Transforming an Undergraduate Dynamics Course Using Team-Based Learning

ME 320 (Dynamics) is a required, three-credit course for sophomore- and junior-level students in the Mechanical Engineering major. ME 320 is offered every fall and spring semester, consistently enrolling 40 to 90 students. Successful completion of prerequisite courses in physics, calculus, and mechanical engineering statics is required upon entry into the course. Major course themes of ME 320 include kinematics and kinetics of both particles and rigid bodies as applied to mechanical engineering problems. Student grades are composed of homework (15%), in-class quizzes (5%), in-class group problems (15%), in-class individual and group performance (5%), semester exams (three, worth 15% each), and a final exam (15%). After taking ME 320, students are prepared for advanced courses in the Mechanical Engineering major, including a course in controls.

I first started teaching ME 320 in 2011, having just taken over as the primary instructor of the course after its long history under a traditional lecture pedagogy. During my first year of teaching ME 320, I made some updates to the course to try to make it more relevant to students, but I still mostly used the traditional lecture classroom model. In a typical class period that semester, I gave a lecture and then spent the remainder of the class working step-by-step through detailed example problems in front of the class, making sure to stop and ask for questions from students throughout. However, I quickly realized that I was losing many of my students. Instead of taking meticulous notes on the solutions that I was working out for them, many students seemed to be lost in their personal electronic devices. To counteract this, I tried to be more enthusiastic, bring humor into the classroom, and bring in examples that I thought the students might find fun and relevant, but nothing I did seemed to capture their attention for 75 minutes. I realized that my class was not working the way that I wanted it to, and eventually, I realized that I needed to make a significant change.

Since then, I have made many incremental changes to the way that I teach ME 320, starting in Spring 2012, when I decided to make one small adjustment. In the last 20 minutes of class, instead of demonstrating how I would work through the last example problem for the day in front of the students, I handed out that problem to be worked through in groups of the students’ choosing as a “collaborative quiz.” Little did I know, this would become one of the most important moments in my experience as an educator. Discussions broke out across the lecture hall among students, hands went up because students had questions on how to apply the theory we had just discussed to solve the problem at hand, and everyone put their phones away. Some even stuck around after class. Somehow, students now seemed to be completely self-motivated to understand the concepts and to complete the challenge of solving the example problem. By making the switch from passive to active learning, and by encouraging students to work together with their peers, I was able to change the classroom culture completely. I realized that my students actually did want to learn dynamics, and that motivated me to continue to try other new, effective ways to help harness the energy and engagement I had observed in the classroom that day during the collaborative quiz. One step at a time, ME 320 has become an active- and team-based-learning class, built to encourage effective student learning.

Through this portfolio, I describe some of the steps that I have taken over a span of nearly 10 years to design an active, team-based learning classroom for ME 320, most of which were developed in collaboration with Dr. Molly McVey. In particular, we will focus on the team-based aspect of the course, including the ways in which we have incorporated the following four principles of team-based learning into the course (Michaelsen, Knight, and Fink 2004):

1. Teams should be strategically formed, permanent, and properly managed.
2. Students must be held accountable for some portion of their learning and class preparation via the Readiness Assurance Process, which includes both individual and team test components that receive immediate feedback.
3. Team assignments must promote both understanding of course material and team development, and should include application activities. Teams should work on significant problem(s), they should be required to make a specific choice within their solution, all teams should work on the same problem, and the teams should report their findings simultaneously.
4. Students should receive frequent, immediate feedback. Peer evaluations must be part of the feedback process.

In addition, we will discuss strategies for building effective student teams, how we have implemented technology into the team-based learning classroom, how we have built team activities into course assignments, and how team-based learning can ultimately improve student performance and classroom culture. We hope that this portfolio may serve as a tool for other instructors interested in incorporating team-based learning into their courses.

After seeing success trying out a “collaborative quiz” activity that Spring 2012 semester, I was inspired to continue to expand my repertoire of new teaching strategies that might encourage my students to learn effectively in the ME 320 classroom. So, at the beginning of the Spring 2013 semester, I attended a teaching workshop sponsored by the School of Engineering, which was titled Implementing Hybrid Teaching Models: Methods and Resources. The talks that I heard as part of this workshop gave me a lot of new ideas, and step by step, I began to try them out in my classroom. A more recent collaboration with Dr. Molly McVey has helped me to further build strategies to encourage effective student learning in my course.

