Applying Felten's Principles of SoTL Practice to Transform Informal Learning Spaces for Indigenous Students
Bibliographic record
Abstract
Felton’s (2013) Principles of good practice in SoTL were applied to a study with Indigenous students’ learning experiences in informal settings. The principles: Inquiry focused on student learning (P1); Grounded in context (P2); Methodologically sound (P3); Conducted in partnership with students (P4); and Going public (P5). P1: As a collaborative team of academic librarians and educators, we were curious “how do Indigenous students learn in informal spaces?” We set out to explore Indigenous undergraduate students’ experiences, preferences, and approaches to learning in informal spaces. P2: This SoTL inquiry was conducted at the University of Calgary, a research-intensive Canadian university, with a population of approximately 900 self-identified Indigenous students (2.7 % of the student population). Situated within our University’s Indigenous Strategy this commitment to transformation supports enhanced understanding of Indigenous students’ learning (Brown, 2019). P3: Methodologically sound: Participatory photography, including Photovoice and photo-elicitation methods, was selected as a research framework to explore with Indigenous students (Castleden et. al., 2008). As researchers and co-researchers, we learned together. Photovoice provided students the opportunity to actively engage by taking photos of spaces, documenting and reflecting on their learning and experiences. Photo-elicitation expanded on this with additional participants reflecting on how they learn in various spaces depicted in photos. P4: We intentionally recruited Indigenous students to be co-researchers and made this explicit (Cullinane & O'Sullivan, 2020). As partners we generated the research question, identified how we would work together, and planned the dissemination of our work. P5: The authors have presented at local, national, and international conferences, published two proceedings, and the open-access university platform. An e-book will be written and published by the researchers and student co-researchers. With the knowledge gained in this SoTL research we have data to implement the process of change at our university which advances the goals of the Indigenous strategy.
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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 | 0.057 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.049 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".