Enhancing student engagement and supervisor efficiency in doctoral supervision: a study on multimodal and rubric-based feedback

Effective feedback is critical in doctoral supervision, yet traditional methods often lack clarity and engagement. This study examines the impact of a multimodal and rubric-based feedback approach on student engagement and supervisor efficiency. Over a 12-month period, doctoral students and supervisors participated in an intervention where feedback was delivered through written comments, audio recordings, and visual annotations, supported by a standardized rubric. Data from 18 doctoral students and six supervisors were collected through pre- and post-intervention surveys, feedback logs, and semi-structured interviews. Findings show significant improvements in cognitive, affective, and behavioral engagement, with students demonstrating better comprehension and motivation. Supervisors reported a 37% reduction in feedback time and a 45% improvement in feedback quality, though concerns about the perceived lack of personalization in rubric-based feedback and technical challenges emerged. Thematic analysis highlighted multimodal feedback’s role in reducing repetitive clarifications and enhancing feedback accessibility. While adaptation challenges were noted, a hybrid feedback model combining structured rubrics with personalized interactions is recommended. This study underscores the need for professional development, and discipline-specific refinements to optimize multimodal feedback in doctoral supervision.

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Publication Details

Journal
Cogent Education
Published
2025-11-26
DOI
https://doi.org/10.1080/2331186x.2025.2590860
Primary Topic
Doctoral Education Challenges and Solutions
Type
article
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article

Enhancing student engagement and supervisor efficiency in doctoral supervision: a study on multimodal and rubric-based feedback

Mohammad Bavali, Fatemeh Behjat, Zahra Homayounzadeh
Cogent Education
Doctoral Education Challenges and Solutions
article

Enhancing student engagement and supervisor efficiency in doctoral supervision: a study on multimodal and rubric-based feedback

Mohammad Bavali, Fatemeh Behjat, Zahra Homayounzadeh
article en

Abstract

Effective feedback is critical in doctoral supervision, yet traditional methods often lack clarity and engagement. This study examines the impact of a multimodal and rubric-based feedback approach on student engagement and supervisor efficiency. Over a 12-month period, doctoral students and supervisors participated in an intervention where feedback was delivered through written comments, audio recordings, and visual annotations, supported by a standardized rubric. Data from 18 doctoral students and six supervisors were collected through pre- and post-intervention surveys, feedback logs, and semi-structured interviews. Findings show significant improvements in cognitive, affective, and behavioral engagement, with students demonstrating better comprehension and motivation. Supervisors reported a 37% reduction in feedback time and a 45% improvement in feedback quality, though concerns about the perceived lack of personalization in rubric-based feedback and technical challenges emerged. Thematic analysis highlighted multimodal feedback’s role in reducing repetitive clarifications and enhancing feedback accessibility. While adaptation challenges were noted, a hybrid feedback model combining structured rubrics with personalized interactions is recommended. This study underscores the need for professional development, and discipline-specific refinements to optimize multimodal feedback in doctoral supervision.

Cogent EducationVol. 12(1)
Islamic Azad University, Tehran (IR)
Openalex Percentile: Top 47%
Doctoral Education Challenges and Solutions
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Enhancing student engagement and supervisor efficiency in doctoral supervision: a study on multimodal and rubric-based feedback — Mohammad Bavali, Fatemeh Behjat, et al. · Cogent Education (2025) | TGRS Research Map | TGRS