Since then, a typical class period in ME 320 looks a lot different from a traditional lecture. Now, students come to class having prepared for team activities by watching a video lecture, reviewing PowerPoint slides, reading the class textbook, or some combination of the three. Class begins with an individual and team readiness assurance quiz, and then the students transition to a group development activity. Then I spend some time delivering a short lecture that highlights difficult concepts and concludes with a brief discussion of an example problem. After that, students use the remainder of the class time to work with their peers to solve example problems (Figure 1). Graduate teaching assistants and undergraduate teaching fellows (students who had previously been very successful in the course) are essential elements of the active learning classroom, facilitating team activities and assisting with assignment grading.

Once we began implementing active learning activities into ME 320, group work became an essential component of the course. However, pinpointing the best strategies for creating and maintaining these student groups took some time. At first, I allowed students to work with whomever they wanted, forming casual groups. Next, and after moving to an active learning classroom for the first time, I assigned students to groups of three, shuffling the groups after each exam. However, I noticed that several of these groups of three began to form what I call “supergroups,” organically merging with a second group to form a larger group of six. We now realize that this natural shift in group size is something that we might expect based on the principles of team-based learning suggested by Michaelsen, Knight, and Fink (2004).

According to Michaelsen, Knight, and Fink (2004), team-based learning is defined as “...a particular instructional strategy that is designed to (a) support the development of high-performing learning teams, and (b) provide opportunities for these teams to engage in significant learning tasks.” Ultimately, team-based learning elevates student groups (which could be random assemblages of individuals) to teams, in which each student has a unique and essential contribution to the success of the group (Table 1). Because of this, I now assign five to six students to each team within ME 320, and I do not shuffle or alter those teams in any way over the course of the semester. Maintaining the same teams for the duration of the course allows the group members to continue to grow and improve together over the long term and find their own roles within the larger group.

The initial formation of high-performing student teams should be done intentionally to increase chances of group success. In recent years of ME 320, we have used the software CATME, a web-based tool that surveys student users to place them into teams based on demographics, scheduling availability, leadership role, performance in previous classes, and other identifying information. CATME and other new technologies have been helpful for the evolution of team-based learning in ME 320. My lectures, which had traditionally been the focus of the class, have now been recorded (using Camtasia) and posted to Blackboard as resources that students can use to prepare for class. Students use iClickers to answer quick reading questions at the beginning of the class period (individual and team readiness assurance tests). Clickers are also used during group work as quick check-ins to gauge how the activities are going and to check for common misconceptions.

The last step in fostering high-performing student teams in ME 320 was to ensure that group work and development were explicitly incorporated into class time and student grading, to emphasize the value placed on team activities (Table 1). First, we implemented two-stage exams, during which students take each exam in two parts: first as an individual and then with their teams, with each stage worth 50% of the total exam grade. The second, team stage, gives students the opportunity to teach and explain their answers to the rest of their group through peer-to-peer learning, and to retain information and address misconceptions by allowing students to revisit and think more deeply about exam topics. This experience also helps students to build camaraderie within their teams and their class as a whole, helping them to build support systems within the Mechanical Engineering major. We have also implemented several team-building exercises over the years to ensure that students get to know their team members and get plenty of opportunities to improve their team performance over the course of the semester. Team-building activities have been short (~5 minutes), and have consisted of either reflective discussion questions (In the context of dynamics group work, what is one strength and one weakness you bring to your team?) or ice-breaker questions (What is your favorite restaurant and why?). Finally, individual performance within a team composes 5% of a student’s final grade for the course. This component is based on the instruction team’s evaluation of each individual’s performance within the team, taking into consideration the peer evaluations provided by team members.

Learning goals, learning activities, and assessment of student learning have all become important parts of my teaching. For example, after establishing learning objectives (i.e., unit objectives) for each chapter covered in the course, Dr. McVey and I intentionally targeted exam questions to learning objectives. This required documenting student performance on each exam question. This information has allowed us many opportunities to assess the effects of pedagogical changes on student learning. For example, to evaluate the effect of team-based learning activities on student performance in ME 320, we compared both individual and team exam scores based on specific learning objectives between Fall 2014 (pre-transformation) and Spring 2016 (post-transformation). We also compared individual performance for students in teams categorized into higher-, average-, and lower-performing teams during the Spring 2016 team-based learning semester. Finally, we used student surveys to gain an understanding of the qualitative effects of team-based learning on individuals.

