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All Journal Indonesian Journal of Linguistics and Educational Studies
Fitria Yuliani
Universitas Pignatelli Triputra

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Multimodal feedback and student engagement: a linguistic analysis of digital assessment practices in Indonesian universities Fitria Yuliani
Indonesian Journal of Linguistics and Educational Studies Vol. 1 No. 1 (2026): Language, education, and digital pedagogy in Indonesian contexts
Publisher : CV Narasi Khatulistiwa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67490/ijled.v1i1.545

Abstract

Background: The expansion of digital assessment in Indonesian higher education has intensified the need to understand how multimodal feedback shapes student engagement beyond conventional text-based evaluation. Objective: This study investigates how linguistic, visual, audio, and interactional resources in Learning Management Systems construct authority, affect, and engagement in university feedback practices. Method: Using a qualitative-dominant mixed-method design, this research analyzes 240 feedback instances across Moodle, SPADA, and Google Classroom through Multimodal Discourse Analysis, Appraisal Theory, and Interactional Sociolinguistics. Results: The findings reveal that multimodal congruence—where evaluative language, prosodic cues, and visual design align—significantly correlates with substantive revision and reflective participation. Dialogically framed feedback employing hedging, inclusive stance, and calibrated graduation expands interpretive space and enhances emotional stability. Conversely, monologic closure, imperative density, and prosodic finality are associated with surface-level compliance and reduced cognitive engagement. Implication: These findings indicate that effective digital feedback requires multimodal and dialogic alignment to foster deeper student engagement, emotional support, and meaningful learning outcomes beyond surface-level compliance. Novelty: The novelty of this study lies in proposing an integrated cross-modal analytical framework that operationalizes linguistic and interactional features as measurable predictors of engagement within digital assessment analytics.
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