Motivation to Learn via Computer Conferencing: Exploring How Task-Specific Motivation and CC Expectations are Related to Student Acceptance of Learning via CC
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".