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Getting students to do economics: an introduction to team-based learning.

Abstract Team-Based Learning (TBL) is a highly structured form of cooperative learning that facilitates development of higher-order cognitive skills such as application, analysis and evaluation. In this paper, I discuss the basics of the TBL approach in the context of a data analysis course for economics majors and address some of the questions and concerns about TBL that are common among instructors new to the pedagogy. Data from student surveys suggest that this approach is highly engaging for students and encourages them to work more effectively on much more complex problems than would otherwise be possible.

Keywords Team-based learning * Collaborative learning * Student engagement



Collaborative learning is one of the most developed and most researched instructional approaches (McGoldrick 2012). Although economists are slowly increasing their use of interactive pedagogies, it is still relatively rare for economics instructors to use collaborative learning techniques (Watts and Schaur 2011). This is especially unfortunate given the wealth of evidence on the benefits of collaborative learning, including higher achievement and increased engagement (see McGoldrick 2012). Moreover, Marburger (2005) suggests that collaborative learning may be particularly effective for helping students of economics to master higher-order learning skills such as analysis.

Collaborative learning can take many forms, from a simple 'think-pair-share' exercise to jigsaw problems to highly-structured team problem-solving. One format that falls on the latter end of that spectrum is Team-Based Learning (TBL), a specific form of structured group work (Michaelsen et al. 2003). (1) A key feature of TBL is that it is a "whole course" pedagogy, that is, it is a way of structuring an entire course, rather than a technique that can be implemented ad hoc in one or two class meetings. The TBL structure can be summarized as 1) students acquire basic concepts on their own, outside of class; 2) students are held accountable for the out-of-class work through a specific assessment process at the beginning of each course unit; 3) students spend class time working in permanent (semester-long) teams, on carefully constructed exercises that emphasize application, evaluation and other higher-order skills; and 4) students periodically assess their teammates and those evaluations are used in determining each individual's final course grade. (2)

There is ample evidence from other disciplines that TBL improves student learning and engagement (Sisk 2011; Haidet et al. 2014). In economics, only a few instructors have documented their experience with TBL. Espey (2012) describes her adoption of TBL in both a microeconomics principles course and an upper-division environmental economics course. Although she does not provide data on student outcomes or evaluations, she reports that TBL has allowed her to dive deeper into material and ask students to analyze more complex problems. Hettler (2006) found no significant difference in outcomes, as measured by the Test of Understanding of College Economics (TUCE) or course exams, between a section of macroeconomics principles taught with TBL compared to one taught in a traditional lecture format. (3)

In this paper, I discuss TBL in the context of an upper-division data analysis course for economics majors. I describe the course and institutional context and how the course was structured. These sections will hopefully serve as a primer for any instructors who may be interested in trying TBL in their own courses. I also present data on student reaction to the TBL structure. Although I do not have data to directly compare student learning outcomes or achievement with and without TBL, the qualitative data suggest that TBL is highly engaging for students and encourages them to work more effectively on much more complex problems than would otherwise be possible. In my conclusion, I address some common concerns for those considering adopting TBL.

TBL in a Data Analysis Course

The course in which I first used TBL Learning was Economics 301, "Collection and Use of Data in Economics." The course is somewhat unusual in that the focus is on "data literacy," rather than statistics. Students grapple with data issues such as how to define vague concepts (e.g., what variables would you use to measure 'school quality' or 'safety'), the measurement of variables (e.g., when should one use levels versus percentages or per capita), and implications of survey bias. Students must also decide what type of analysis is most appropriate for a given application (e.g., when is a comparison of means or a correlation coefficient appropriate versus a regression); the final section of the course then focuses on graphical presentation of results. It is a required course for all economics majors and the prerequisites include principles of microeconomics and macroeconomics, a lower-division statistics course, and a lower-division management information systems course (called principles of information systems at my university). All four of these courses are also lower-division requirements for all economics majors.

TBL is a particularly good fit for this type of class, where the focus is on application and analysis, using basic building blocks of content that students have already acquired (or should have acquired) in previous courses. The team structure means that regardless of the size of class, students can engage in deep discussions about the material, and tying team applications to pre-class data assignments creates a strong incentive for students to complete the assignments without requiring extensive grading.

