Students' Perceptions of Learner-Learner Interactions that Weaken a Sense of Community in an Online Learning Environment
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
Despite the growth of its popularity in recent years, online learning has demonstrated high dropout rates compared to dropout rates in traditional face-to-face courses. Prior research attributes attrition to the physical isolation of students from one another and the lack of interaction between and among them—factors which foster feelings of alienation, isolation, and disconnection. The goal of this research study was to more deeply understand the causes of such negative feelings, which may eventually lead students to drop out of online courses. More specifically, this study adopted a qualitative approach by interviewing six graduate students to further explore which specific learner-learner interactions weaken online students’ sense of community. Seven learner-learner, interactions were identified: the keener, lack of meaningful data, selective listening, lack of attribution, going off on tangents, editing notes, and cultural exclusion.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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