An analysis of the use of good feedback practices in online learning courses

Anderson Pinheiro Cavalcanti; Vitor Rolim; Máverick André; Fred Freitas; Rafael Ferreira; Dragan Gasevic

doi:10.1109/ICALT.2019.00061

An analysis of the use of good feedback practices in online learning courses

Anderson Pinheiro Cavalcanti, Vitor Rolim, Máverick André, Fred Freitas, Rafael Ferreira, Dragan Gasevic

Department of Data Science & AI

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

17 Citations (Scopus)

Abstract

Feedback is an essential component of any learning experience. It allows students to identify gaps in their learning and improve their self-regulation. However, providing useful feedback is a challenging and time-consuming task. In digital learning environments, this challenge is even more significant due to a large number of students. Thus, this paper reports on the findings of an analysis of the quality of feedback provided by instructors in an online course. The paper also proposes a supervised machine learning algorithm that can identify the presence of good practices in feedback messages sent to students in a digital learning environment. The results reveal the most commonly used kinds of feedback and how to identify them automatically. The results of the study could potentially be used to improve the quality of the feedback provided by instructors in online education.

Original language	English
Title of host publication	Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019
Editors	Maiga Chang, Demetrios G Sampson, Ronghuai Huang, Alex Sandro Gomes, Nian-Shing Chen, Ig Ibert Bittencourt, Kinshuk , Diego Dermeval, Ibsen Mateus Bittencourt
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	153-157
Number of pages	5
ISBN (Electronic)	9781728134857
ISBN (Print)	9781728134864
DOIs	https://doi.org/10.1109/ICALT.2019.00061
Publication status	Published - 2019
Event	IEEE International Conference on Advanced Learning Technologies 2019 - Maceio, Brazil Duration: 15 Jul 2019 → 18 Jul 2019 Conference number: 19th http://www.ic.ufal.br/evento/icalt2019/ https://ieeexplore.ieee.org/xpl/conhome/8809605/proceeding (Proceedings)

Conference

Conference	IEEE International Conference on Advanced Learning Technologies 2019
Abbreviated title	ICALT 2019
Country/Territory	Brazil
City	Maceio
Period	15/07/19 → 18/07/19
Internet address	http://www.ic.ufal.br/evento/icalt2019/ https://ieeexplore.ieee.org/xpl/conhome/8809605/proceeding (Proceedings)

Keywords

Feedback
Learning Analytics
Online learning
Text Mining

Access to Document

10.1109/ICALT.2019.00061

Cite this

Pinheiro Cavalcanti, A., Rolim, V., André, M., Freitas, F., Ferreira, R., & Gasevic, D. (2019). An analysis of the use of good feedback practices in online learning courses. In M. Chang, D. G. Sampson, R. Huang, A. S. Gomes, N-S. Chen, I. I. Bittencourt, K., D. Dermeval, & I. M. Bittencourt (Eds.), Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019 (pp. 153-157). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICALT.2019.00061

Pinheiro Cavalcanti, Anderson ; Rolim, Vitor ; André, Máverick et al. / An analysis of the use of good feedback practices in online learning courses. Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019. editor / Maiga Chang ; Demetrios G Sampson ; Ronghuai Huang ; Alex Sandro Gomes ; Nian-Shing Chen ; Ig Ibert Bittencourt ; Kinshuk ; Diego Dermeval ; Ibsen Mateus Bittencourt. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 153-157

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title = "An analysis of the use of good feedback practices in online learning courses",

abstract = "Feedback is an essential component of any learning experience. It allows students to identify gaps in their learning and improve their self-regulation. However, providing useful feedback is a challenging and time-consuming task. In digital learning environments, this challenge is even more significant due to a large number of students. Thus, this paper reports on the findings of an analysis of the quality of feedback provided by instructors in an online course. The paper also proposes a supervised machine learning algorithm that can identify the presence of good practices in feedback messages sent to students in a digital learning environment. The results reveal the most commonly used kinds of feedback and how to identify them automatically. The results of the study could potentially be used to improve the quality of the feedback provided by instructors in online education.",

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Pinheiro Cavalcanti, A, Rolim, V, André, M, Freitas, F, Ferreira, R & Gasevic, D 2019, An analysis of the use of good feedback practices in online learning courses. in M Chang, DG Sampson, R Huang, AS Gomes, N-S Chen, II Bittencourt, K, D Dermeval & IM Bittencourt (eds), Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 153-157, IEEE International Conference on Advanced Learning Technologies 2019, Maceio, Brazil, 15/07/19. https://doi.org/10.1109/ICALT.2019.00061

An analysis of the use of good feedback practices in online learning courses. / Pinheiro Cavalcanti, Anderson; Rolim, Vitor; André, Máverick et al.
Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019. ed. / Maiga Chang; Demetrios G Sampson; Ronghuai Huang; Alex Sandro Gomes; Nian-Shing Chen; Ig Ibert Bittencourt; Kinshuk; Diego Dermeval; Ibsen Mateus Bittencourt. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 153-157.

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

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T1 - An analysis of the use of good feedback practices in online learning courses

AU - Pinheiro Cavalcanti, Anderson

AU - Rolim, Vitor

AU - André, Máverick

AU - Freitas, Fred

AU - Ferreira, Rafael

AU - Gasevic, Dragan

N1 - Conference code: 19th

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N2 - Feedback is an essential component of any learning experience. It allows students to identify gaps in their learning and improve their self-regulation. However, providing useful feedback is a challenging and time-consuming task. In digital learning environments, this challenge is even more significant due to a large number of students. Thus, this paper reports on the findings of an analysis of the quality of feedback provided by instructors in an online course. The paper also proposes a supervised machine learning algorithm that can identify the presence of good practices in feedback messages sent to students in a digital learning environment. The results reveal the most commonly used kinds of feedback and how to identify them automatically. The results of the study could potentially be used to improve the quality of the feedback provided by instructors in online education.

AB - Feedback is an essential component of any learning experience. It allows students to identify gaps in their learning and improve their self-regulation. However, providing useful feedback is a challenging and time-consuming task. In digital learning environments, this challenge is even more significant due to a large number of students. Thus, this paper reports on the findings of an analysis of the quality of feedback provided by instructors in an online course. The paper also proposes a supervised machine learning algorithm that can identify the presence of good practices in feedback messages sent to students in a digital learning environment. The results reveal the most commonly used kinds of feedback and how to identify them automatically. The results of the study could potentially be used to improve the quality of the feedback provided by instructors in online education.

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ER -

Pinheiro Cavalcanti A, Rolim V, André M, Freitas F, Ferreira R, Gasevic D. An analysis of the use of good feedback practices in online learning courses. In Chang M, Sampson DG, Huang R, Gomes AS, Chen N-S, Bittencourt II, K, Dermeval D, Bittencourt IM, editors, Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 153-157 doi: 10.1109/ICALT.2019.00061

An analysis of the use of good feedback practices in online learning courses

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