Deviating From the Traditional Instructional Tools: Integrating Twitter in a Sociology of Deviance Course | S’éloigner des outils pédagogiques traditionnels : intégrer Twitter dans un cours sur la sociologie de la deviance
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
As the use of social media in post-secondary education expands, so does the research literature examining its effectiveness in engaging students. Studies have examined the use of Twitter as an assessment and engagement tool, and since this is a broad and growing research area, better understanding whether Twitter can promote these outcomes in an upper-level university course is valuable. This paper explores these themes based on a student survey (N=37) conducted in a Sociology Deviance course. It also reviews how students responded to the use of Twitter as a “community-classroom” engagement and assessment tool. Findings reveal that Twitter did contribute to some students’ sense of community. We offer suggestions for how instructors can successfully integrate Twitter activities into their course assessment to make them more engaging and to improve connectedness.L’utilisation des médias sociaux dans l’éducation postsecondaire prend de l’ampleur, entraînant l’augmentation de la documentation de recherche qui examine leur efficacité à motiver les élèves. Des études se sont penchées sur l’utilisation de Twitter comme outil d’évaluation et de participation. Comme il s’agit d’un domaine de recherche vaste et en croissance, il est important de mieux comprendre si Twitter peut favoriser ces résultats dans le cadre d’un cours universitaire de haut niveau. Cet article explore ces thèmes en s’appuyant sur un sondage réalisé auprès des étudiants (N=37) dans un cours de sociologie de la déviance. Il examine également comment les étudiants ont réagi à l’usage de Twitter comme outil de participation à une « classe-collectivité » et comme outil d’évaluation. Les conclusions révèlent que Twitter a contribué au sentiment d’appartenance à la collectivité de certains étudiants. Nous offrons des suggestions sur la façon dont les instructeurs peuvent intégrer avec succès des activités liées à Twitter dans leurs évaluations de cours afin de rendre ceux-ci plus motivants et d’améliorer la connectivité.
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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 | 0.002 |
| 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 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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