Multimodal academic discourse socialization : an ethnographic multiple-case study of geoscience students’ poster presentations at a Canadian university
Bibliographic record
Abstract
Academic discourse socialization (ADS) provides useful theoretical, methodological, and pedagogical insights into the processes, affordances, and challenges associated with students’ learning and engagement in academic discourses and tasks (Duff & Anderson, 2015). While research has predominantly documented oral and written ADS, language socialization theorists have increasingly examined the significant affordances of multimodal and embodied meaningmaking resources (Duff, Zappa-Hollman, & Surtees, 2019). However, the roles and dynamic interrelationships among these different modes require further ADS research. Another research gap concerns the type of academic task that is analyzed. Compared to lecture-type student presentations (Duff & Kobayashi, 2010), fewer studies have explored poster presentations, which foreground the orchestration of verbal, written, visual, and embodied resources to effectively communicate their meanings in dynamic ways (MacIntosh-Murray, 2007). Despite this complexity and the ubiquity of poster presentations in courses and at conferences, little is known about students’ actual multimodal meaning-making practices in poster presentations. This thesis therefore explores the nexus of these two interrelated, underexplored areas. Drawing on Vygotskian sociocultural theory, ADS, and ecological approaches (Duff, 2007; van Lier, 2004), this thesis reports findings from a multiple-case study of undergraduate students’ multimodal ADS and poster presentation performance in a geoscience course at a Canadian university. Data generated through semester-long classroom observations, interviews with the instructor and students, and participant-produced documents (e.g., posters) were qualitatively analyzed following a multi-cycle procedure (Miles et al., 2019). Video-recorded data were analyzed using multimodal interaction analysis (Norris, 2019) to examine four participants’ moment-to-moment deployment of multiple meaning-making resources in their poster presentations. Findings show that students were socialized into the recurrent in-class “observation versus interpretation” activity to learn to differentiate them in the visual geographical data in highly multimodal and embodied ways. The analyses of students’ videorecorded poster presentations further demonstrate how these multimodal and embodied practices were manifested in students’ performance using spoken and written language, visuals, iconic and deictic gestures, and viewers’ questions as additional semiotic resources. This study emphasizes that multimodal enactments constitute a crucial dimension of disciplinary practices and values connected with learning to think, view, and represent knowledge “like geoscientists.”
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".