Moving Content Out of the Classroom

There has been a lot of discussion recently about flipped classrooms, where students acquire basic content on their own before class so that class time is freed up for more in-depth application work. TBL falls squarely into this format. The Readiness Assurance Process ensures that students complete pre-class readings or assignments, while the team applications provide a template for in-class work.

Assessment at the Beginning of Each Unit

TBL courses are divided into modules. My course has four, ranging from 2 to 4 weeks for each. At the beginning of each module, students complete readings or watch videos that introduce/review the basic content they will need. For my class, I provide a study guide with questions highlighting the definitions and concepts students should be sure to know. (4) Then on the first day of the unit, students go through the Readiness Assurance Process. They first take an individual readiness assessment (RA). (5) The RA questions are multiple-choice and since the point is to make sure students have sufficient understanding of basic concepts, the questions are largely definitions and recall.

Team Assessment Ensures Content Knowledge

A key feature of the Readiness Assurance Process is that it is not intended to test higher-level skills. It is to make sure students are ready to move on and start applying the concepts. So even if students do not do the review they should do, and do poorly when they take the RA on their own, the TBL process ensures that they will still be ready to move on because immediately after students finish the RA individually, they re-take the same assessment as a team. To do this most effectively, most TBLers use a special form, called an "IF-AT" form (Immediate Feedback Assessment Technique). (6) IFATs are multiple-choice scratch-off forms, they look a bit like scantrons but instead of bubbles, there is gray scratch-off material, like on a lottery card. For each question, the teams decide on their answer and scratch off the corresponding letter. If they are correct, they will see a star. If they are wrong, they can try again and still receive partial credit. For example, my RAs have five answer options for every question and teams get 3 points for one scratch, 2 points for two scratches and 1 point for three scratches (i.e., if a team cannot get it right in three tries, they get zero points). (7) Thus, not only do students get instant feedback but if a team is wrong on their first attempt, they still have incentive to keep discussing the question so they can try again. The scratch-off form also creates a sort of 'game' atmosphere. It is not unusual for teams to cheer when they see the star.

The way many of the teams in my classes complete the team RA is to first have everyone say which answer they chose. If there is any disagreement, students then explain their choice and they try to convince others who might want to scratch off a different letter. Sometimes weaker students will say things like, "Well, I put A but I really was just guessing and have no idea," but even then, they will usually want someone else to explain why a different answer is right. Although some faculty may have concerns about free-riding in these sorts of group activities, I have never seen a team just give the IF-AT form to one person and have that person complete it without input from everyone else. So by the time the teams are done, students not only know the answers to all of the RA questions but they have discussed both the right and wrong answers and they generally understand the concepts well enough to dive into the applications. In addition, if there are still questions, I give a 'mini-lecture' where I provide further clarification.

It is probably not surprising that the individual RAs are generally the students' least-favorite aspects of TBL. On the other hand, students tend to really like the team RAs. Still, I receive many comments along the lines of "I do not like that we get tested before covering the material in class" or "I think Professor Imazeki needs to lecture more before the RAs." In the concluding section below, I discuss some of the ways I try to minimize this sort of student resistance.

Team Applications

By the time students are done with the team RA, they are ready for the team applications. For the next several class meetings, class time is almost entirely devoted to teams working on problems that require they think through and discuss the kind of data issues that empirical researchers routinely address. During the all-class discussion that follows the team discussions, my contribution tends to be limited to directing the discussion. I may spend a few minutes at the end of class tying together concepts but that is the closest I get to lecturing. TBL best practices say that good applications should satisfy the four S's: significant problem, same problem, specific choice, and simultaneous report (see Roberson and Franchini 2014, for a thorough discussion of good task design).

Significant Problem Of course, we all want our students to be working on problems that are significant, which I take to mean both relevant and complex enough to require application and integration of course concepts. But actually coming up with "significant" problems is not always easy. Many of the canned examples from textbook supplements are neither relevant nor complex, particularly if you want students to think critically and not just plug-and-chug. For most economics courses, current events can be an excellent source for significant applications. I use a number of applications based on headlines and real-world examples, many involving issues that are not actually resolved among experts (more about this below). For example, for discussing problems that arise from trying to define vague concepts, students are asked to decide what variable to use in a comparison of whether Americans are better off today than they were four years ago.

