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Record W4234705573 · doi:10.2979/teachlearninqu.1.2.35

The Scholarship of Teaching and Learning in an Age of Accountability: Building Bridges

2013· article· en· W4234705573 on OpenAlexaff
Pat Hutchings, Paola Borin, Linda Keesing-Styles, Lynn Martin, Renee Michael, Lauren Scharff, Scott Simkins, Ahmed Ismail

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsMcMaster UniversityToronto Metropolitan University
Fundersnot available
KeywordsAccountabilityScholarshipHigher educationMathematics educationScholarship of Teaching and LearningPedagogySociologyFaculty developmentTeaching methodEngineering ethicsPsychologyProfessional developmentPolitical scienceTeaching and learning centerEngineeringLaw

Abstract

fetched live from OpenAlex

In recent years, as pressures for accountability have increased in higher education, some members of the Scholarship of Teaching and Learning (SoTL) community may worry that the inquiry-based, improvement-focused practices they advocate could be put at risk by easy-to-administer, one-size-fits-all forms of assessment, quality assurance, and administrative control. But while acknowledging both real and perceived tensions between these two movements, we also examine some of the ways and settings in which they are converging, featuring a number of international examples in which external quality and assessment mandates have been employed to support SoTL-like work. We look, too, at the roles that scholars of teaching and learning can play as mediators and brokers between the two movements, helping to translate accountability requirements into opportunities for improvement. In short we argue that these two movements present opportunities for each other. SoTL can contribute to what is, or should be, the central goal of accountability: ensuring and improving the quality of student learning. The accountability movement, for its part, can provide a new context for integrating and valuing SoTL as a force for positive change on campuses and beyond. Taken together, the two approaches can make meaningful contributions to higher learning today. The paper concludes with recommendations to the SoTL community for building bridges between the two movements.

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.

How this classification was reachedexpand

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)0.079
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.009
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 head0.132
GPT teacher head0.448
Teacher spread0.315 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractyes

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