Implementing Team-Based Learning to Strengthen Communication Skills among Undergraduate Kinesiology Students
Why this work is in the frame
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Bibliographic record
Abstract
Kinesiology is the study of human movement and grounded in learning about physiological and psychological mechanisms of physical activity, exercise, and sport. Despite the educational focus promoting an active lifestyle, teaching strategies often ignore the hands-on and interactive components of the field, in favour of a traditional passive teaching style (Bulger, Housner, & Lee, 2008). This teaching approach can be problematic as most undergraduate Kinesiology students will either pursue an academic career path, or enter a health care field (e.g., kinesiologist, medical doctor, physical therapist, etc.) Whichever path a student chooses, it will require strong communication skills, whether it be sharing research ideas or working with a patient. To improve these skills, instructors can use an interactive classroom. A recent study evaluating communication competence in undergraduate nursing students found overall improvements in communication efficacy and communication ability when implementing team-based learning (TBL; Cho & Kweon, 2017). Therefore, a larger focus in Kinesiology should be on promoting effective communication skills so that students are more prepared when they graduate. By incorporating TBL into Kinesiology courses, students can become more interactive in the classroom and build upon fundamental skills that are paramount in academic and health care settings (Meeuswen, King, & Pederson, 2005).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it