First, we examined how individual student performance on exam questions linked to learning objectives varied between Fall 2014 (pre-transformation) and Spring 2016 (post-transformation). While specific exam problems were not identical between semesters, they were written to test the same learning objectives, allowing us to compare student performance on a particular learning objective before and after a transition to team-based learning pedagogy in ME 320. Results of this analysis suggest that students performed better as individuals when they were exposed to ME 320 course material through a team-based learning framework (Figure 2). This pattern was true across seven of the nine tested learning objectives, three of which were statistically significant increases in student performance (12.6, 14.6, and 15.4b; ANOVA, p< 0.05). However, two of the nine learning objectives showed a statistically significant decrease in student performance (16.7b and 18.5b; ANOVA, p< 0.05). While this latter result was unexpected, we believe it demonstrates that student learning data tends to be messy, requiring multiple data sources when we try to understand how pedagogical changes in teaching affect student learning. This also demonstrates active learning on the part of the instructional team!

Student group performance followed a similar trend to that of individual student performance. When comparing the raw score (out of 10) for exam questions mapped to specific learning objectives between Fall 2014 and Spring 2016, results indicate an increase in raw score for seven of nine learning objectives, and a decrease in raw score for two of nine learning objectives post-transformation (Figure 3). Significant increases in student performance were observed for learning objectives 12.6, 14.6, and 15.4b (ANOVA, p< 0.05), while significant decreases in student performance were observed for learning objectives 16.7 and 18.5 (ANOVA, p< 0.05).

Next, we analyzed how students performed individually as a result of their membership in a low-, average-, or high-performing group. First, teams were categorized into performance groups based on how they performed relative to the group exam score average. Average-performing teams had group exam scores hovering around the mean class score, while low-performing teams had a group exam score falling within –1 standard deviation from the mean score, and high-performing teams had a group exam score that was +1 standard deviation from the mean score. Individual exam scores were then grouped based on the performance level of the team of which each individual was a member. Results show no observable difference among individuals belonging to different performance groups for Exam 1, a non-significant but noticeable trend toward higher individual performance based on group level for Exam 2, and a significantly higher score obtained by individuals belonging to higher-performing groups for Exam 3 (Figure 4). This suggests that the individual benefit of being part of a high-performing team may not be fully realized until the last exam of the semester, supporting the need for maintenance of teams for the entire duration of the course. We continue to investigate this trend across several semesters of data.

Based on the survey responses that we have received over the past several years, student perceptions of team-based learning in ME 320 have been overwhelmingly positive. In Spring 2016, we received several student comments that indicated that our efforts to create and maintain high-performing teams in ME 320 had been successful. As one student reported, “I am very pleased with the group I ended up with. We met an hour before class Tuesdays and Thursdays to work out example problems, discuss homework, and work on extra credit—which was both fun and helpful.” Another student said, “I loved working with my team this semester. As we connected more and more during class (especially through team building exercises), we were able to learn more about each other.” A third student comment highlighted the potential of team-based learning to benefit student performance and retention: “I think our team worked really well together.... We would not move on until everyone understood what they previously did not...the other members of the group would step in and make sure that the struggling member understood the concept and problem.” More recently, in Spring 2019, I gathered student opinions of their experiences with team-based learning in ME 320 as part of an iClicker survey administered at the end of the semester. Results from this short survey indicated that students felt positive about their experience working with their team and as part of an active, team-based learning classroom in general. For example, more students stated that they agreed that active learning was helpful for their learning, while fewer students agreed that passively listening to an example problem being worked out was helpful for their learning (Figure 5).

While we have made a lot of progress with my transformation of ME 320 to a team-based learning classroom model, there are still aspects of the course that we plan to continue to improve. For example, we would like to conduct additional research on student performance to develop a system of identifiers typical of high-performing groups. We also plan to improve exam questions and create new team-building activities that will be meaningful to students.

Incorporation of team-based learning has completely changed the way that I teach ME 320. By adopting student-centered teaching pedagogy, my role as an educator has become more satisfying and meaningful over time. One of the overarching lessons that I have taken away from the experience of transforming ME 320 is that taking a risk to make any change in a course can benefit student learning in ways that may be unpredictable and surprising. When making changes, it is also completely fine to take things one step at a time. For me, one small change in Spring 2012 led to more changes, which led to a complete course redesign, as well as a complete transformation of my pedagogy as an educator. I just continued to implement small changes each semester, holding onto the things that worked and dropping the things that did not.

