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Record W4393071056 · doi:10.3389/feduc.2024.1366215

Formative assessment in higher education: an exploratory study within programs for professionals in education

2024· article· en· W4393071056 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

VenueFrontiers in Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsSt. Thomas University
Fundersnot available
KeywordsFormative assessmentExploratory researchHigher educationComputer scienceEngineering managementMedical educationKnowledge managementMathematics educationEngineeringPsychologyPolitical scienceSociologyMedicine

Abstract

fetched live from OpenAlex

This study explores how prospective professionals in higher education can learn about and apply formative assessment methods relevant to their future educational workplaces. In the academic year 2022–23, 156 pre-service teachers, social workers, and heads of social services took part in a three-stage mixed-method study on university learning experiences involving formative assessment practices. They were exposed to self-, peer-, and group-assessment strategies. Data collected after each stage revealed participants’ perspectives on each method. Findings show that students who engaged in formative assessment comprehended assessment complexity and were motivated to use diverse assessment forms. Formative assessment proves effective for both evaluation and development, supporting higher education students in honing assessment competencies for future professional roles in educational and social sectors.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.437
Teacher spread0.385 · 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