Same Problem A common approach for cooperative learning is to have groups do "jig-saw" problems, where each group (or member of the group) works on a slightly different problem and then the parts have to be put together to form an overall conclusion or product. While this can work well for some purposes, in TBL courses, everyone works on the same problem so they become invested not only in their own response but in the responses given by others. Both within and between groups, discussion is more lively as students compare answers and then must defend and explain their approach to the problem.

Specific Choice To ensure productive team discussions, teams must agree on one choice and, as a team, defend that choice to other teams. For most of my team applications, the way I force students to make a specific choice is by giving them multiple choice options. The catch is that a large number of the applications have more than one answer choice that could be "right", depending on what assumptions one makes. For example, one of my favorite applications is about the Current Population Survey (CPS) definition of income. Before class, students go to the CPS website and get data on median household income and have to read about how the CPS defines income. (8) The team application reiterates that income does not include noncash benefits, including in-kind transfers like food stamps and employer-provided work benefits, and then asks:

The exclusions in the CPS definition mean that the measured income gap between rich and poor (assume 'rich' and 'poor' are measured by 10th and 90th percentile of the population), when compared to the "true" income gap, is likely to be:

A. understated

B. overstated

C. unaffected

Almost all students quickly recognize that the exclusion of noncash benefits means that the measured income of poor people is likely less than their true income. Some students see that richer people's incomes are also understated because work benefits are not included either. Someone always also points out that income is measured pre-tax and rich people pay more in taxes. The point is that through the team discussion, students have to identify not only how income is affected for different people but they have to think about how big those effects are likely to be. Since none of them have any real idea what those magnitudes are, they have to make assumptions, and those assumptions will ultimately drive which answer they choose.

For each application, there is a team worksheet where the teams must write down which answer choice they selected and provide a justification for that choice, including identifying any assumptions they are making. (9) Identifying the assumptions is always the most difficult part for them. It really takes some work to get them to admit that they are assuming information. But the team discussion generally helps with this. The answers are almost always split, both within teams and then among teams, which means there is someone else in the room who is making very different assumptions and coming to a different conclusion.

The biggest challenge for teaching with these applications is that certain students can be very resistant to the idea that there is no one 'right' answer. I have to repeatedly emphasize to students the 'if-then' nature of the answers. "IF you assume X, THEN you would want to choose answer A; but IF you assume Y, THEN you would want to choose answer B." (10) I also repeatedly tell students that although some questions may have more than one answer that one could justify, there is still a right way to think about the questions, i.e., to identify what assumptions will lead to different answers. I point out to them that this is the way the real world works. For example, when they hear politicians saying things that seem to be contradictory, it does not necessarily mean that one side is "wrong," but they could be making different assumptions. Of course, then one should next ask whether those assumptions are valid.

I also have students register their choices individually before the team discussion (using an audience response system). I may or may not show them the distribution of those answers. The important thing is that they have to give the question at least a little bit of independent thought, and they have to register their own choice, before discussing the problem with their team. This not only gives the teams an easy starting point (they go around and ask everyone what answer they chose) but once people have registered an answer, even if they do not have a ton of confidence in it, they will usually either try to defend it or want a coherent explanation of why the team should go with a different choice.

Simultaneous Report After the teams have some time to discuss the application and make their choice, every team reports their choice at the same time. This means teams cannot change their answer once they see what everyone else chose. I do the simultaneous report with small whiteboards. Each team writes the letter corresponding to their choice on their boards and holds it up at the same time. Other options include having cards with the letters on them, or different color cards. What is important is to be able to see which team has chosen which answer because teams need to be accountable for their answer. When I ask Team 6, for example, to explain their choice, they cannot change their response to something different. Similarly, I can see immediately if one or two teams choose something different than all the others. That is usually where I start the all-class discussion.

