What is student engagement?
Our modern understanding of student engagement can largely be credited to the pioneering research of Alexander Astin in the 1980s. Astin framed engagement as “the quantity and quality of physical and psychological energy that students invest in the college experience.” Such engagement fosters learning that is proportional to that student investment (Axelson & Flick, 2010). Engagement entails more than just exposure — real engagement happens when students take interest, become invested, and feel involved in learning and have a sense of connection with the concepts and other people in the course (instructors, TAs, and other students). Essentially, authentic student engagement involves cognitive focus (attention) and emotional fuel (motivation, interest, curiosity), which sets the groundwork for constructive learning behaviour that leads to deep and long-lasting learning (Astleitner & Wiesner, 2004). When students are focused, interested, and motivated, learning becomes more efficient, requiring less time on task (e.g., studying) (Nonis & Hudson, 2010).
With that definition in mind, let’s dive a little deeper by looking at key types of engagement — cognitive, emotional, and behavioural — and some of the science behind how student engagement is cultivated.
There is a large body of literature from the fields of cognitive and educational psychology on the topic of cognitive engagement and how to cultivate it in online course delivery. A big part of building cognitive engagement is understanding what enhances attention and memory and what impairs these core faculties. Here we are focused on online course facilitation and delivery, so we will not go into the principles of designing online teaching materials and resources. An overview of the most impactful principles and strategies, however, can be very helpful if you are going to be presenting information or creating learning materials (for instance videos and webpages, slides, reading materials, and even course announcements); we have included some supplementary materials on the design and development of learning resources.
If you are interested in designing and developing course materials based on cognitive principles of engagement, here are some recommended resources drawn from psychologist Richard Mayer’s research on e-learning and cognitive principles of multimedia learning.
- User Experience Design for Learning (UXDL) is a resource developed at the Centre for Extended Learning at the University of Waterloo that provides practical strategies for designing educational resources that are useful, desirable, accessible, intuitive, and credible.
Books and articles
- Clark, R. & Mayer, R. E. (2016). E-learning and the science of instruction (4th ed.). San Francisco: Pfeiffer.
- Mayer, R. E. (Ed., 2014). The Cambridge handbook of multimedia learning. New York: Cambridge University Press.
- Mayer, R. E. (2017). Using multimedia for e-learning. Journal of Computer Assisted Learning, 33, 403-423.
The key faculty associated with cognitive engagement is attention. Without capturing and maintaining attention, students will struggle to remember and integrate information. Attention is required for information to pass into memory, and a person can focus on only a small amount of information in a given moment (Cowan, 2010). There are many strategies that we, as online course facilitators, can implement to remove factors that impede attentional focus and to foster the type of attention that is most conducive to learning.
Principles for enhancing cognitive engagement
There are a handful of principles that are known to impact how students attend and learn, which guide the strategies that course facilitators can use to foster cognitive engagement.
- Guide attention to relevant information, so that it may be efficient and selective.
- Reduce unnecessary distractions or information processing so that these limited cognitive resources are not wasted on extraneous processing/information.
- Present personally relevant information, which captures attention rapidly and effortlessly (Röer, Bell, & Buchner, 2013). Further, information that is made personally relevant is better stored and remembered, a phenomenon known as the Self-reference effect (Lieberman, Jarcho, & Satpute, 2004; Rogers, Kuiper, & Kirker, 1977).
- Consider the conditions that support optimal learning states, such as Flow. The state of being in Flow (“being in the zone”) is considered an optimal state for learning (Csikszentmihalyi, 2014). Flow states are characterized by a sense of getting lost in the task and losing the sense of time passing. When in Flow, maintaining attentional focus feels effortless, even when engaged in tasks (for instance playing an instrument or sport) that are typically challenging and effortful (Csikszentmihalyi & Nakamura, 2010). Flow is an intrinsically rewarding state (Landhäußer & Keller, 2012) and is associated with positive affect (Ullén, de Manzano, Theorell, & Harmat, 2010). For this reason, it is an ideal condition to learn in.
Cognitive engagement is essential to student success in all aspects of an online course. It is of special importance when fostering student-content engagement, a topic we will cover in Unit 4. Student-content interaction.
Emotional engagement reflects the degree to which a learner is emotionally invested and motivated to maintain and sustain attention and put in effort. It is the fuel for learning and what propels learners forward.
Emotional engagement is characterized by several cognitive emotions, such as interest and curiosity. Both positive and negative affective states impact attention and how we approach and process information. For instance, research by cognitive psychologist Barbara Fredrickson shows that positive affective states can broaden attentional scope and capacity (Fredrickson, 2001). Being in a positive affective state is conducive to
- openness to new ideas,
- making novel connections,
- cognitive flexibility,
- taking an exploratory approach, and
- creative problem-solving.
On the other hand, negative affective state (such as mild stress, anxiety, or confusion) can have the effect of:
- narrowing or focusing attention,
- leading to selective and detail-oriented processing,
- taking a more exploitive approach of sticking with a concept, and
- using analytic problem-solving
(Fredrickson, 2001; Fredrickson & Branigan, 2005).
