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Record W2078426247 · doi:10.3200/joeb.83.3.153-158

Relationship Between Use of Online Support Materials and Student Performance in an Introductory Finance Course

2008· article· en· W2078426247 on OpenAlex
Ernest N. Biktimirov, Kenneth J. Klassen

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

VenueJournal of Education for Business · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsBrock University
Fundersnot available
KeywordsConsistency (knowledge bases)Computer scienceClass (philosophy)Course (navigation)Online courseMathematics educationWorld Wide WebMultimediaPsychologyArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

The authors examined the relationship between student online activity, including access to specific course materials, and performance in a traditional face-to-face introductory finance course that a class Web site supported. The authors used 6 measures: (a) total hits, (b) hit consistency, (c) number of unique files that the students accessed, (d) accesses to homework solutions, (e) accesses to PowerPoint slides, and (f) accesses to exam solutions. Results indicated that access to homework solutions and, to lesser extent, hit consistency, were both positively related to student performance. In addition, results showed that access to specific files, rather than access to online course materials in general, was associated with better student performance.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.086
GPT teacher head0.398
Teacher spread0.313 · 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