unchanged unless I put the time and effort into forging a reliable serve.

When a child seems to have life figured out one day but not the next, parents can tie themselves in knots trying to understand "why." And yet, those behaviors are akin to my tennis. Executive function relates to basically anything requiring management , coordination, and planning in life. When skills aren’t yet solid enough, that creates exhaustingly inconsistent performance.

The practical solution for inconsistency is not overthinking the roller coaster itself but seeking its cause. Let go of judgment, consider ADHD and executive function, and identify where skills might be lacking. A child’s performance will remain up and down until that underlying ability fully forms.

Motivation and Inconsistency

I don’t even know if we need to change anything; she gets her work done when she cares enough.

How come you behaved for dinner when I promised you ice cream, but not the rest of the weekend?

The relationship of inconsistency to motivation adds more confusion. Maybe a student gets a huge paper done on time, for the first time, because they don’t want to miss a ski trip.

Consider though, stories of people accomplishing super-human feats when panicked, like lifting a heavy object off a child. Pushing someone to an extreme creates a window of intensity that ramps up immediate performance.

When pushed hard enough, we all do amazing things briefly that we could never maintain day to day. Pressure and rewards lead to over-performance only for a short sprint. But that unsustainable pattern may falsely imply, If you can manage under crisis, you should be able to all the time .

Inconsistency can get misattributed to either bad choices or lack of effort. Children end up feeling judged or blamed even though it’s not something they can control until their ADHD symptoms become less impactful.

Kids with ADHD typically do care about school or other goals. It can seem like they don’t when they struggle with their impulsivity, persistence, or organization.

Even the ability to develop, sustain, and problem-solve plans is affected by ADHD. What we call "motivation" requires caring combined with any specific skills needed to accomplish a goal.

Replace any rumination or judgment with a basic ADHD-related question instead. Working hard matters, but what skills are also involved and what should we do to strengthen them? It’s a freeing perspective for both parents and kids.

How to Build Skills

It’s like there’s conflicting evidence; the data doesn’t line up.

I don’t understand—you’re clearly capable. Don’t you care how you do?

Overthinking inconsistency not only confuses people; it can delay treatment. When someone focuses (but not in their hard classes), or usually hands in homework (but larger projects fall apart), it’s easy to rationalize away help. But inconsistency is not a sign a child could do better if they wanted; it indicates a need to increase their ADHD support.

How do we build ADHD-related skills? It is estimated that ADHD represents up to a one-third delay in executive functioning , a framework that presents countless opportunities for intervention. We start by reframing difficulties as ADHD-related, instead of effort-related. With that renewed clarity, we can then choose new plans that build consistency.

Which kind of plan will work depends on the specific challenge. For focus and impulse control, medication tends to be most effective. Early academic habits grow through routines that parents and teachers create and sustain. Numerous other cognitive, academic, and emotional skills develop through work with therapists and coaches.

Instead of feeling confused by inconsistency, see it as a signpost pointing at the next step in ADHD care. A strong tennis player lands most of their serves even when not at their best. A student with ADHD taking a well-adjusted medication focuses better when pushed by harder classes. An exhausted child with a well-structured morning routine makes the bus even on an off day.

It’s not “personal” or willful that a child acts inconsistently. It typically means the right plan has not been implemented yet.

Mark Bertin, M.D., is a developmental pediatrician and author of Mindful Parenting for ADHD and Mindfulness and Self-Compassion for Teen ADHD.

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