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Record W1920149733

Classroom Motivational Climate in Online and Face-to-Face Undergraduate Courses: The Interplay of Gender and Course Format.

2015· article· en· W1920149733 on OpenAlexvenueno aff
Yan Yang, Yoon Jung Cho, Angela Watson

Bibliographic record

VenueInternational journal of e-learning & distance education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPerceptionSense of communityFace (sociological concept)Face-to-faceVariety (cybernetics)Community collegeMathematics educationClassroom climateOnline courseSocial psychologyMedical educationComputer science
DOInot available

Abstract

fetched live from OpenAlex

In this study, the role of gender and course format in college students’ perceptions of classroom motivational climate (i.e., sense of classroom community and perceived classroom goal structure) was examined. Participants were 722 college students from a variety of majors at a comprehensive Midwest American university. Female students felt a stronger sense of community and perceived lower levels of performance-approach goal structure in online classes than their male counterparts experienced. Male students perceived the face-to-face classes as being more communal and less performance-approach oriented than the females did. Further, both male and female students perceived a stronger mastery-approach classroom goal structure in face-to-face than in online classes. These findings suggest that instructors should consider the roles of gender and course format in designing instruction and creating motivational learning environments.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.369
Teacher spread0.347 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2015
Admission routes1
Has abstractyes

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