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Record W3012073698 · doi:10.20343/teachlearninqu.8.1.6

The 4M framework as analytic lens for SoTL’s impact: A study of seven scholars

2020· article· en· W3012073698 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsBrock University
Fundersnot available
KeywordsScholarship of Teaching and LearningMacroScholarshipSociologyInstitutionMacro levelThrough-the-lens meteringPedagogyMathematics educationPsychologyLens (geology)Teaching methodComputer sciencePolitical scienceSocial scienceTeaching and learning centerEngineering

Abstract

fetched live from OpenAlex

The Scholarship of Teaching and Learning (SoTL) encompasses research on postsecondary teaching and learning across all disciplines. Why do scholars engage in the study of teaching and learning? What supports and challenges do they encounter? What is the impact of SoTL? Using a micro-meso-macro-mega (4M) framework, I explore these questions in interviews with seven SoTL scholars from various disciplines in one institution. Primarily, this article provides a case study illustration of the use of the micro-meso-macro-mega framework to explore SoTL. In addition to exploring participants’ reflections vis-à-vis the four levels, I reflect on possible connections to motivation theory as a lens for themes arising from the participants’ accounts of supports and barriers and the impact of their SoTL work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.066
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.215
GPT teacher head0.503
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it