In the way that I interact with my students today, in an active, team-based classroom, I realize that I understand them much better than I ever did in the earlier days of ME 320. Instead of wondering what my students were thinking during a lecture, in ME 320 today I think that it would actually be impossible for me not to know what information students were missing, which misconceptions they are hanging onto, and how they are progressing through course learning objectives. This has been a complete paradigm shift for me and the most significant realization of what has changed about my teaching: By holding ourselves accountable as educators to make sure that students are actually meeting our learning goals, we can gain insights about which aspects of our teaching are effective and which are not.

Despite its evidence-based successes, group work still tends to get a bad rap. Perhaps based on a bad experience that some of us have had while working as part of a group on a college assignment, it seems like there are still many instructors who are hesitant to assign group work, and especially to create groups that will last for an entire semester. However, the results that I saw after implementing team-based learning in ME 320 actually contradict that stigma. I did not experience any push-back from my students about being assigned semester-long groups. In fact, as mentioned previously, student responses were overwhelmingly positive when asked in an iClicker survey whether or not they enjoyed working with their assigned groups.

An exciting, unexpected consequence of student success in ME 320 has been the influx of large numbers of undergraduate students into two graduate-level, elective courses that I also teach, ME 750/751 (Biomechanics of Human Motion) and ME 722 (Modeling Dynamics of Mechanical Systems). When I first started teaching these two graduate courses, they would enroll just a handful of graduate students each. Now, these courses are consistently enrolling to capacity, to such an extent that we needed to make an effort to start holding seats for incoming graduate students to ensure that they would still be able to participate in this undergraduate-filled course. In conversations with students, I have found out that the reason undergraduates have been enrolling in these advanced courses is that they enjoyed their experiences in ME 320. It is inspiring to think that the high level of performance and developed class camaraderie in ME 320 was enough to encourage them to voluntarily take on the challenge of a graduate-level elective course.

I am very satisfied with the team-based structure of ME 320, but I will continue to try to improve student learning in the course with more small changes. One obstacle that I still face in ME 320 is creating more effective homework problems. Homework is a critical aspect of student learning in ME 320 because it gives students time to practice challenging concepts that have been presented to them in the classroom (especially using the “applying” and “analyzing” levels of Bloom’s taxonomy). Over the semesters that I have been teaching ME 320, I have approached homework assignments in several different ways. That led me to test the efficacy of these different strategies through the support of a grant from the Center for Teaching Excellence. In particular, I was interested in comparing the efficacy of online homework problems (which had been offered for many semesters) versus structured problems by relating student performance to homework format. While online homework was incredibly convenient for me as the instructor (automatic grading), there were some unintended consequences for students. For example, students were graded on their final answers alone, rather than their ability to work out the solutions. This also meant that the homework solutions, which have the potential to be important study tools, were often not available to the students. I plan to continue to develop strategies that will make homework more effective in ME 320.

Additionally, while two-stage exams have worked well in ME 320, student feedback about a lack of partial credit on the individual exam portion has motivated me to modify the exam structure. In the past, exam scores have been calculated using both the individual exam score (50%) and the group score (50%), with four 10-point questions on each and partial credit given on the group portion only. In the future, I will likely change this to eight 10-point questions with partial credit on the individual exam and two different questions worth 10 points each with partial credit for the group exam. This change will also allow me to test students on more learning objectives on each exam.

To conclude, we will offer a few important pieces of advice for instructors looking to implement team-based learning with high-performing teams in their courses. We have arrived at these pieces of advice from our own experience, and from our research on the four principles of team-based learning presented by Michaelsen, Knight, and Fink (2004). Our recommendations are as follows:

• Use CATME to form groups intentionally in ways that are inclusive and effective.
• Maintain student teams over the entire duration of a course, rather than shuffling students around intermittently (e.g., after each exam).
• Hold students accountable for their role within their team by requiring them to prepare for in-class work using provided course materials like video lectures, PowerPoint slides, or other texts.
• Make sure that the value of student teams is clearly reflected in student evaluation. (ME 320 students rely on team activities for 45% of their final semester grades.)

Acknowledgments and References:

• Some of the results reported in this portfolio were previously published in the American Society for Engineering Education journal in 2017 under the paper ID #18468.
• Michaelsen, L. K., A. B. Knight, and L. D. Fink. "Team-based learning: A transformative use of small groups in college teaching." (2004).
• What is Bloom’s Taxonomy? A Definition for Teachers
• Team-Based Learning Collaborative
• Contact CTE with comments on this portfolio: cte@ku.edu.