“The Chocolate Conundrum” and Other Easy Active Learning Additions to Traditional Undergraduate Science Courses Designed to Teach for Critical Thinking
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The need for science students to acquire critical thinking skills during their undergraduate degree is clear, but how to ensure that they indeed develop these skills is still open for discussion. Here, we show that straightforward active learning components designed to teach for critical thinking can be added to a standard second-year analytical chemistry course and that they cause an increase in the critical thinking skills of the students. We analyze our data both quantitatively (using the Danczak-Overton-Thompson (DOT) test) and qualitatively (using student feedback). The course components designed to teach for critical thinking are an open-ended group exercise called “The Chocolate Conundrum”, self-reflection exercises for students to self-assess their critical thinking skills, and a group project designed to enable students to learn to critically review a peer-reviewed journal paper. By linking these components to established teaching theories and synthesizing current knowledge in the field into practical exercises that can be added to current science undergraduate courses, our work highlights how simple and innovative approaches for fostering critical thinking can have impactful outcomes. Students report greatly increased confidence in their critical thinking skills at the end of the course. We hope that our research shows the value of adding simple active learning components to current chemistry and science courses to explicitly teach for critical thinking.
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How this classification was reachedexpand
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".