MétaCan
Menu
Back to cohort
Record W3082745529 · doi:10.24059/olj.v24i3.2151

Blended Learning in STEM and Non-STEM Courses: How do Student Performance and Perceptions Compare?

2020· article· en· W3082745529 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

VenueOnline Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsYork University
Fundersnot available
KeywordsBlended learningPerceptionMathematics educationStem cellPsychologyMedical educationMedicineEducational technologyBiology

Abstract

fetched live from OpenAlex

Examined in this study is the question of whether students in STEM courses perform better and have more positive perceptions than students in non-STEM courses, when both are offered in the blended format. As part of a blended learning initiative, 6 STEM and 8 non-STEM university courses were redesigned using the blended format. Students (n = 318) were surveyed on perceptions of their blended experience and courses grades were compared. Results indicated that STEM students performed significantly higher than non-STEM students; however, STEM students did not perceive their courses as positively as non-STEM students. The conclusion was that focusing blended learning course redesign in STEM fields in higher education may be advantageous, although more research is needed to confirm the findings and to investigate why student perceptions were relatively low for STEM students.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.320
Teacher spread0.297 · 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