This is a reflection to the relationship between motivation and student engagement in the college classroom, as presented by Barkley in Student Engagement Techniques.
Student engagement is a term used often at my place of work. I probably hear it at least monthly at staff meetings, in the lunchroom, or in passing conversations. The only reason I mention that is because like much of what I’ve learned so far in my journey through the Provincial Instructor Diploma Program, it boggles my mind that nobody has, in the 7 years as a college instructor, explained some fundamental concepts of adult education to me. And once again, I was blown away by the simple Venn diagram that illustrates student engagement at the intersection of motivation and active learning. So simple yet so profound. Because all three of those terms are something I’ve become familiar with in my profession. But the relationship between them has never been so clearly demonstrated. This basic diagram gave me pause and created a vision for my future in this profession. It piqued my interest in the textbook, in this course, and in putting these concepts into practice as soon as possible.
I was quickly brought back down to earth as I continued to read on about student motivation. Terms like self-efficacy, attribution theory, self-worth models, and flow helped me realize I was a long way from discovering the holy grail of teaching. There is obviously a lot of work ahead of me in order to get a good grasp of the concept of student engagement. But what better place to start than further investigating the idea about the product of expectancy and value.
The key insight gained from reading the first two chapters of Student Engagement Techniques is the expectancy-value model of motivation. Effectively, students’ motivations are influenced by what they believe they can accomplish and what they think is important.
To me, the idea of expectancy (what a student believes he can accomplish) is best described by Bandura’s self-efficacy theory. There is a great deal of research involving the relationship between self-efficacy and motivation. Chang et al (2014) investigated the effects of online college students Internet self-efficacy on learning motivation and performance. They concluded that students with high Internet self-efficacy outperformed those with low Internet self-efficacy and encouraged educators to identify the psychological characteristics of online learners to provide suitable support for their learning. The study integrated Keller’s proposed model of attention, relevance, confidence, and satisfaction (ARCS), which has been found to be beneficial to the improvement of learner motivation. Ultimately, the study found that Internet self-efficacy helped students transform motivation into learning action, which improved learning performance.
Hsieh (2014) investigated the relationship between different types of learning motivation, engagement behaviours and learning outcomes in undergraduate students in Taiwan. One of the outcomes of this study was that student background characteristics (such as gender, socioeconomic status, and major) and their learning motivation (intrinsic, extrinsic, task value, or self-efficacy) were more important predictors of learning outcomes than student engagement behaviours (such as active participation, interaction with instructors, and cognitive effort). To me, this means that regardless of how well designed an instructional strategy or a participatory learning activity is, if it is not founded on the proper degree of motivation, it may very well fall flat.
Barkley (2010) uses Csikszentmihalyi’s concept of “flow” to explain value. This concept describes a state of deep intrinsic motivation where action and awareness merge. She goes on to provide Wlodkowski’s suggestions about how to help students achieve a sense of flow: “(1) goals are clear and compatible, allowing learners to concentrate even when the task is difficult; (2) feedback is immediate, continuous, and relevant as the activity unfolds so that the students are clear about how well they are doing; and (3) the challenge balances skills or knowledge with stretching existing capacities” (Barkley, 2010, p. 14).
As I look back on life and try to remember times where I experienced flow, my memory keeps recalling video games. I distinctly remember explaining to my friends why I enjoyed engaging with certain games – because it felt like an escape and I wasn’t thinking about anything else happening in the world or life while I was playing. I can clearly make a connection between those times of complete immersion and Wlodkowski’s suggestions of achieving flow. Looking back, those games had clear and compatible goals, feedback was immediate and continuous, and the challenge was appropriately difficult. I suppose I was properly motivated through expectancy and value. Wheeler (2016) seems to agree with this idea as one of his suggestions for achieving flow in students is games and gamification. He also suggests role play, simulation and problem solving as other forms of immersive learning.
There are a number of key takeaways that I have decided to move forward with as a result of my investigation into student motivation and in particular the expectancy-value model.
Firstly, I have to improve the establishment of self-efficacy and flow into my lessons. While I think I have made great strides this academic year in providing more active learning opportunities for my students, I now fear that they may not be founded on proper motivation. This investigation has enhanced the importance of the bridge in for me. I now see it as something much more than just grabbing the students’ attention. It is an enormous opportunity to base the lesson on expectancy and value and keep students motivated and engaged throughout the participatory learning activities. Taking that a step further, I should build in many more bridge ins throughout a lesson. As an example, I am currently teaching a four hour class where each lesson begins with a bridge in followed by multiple participatory learning activities and concluding with a single summary. It may be much more beneficial to plan these lessons to incorporate motivation enhancing bridge ins at the beginning of each participatory learning activity followed by a summary of that learning activity in hopes of helping the students achieve a sense of satisfaction. This can also be done after breaks and during the introduction of a course assignment. Ultimately, I should maximize the opportunities to enhance student motivation with every student engagement technique that I decide to use. I am going to further investigate the ARCS model to achieve this.
Another takeaway from this reflection is for me to do a more effective job of learning about my students. I have the benefit of teaching in a fairly close-knit program that provides ample opportunity to establish and maintain good relationships with my students. If I can incorporate learning about their self-efficacy, their learning motivations, what they value and expect, it may help me get more in tune with how I can support their learning experience. I am going to research surveys that could help me obtain data about these characteristics about my students.
Lastly, I am going to focus more on planning immersive learning experiences where appropriate. Gamification is a primary example. One success earlier this semester was a Kahoot! quiz that followed a video that we watched. Students competed for a small prize during the quiz and I felt like it really increased engagement with the video. The students were certainly immersed in the competition. While this happened almost by accident, I can now see that the success may have been based on the expectancy-value model. Another success was a role play scenario that I established. Where I would have normally lectured to my students about joint health and safety committees, this semester we established our own committee and each student was given a role to play at our mock meeting. The students were immersed for a straight sixty minutes contributing to the meeting and fulfilling their roles. Once again, it happened partly by accident, but I now see that this fits squarely within the expectancy-value model. I will continue to investigate opportunities to incorporate gamification and role play wherever I can.
Barkley, E.F. (2010). Student Engagement Techniques A Handbook for College Faculty. San Francisco: Jossey-Bass
Chang, C-S. (2014) Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in Education and Teaching International, Vol. 51, No. 4, 366-377.
Hsieh, T-L. (2014). Motivation matters? The relationship among different types of learning motivation, engagement behaviors and learning outcomes of undergraduate students in Taiwan. Higher Education, Vol. 68, 417-433.
Wheeler, S. (2016). The Flow Theory in the Classroom: A Primer. Retrieved from www.teachingthought.com/learning/flow-theory-clasroom-primer/