TY - JOUR
T1 - Dialogic feedback at scale
T2 - Recommendations for learning analytics design
AU - Maheshi, Bhagya
AU - Dai, Wei
AU - Martinez-Maldonado, Roberto
AU - Tsai, Yi-Shan
N1 - Publisher Copyright:
© 2024 The Author(s). Journal of Computer Assisted Learning published by John Wiley & Sons Ltd.
PY - 2024/12
Y1 - 2024/12
N2 - Background: Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process. Objectives: This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale. Methods: We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback. Results and Conclusions: The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. In aligning LA with dialogic feedback principles, we propose that LA should promote the following objectives: reflection, adaption, personalisation, emotional management, and scaffolding feedback provision.
AB - Background: Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process. Objectives: This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale. Methods: We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback. Results and Conclusions: The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. In aligning LA with dialogic feedback principles, we propose that LA should promote the following objectives: reflection, adaption, personalisation, emotional management, and scaffolding feedback provision.
KW - backward feedback
KW - dialogic feedback
KW - feedback request
KW - formative assessments
KW - learning analytics
UR - http://www.scopus.com/inward/record.url?scp=85197428801&partnerID=8YFLogxK
U2 - 10.1111/jcal.13034
DO - 10.1111/jcal.13034
M3 - Article
AN - SCOPUS:85197428801
SN - 0266-4909
VL - 40
SP - 2790
EP - 2808
JO - Journal of Computer Assisted Learning
JF - Journal of Computer Assisted Learning
IS - 6
ER -