Assessing learning analytics impact on coding competence growth

David Boulanger; Jeremie Seanosky; Rebecca Guillot; Isabelle Guillot; Claudia Guillot; Shawn Fraser; Vivekanandan Kumar; Kinshuk

doi:10.1109/ICALT.2019.00057

Assessing learning analytics impact on coding competence growth

David Boulanger, Jeremie Seanosky, Rebecca Guillot, Isabelle Guillot, Claudia Guillot, Shawn Fraser, Vivekanandan Kumar, Kinshuk

School of Computing and Information systems

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

2 Citations (Scopus)

Abstract

The literature reveals that the effectiveness of learning analytics (LA) tools is best evaluated with a mixed-method approach and not only with summative measurements such as grades. A recent study on the impact of an LA tool over academic performance did not substantiate its effect in improving grades for coding tasks despite qualitative comments of experimental group participants indicating that the tool was effective in improving coding competences in Java. In analyzing this viewpoint, this paper describes the impact of LA formative feedback on the growth of students' coding competences.

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 Kinshuk, Diego Dermeval, Ibsen Mateus Bittencourt
Pages	170-172
Number of pages	3
ISBN (Electronic)	9781728134857
DOIs	https://doi.org/10.1109/ICALT.2019.00057
Publication status	Published - Jul. 2019
Event	19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019 - Maceio, Brazil Duration: 15 Jul. 2019 → 18 Jul. 2019

Publication series

Name	Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019

Conference

Conference	19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019
Country/Territory	Brazil
City	Maceio
Period	15/07/19 → 18/07/19

Keywords

Analytics
Coding
Competence
Time series

Access to Document

10.1109/ICALT.2019.00057

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Boulanger, D., Seanosky, J., Guillot, R., Guillot, I., Guillot, C., Fraser, S., Kumar, V., & Kinshuk (2019). Assessing learning analytics impact on coding competence growth. In M. Chang, D. G. Sampson, R. Huang, A. S. Gomes, N.-S. Chen, I. I. Bittencourt, K. Kinshuk, D. Dermeval, & I. M. Bittencourt (Eds.), Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019 (pp. 170-172). Article 8820896 (Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019). https://doi.org/10.1109/ICALT.2019.00057

Boulanger, David ; Seanosky, Jeremie ; Guillot, Rebecca et al. / Assessing learning analytics impact on coding competence growth. 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 Kinshuk ; Diego Dermeval ; Ibsen Mateus Bittencourt. 2019. pp. 170-172 (Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019).

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title = "Assessing learning analytics impact on coding competence growth",

abstract = "The literature reveals that the effectiveness of learning analytics (LA) tools is best evaluated with a mixed-method approach and not only with summative measurements such as grades. A recent study on the impact of an LA tool over academic performance did not substantiate its effect in improving grades for coding tasks despite qualitative comments of experimental group participants indicating that the tool was effective in improving coding competences in Java. In analyzing this viewpoint, this paper describes the impact of LA formative feedback on the growth of students' coding competences.",

keywords = "Analytics, Coding, Competence, Time series",

author = "David Boulanger and Jeremie Seanosky and Rebecca Guillot and Isabelle Guillot and Claudia Guillot and Shawn Fraser and Vivekanandan Kumar and Kinshuk",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019 ; Conference date: 15-07-2019 Through 18-07-2019",

year = "2019",

month = jul,

doi = "10.1109/ICALT.2019.00057",

language = "English",

series = "Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019",

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editor = "Maiga Chang and Sampson, {Demetrios G} and Ronghuai Huang and Gomes, {Alex Sandro} and Nian-Shing Chen and Bittencourt, {Ig Ibert} and Kinshuk Kinshuk and Diego Dermeval and Bittencourt, {Ibsen Mateus}",

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Boulanger, D, Seanosky, J, Guillot, R, Guillot, I, Guillot, C, Fraser, S , Kumar, V & Kinshuk 2019, Assessing learning analytics impact on coding competence growth. in M Chang, DG Sampson, R Huang, AS Gomes, N-S Chen, II Bittencourt, K Kinshuk, D Dermeval & IM Bittencourt (eds), Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019., 8820896, Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019, pp. 170-172, 19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019, Maceio, Brazil, 15/07/19. https://doi.org/10.1109/ICALT.2019.00057

Assessing learning analytics impact on coding competence growth. / Boulanger, David; Seanosky, Jeremie; Guillot, Rebecca 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 Kinshuk; Diego Dermeval; Ibsen Mateus Bittencourt. 2019. p. 170-172 8820896 (Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019).

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

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AU - Kumar, Vivekanandan

AU - Kinshuk,

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AB - The literature reveals that the effectiveness of learning analytics (LA) tools is best evaluated with a mixed-method approach and not only with summative measurements such as grades. A recent study on the impact of an LA tool over academic performance did not substantiate its effect in improving grades for coding tasks despite qualitative comments of experimental group participants indicating that the tool was effective in improving coding competences in Java. In analyzing this viewpoint, this paper describes the impact of LA formative feedback on the growth of students' coding competences.

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KW - Coding

KW - Competence

KW - Time series

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A2 - Chang, Maiga

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A2 - Dermeval, Diego

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T2 - 19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019

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Boulanger D, Seanosky J, Guillot R, Guillot I, Guillot C, Fraser S et al. Assessing learning analytics impact on coding competence growth. In Chang M, Sampson DG, Huang R, Gomes AS, Chen NS, Bittencourt II, Kinshuk K, Dermeval D, Bittencourt IM, editors, Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019. 2019. p. 170-172. 8820896. (Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019). doi: 10.1109/ICALT.2019.00057

Assessing learning analytics impact on coding competence growth

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