Peer Evaluations

The fourth component of the TBL structure is peer evaluations. This is the part of TBL that students are often most worried about at the beginning of the semester. But in the five semesters (nine classes) I have used TBL, I have not seen a single evaluation that appeared to be a student or team trying to 'game the system' (i.e., 'rewarding' a friend or 'punishing' someone unfairly). I have seen a few where students seemed to be not putting in much effort or thought, but it has never caused someone's grade to be different than I thought made sense.

There are different ways to do the peer evaluations. The approach I use is to have students give a numeric score to each member of their team (not including themselves) and those scores must add up to 100 (see for a discussion of alternative approaches). They must also provide a qualitative explanation of those scores, and those comments are passed on (anonymously) to each student. On the evaluation form, which students complete on Blackboard (the learning management system), students are instructed to specifically consider factors such as preparation, contribution, respect for others and flexibility. These evaluations are done twice a semester. The mid-semester evaluations provide students with feedback so they can adjust behavior if necessary. The end-of-semester evaluations are the ones that actually count. In order to make sure that students give both numeric and qualitative feedback, I give them individual points for completion.

Incorporating Evaluations into Grades

Most faculty using TBL use the evaluation scores either as a multiplier applied to the team part of the grade, or as a separate component of the course grade (see http://www. for a discussion of both). I use the former, so I take the peer evaluation scores and convert those to a weight. That is, since I mostly have teams of six, the average score for each student is 20 (e.g., if someone wanted to give everyone on the team the same score, that score would be 20) so I start by taking an individual's average score as a percentage of 20. Thus, really good team members will have weights of greater than 1, although I also cap the weights at 1.25. So, for example, if a team has perfect scores on their team RAs and team applications (a situation that has not actually happened in any of my classes), and one member of the team is the clear leader and has high scores from everyone, then that person could potentially get 125% for the team portion of their grade. If that person were also to have perfect scores on all their individual assignments, they could actually have more than 100% of the points possible for the semester (again, this has never actually happened).

The peer evaluations only impact the part of the final grade that is based on team activities and this can vary across TBL courses. Many TBLers have the students themselves determine how much weight will be given to team and individual activities. For example, Larry Michaelson and others have the teams discuss and then send a representative to meet with other team representatives in a fishbowl-type discussion. That approach can be great for getting student buy-in and for building team cohesion. However, I did not feel comfortable doing it with my classes so I simply set the weights myself. (11)

Do Students Take It Seriously and Think It Is a Fair Process?

As mentioned above, I have not yet seen any evidence that students try to game the system. I also have not had any complaints from students about their evaluations being unfair. The qualitative feedback is a key factor with this. Even if one student were to unfairly criticize a teammate, it would be clear from the other team members' comments that the student was out of line. At the same time, when a particular student is not pulling their weight, that generally shows up in comments from multiple teammates, not just one. One thing I initially found surprising is how much students will ding a teammate for being absent. Comments like "he has missed a lot of classes" or "she does not tell us when she's going to miss class" almost always accompany low scores. Those comments matter: I have seen quite a few students start coming to class more regularly after they get their mid-semester evaluations.

The instructions, asking students to think about things like respect for others and flexibility, are also important for getting good qualitative feedback. It is not unusual to see comments like, "John always makes sure to get everyone's opinion before we finalize our answer" or "Jane always has a strong opinion, and it's usually right, but she's also good about listening to other people's explanations and admitting when she's wrong" or "I wish Jim would contribute more; when he does, he usually has good points but he's kind of quiet." In general, the majority of comments, both good and bad, are respectful and actually constructive.

Student Response to TBL

At the end of every semester, I survey my students specifically about TBL. (12) I have summarized the responses from the last four semesters in Table 1. (13) Response was most positive (highest percentages agreeing or strongly agreeing with most of the statements) in Spring 2011, when I had two sections of 75 students each. The positive responses fall a bit in subsequent terms but over 85% still said TBL makes them more likely to attend class and to feel more involved in class, about two-thirds would choose a TBL section over another section of the same course that does not use TBL, and over three-quarters said that they felt they gained a deeper understanding of the material with TBL compared to traditional lectures.

