Improving critical thinking using web based argument mapping exercises with automated feedback
Why this work is in the frame
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Bibliographic record
Abstract
<span>In this paper we describe a simple software system that allows students to practise their critical thinking skills by constructing argument maps of natural language arguments. As the students construct their maps of an argument, the system provides automatic, real time feedback on their progress. We outline the background and theoretical framework that led to the development of the system and then give a detailed example of how a student would work through a particular argument mapping exercise using the software. We then describe how the system was used in a single semester undergraduate critical thinking course. We evaluated the course using a standardised critical thinking test and measured an improvement in critical thinking skills of 0.45 standard deviations from pre-test to post-test; a modest, but encouraging result for a single semester course. We compare these results to those obtained in a number of other critical thinking courses, incorporating a variety of teaching methods. We conclude the paper with some comments on the limitations of the system and ways in which it might be improved and extended.</span>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it