Source: Action in Teacher Education, 43:1, 4-19
(Reviewed by the Portal Team)
One purpose of this study was to examine the impact of Team-based learning (TBL) readiness assurance stage on pre-service teachers’ pedagogy learning in an Educational Technology course.
In the following sessions, the authors summarized three factors that deemed important from the socio-cognitive conflict theory and analyzed how those factors affected pre-service teachers or students’ learning.
The authors’ review of the literature indicated that three interpersonal dispositions could confound students’ learning at the readiness assurance stage of TBL: students’ accountability, social learning style, and conformity.
In turn, these dispositions could possibly cut the benefits of TBL according to the socio-cognitive conflict theory.
In addition, they were not clear whether these impacts differed between online and on-campus TBL.
Therefore, the purposes of this study were first to identify whether the online readiness assurance stage of TBL had the same effect on individual students’ learning as its on-campus mode, and second, to explore the potential impact of students’ accountability, social learning style, and conformity.
Specifically, they were interested in the following questions.
RQ1: Did the online readiness assurance stage work better for students’ learning when compared to its on-campus counterpart?
RQ2: How did students’ accountability, social learning style, and conformity affect their learning at the readiness assurance stage of online and on-campus TBL differently?
RQ3: How did the high- and low- performance students behave differently at the readiness assurance stage of online TBL?
A mixed-method approach called the Convergent Parallel Design was used in this study (Creswell, 2014).
In this design, the authors conducted quantitative and qualitative data collection and analysis simultaneously.
Qualitative results were used to compare potential discrepancy with or supplement the quantitative findings.
Quantitative data in the study were from surveys and tests that focused on students’ achievement and perception.
Qualitative data were students’ conversations in online TBL.
The triangulation of these results would help to understand students’ learning in TBL from different aspects (Creswell & Clark, 2011).
Participants and Context of Study
This study was conducted in two classes of an undergraduate education course in the fall of 2017.
The course was required for all undergraduate pre-service teachers at the university.
The purpose was to improve students’ knowledge and skills in integrating technologies with sound pedagogies in K-12 classrooms.
It was offered in a blended mode, meaning students took class sessions in online, flipped, or on-campus modes depending on the topics and learning objectives.
Although two classes were taught by different instructors, they followed the same syllabus and used the same materials.
The authors used a convenience sampling method to recruit participants from the two classes.
A total of 56 out of 61 students consented and participated in the study.
Prior to this study, teams with 4–6 members had been formed for other course projects in both classes.
In this study, teams in each class were randomly assigned to the experimental group and control group.
Students in the experimental group were assigned with online TBL while those in the control group were assigned with traditional on-campus TBL.
Before TBL, the same reading materials were posted on the course sites for the two classes.
Students were required to read and prepare for the upcoming TBL sessions.
Once students greeted each other online, they took the individual readiness assurance test (iRAT) and team readiness assurance test (tRAT) using the text/audio/video communication and application sharing features available in the system.
On-campus TBL teams went through the same process as the online TBL students.
The only difference was that the tests and team discussions were conducted in a physical classroom instead of online.
The readiness assurance stage in the online and on-campus modes lasted for about forty-five minutes respectively.
An online survey was sent to students before they started TBL asking for their demographics and social learning styles.
An online post-survey was delivered inquiring about students’ learning experiences at the end of TBL.
Two tests measured students’ cognitive knowledge.
In each test, four multiple-choice questions measured students’ lower-order thinking (LOT) and the other four measured their higher-order thinking (HOT).
The two tests were aligned to ensure that each pair measured the same topic and cognitive level.
The first test was delivered as iRAT and tRAT.
The other test was delivered after the readiness assurance stage as a posttest. V
Results and discussion
Results of this study confirmed the benefit of the TBL readiness assurance stage on improving pre-service teachers’ understanding and application of pedagogy.
Online TBL was as equally effective as its on-campus counterpart.
Therefore, the authors suggest the inclusion of this stage in Education courses, especially online courses, for several reasons.
First, it has a great potential to not only solve students’ preparation issue but also improve their conceptual understanding and application of pedagogy.