The open-ended comments had similar percentages of positive responses. Many students felt that TBL 'made class more fun' and 'was totally different from any class I have taken, in a good way'. Here are two comments that capture attitudes that seem pretty typical for most students (all grammatical and typographical errors left intact):
   Team based learning was very helpful, it let you discuss things
   with your group and clear things up. I know many people including
   myself tend to hold back with questions when confused because of 1)
   not being able to form a good solid question because of the
   confusion or 2) being embarrassed to ask a question that may make
   you look stupid. With team based learning that kind of confusion
   was easily cleared up.

   At first I was very apprehensive about the team group. When I
   learned that the whole class is developed around teams I said to
   myself "oh here we go, others are gonna band wagon on few people's
   hard work' as it always turns out that way with teams. However the
   way Professor Imazeki set up the teams really worked out well.
   Everyone had good input. At some point I started to miss a few
   classes due to personal reasons and my team members motivated me,
   check up on me and brought me back to class. I enjoyed working on
   my own at home and comparing my findings with my teammates in order
   to reach collaborative answers in class. I have never had such
   great experience with team work. I would love to have other classes
   designed around this kind of team work versus team project where
   the pressure usually falls on one or two people who care.

Not All Students Love TBL

In every class, there have also been a few comments along the lines of "It would have helped if the professor had explained things a little more," and three or four students have been downright hostile. In at least two of those cases, the students really were more frustrated by the material, rather than the TBL method (that is, they hated that there was not always a 'right answer' to everything). A few students commented on what they saw as free-riding behavior, noting that not all group members always participate equally but they get credit for the team RAs and applications. To me, those comments indicate I need to do a better job of explaining how the peer evaluations impact the team part of the grade (since if a student really is not contributing, then the rest of the team should give them a lower evaluation score and they do not get the same credit for team efforts).

Getting Student Buy-in

One important ingredient for TBL success is for students to understand why we are using TBL. Overall, once students understand why I am using TBL, and once they see that this is not like other group work they have experienced in the past, the vast majority enjoy it, if not prefer it, to typical lectures. I do think it is important to lay the groundwork on the first day, to explain to students exactly why we will be using TBL and why I believe it is a better learning experience for them than listening to me lecture. To do that, on the first day of class, I ask the two questions from Smith (2008):

Thinking of what you want to get out of your college education and this course, which of the following is most important to you?

A. Acquiring information (facts, principles, concepts)

B. Learning how to use information and knowledge in new situations

C. Developing lifelong learning skills.


Of these three goals, which do you think you can most easily achieve outside of class with your own reading and studying, and which is best achieved in class, working with your classmates and the professor?

Typically, there are just a few students who answer the first question with choice A and the rest are split between B and C. We discuss how A, acquiring information, is a necessary step before you can get to B and C, but when I emphasize that the question asks what they want to get out of their college education, most students agree that knowledge alone is not that useful if you do not know what to do with it. In response to the second question, students immediately see that acquiring information is easiest on your own and from there, explaining why I use TBL is relatively straightforward. (14)

Concluding Advice

To wrap up, let me address some questions about basic logistics that I often receive from people considering adopting TBL.

Would This Work in Really Large Classes with Fixed Seats?

The largest sections I have taught had 75 students and I taught one section, my first semester using TBL, in a classroom with fixed seats. Since then, I have requested rooms with movable seats because I think it is easier if students can face each other in their teams. With fixed seats, you need to be crystal clear about where each team is seated. I think it can work if each team is together in two rows so the students in the front row can turn around and talk with the students behind them. Espey (2008) suggests that the room configuration does not affect learning outcomes but student attitudes improve with more flexible seating.

I would certainly suggest starting with smaller classes if possible but with movable seats, TBL really can work for a class of any size. If you have hundreds of students, then you likely also have at least a few teaching assistants who can help with walking around and keeping the groups under control. The TBL website has some videos that show TBL in action in some very large classrooms.

How Do You Create Good Teams?

