This is a brief summary of the following paper:

Sanghoon Park & Heoncheol Yun (2018): The Influence of Motivational Regulation Strategies on Online Students’ Behavioral, Emotional, and Cognitive Engagement. American Journal of Distance Education. 32(1), pp. 43-56.

It studies the impact of eight motivational regulation strategies on three types of student engagement. Behavioral engagement concerns participation in learning activities. Emotional engagement pertains to the affective attitudes toward learning and school. Cognitive engagement refers to the approach students use to analyze and verify their learning, e.g., asking questions to themselves to check whether they learned something. The study is based on a cohort of 95 undergraduate and graduate students enrolled in online courses. Previous work has shown that students at these different levels have different characteristics in terms of their use of motivational regulatory strategies and in how they procrastinate.

Online study requires a higher degree of autonomy and self-regulation compared with traditional classroom learning, where instructors have more control over learning activities. As the authors mention, “with the growing trend of online learning in higher education […], the need to support a highly motivated and self-regulated online learner has never been greater”. Motivation is an intrinsic process that cannot be measured. Engagement is extrinsic, the outcome of motivation.

Self-regulation is very important in learning. Self-regulated learners take an active role in controlling, monitoring, and evaluating their learning. There is evidence that self-regulated learners (not clear exactly what makes a learner self-regulated) exhibit confident behaviors and high performance. They also tend to possess more intrinsic motivation.

Motivational Regulation Strategies are the strategies employed by students or lecturers to optimize students’ learning efforts during the learning process. According to Wolters and Mueller (2010), MRSs refer to “thoughts and behaviors through which students act to initiate, maintain, or supplement their willingness to start or to provide effort toward completing academic activities”. The paper lists eight motivational regulation strategies discussed by Schwinger, Steinmayr, and Spinath (2012):

  1. Enhancement of a situational interest: turning a relatively tedious task into a more fascinating one through imaginative modification​
  2. Enhancement of personal significance: connection between the task and one’s personal interests​
  3. Mastery self-talk: highlight the goal to enlarge one’s competence and master challenging tasks
  4. Performance-approach self-talk: competitive with colleagues​
  5. Performance-avoidance self-talk: avoiding bad comments or people that would make fun of poor performance
  6. Environmental control: intentionally eliminating possible distractions and also telling others about the learning plan so they can protect it​
  7. Self-consequating: self-administered gratification or reward for achieving a certain goal​
  8. Proximal goal setting: dividing learning materials into small and manageable pieces to experience success more quickly and frequently​

I think most of them are of a more personal nature and depend very strongly on the students themselves. A couple can be leveraged by instructors, though. For example, “Turning a relatively tedious task into a more fascinating one through imaginative modification”. Listening to lectures is a bit boring and I think including some interactive activities can increase engagement. Student response in the examples I’ve used (basically just mentimeter, so far) tends to be pretty good. Personally, I also try to practice “Enhancement of personal significance: Establishing” by assuming that most students want to be good professionals and highlighting the importance of the topic I am teaching for them to reach that goal but I am not sure I achieve anything with this.

The paper leverages a hierarchical multiple regression to establish which strategies are good predictors for self-reported engagement, considering the three types of engagement. The main takeaways from the statistical analysis are the following:

  • students should be encouraged not to use the “performance-avoidance self-talk” strategy if behavioral engagement is required for online learning activities.
  • controlling the environment for distractions is a predictor for behavioral engagement
  • mastery self-talk positively influences emotional engagement. The emphasis here is on emphasizing mastery of learning goals, instead of performance comparison with peers.
  • “performance-avoidance self-talk” is, surprisingly, a positive predictor of cognitive engagement. The same goes for “enhancement of personal significance”.

References

  • Schwinger, M., Steinmayr, R., & Spinath, B. (2012). Not all roads lead to Rome: Comparing different types of motivational regulation profiles. Learning and Individual Differences, 22, 269–279. doi:10.1016/j.lindif.2011.12.006

  • Wolters, C. A., & Mueller, S. A. (2010). Motivation Regulation. In Baker, E., McGaw, B., & Peterson, P. (Eds.), International Encyclopedia of Education (3rd ed., pp. 631–635). Oxford, UK: Elsevier.