I-Click Photography: An Exploration of Student Perspectives on Learning and Engagement
Bibliographic record
Abstract
As has been seen in previous research, school engagement is a necessary factor in student success (Al-Hendawi, 2012; Baker, Derrer, Davis, Dinklage-Travis, & Linder, 2001; Boyle & Lipman, 2002; Covell, 2009; Gamoran, 1992; Simons-Morton & Chen, 2009; Willms, 1999a; Wolfe & Mash, 2006). However, students with emotional and/or behavioural difficulties tend to have lower rates of academic success and school completion (Wagner et al., 2003; Kauffman, 2008; Ryan, Pierce, & Mooney, 2008). Shedding light on how these students perceive their learning environments can help to facilitate the development of effective prevention and intervention programs that seek to promote success for all learners. \nThis research study aims to explore students’ perspectives on their learning environments at school, through the use of participatory action research (PAR). In collaboration with the teachers and parents, a photography project took place at an elementary school in the Montreal area in Canada. Seven elementary students from grade one to grade six, who had been identified as having socio-emotional difficulties participated and took photographs of what was most important to them about learning at school. Students were interviewed about their photographs and were then invited to share their stories and photographs with their teachers, parents, and peers through a final closing photo exhibition. Teacher focus groups were also conducted in order to understand how these students’ environments may play a role in their learning. \nUsing grounded theory to guide this qualitative analysis of the students’ visual storytelling narratives, we explored emerging themes and patterns from these narratives to understand student perceptions. Interestingly, consistent with other research pointing to the importance of family-school collaboration, students’ perspectives of their school environment seems to always be coupled with how it relates to their home lives. Secondly, although this study discussed learning and engagement, student narratives seem to focus more on social relationships as highly influential in their school life; the students did not seem to include much on academic engagement. Finally case study summaries using focus group discussions and field notes reveal the strengths and challenges that each child was perceived to have, as well as how each child engaged with the methodology of using photography as a tool to express various needs and wants. \nOverall it seems that the findings may suggest that these students put other forms of learning and engagement at the forefront of their school experience. With this understanding, a supportive environment can be created for these students and adapted to their perceptions of engagement in school. Final discussions include reflections on the methodology as a school engagement activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".