Slack: Adopting Social-Networking Platforms for Active Learning
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
ABSTRACT Online learning in postsecondary institutions has increased dramatically across the United States and Canada. Although research demonstrates the benefits of online learning for student success, instructors face challenges in facilitating communication, delivering course content, and navigating outdated and cumbersome technologies. The authors examine the use of a free third-party platform called Slack as a tool to facilitate better communication among students and faculty, enable the delivery of diverse and dynamic course content, and reach students in an online course that supports both independent and collaborative learning. The authors present a case study of Slack’s use in an online second-year environmental politics course taught at a large Canadian public university. There is a significant and growing literature on how to best engage students in online learning, including active and social learning models as promising approaches to digital teaching. The authors argue that using collaborative social technologies such as Slack—which both replicates and integrates the online and social-media environments that students already inhabit—can assist faculty in meeting their pedagogical goals online. The article documents the instructors’ experience in managing discussion and involving students in their online learning through active learning exercises. Best practices are examined.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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