Cognitive Presence in Online Learning: A Systematic Review of Empirical Research from 2000 to 2019
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.
Bibliographic record
Abstract
This systematic review synthesized research on cognitive presence– the process of collaborative knowledge construction–in online learning to identify trends from two decades (2000 to 2019) of scholarship. A total of 30 articles on cognitive presence were analyzed to gain deeper understanding of the current state of research and identify the gaps in literature. The distribution of publishing years, countries, instructional setting, disciplines, research methods, data collection and data analysis methods, research topics and cognitive presence phases were reviewed. The review shows that the majority of the studies were carried out in higher education in the United States and Canada within the field of education. More than half of the studies used quantitative research methods, of which discussion transcripts were the prominent method for data collection and content analysis was used the most to analyze data. Research focus of these studies was mainly on instructional strategies and learning outcomes in the online courses. Among instructional strategies, reflection on practice, case-based learning, inquiry-based learning, and peer facilitation were most researched strategies. For learning outcomes, levels of cognitive presence (triggering, exploration, integration, and resolution), critical thinking, and interaction were examined the most. In addition, the frequency of students' contributions to online discussion were categorized using the Practical Inquiry Model and revealed that the highest contributions fell within the exploration and integration phases with a small percentage in triggering and resolution phases of cognitive presence. These results provide insights for educators, researchers, and instructional designers into the cognitive presence research trends to improve the quality of online learning.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it