A Path Analysis Of The Concepts In Moore’s Theory Of Transactional Distance In A Videoconferencing Learning Environment
Bibliographic record
Abstract
The lack of empirical testing of theories in past studies in distance education has resulted in a fragile theoretical basis of this field. Investigating 121 learners’ experiences with videoconferencing, this study used path analysis to examine the postulates of Moore’s Theory of Transactional Distance. A major focus of the study was estimating the effects of the dimensions of dialogue, structure, learner autonomy, and transactional distance—the constituent concepts of Moore’s theory—on learning outcomes in such a learning environment. In-class discussion, one of the dimensions of dialogue, was found to contribute positively, directly, and indirectly to learning outcomes, whereas transactional distance between instructors and learners was inversely related to learning outcomes. None of the dimensions of structure and learner autonomy was found to have significant effects on learning outcomes. The data suggested that when learning outcomes were assessed only in terms of the student’s perception of how much he or she has learned, the relationships among the concepts in the transactional distance theory were only partly supported. Dans les etudes anterieures menees en education a distance, le peu de verifications empiriques des theories nous a legue des fondements theoriques faibles. Cette etude, qui analyse les experiences d’apprentissage par videoconference de cent vingt et un apprenants, a adopte une analyse causale des postulats de la theorie de Moore sur la distance transactionnelle. L’etude s’est attachee a evaluer les effets du dialogue, de la structure, de l’autonomie de l’apprenant et de la distance transactionnelle--concepts constituants de la theorie de Moore--sur les resultats d’apprentissage dans un tel environnement d’apprentissage. La discussion en classe, qui est l’un des aspects du dialogue, s’est revelee contribuer de maniere positive, directement et indirectement, aux resultats d’apprentissage, alors que la distance transactionnelle entre formateurs et apprenants etait en rapport inverse avec les resultats d’apprentissage. Il est apparu que ni la structure ni l’autonomie de l’apprenant n’entrainaient d’effets significatifs sur les resultats d’apprentissage. Les donnees laissent entendre que si l’on evalue les resultats d’apprentissage en s’appuyant seulement sur la perception du « combien » les etudiants ont appris, les correlations entre les concepts de la theorie de la distance transactionnelle ne sont que partiellement corroborees.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".