Achieving Critical Life Skills with Inquiry-Based Learning in Social Work Education: Self and Peer Assessment Reports
Bibliographic record
Abstract
This paper reflects the results from a 3-year quantitative study in higher education on inquiry-based learning (IBL). Utilizing primary data collection in a quasi-experimental survey, we examined the impact of IBL on six cohorts of undergraduate students. We aimed to answer our main research question: Can IBL be an effective pedagogy that helps students develop their key skills, through: (1) exploring how students assessed themselves and their peers on four skills; and (2) comparing student and peer assessments across social work courses utilizing IBL as pedagogy utilizing a social work course taught with traditional methods (non-IBL), and a nonsocial-work course using IBL. We analyzed the quantitative data applying bivariate analysis (paired and independent t-tests) with SPSS. We found that in social work and nonsocial-work courses using IBL as pedagogy, students and their peers identified an increase in the development of their key skills; peer-assessments were consistently higher than self-assessments. Our study reveals that IBL may offer an opportunity to provide authentic learning activities and assessments in social work education to support students’ development of four key skills required for success in higher education.
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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 | 0.014 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".