Using the Artistic Pedagogical Technology of Photovoice to Promote Interaction in the Online Post-Secondary Classroom: The Students' Perspective.
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Bibliographic record
Abstract
This study explores the effect of the artistic pedagogical technology (APT) called photovoice (PV) on interaction in the online post-secondary classroom. More specifically, this paper focuses on students’ perspectives regarding the effect of PV on student to student and student to instructor interactions in online courses. Artistic pedagogical technologies are teaching strategies based on the arts (Perry & Edwards. 2010). APTs use music, poetry, drama, photography, crafts or other visual media as the basis of teaching activities. Photovoice is the purposeful use of selected visual images and affiliated refection questions as an online teaching strategy. Social Development Theory (Vygotsky, 1978) and Janzen’s Quantum Perspective of Learning (Janzen, Perry & Edwards, 2011) provide the theoretical basis of the study. The convenience sample included 15 graduate students from the Faculty of Health Disciplines at an online university. Participants completed a 4 month master’s course in which PV was used. Data were collected after final course grades were official. Data were gathered using an online questionnaire based on an adaptation (with permission) of Rovai’s (2002) Classroom Cohesion Scale (CSS) and Richardson and Swan’s (2003) Social Presence Scale (SPS). A follow-up focus group with 6 of the original 15 participants was held. Quantitative and qualitative data were collected. This paper focuses on findings from the quantitative data with supportive qualitative comments. Data analysis of the quantitative data takes the form of descriptive statistics. Data analysis of the qualitative data used NVivo software. In sum, the majority of respondents did find that PV had a positive influence on course interactions, but also on their sense of community, comfort in the educational milieu, and on how well they got to know themselves, other learners, and the instructor. Questions for further research are posed.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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