Getting started with team-based learning (TBL): An introduction

Abstract

Instructors of active-learning classes in economics face the challenges of motivating students to prepare before class and engaging fully in class activities. Team-based learning (TBL) pedagogy meets these challenges by (1) placing students in fixed, instructor-created teams that develop the ability to work productively together, (2) holding students accountable to the instructor and their teammates both for their efforts to prepare before class and for their ability to interact constructively with teammates, and (3) presenting learning activities in a highly-structured course format that provides students multiple opportunities to express their understanding and receive feedback from peers. The authors of this article describe how the elements of TBL courses work in concert to motivate student out-of-class preparation and in-class engagement to increase student learning of economics.

Keywords:

• Active learning
• pedagogy
• team-based learning

JEL CODE:

• A22

Notes

1 Our discussion assumes in-person classroom implementation of TBL, but the principles highlighted here are equally applicable in either synchronous or asynchronous online implementations. See Palsolé and Awalt (2008) for a discussion of the latter.

2 A transparent team formation process is helpful in the event that one or several teams finds it difficult to work together. Students in randomly selected teams (vs. instructor-selected teams) seem less likely to blame the instructor for team problems and more likely to solve problems themselves. Simkins, Maier, and Ruder (2019) and LearnTBL (2018) provide a variety of team-formation strategies.

3 One might have students prepare for such an in-class exercise by reading a synopsis of research findings on effective teams. For example, Duhigg (2016) offers a useful summary of Google’s efforts to improve teamwork at the firm.

4 IF-AT forms are available from Epstein Educational Enterprises (2020).

5 For example, for a four-choice question, the following scoring scheme might be used: answering the question correctly on the first scratch earns four points, answering correctly on the second scratch earns two points, and answering correctly on the third scratch earns one point. The nonlinear nature of the scoring provides an incentive for the team to correctly answer the question on the first scratch, and also ensures that teams stay engaged with each quiz question even if their first attempt is incorrect.

6 When students discover the correct answer to each question right away they are more likely to learn from the quiz (Opitz, Ferdinand, and Mecklinger 2011). In very large face-to-face classes and in synchronous online classes, instructors can administer the team quiz in the LMS, changing the default quiz settings to allow multiple attempts and to award decreasing points as the number of attempts increases.

7 Instructors can quickly evaluate individual in-class quizzes (iRATs) using the Zipgrade (2021) app. The app enables hundreds of iRATs to be scanned in minutes and produces analytics on individual responses to each question. For team-based quizzes (tRATs) the instructor can quickly scan team IF-AT cards as she collects them from the teams.

8 The facts that team quiz scores average nearly 100% and that engaged students always get 100% of the points for in-class activities limit student frustration with the difficult questions on the iRATs.

9 If an extensive set-up is required or if an instructor wishes to address student questions on the technical framework before the AE, the set-up and Q&A can be accomplished via recorded instructor videos and an LMS discussion forum before class in order to preserve class time for team work on AEs.

10 One instructor can manage classes of up to 50 to 60 students—ten teams; larger classes require TA support and perhaps a modified debriefing process. Kibble (2016) and LearnTBL (2018) offer guidance for teaching with TBL in larger classes. Larry Michaelsen initially developed Team-Based Learning techniques for classes of 120 (Sibley and Ostafichuk 2014).

11 A predictable rotation of reporters among team members can result in some students disengaging from team deliberations when it is not their turn to report. To reduce this behavior, we suggest picking the student reporter by means of a random process. A “spin the wheel” app is particularly useful for this purpose and adds another element of fun to the process. Bartlett (1995, 139) notes that “adding the element of chance (in group work) … seems to be an acceptable way to have students take more responsibility for their own learning and that of others.”

Additional information

Funding

This work was supported by the National Science Foundation under IUSE Grant DUE-1712295. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.