Some TBLers create the teams in class (having students line up and count off) but I always create the teams myself because it seems easier for bigger classes. On the first day, students fill out an information sheet and I collect some information from them that I then use in creating the teams. The main things I am concerned about are having a mix of gender, 'ability' (15) and laptop availability on each team (for the data class, each team needs a laptop for a few classes so I try to have at least two people per team who say they are 'willing and able to bring a laptop to class'). I also check that the non-native English speakers are distributed somewhat equally across teams, and that there are no teams that might have cliques (e.g., members of the same fraternity or sports team). Although I do think my approach has helped ensure that all the teams are roughly equal, some TBLers will argue that it does not (or should not) matter all that much. Creating teams completely randomly might mean that one team ends up with four or five "slackers" while another team ends up with four or five 4.0 students, but if you have well-designed applications, the TBL structure should mean that all students have equal incentive to contribute.

I am Not Sure I am Ready to Adopt TBL Whole-Hog But Would Like to Adopt Certain Parts. How Can I Get My Feet Wet?

There are big advantages to adopting TBL as a whole-course approach but it can be difficult to do because it usually requires re-designing the entire course. A good way to build up to that is to start with 4S applications. If your typical approach is to assign problem sets that students do as homework, think about converting those to 4S applications and having students work through them in teams during class. You may need to reduce lecturing time in order to make time for that, but you may find that you can condense your lecture and have students discover some of the same information on their own as they work through the applications. For upper-division courses, establishing teams and having them do RAs would be a good way to get students to review material from principles and to do pre-class reading, even if you still spend a lot of time lecturing.

It should be clear by now that TBL is dramatically different from traditional chalk-and-talk. For those who are curious to find out more, the absolute best place to start is the TBL website. The book by Michaelsen et al. (2003) is also a good starting place. There are definitely start-up costs to designing a course with TBL but most instructors find that the costs are well worth the benefits of increased student engagement and the ability to dive deeper into more complex applications.

Appendix: Syllabus Explanation of TBL

We will be using a learning strategy known as 'team-based learning' (TBL); the majority of the work in this class will be done in teams that will be established at the beginning of the semester.

How does TBL work? You will spend most of your time working in teams, applying what you have learned from outside readings (and your own review of statistics). The course is divided into several units where each unit lasts a few weeks and follows the same structure:

1. Students read the assigned material for the unit. This will generally be readings in the Greenlaw (2006) and Klass (2012) books. There will be reading guides provided that are a series of questions that you should be able to answer by the time you come to class.

2. At the beginning of each unit, students will take an "individual Readiness Assessment" (iRA) in class to be sure that they have sufficient knowledge to work problems from this unit. Questions will primarily be over definitions or will be simple applications of facts and definitions. These will be multiple-choice (you will need scantron forms) and will be graded.

3. Immediately following the iRA, students will answer the same questions as a team, with a "team Readiness Assessment" (tRA). This too will be graded. All team members receive the team score.

4. Disputes over missed questions on the tRA can be appealed to the instructor. The appeal must come from the team, it must be written, and it must come no later than the beginning of the next class (detailed instructions for appeals will be distributed later and are posted on Blackboard). All affected students on the team will have their scores changed.

5. The instructor will address common errors on the RA to the class as a whole.

6. Over the following classes, teams solve real-world problems and answer questions that economists must answer as they do their work. Team Applications generally pose a question and ask each team to make a decision. Your team will need to poll each member, listen to each member's ideas and their explanation of why their idea is the best, and then reach a team consensus. At the end of your deliberation, all of the teams will simultaneously report decisions. Then we'll discuss the question as a class. Any member of your team may be called upon to explain your team's response and points may be awarded to the team based on these responses. Several of the Applications also have an individual component that must be completed prior to coming to class. These assignments will involve reading chapters in the Maier book (1999), or articles by other economists, and answering some questions, and/or getting data and doing something with it. That information will then be used to have deeper discussions and make better decisions with your team. In general, you can expect to have something 'due' almost every class.

7. At the end of the semester, students complete a confidential evaluation of their teammates, based on their participation in team activities (Did they come to class regularly? Were they prepared for the day's activity? Did they contribute productively to the team? Respect others' ideas?). There is a copy of the Peer Evaluation form on Blackboard; note that you will have to distinguish between your teammates. The peer evaluations will be used to weight the Team portion of your grade.

DOI 10.1007/s11294-015-9541-0


Espey, M. (2008). Does space matter? Classroom design and team-based learning. Review of Agricultural Economics, 30(4), 764-775.

