Uses and gratifications factors for social media use in teaching: Instructors’ perspectives
Bibliographic record
Abstract
This research was motivated by an interest in understanding how social media are applied in teaching in higher education. Data were collected using an online questionnaire, completed by 333 instructors in higher education, that asked about general social media use and specific use in teaching. Education and learning theories suggest three potential reasons for instructors to use social media in their teaching: (1) exposing students to practices, (2) extending the range of the learning environment, and (3) promoting learning through social interaction and collaboration. Answers to open-ended questions about how social media were used in teaching, and results of a factor analysis of coded results, revealed six distinct factors that align with these reasons for use: (1) facilitating student engagement, (2) instructor’s organization for teaching, (3) engagement with outside resources, (4) enhancing student attention to content, (5) building communities of practice, and (6) resource discovery. These factors accord with a Uses and Gratifications perspective that depicts adopters as active media users choosing and shaping media use to meet their own needs. Results provide a more comprehensive picture of social media use than found in previous work, encompassing not only the array of media used but also the range of purposes associated with use of social media in contemporary teaching initiatives. Keywords: Adoption of technology, educational technology, higher education, instructor experiences, social media, teaching, Uses and Gratifications
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How this classification was reachedexpand
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 | 0.000 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".