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Record W3179047230 · doi:10.1080/07294360.2021.1945543

Student work: a re-conceptualization based on prior research on student workload and Newtonian concepts around physical work

2021· article· en· W3179047230 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 · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWorkloadConceptualizationWork (physics)Mathematics educationPsychologyStudent engagementComputer scienceEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this article, we propose a new model of student workload. We conducted an extensive literature review of student workload, its impact on students’ lives, factors influencing student workload, objective and subjective measurements. The previous conceptualizations of student workload conflate student work and course workload, two related but distinct concepts. By synthesizing prior research and concepts from Newtonian physics such as work, force, and distance, we have discovered a model that better explains and differentiates the nature of and the various factors contributing to student work and load. We re-define student work as the product of student academic effort and their achievement in the course. In this model, student academic effort is generated to meet course demands in four domains (cognitive, physical, social, and psychological) with specific challenges and resources associated with each one. This new model will help us to better understand the student experience of academic work, effort, and the challenges students face so that we can make changes to enhance learning.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.513
Teacher spread0.402 · 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