Humanising feedback encounters: a qualitative study of relational literacies for teachers engaging in technology-enhanced feedback

Payne, Ameena; Ajjawi, Rola; Holloway, Jessica

doi:10.1080/02602938.2022.2155610

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…However, writing detailed feedback was time-consuming for educators, especially for more complex or conceptual problems. Written feedback also reportedly perceived by learners to lack an emotional and relational quality (Cavaleri et al, 2019;Payne et al, 2022).…”

Section: Modes Of Communicating Feedback and Processesmentioning

confidence: 99%

“…Learners preferred feedback that offered a high level of detail and addressed higher-order conceptual issues, which was not always possible to provide via conventional written modes (Ice et al, 2010;Orlando, 2016). Audio, video and screencast technologies have been utilised to obviate the drawbacks of written modes of feedback (Cavaleri et al, 2019;Payne et al, 2022). The combined use of video and text feedback was reported to be more effective in encouraging students to engage with, and apply the feedback to, their assignments (Yiğit & Seferoğlu, 2023).…”

Section: Modes Of Communicating Feedback and Processesmentioning

confidence: 99%

“…Feedback provides students with insights into their errors and on how to improve the expression and clarity of ideas (Starfield, 2019). While the advancement of technology has brought about innovative feedback modalities such as audio or video (Munshi & Deneen, 2018;Payne et al, 2022), there are inherent challenges in ensuring their efficacy and succinctness, especially when the feedback providers are NESB teaching staff (Bal-Gezegin, 2015;Demir & Özmen, 2017). Notably, NESB educators may often grapple in providing feedback with language and sentence structure (Starfield, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Artificial Intelligence Use in Feedback: A Qualitative Analysis

Pang,

Kootsookos,

Cheng

2024

JUTLP

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Feedback, particularly the formative or ‘feed-forward’ type is important for students in higher education to understand their errors and improve their expression and clarity of ideas. While technology-assisted feedback modes, e.g., audio or video are prevalent, ensuring their efficacy and succinctness, particularly for non-English-speaking background (NESB) educators can be challenging. This study investigates the attitudes and experiences of NESB educators in the School of Engineering of RMIT University, with a focus on their use of AI-assisted tools for providing feedback to students in higher education settings. Utilising a survey, the researchers examined how personal and linguistic attributes influenced feedback strategies and explored the educators' perspectives on integrating AI tools, such as ChatGPT and BARD, in their teaching practice and to enhance student engagement with the feedback they received. Through thematic analysis the findings reveal that personal background and linguistic proficiency significantly influenced the provision of feedback. Furthermore, even though educators had different levels of familiarity with AI-assisted tools, there was a general consensus on the potential utility of these tools for improving feedback provision. These will require targeted staff training, careful human oversight to ensure quality and avoid bias, and customised AI training to align feedback with individual teaching styles.

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Section: Modes Of Communicating Feedback and Processesmentioning

confidence: 99%