How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching

Katherine Herbert; Ian Holder

doi:10.1007/978-981-13-6661-1_30

How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

This paper builds on the current studies on data mining’s potential benefits to online learning environments. Many Teaching Academics who are non-experts in data mining techniques however are not able to take advantage of these potential benefits. The objective of this paper is to illustrate how learning analytics is bridging the gap between data mined from Learning Management Systems and teaching practice development in higher education, specifically for Teaching Academics who recently transitioned into online teaching. The authors suggest that bridging this gap is an essential step in the development of online teaching practices and online courses. A customised Dashboard that curates data mined from a university’s LMS is discussed, showcasing the impact on the practices of Teaching Academics. The results from the preliminary exploration suggest that learning analytics can bridge the gap between expert and non-experts of data mining techniques and can become a valuable tool for teaching practice development.

Original language	English
Title of host publication	Data Mining. AusDM 2018
Subtitle of host publication	Communications in Computer and Information Science
Editors	Rafiqul Islam, Yun Sing Koh, Yanchang Zhao, Graco Warwick, David Stirling, Chang-Tsun Li, Zahidul Islam
Publisher	Springer
Chapter	30
Pages	387-395
Number of pages	9
Volume	996
ISBN (Electronic)	9789811366611
ISBN (Print)	9789811366604
DOIs	https://doi.org/10.1007/978-981-13-6661-1_30
Publication status	Published - 16 Feb 2019
Event	16th Australasian Data Mining Conference: AusDM 2018 - Charles Sturt University Bathurst, Bathurst, Australia Duration: 28 Nov 2018 → 30 Nov 2018 Conference number: 16th http://ausdm18.ausdm.org/

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	996

Conference

Conference	16th Australasian Data Mining Conference
Country/Territory	Australia
City	Bathurst
Period	28/11/18 → 30/11/18
Other	The Australasian Data Mining Conference (AusDM) has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. It is devoted to the art and science of intelligent analysis of (usually big) data sets for meaningful (and previously unknown) insights. This conference will enable the sharing and learning of research and progress in the local context and new breakthroughs in data mining algorithms and their applications across all industries.
Internet address	http://ausdm18.ausdm.org/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-981-13-6661-1_30

Cite this

Herbert, K., & Holder, I. (2019). How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching. In R. Islam, Y. Sing Koh, Y. Zhao, G. Warwick, D. Stirling, C.-T. Li, & Z. Islam (Eds.), Data Mining. AusDM 2018: Communications in Computer and Information Science (Vol. 996, pp. 387-395). (Communications in Computer and Information Science; Vol. 996). Springer. https://doi.org/10.1007/978-981-13-6661-1_30

Herbert, Katherine ; Holder, Ian. / How learning analytics becomes a bridge for non-expert data miners : Impact on higher education online teaching. Data Mining. AusDM 2018: Communications in Computer and Information Science. editor / Rafiqul Islam ; Yun Sing Koh ; Yanchang Zhao ; Graco Warwick ; David Stirling ; Chang-Tsun Li ; Zahidul Islam. Vol. 996 Springer, 2019. pp. 387-395 (Communications in Computer and Information Science).

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title = "How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching",

abstract = "This paper builds on the current studies on data mining{\textquoteright}s potential benefits to online learning environments. Many Teaching Academics who are non-experts in data mining techniques however are not able to take advantage of these potential benefits. The objective of this paper is to illustrate how learning analytics is bridging the gap between data mined from Learning Management Systems and teaching practice development in higher education, specifically for Teaching Academics who recently transitioned into online teaching. The authors suggest that bridging this gap is an essential step in the development of online teaching practices and online courses. A customised Dashboard that curates data mined from a university{\textquoteright}s LMS is discussed, showcasing the impact on the practices of Teaching Academics. The results from the preliminary exploration suggest that learning analytics can bridge the gap between expert and non-experts of data mining techniques and can become a valuable tool for teaching practice development.",

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Herbert, K & Holder, I 2019, How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching. in R Islam, Y Sing Koh, Y Zhao, G Warwick, D Stirling, C-T Li & Z Islam (eds), Data Mining. AusDM 2018: Communications in Computer and Information Science. vol. 996, Communications in Computer and Information Science, vol. 996, Springer, pp. 387-395, 16th Australasian Data Mining Conference, Bathurst, New South Wales, Australia, 28/11/18. https://doi.org/10.1007/978-981-13-6661-1_30

How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching. / Herbert, Katherine; Holder, Ian.
Data Mining. AusDM 2018: Communications in Computer and Information Science. ed. / Rafiqul Islam; Yun Sing Koh; Yanchang Zhao; Graco Warwick; David Stirling; Chang-Tsun Li; Zahidul Islam. Vol. 996 Springer, 2019. p. 387-395 (Communications in Computer and Information Science; Vol. 996).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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T1 - How learning analytics becomes a bridge for non-expert data miners

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AU - Holder, Ian

N1 - Conference code: 16th

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Y1 - 2019/2/16

N2 - This paper builds on the current studies on data mining’s potential benefits to online learning environments. Many Teaching Academics who are non-experts in data mining techniques however are not able to take advantage of these potential benefits. The objective of this paper is to illustrate how learning analytics is bridging the gap between data mined from Learning Management Systems and teaching practice development in higher education, specifically for Teaching Academics who recently transitioned into online teaching. The authors suggest that bridging this gap is an essential step in the development of online teaching practices and online courses. A customised Dashboard that curates data mined from a university’s LMS is discussed, showcasing the impact on the practices of Teaching Academics. The results from the preliminary exploration suggest that learning analytics can bridge the gap between expert and non-experts of data mining techniques and can become a valuable tool for teaching practice development.

AB - This paper builds on the current studies on data mining’s potential benefits to online learning environments. Many Teaching Academics who are non-experts in data mining techniques however are not able to take advantage of these potential benefits. The objective of this paper is to illustrate how learning analytics is bridging the gap between data mined from Learning Management Systems and teaching practice development in higher education, specifically for Teaching Academics who recently transitioned into online teaching. The authors suggest that bridging this gap is an essential step in the development of online teaching practices and online courses. A customised Dashboard that curates data mined from a university’s LMS is discussed, showcasing the impact on the practices of Teaching Academics. The results from the preliminary exploration suggest that learning analytics can bridge the gap between expert and non-experts of data mining techniques and can become a valuable tool for teaching practice development.

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PB - Springer

Y2 - 28 November 2018 through 30 November 2018

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Herbert K, Holder I. How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching. In Islam R, Sing Koh Y, Zhao Y, Warwick G, Stirling D, Li CT, Islam Z, editors, Data Mining. AusDM 2018: Communications in Computer and Information Science. Vol. 996. Springer. 2019. p. 387-395. (Communications in Computer and Information Science). doi: 10.1007/978-981-13-6661-1_30

How learning analytics becomes a bridge for non-expert data miners: Impact on higher education online teaching

Abstract

Publication series

Conference

UN SDGs

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