Student empowerment and development through note-taking in one-to-one sessions
Bibliographic record
Abstract
This study was prompted by a senior management request at the authors’ university to change record keeping practices. What followed was an exploration of the theoretical foundations that underpin the authors’ underlying philosophy on case notes as a means for advancing student empowerment. Findings revealed that through the application of reflective practice, case notes could enhance student empowerment and development. Without reflection, however, case notes were more likely to follow the medical model in which they were ‘norm referenced and deficit driven’ (Cheek and Rudge, 1994, p.42). Co-authored, cloud-based case notes had the power to embody the ‘person-centred, emancipatory values’ (Webster, 2023, p.2) espoused by ALDinHE and ICALLD partner organisations such as AALL. These case notes were found to have changed the dynamic between student and learning developer; students had greater agency both during and after the session to interpret, adapt, and reflect upon their experiences. The new practices enhanced inclusivity by emphasising a strengths-based approach and by reducing students’ cognitive and emotional barriers. The ALDcon25 workshop explored how expanded notions of accessibility, equity, and inclusivity could change practices in one-to-one (1-2-1) sessions. Drawing upon the theories of self-regulated learning (Chickering and Reisser, 1993; Zimmerman, 2015) and critical pedagogy (Freire, 2018) that inform the authors’ practices, the session shared key elements of literature review, survey results, and findings on case note practices. An interesting highlight was the intersections and disjunctions between theory and practice. Participants were encouraged to discuss best practices to enhance student empowerment during the session with a view to leave with tangible ideas to implement in their respective work.
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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 | 0.030 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".