• A Three-Component Model of Student Engagement to measure and direct instructional strategies.

  10/06/2026

  updated 10/07/2026

  Marcus G. Yeo

  The Variable Component-Contribution model

  Proposal: The Variable Component-Contribution (VCC) model calculates and graphically depicts student engagement based on affective, cognitive, and psychomotor testing. It can be used to plot engagement, assess the impact of delivery strategies, and direct the design and facilitation of future lessons. Rationale, tools for measurement and analysis, strategies, and activities for implementation are presented.

  Rationale: A number of existing models include motivation and cognition as levers for engagement, so this piece will focus on the separation of active learning into reflection (cognition) and action (psychomotor). Psychomotor being defined as all interaction with subject matter or learning environment via the human interface.

  To start, there are numerous studies which show physical activity’s ability to increase cognitive functioning (Mualem et al., 2018), indicating the existence of a psychomotor lever.

  Adding a social component, Taylor and Marienau (2016) looked at the collected works of Brookfield, Fahim, and Wilbur, concluding “brief venture into the unknown will trigger mildly increased adrenaline or cortisol production, which can enhance learning.” Getting up and moving in a social setting can improve engagement.

  The pandemic of 2019 afforded an opportunity to compare the engagement of online versus in-person delivery. A study by Raes (2021) “did not find any significant differences between physical and remote presence regarding conceptual understanding, yet significant differences were found in regard of affective engagement in favour of the on-site students and remote students having the opportunity to interact.”  Here mere physical presence is seen to improve engagement.

  This is a departure from the Barkley and Major (2020) model which views engagement as a mental state, the product of motivation (affective) and active learning (cognitive). Active learning defined as “doing what we think and thinking about what we are doing.” (Bonwell & Eison, 1991). Separating active learning into its constituent parts, reflection and action, acknowledges the influence of the human interface on engagement, and allows for greater refinement in tracking student needs.

  Another contemporary, Fredricks’ et al. (2004) three-component model, is comprised of cognitive, emotional, and behavioural engagement. The VCC model differs in that it does not measure the exhibition of specific learned behaviours, but rather the student’s level of physical interaction with task and/or peers. It’s the desirable difficulty (Bjork) of generation via the human interface that improves engagement, by making the work tangible and personal. It improves engagement by feeding a sense of self-worth, showing progress, and proving theory.

            

  The Variable Component-Contribution (VCC) model: Student engagement has three components; motivation (affective), reflection (cognitive), and action (psychomotor). Expressed as an intensity on a scale of zero to five, and depicted as spheres of influence, the components equally overlapped produce realms of engagement.

  

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  The VCC model overcomes the argument against a traditional Venn diagram, only expressing overlap, by introducing intensities of influence. A departure from the Fredricks et al. (2004) wheel of engagement, and the double helix of Barkley and Major (2020), this three-component model affords greater accuracy in plotting level and predominant types of engagement.

  Types of Engagement:

  Active Engagement is the combined forces of motivation, reflection, and action. It is where learning occurs.

  Passive Engagement lacks at least one component, and doesn’t contribute to learning.

  • Automated Engagement is motivated action without reflection.
  • Philosophical Engagement is motivated reflection, but no action.
  • Practical Engagement is action and reflection, without motivation.

  Levels of force:

                         Motivation                      Reflection              Action

                         0 Apathy                     0 Ignorance             0 Absent

                         1 Concern             1 Awareness                   1 Still

                        2 Inclination                    2 Understanding            2 Active

                        3 Investment                   3 Selection                 3 Proficient

                        4 Passion                         4 Deconstruction        4 Masterful

                        5 Zeal                               5 Invention                     5 Flowing

  Measurement Tools: Two quizzes and one checklist are used to determine intensity of force. The quiz questions are designed to increase in difficulty, completion indicating increased engagement. The checklist follows a marking guide.

