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Record W4413137306 · doi:10.1016/j.ijer.2025.102737

“They hear it from me”: Student voices on critically assessing digital multimodal composing

2025· article· en· W4413137306 on OpenAlex
Jonathan Ferreira, Maureen Kendrick

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Educational Research · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council
KeywordsPsychologyMathematics educationLinguistics

Abstract

fetched live from OpenAlex

• Grade 8 youth composed digital stories and video essays to counter social injustices. • Students used digital, multimodal and disciplinary tools to enhance critical actions. • Their rubric criteria, reflections and interviews highlighted critical DMC practices. • Student perspectives on DMC practices fostered transparency, reflection, and action. • Justice-oriented assessment helps reorient DMC practices toward social justice. This ethnographic case study investigates how student perspectives on digital multimodal composing (DMC) practices can inform a justice-oriented approach to assessment in English Language Arts (ELA). While existing research often privileges teacher perspectives in assessing DMC, this study centres the voices of two culturally and linguistically diverse Grade 8 students in a Canadian ELA classroom. Drawing on multimodality, critical digital literacies, and disciplinary literacies, we examine interviews, self-assessment reflections, student-suggested rubrics, and final DMC projects to understand how youth critically apply digital, multimodal and disciplinary tools to design digital stories and video essays that challenge social injustices. Our thematic analysis reveals that students remix digital tools, such as voiceovers, music, and visual design, not only to meet assignment expectations but also to critically engage their audience. Student perspectives on their DMC practices emphasize their multimodal and audience awareness, including intentional choices about sound, pacing, and visual impact. Students also engage in disciplinary weaving, combining self and world connections with judicious sourcing to denounce racial, cultural, and gender discrimination. These insights fostered transparency and enabled the classroom teacher to provide formative, student-responsive feedback and honour diverse ways of knowing. This study contributes to current scholarship by advancing a justice-oriented model of DMC assessment that values student agency and encourages educators to assess how students reorient digital, multimodal and disciplinary tools toward social justice. By foregrounding student voices, this study positions justice-oriented DMC assessment as a pedagogical tool capable of disrupting hegemonic norms in disciplinary classrooms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.108
GPT teacher head0.486
Teacher spread0.378 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it