Case study analysis of reflective essays by chemistry post-secondary students within a lab-based community service learning water project
Bibliographic record
Abstract
Intentional reflection is a key component of Community Service Learning (CSL) as it guides students to integrate knowledge of theory with experience in practice. A semester-long chemistry curriculum with an integrated CSL intervention was implemented in a Canadian university to investigate how reflection in the laboratory setting enhances post-secondary students’ ( n = 14) conscious awareness of their learning and their attitudes toward having reflection as part of a course. In typical chemistry laboratories, students follow cookbook recipes from the lab manual and are assessed through written lab reports. These lab reports are similar to a technical report with scientific writing where the design aims to communicate scientific information to other scientists. A case study was conducted with reflective essays, focus group interviews, and student observation to analyze qualitatively how students' attitudes changed in their learning over the course of the CSL activity and how they engaged in this type of reflection. The expected audience that may be interested in this study are those involved in teaching chemistry in higher education and those that are interested in Community Service Learning and experiential learning. The results demonstrate that science students are able to articulate their academic growth, civic engagement, and personal growth through reflective pieces. Furthermore, the reflective pieces support self-regulated learning with a positive engagement and attitude over time. The results support the integration of reflective pieces in laboratory settings.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".