Community College Anatomy and Physiology Education Research (CAPER): Can Educational Research Drive Pedagogical Change?
Bibliographic record
Abstract
Human Anatomy and Physiology (A&P) is a required course for many community college (CC) students aiming for careers in health sciences. CC instructors face heavy workloads and few opportunities for professional development. Students face heightened academic and non‐academic challenges which can lead to debilitating anxiety. Traditional instructor‐centered teaching strategies predominate. The result is predictable: an environment where there is high instructor burnout and high student attrition rates. Transitioning to more evidence‐based instructional practices (EBIPs) has been shown to promote student learning. Despite the potential positive impact of this change on CC institutions and their students, widespread adoption of student‐centered strategies remains elusive. Evidence shows change requires more than reading journal articles or attending workshops. The Community College Anatomy and Physiology Education Research (CAPER) project takes an evidence‐based teaching approach to fostering transformation. In each year of the two year project, six CC A&P instructors (two from each of three schools) combine a professional development course with the design, implementation, and dissemination of a small‐scale educational research project investigating the impact of a student‐centered teaching strategy on learning and anxiety. We are currently in year 1, and six CC instructors have completed the professional development course and project proposals and are implementing their research projects. Participants often assumed that they were required to develop a novel and innovative project using gold‐standard experimental designs and quantitative analyses, and were skeptical about the utility of qualitative measures and experimental designs not involving control groups. In addition to providing access to external experts in qualitative and quantitative analysis, we emphasized that participants could make a contribution to the field by following one of two approaches. First, they could look at less well‐understood impacts of an established EBIP, such as science anxiety, or attempt to validate the effectiveness of an EBIP in on the community college student population. Alternatively, they could investigate a newly developed teaching practice using well‐established data collection methods with the intent of possibly identifying a new EBIP. While an important goal of CAPER is to produce publishable data regarding the efficacy of EBIPs in CCs, an equally important goal is pedagogical transformation. Thus, softening the rigor of experimental design for our target audience of community college instructors may actually promote scholarly teaching. Data that has a larger noise‐signal ratio than what would be acceptable in traditional research domains may still have a place in educational research, by providing an achievable target for potential novice educational researchers. Support or Funding Information This grant is supported by NSF grant #1829157. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.133 | 0.256 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".