Espey, M. (2012). Team-based learning in economics: A pareto-improvement. In M. Sweet, & L. K. Michaelson (Eds.), Team-based learning in the social studies and humanities: Group work that works to generate critical thinking and engagement (pp. 99-112). Sterling: Stylus Publishing.

Greenlaw, S. (2006). Doing economics: A guide to understanding and carrying out economic research. Boston: Houghton Mifflin.

Haidet, P., Kubitz, K., & McCormack, W. T. (2014). Analysis of the team-based learning literature: TBL comes of age. Journal on Excellence in College Teaching, 25(3&4), 303-333.

Heftier, P. (2006). The effectiveness of team-based learning in building content knowledge and problem solving skills in principles of macroeconomics, presented at the 2006 ASSA conference, http://www.

Klass, G. (2012). Just Plain Data Analysis: Finding, Presenting and Interpreting Social Science Data (2nd ed.,). Lanham: Rowman & Littlefield Publishers, Inc.

Maier, M. (1999). The data game: Controversies in social science statistics. Armonk: M.E. Sharpe, Inc.

Marburger, D. R. (2005). Comparing student performance using cooperative learning. International Review of Economics Education, 4(1), 46-57.

McGoldrick, K. M. (2012). Using cooperative learning exercises in economics. In G. M. Hoyt, & K. M. McGoldrick (Eds.), International Handbook on Teaching and Learning Economics (pp. 57-67). Cheltenham: Edward Elgar Publishing.

Michaelsen, L., Bauman Knight, A., & Fink, L. D. (2003). Team-based Learning: A Transformative Use of Small Groups in College Teaching. Sterling: Stylus Publishing.

Michaelsen, L., Davidson, N., & Howell Major, C. (2014). Team-based learning practices and principles in comparison with cooperative learning and problem-based learning. Journal on Excellence in College Teaching, 25(3&4), 57-84.

Roberson, B., & Franchini, B. (2014). Effective task design for the TBL classroom. Journal on Excellence in College Teaching, 2J(3&4), 275-302.

Sisk, R. J. (2011) Team-based learning: systematic research review. Journal of Nursing Education, 50(12), 665-9. doi: 10.3928/01484834-20111017-01.

Smith, G. A. (2008). First-day questions for the learner-centered classroom. The National Teaching and Learning Forum, 17(5), 1-4.

Team-Based Learning Collaborative, (2015).

Watts, M., & Schaur, G. (2011). Teaching and assessment methods in undergraduate economics: a fourth national quinquennial survey. The Journal of Economic Education, 42(3), 294-309.

(1) Michaelsen et al. (2014) provide an excellent discussion of the differences between cooperative learning, collaborative learning, problem-based learning and team-based learning.

(2) The Appendix contains an example of language that could be put in a syllabus to explain TBL to students.

(3) It should be noted that Hettler's 2006 results were from the first semester in which TBL was implemented by the instructor. Given the Teaming curve' associated with TBL, it is possible that issues with implementation may have reduced the effectiveness of the pedagogy.

(4) I should note that many of those questions are also on a knowledge survey that students take the first week of the semester; that gives me and them some indication of how much review they will need to do.

(5) In the TBL community, these are more often called 'RATs', short for Readiness Assurance Test.

(6) IF-AT forms are available from Epstein Educational Enterprises (

(7) You can also get IF-AT forms with four answer choices.

(8) To ensure students complete these pre-class assignments, there is a quiz on the learning management system with questions that can be easily answered from the assignment; students can take the quiz as many times as they want to get full credit.

(9) I give teams a small number of points for their worksheets, based on the completeness of their explanations; however, many TBL instructors do not give grades or credit for team applications.

(10) I also point out to them that, usually, both X and Y are assumptions people might have for different reasons, like political beliefs, which is why I am constantly telling them all to aware of their own biases.

(11) I set the weights so that 25% of the final grade is based on team activities (that's 18% from the team RAs and 7% from the team applications). The other 75% of the grade comes from the individual RAs (10%), individual participation based on clicker responses and pre-class homeworks (10%), two in-class exams (20%), and two writing projects (15 and 20%). Thus, 55% of a student's grade is based on summative assessments ((he exams and writing projects).

