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Record W2155457729 · doi:10.2190/r4wg-88tj-c3vf-yqj0

Motivation to Learn via Computer Conferencing: Exploring How Task-Specific Motivation and CC Expectations are Related to Student Acceptance of Learning via CC

2002· article· en· W2155457729 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

VenueJournal of Educational Computing Research · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsSimon Fraser UniversityConcordia University
Fundersnot available
KeywordsPsychologyOperationalizationRelevance (law)Task (project management)Goal orientationAttractivenessMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

This study investigated the relationship between student motivation and student acceptance of learning via computer conferencing (CC). Student acceptance of CC was operationalized as frequency of contributing messages online, satisfaction with CC, grades, and effort on CC. Student motivation was conceptualized to include students' general motivational characteristics, such as goal orientation, as well as more contextual aspects, such as personal relevance of tasks. Students ( n = 167) in ten courses filled out questionnaires at the beginning and end of each course. Personal relevance of the tasks, task attractiveness, and students' beliefs concerning the relationship of CC to learning (outcome expectations) were the most important predictors of student satisfaction with CC. Learning orientation was correlated with grades ( n = 78) and self-reported effort on CC activities ( n = 167). To provide a sense of the contexts in which CC was used, interviews were conducted with instructors ( n = 8). Suggestions are made concerning the implementation of CC for 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)0.002
metaresearch head score (Gemma)0.003
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 score0.351
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.176
GPT teacher head0.414
Teacher spread0.238 · 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