Emotional states that can enhance emotional engagement
There are several emotions, both positive and negative, that can impact cognitive engagement and are conducive to learning. Positive emotions that can have an expansive impact on attention and learning are listed below. Negative emotions that can help to focus attention, as long as these emotions are not too strong or intense, are also listed.
- Motivation (intrinsic or extrinsic)
- Feeling connected
- Feeling acknowledged and validated
- Feeling supported
- Wonderment or awe
Negative emotions (all in mild form, too much can be detrimental)
- Anxiety, tension
- Sense of pressure
A little emotion goes a long way
It is important to clarify here that when we talk about the benefits of emotion on cognition and learning, we are talking about rather subtle shifts in emotion. In fact, when people are in a strong emotional state, positive or negative, then many of the benefits of emotion on cognition and learning are lost or even reversed. If negative emotions become too strong or persistent, they can lead to frustration, anger, depression, feelings of helplessness, or a state of stress, which can impair learning and memory (Vogel & Schwabe, 2016). Conversely, too much positive emotion can also be harmful, reducing creativity and leading to distraction, as a result of the way in which positive emotion orients us towards novelty (Davis, 2008). While the relationship between emotion and cognition can be complex, the take-away message here is that a little emotion can go a long way. It’s not as difficult as one may think to nudge students towards emotional states that are most conducive to engagement and learning.
Behavioural engagement is essentially what students do. Behavioural engagement reflects observable and measurable actions, such as:
- the amount of time students invest in a course;
- the degree to which they persist when a concept is difficult;
- whether they reach out to an instructor, TA, or other students; and
- how students approach content and assessments.
It is often this behavioural investment of students that we observe (and evaluate) as instructors and TAs.
When we observe a student who has failed to engage in a course, activity, or assessment, it is typically their behavior that has led us to that conclusion. We might conclude that the student simply isn’t interested or motivated; however, engagement for the purpose of learning is not completely the responsibility of the student. If factors that impact cognitive or emotional engagement have not been considered in the design and/or delivery of a course, then we should expect only those students who have the highest intrinsic motivation to be engaged, leaving most students feeling detached rather than invested and not showing positive signs of behavioural engagement (e.g., not participating in discussions, not investing sufficient time to learn the concepts or skills, handing in assessments late or incomplete, etc.).
Check and reflect
You are a TA or instructor facilitating a second-year course in your discipline, and you notice that one of your students, Maeve, has submitted her last two low-stakes quizzes minutes before the quizzes closed and has just handed in her first substantial assignment a day late and her work on the assignment is sloppy (e.g., missing details and riddled with simple mistakes).
While we may not reach all students, and there are certainly limits to what we can do, an awareness of engagement can help guide our online teaching to be as successful as possible. In subsequent units we will explore some of the more practical dimensions of fostering engagement online.
Astleitner, H., & Wiesner, C. (2004). An integrated model of multimedia learning and motivation. Journal of Educational multimedia and Hypermedia, 13(1), 3-21.
Axelson, R. D., & Flick, A. (2010). Defining Student Engagement. Change: The Magazine of Higher Learning, 43(1), 38-43.
Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why? Current directions in psychological science, 19(1), 51-57.
Csikszentmihalyi, M. & Nakamura, J. (2010). Effortless attention in everyday life: A systematic phenomenology. In B. Bruya, Effortless attention: A new perspective in the cognitive science of attention and action (pp. 179-189). Cambridge: Bradford Book.
Csikszentmihalyi, M. (2014). Applications of flow in human development and education. Dordrecht: Springer.
Davis, M. (2008). Understanding the relationship between mood and creativity: A meta-analysis. Organizational behavior and human decision processes, 108(1), 25-38.
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American psychologist,, 56(3), 218-226.
Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition & Emotion, 19(3), 313-332.
Landhäußer, A., & Keller, J. (2012). Flow and its affective, cognitive, and performance-related consequences. In S. Engeser, Advances in flow research. New York: Springer.
Lieberman, M. D., Jarcho, J. M., & Satpute, A. B. (2004). Evidence-based and intuition-based self-knowledge: An fMRI study. Journal of Personality and Social Psychology, 87(4), 421-435.
Nonis, S. A., & Hudson, G. I. (2010). Performance of college students: Impact of study time and study habits. Journal of Education for Business, 85, 229–238.
Röer, J. P., Bell, R., & Buchner, A. (2013). Self-relevance increases the irrelevant sound effect: Attentional disruption by one's own name. Journal of Cognitive Psychology, 5(8), 925-931.
Rogers, T. B., Kuiper, N. A., & Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35(9), 677-688.
UCLA (2020). Alexander (Sandy) Astin. Retrieved from https://gseis.ucla.edu/directory/alexander-astin/
Ullén, F., de Manzano, Ö., Theorell, T., & Harmat, L. (2010). The physiology of effortless attention: Correlates of state flow and flow proneness. In B. Burya, Effortless attention: A new perspective in the cognitive science of attention and action (pp. 205-218). Cambridge, Massachusetts: Bradford Book.
Vogel, S., & Schwabe, L. (2016). Learning and memory under stress: implications for the classroom. Science of Learning, 1(1), 1-10.