(12) The questions are largely adapted from a survey that San Diego State University Instructional Technology Services asks all clicker-using faculty to give.

(13) I omit responses for Fall 2010 because that was both the first semester I taught the class and the first semester I used TBL, and I made numerous adjustments to the course between the Fall 2010 and Spring 2011 semesters. The course overall has largely remained unchanged since Spring 2011.

(14) It should be noted that this would be a useful exercise for anyone teaching a 'flipped' class.

(15) I measure 'ability' by asking the students if they took the lower-division statistics course more than once and if they have ever tutored for economics or statistics.

Jennifer Imazeki [1]

Published online: 10 September 2015

[mail] Jennifer Imazeki

[1] Department of Economics, San Diego State University, 5500 Campanile Drive, MC4485, San Diego, CA 92182-4485, USA
Table 1 Student responses about TBL

                                               Fall 2012   Spring 2012
                                               n = 39      n = 55

The team-based approach    Agree/strongly      87%         89%
  makes me mote likely       agree
  to attend class.         Disagree/strongly   3%          4%
The team-based approach    Agree/strongly      85          91
  helps me to feel more      agree
  involved in class.       Disagree/strongly   5           2
The team-based approach    Agree/strongly      90          87
  makes the class feel       agree
  smaller to me (less      Disagree/strongly   5           4
  crowded, more              disagree
The team-based approach    Agree/strongly      74          75
  makes it more likely       agree
  for me to respond to     Disagree/strongly   8           9
  a question from the        disagree
In the future, I would     Agree/strongly      67          60
  select a course            agree
  section which uses the   Disagree/strongly   15          13
  team-based approach        disagree
  over another section
  of the same course
  which does not use
  this approach.
I understand why my        Agree/strongly      92          89
  professor is using         agree
  Team-Based Learning      Disagree/strongly   0           6
  in this course             disagree
My professor asks team     Agree/strongly      92          91
  application questions      agree
  which are important      Disagree/strongly   3           6
  to my learning             disagree
Working on the team        Agree/strongly      90          80
  applications allowed       agree
  me to learn about my     Disagree/strongly   3           8
  own strengths and          disagree
  weaknesses as a team
Compared to traditional    Agree/strongly      76          76
  lectures, I feel I         agree
  gained a deeper          Disagree/strongly   8           12
  understanding of the       disagree
  material by working
  with a team on the

                                               Fall 2011   Spring 2011
                                               n = 59      n = 123

The team-based approach    Agree/strongly      88 %        90%
  makes me mote likely       agree
  to attend class.         Disagree/strongly   6%          1 %
The team-based approach    Agree/strongly      88          93
  helps me to feel more      agree
  involved in class.       Disagree/strongly   7           2
The team-based approach    Agree/strongly      80          89
  makes the class feel       agree
  smaller to me (less      Disagree/strongly   8           3
  crowded, more              disagree
The team-based approach    Agree/strongly      80          80
  makes it more likely       agree
  for me to respond to     Disagree/strongly   10          3
  a question from the        disagree
In the future, I would     Agree/strongly      64          80
  select a course            agree
  section which uses the   Disagree/strongly   14          4
  team-based approach        disagree
  over another section
  of the same course
  which does not use
  this approach.
I understand why my        Agree/strongly      88          97
  professor is using         agree
  Team-Based Learning      Disagree/strongly   3           2
  in this course             disagree
My professor asks team     Agree/strongly      92          94
  application questions      agree
  which are important      Disagree/strongly   4           1
  to my learning             disagree
Working on the team        Agree/strongly      90          93
  applications allowed       agree
  me to learn about my     Disagree/strongly   8           2
  own strengths and          disagree
  weaknesses as a team
Compared to traditional    Agree/strongly      78          87
  lectures, I feel I         agree
  gained a deeper          Disagree/strongly   14          4
  understanding of the       disagree
  material by working
  with a team on the
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Author:Imazeki, Jennifer
Publication:International Advances in Economic Research
Article Type:Report
Geographic Code:1USA
Date:Nov 1, 2015
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