This is critical for students’ learning at a higher cognitive level according to the rationale of Bloom’s taxonomy (Anderson & Krathwohl, 2001).
Second, students meet online and discuss questions in real time with webcam enabled in the TBL readiness assurance stage.
When they observed the active participation of the course instructor and their fellow students, their learning satisfaction increased and they had a higher success rate in online learning (Richardson & Swan, 2003).
Third, the online TBL readiness assurance activities set a model of quality interaction between students and teachers.
This experience will help to shape pre-service teachers’ perception of online teaching.
Based on the results of the study, the authors can illustrate the profile of successful students in the readiness assurance stage of online TBL.
They are accountable for their own learning and don’t easily conform to others in team discussions.
This echoes the findings from studies of socio-cognitive conflict theory, upon which TBL was built.
They think it is important to share this evidence with students explicitly and let them know that they will learn better if they express their disagreement and strive for clarifications during team discussions.
Researchers in prior literature were worried about the negative impact of conformity on students’ higher cognitive-level learning, but the authors did not find such an impact in their study.
Instead, the conformity was found to have a negative and significant impact on online students’ lower cognitive-level learning.
What may have happened in online TBL discussions was that students who easily conformed did not seek answers further or ask questions for clarification.
According to the socio-cognitive conflict theory, their knowledge structure was kept intact, and learning did not take place.
However, they did not find the same significant impact on the learning outcome of on-campus TBL students.
Both the on-campus and online students had been randomly assigned to teams and worked on group projects prior to this study.
The only difference between them was the environment to conduct the TBL.
Williams, Duray, and Reddy (2016) identified the online environment and anonymity as the reasons for conformity development among participants.
In their study, the authors used a synchronous communication tool and students saw each other via webcams.
Assuming that anonymity was greatly reduced, they speculated that the online environment could be a reason for the reinforcement of conformity.
Although students were trained and practiced with the technologies ahead of time, their unfamiliarity and comfort level with online synchronous communication could possibly prevent their cognitive confrontations in online discussions.
To address this negative impact, the authors suggest that an online TBL practice session may be conducted before formal TBL sessions in order to help students to settle in the online group development.
The qualitative evidence showed that voluntary leadership in tRAT did not guarantee the development of positive group dynamics in some online teams.
Therefore, the authors propose a role intervention.
Fink (2004) did not recommend using role assignment, thinking it would prohibit the organic development of students’ accountability.
However, Dasgupta (2011) suggested the Stereotype Inoculation Model for peer learning, where students’ exposure to several high performers in their own teams helped them to learn better.
Zha and Ottendorfer (2011) found that the assignment of the leadership role boosted online undergraduate students’ learning regardless of their prior course GPAs.
Based on the results of these studies, the authors propose that a leadership role should be assigned to a couple of students in each online team.
Sufficient training would be needed to teach them how to develop positive group dynamics.
Thereafter, they may work with other high performers in a team to promote a positive and inclusive group dynamic.
Anderson, L. W., & Krathwohl, D. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York, NY: Longman.
Creswell, J. W. (2014). A concise introduction to mixed methods research. Thousand Oaks, CA: Sage.
Creswell, J. W., & Clark, V. L. P. (2011). Designing and conducting mixed methods research. Thousand Oaks, CA: Sage.
Dasgupta, N. (2011). Ingroup experts and peers as social vaccines who inoculate the self-concept: The stereotype inoculation model. Psychological Inquiry, 22(4), 231–246.
Fink, L. D. (2004). Beyond small groups: Harnessing the extraordinary power of learning teams. In L. K. Michaelsen, A. B. Knight, & L. D. Fink (Eds.), Team
Richardson, J., & Swan, K. (2003). An examination of social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Network, 7(1), 68–88.
Williams, E. A., Duray, R., & Reddy, V. (2016). Teamwork orientation, group cohesiveness, and student learning: A study of the use of teams in online distance education. Journal of Management Education, 30(4), 592–616.
Zha, S., & Ottendorfer, C. (2011). Effects of peer-led online asynchronous discussion on undergraduate students’ cognitive achievement. American Journal of Distance Education, 25(4), 238–253.