Student appreciation of data-driven feedback: a pilot study on OnTask

Yi Shan Tsai; Rafael Ferreira Mello; Jelena Jovanović; Dragan Gašević

doi:10.1145/3448139.3448212

Student appreciation of data-driven feedback: a pilot study on OnTask

Yi Shan Tsai, Rafael Ferreira Mello, Jelena Jovanović, Dragan Gašević

Department of Data Science & AI

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

21 Citations (Scopus)

Abstract

Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students' experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students'self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the g'partnership' between the human teacher and the computer, and developing feedback literacy among learners.

Original language	English
Title of host publication	LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning
Subtitle of host publication	The Eleventh International Conference on Learning Analytics & Knowledge
Editors	Maren Scheffel, Nia Dowell, Srecko Joksimovic, George Siemens
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	511-517
Number of pages	7
ISBN (Electronic)	9781450389358
DOIs	https://doi.org/10.1145/3448139.3448212
Publication status	Published - 2021
Event	International Learning Analytics & Knowledge Conference 2021 - Online, Irvine, United States of America Duration: 12 Apr 2021 → 16 Apr 2021 Conference number: 11th https://www.solaresearch.org/events/lak/lak21/ https://dl.acm.org/doi/proceedings/10.1145/3448139 (Proceedings)

Conference

Conference	International Learning Analytics & Knowledge Conference 2021
Abbreviated title	LAK 2021
Country/Territory	United States of America
City	Irvine
Period	12/04/21 → 16/04/21
Internet address	https://www.solaresearch.org/events/lak/lak21/ https://dl.acm.org/doi/proceedings/10.1145/3448139 (Proceedings)

Keywords

Feedback
Feedback literacy
Learning analytics
Learning theories
OnTask

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10.1145/3448139.3448212

Cite this

Tsai, Y. S., Mello, R. F., Jovanović, J., & Gašević, D. (2021). Student appreciation of data-driven feedback: a pilot study on OnTask. In M. Scheffel, N. Dowell, S. Joksimovic, & G. Siemens (Eds.), LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning: The Eleventh International Conference on Learning Analytics & Knowledge (pp. 511-517). Association for Computing Machinery (ACM). https://doi.org/10.1145/3448139.3448212

Tsai, Yi Shan ; Mello, Rafael Ferreira ; Jovanović, Jelena et al. / Student appreciation of data-driven feedback : a pilot study on OnTask. LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning: The Eleventh International Conference on Learning Analytics & Knowledge. editor / Maren Scheffel ; Nia Dowell ; Srecko Joksimovic ; George Siemens. New York NY USA : Association for Computing Machinery (ACM), 2021. pp. 511-517

@inproceedings{196655ec896347df94e97c866eaf83c6,

title = "Student appreciation of data-driven feedback: a pilot study on OnTask",

abstract = "Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students' experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students'self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the g'partnership' between the human teacher and the computer, and developing feedback literacy among learners.",

keywords = "Feedback, Feedback literacy, Learning analytics, Learning theories, OnTask",

author = "Tsai, {Yi Shan} and Mello, {Rafael Ferreira} and Jelena Jovanovi{\'c} and Dragan Ga{\v s}evi{\'c}",

year = "2021",

doi = "10.1145/3448139.3448212",

language = "English",

pages = "511--517",

editor = "Scheffel, {Maren } and Dowell, {Nia } and Joksimovic, {Srecko } and Siemens, {George }",

booktitle = "LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "International Learning Analytics & Knowledge Conference 2021, LAK 2021 ; Conference date: 12-04-2021 Through 16-04-2021",

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Tsai, YS, Mello, RF, Jovanović, J & Gašević, D 2021, Student appreciation of data-driven feedback: a pilot study on OnTask. in M Scheffel, N Dowell, S Joksimovic & G Siemens (eds), LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning: The Eleventh International Conference on Learning Analytics & Knowledge. Association for Computing Machinery (ACM), New York NY USA, pp. 511-517, International Learning Analytics & Knowledge Conference 2021, Irvine, California, United States of America, 12/04/21. https://doi.org/10.1145/3448139.3448212

Student appreciation of data-driven feedback: a pilot study on OnTask. / Tsai, Yi Shan; Mello, Rafael Ferreira; Jovanović, Jelena et al.
LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning: The Eleventh International Conference on Learning Analytics & Knowledge. ed. / Maren Scheffel; Nia Dowell; Srecko Joksimovic; George Siemens. New York NY USA: Association for Computing Machinery (ACM), 2021. p. 511-517.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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T2 - International Learning Analytics & Knowledge Conference 2021

AU - Tsai, Yi Shan

AU - Mello, Rafael Ferreira

AU - Jovanović, Jelena

AU - Gašević, Dragan

N1 - Conference code: 11th

PY - 2021

Y1 - 2021

N2 - Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students' experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students'self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the g'partnership' between the human teacher and the computer, and developing feedback literacy among learners.

AB - Feedback plays a crucial role in student learning. Learning analytics (LA) has demonstrated potential in addressing prominent challenges with feedback practice, such as enabling timely feedback based on insights obtained from large data sets. However, there is insufficient research looking into relations between student expectations of feedback and their experience with LA-based feedback. This paper presents a pilot study that examined students' experience of LA-based feedback, offered with the OnTask system, taking into consideration the factors of students'self-efficacy and self-regulation skills. Two surveys were carried out at a Brazilian university, and the results highlighted important implications for LA-based feedback practice, including leveraging the g'partnership' between the human teacher and the computer, and developing feedback literacy among learners.

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BT - LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning

A2 - Scheffel, Maren

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Tsai YS, Mello RF, Jovanović J, Gašević D. Student appreciation of data-driven feedback: a pilot study on OnTask. In Scheffel M, Dowell N, Joksimovic S, Siemens G, editors, LAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning: The Eleventh International Conference on Learning Analytics & Knowledge. New York NY USA: Association for Computing Machinery (ACM). 2021. p. 511-517 doi: 10.1145/3448139.3448212

Student appreciation of data-driven feedback: a pilot study on OnTask

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