  Motivation quiz

  1. t/f – True/False/Undecided. Circle one.
  2. multiple choice
     • Subject matters?
       • a. Yes.
       • b. Sort of.
       • c. Not really.
       • d. No.
  3. matching – Link effort to outcome. Here students choose between intrinsic and extrinsic motivators.
  4. short answer – List as many advantages as possible.
  5. analogy – Subject is like?

  Reflective quiz

  1. t/f – Subject is logical?
  2. multiple choice
     • Stem
       • a.
       • b.
       • c.
       • d.
  3. matching – What causes defects?
  4. short answer – How can you improve?
  5. analogy – Subject is like?

  Action checklist

  1. absent
  2. still
  3. active
  4. masterful
  5. flowing

  Calculating Engagement:

  Product of all components present.

  Strategies:

  The U-shaped Classroom. Good engagement is enthusiastic participation and reflection. It’s seen in posture, eye contact, and reaction time. It is heard it in their answers, and identified it by their questions. They display engagement through physical output- be it a gesture, remark, or submission. A classroom where every student can be seen and interact easily reduces barriers, and allows the instructor to provide individual focus. It promotes cohesiveness.

  Feel, Think, Do. “Motivation is the portal to engagement” (Barkley & Major, 2020). Though not the only way to improve engagement, it is the best starting point. First, explain why it’s valuable (affective)- motivate them to want to do the thing. Next, prepare them for/talk about/reflect upon how they find success (cognitive). Then, demonstrate it can be done, and let them take action (psychomotor). Feel, Think, Do.

  References

  Barkley, E.F. & Major, C.H. (2020). Student engagement techniques: A handbook for college faculty (2nd ed.). New York: Wiley Jossey-Bass.

  Bjork, R. A.  (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe & A. Shimamura (Eds.),  Metacognition: Knowing about knowing  (pp. 185–205). MIT Press.

  Bonwell, C. C., & Eison, J.A. (1991) Active learning: Creating excitement in the classroom. Washington, DC: School of Education and Human Development, George Washington University.

  Fredericks, J. A., Blumenfeld, P.C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59-109.

  Mualem, R., Leisman, G., Zbedat, Y., Ganem, S., Mualem, O., Amaria, M., Kozle, A., Khayat-Moughrabi, S., & Ornai, A. (2018). The Effect of Movement on Cognitive Performance.  Frontiers in public health,  6, 100. https://doi.org/10.3389/fpubh.2018.00100

  Taylor, K., & Marienau, C. (2016). Facilitating learning with the adult brain in mind: A conceptual and practical guide. Jossey-Bass.

  Raes, A. (2021). Exploring Student and Teacher Experiences in Hybrid Learning Environments: Does Presence Matter? Postdigital Science and Education. 4. 138-159. 10.1007/s42438-021-00274-0.

  Intellectual Disclosure: No generative AI was used in the creation of this document.

• How to learn a hand skill.

  02/08/2025

  Bilateral Transfer is grasping a skill with both hands. It refers to the idea that we are better able to acquire a new skill, if we practice with both our dominant and non-dominant hands. A number of experiments support this theory (Halsband & Lange, 2006. Senff & Weigelt, 2011. Stöckel & Weigelt & Krug, 2011).

  Some context:

  I’ve only recently discovered the term bilateral transfer, but I’ve been working with it for years. When I first started delivering welding classes, I wanted to make sure I was able to easily perform any weld I might encounter in the field. So, I practiced to a goal of perfection.

  At one point, while struggling to complete, I used my non-dominant hand out of desperation. My success was not great, but when I went back to my dominant hand, I found improvement. From there, I incorporated the practice into my curriculum. Any time a student struggled to make a weld, I’d suggest they try with their other hand. It has usually provided positive results.

  I explain it to the student this way: There are three advantages to using your opposite hand. Firstly, it’s like you’re creating a second pathway to the same end. By using your other hand, you activate the other side of your brain, and build new connections (bilateral transfer). Second, because you’re doing something new, you spend a bit of time thinking about how you do that, how you are going to do it in mirror, and then take any discoveries back to your dominant hand (critical reflection (Brookfield, 1991)). Thirdly, I tell them it doesn’t matter if they succeed or not. They are at the disadvantage of using their non-dominant and unpracticed hand, any expectation of a better result is unrealistic. Have some fun with it (gamification).

