Promoting Active Learning when Teaching Introductory Statistics and Probability Using a Portfolio Curriculum Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of a portfolio curriculum approach, when teaching a university introductory statistics and probability course to engineering students, is developed and evaluated. The portfolio curriculum approach, so called, as the students need to keep extensive records both as hard copies and digitally of reading materials, interactions with faculty, interactions with other students and work they have completed on their own, is designed to encourage active learning, mainly in the areas of cooperation and collaboration. In order to investigate the effectiveness of the portfolio curriculum, a controlled experiment applying a pre-test-post-test control group design is conducted. Two tests are conducted, one before the commencement of the course (pre-test) and one after the completion of the course (post-test). The effectiveness is evaluated by comparing within-subject post-test and pre-test scores and by comparing the scores between subjects in the experimental group, i.e., those who learned using the portfolio curriculum approach and subjects in the control group, i.e., those who learned using a traditional method of teaching. In addition to analysis of the controlled experiment, a Survey of Attitudes Toward Statistics (SATS) was completed on the first and last day of the semester by the participants so as to give a measure of student confidence, understanding, liking, and difficulty of the portfolio curriculum approach as opposed to using a traditional method of teaching and learning. The findings of these investigations are reported and discussed, as are the merits and problems encountered regarding the methodology and student attitudes regarding the portfolio curriculum approach.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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