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Record W2072716722 · doi:10.1080/07294360701805234

Doing course evaluation as if learning matters most

2008· article· en· W2072716722 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

VenueHigher Education Research & Development · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsRoyal Ottawa Mental Health Centre
FundersUmeå UniversitetKungliga Tekniska Högskolan
KeywordsConstructiveTask (project management)Course (navigation)Function (biology)Mathematics educationCourse evaluationComputer sciencePsychologyHigher educationSociologyManagementPolitical scienceEngineeringLawProcess (computing)Programming language

Abstract

fetched live from OpenAlex

This paper investigates barriers for using course evaluation as a tool for improving student learning, through the analysis of course evaluation practices at The Royal Institute of Technology (KTH), a technical university in Stockholm. Although there is a policy on development‐focused course evaluation at KTH, several stakeholders have expressed dissatisfaction with its poor results. Interviews were conducted with faculty and student representatives to investigate the perceived purpose and focus of evaluation and its current utilization. Results show that evaluation is teaching‐ and teacher‐focused. As course development is not in the foreground, evaluations merely have a fire alarm function. It is argued that course evaluation should be regarded as a component of constructive alignment, together with the intended learning outcomes, learning activities and assessment. Finally, the concept system alignment is proposed, extending constructive alignment to the institutional level. The evaluation task can generally be said to be: to describe what actually happens in that which seems to happen to tell why precisely this happens, and to state the possibilities for something else to happen. (Franke‐Wikberg & Lundgren, 1980 Franke‐Wikberg, S. and Lundgren, U. P. 1980. Att värdera utbildning Del 1, En introduktion till pedagogisk utvärdering, Stockholm: Wahlström & Widstrand. [Google Scholar], p. 148)

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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.200
GPT teacher head0.539
Teacher spread0.339 · 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