  The Evidence:

  One of the studies that looked at bilateral transfer, focused on the sequential effects of practicing with either the dominant or non-dominant hand, before being tested with the dominant hand (Senff & Weigelt, 2011). They found that those that first practiced with their non-dominant hand, then their dominant hand (nd/d), showed greater ability than those that practiced with their dominant hand, then their non-dominant (d/nd). Similarly, the nd/d group outperformed those that practiced exclusively with their dominant hand (d/d). It was also noted that those that practiced with only their non-dominant hand (nd/nd), ranked second in terms of performance.

  Another set of experiments then evaluated the sequential effects of using both hands to practice, but evaluated the performance of both the dominant and non-dominant hand (Stöckel & Weigelt & Krug, 2011). They found similar result, with the nd/d group showing greatest improvement with both hands, and the second ranked was a group that switched back and forth between the dominant and non-dominant hand while practicing.

  In terms of brain activity, functional studies (Halsband & Lange, 2006) show that the spatial region of the right hemisphere is used in early skill acquisition, while the left brain motor associated areas engage later, as the skill is refined and practiced. The sequential effect on practice was also examined, with those participants who practiced with their right hand then their left (d/nd), showing activity linked to mirroring activities, while those that practiced left to right (nd/d), demonstrated the transfer of spatial information.

  This fits with the results of an experiment where participants were tasked with two activities, one requiring accuracy, and one requiring strength (Stöckel & Weigelt, 2012). In both cases, the groups were trained either d/nd, nd/d, d/d, or nd/nd. In the accuracy test, the nd/d group scored best, as spatial reasoning was the critical learning. In the strength test however, the d/nd came out on top. This could be attributed to the natural tendency for greater strength in the dominant hand.

  Conclusion:

  All of the participants were right-handed. So, these studies indicate that it may be advantageous for right-handed individuals to begin all motor skill learning with the left hand, for the gain in spatial awareness, before shifting to the right hand for refinement of the motor skill and completion of the task (nd/d). It also suggests that left-handed individuals make acquire skills faster, but could be out paced by their right-handed peers over the long run, as the brain activity shifts from the right to left hemisphere. Further extrapolation- left-handed learners should begin with their left hand, move to their right hand to help refine the motor skill, then back to their left/dominant hand for completion (d/nd/d).

  Going forward, I will test these theories in the shop. Armed with a better understanding of how the brain works, my goal will be to further incorporate this strategy into my delivery, and identify the point at which point students should migrate to their other hand.

  Try it out. Let me know what you think.

  …

  Brookfield, S.D. (1991). Using critical incidents to explore learners’ assumptions. In J. Mezirow and Associates. Fostering critical reflections in adulthood, 177-193. San Francisco: Jossey-Bass.

  Senff, O., & Weigelt, M. (2011). Sequential effects after practice with the dominant and non-dominant hand on the acquisition of a sliding task in schoolchildren. Laterality, 16(2), 227–239. https://doi.org/10.1080/13576500903549414

  Stöckel, T., Weigelt, M., & Krug, J. (2011). Acquisition of a complex basketball-dribbling task in school children as a function of bilateral practice order. Research quarterly for exercise and sport, 82(2), 188–197. https://doi.org/10.1080/02701367.2011.10599746

  Halsband, U., & Lange, R. K. (2006). Motor learning in man: a review of functional and clinical studies. Journal of physiology, Paris, 99(4-6), 414–424. https://doi.org/10.1016/j.jphysparis.2006.03.007

  Stöckel, T., & Weigelt, M. (2012). Brain lateralisation and motor learning: selective effects of dominant and non-dominant hand practice on the early acquisition of throwing skills. Laterality, 17(1), 18–37. https://doi.org/10.1080/1357650X.2010.524222

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