Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load

Jelena Jovanović; Shane Dawson; Dragan Gašević; Alexander Whitelock-Wainwright; Abelardo Pardo

doi:10.1145/3303772.3303782

Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load

Jelena Jovanović, Shane Dawson, Dragan Gašević, Alexander Whitelock-Wainwright, Abelardo Pardo

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

26 Citations (Scopus)

Abstract

The use of learning trace data together with various analytical methods has proven successful in detecting patterns in learning behaviour, identifying student profiles, and clustering learning resources. However, interpretation of the findings is often difficult and uncertain due to a lack of contextual data (e.g., data on student motivation, emotion or curriculum design). In this study we explored the integration of student self-reports about cognitive load and self-efficacy into the learning process and collection of relevant students' perceptions as learning traces. Our objective was to examine the association of traced measures of relevant learning constructs (cognitive load and self-efficacy) with i) indicators of the students' learning behaviour derived from trace data, and ii) the students' academic performance. The results indicated the presence of association between some indicators of students' engagement with learning activities and traced measures of cognitive load and self-efficacy. Correlational analysis demonstrated significant positive correlation between the students' course performance and traced measures of cognitive load and self-efficacy.

Original language	English
Title of host publication	Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19)
Subtitle of host publication	Learning Analytics to Promote Inclusion and Success
Editors	Christopher Brooks, Rebecca Ferguson, Ulrich Hoppe
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	511-520
Number of pages	10
ISBN (Electronic)	9781450362566
DOIs	https://doi.org/10.1145/3303772.3303782
Publication status	Published - 2019
Event	International Learning Analytics & Knowledge Conference 2019 - Arizona State University, Tempe, United States of America Duration: 4 Mar 2019 → 8 Mar 2019 Conference number: 9th https://lak19.solaresearch.org/

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	International Learning Analytics & Knowledge Conference 2019
Abbreviated title	LAK 2019
Country/Territory	United States of America
City	Tempe
Period	4/03/19 → 8/03/19
Internet address	https://lak19.solaresearch.org/

Keywords

Cognitive load
Learning analytics
Perceived difficulty
Self-efficacy
Self-reports
Trace data

Access to Document

10.1145/3303772.3303782

Cite this

Jovanović, J., Dawson, S., Gašević, D., Whitelock-Wainwright, A., & Pardo, A. (2019). Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load. In C. Brooks, R. Ferguson, & U. Hoppe (Eds.), Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19): Learning Analytics to Promote Inclusion and Success (pp. 511-520). (ACM International Conference Proceeding Series). Association for Computing Machinery (ACM). https://doi.org/10.1145/3303772.3303782

Jovanović, Jelena ; Dawson, Shane ; Gašević, Dragan et al. / Introducing meaning to clicks : towards traced-measures of self-efficacy and cognitive load. Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19): Learning Analytics to Promote Inclusion and Success. editor / Christopher Brooks ; Rebecca Ferguson ; Ulrich Hoppe. New York NY USA : Association for Computing Machinery (ACM), 2019. pp. 511-520 (ACM International Conference Proceeding Series).

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title = "Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load",

abstract = "The use of learning trace data together with various analytical methods has proven successful in detecting patterns in learning behaviour, identifying student profiles, and clustering learning resources. However, interpretation of the findings is often difficult and uncertain due to a lack of contextual data (e.g., data on student motivation, emotion or curriculum design). In this study we explored the integration of student self-reports about cognitive load and self-efficacy into the learning process and collection of relevant students' perceptions as learning traces. Our objective was to examine the association of traced measures of relevant learning constructs (cognitive load and self-efficacy) with i) indicators of the students' learning behaviour derived from trace data, and ii) the students' academic performance. The results indicated the presence of association between some indicators of students' engagement with learning activities and traced measures of cognitive load and self-efficacy. Correlational analysis demonstrated significant positive correlation between the students' course performance and traced measures of cognitive load and self-efficacy.",

keywords = "Cognitive load, Learning analytics, Perceived difficulty, Self-efficacy, Self-reports, Trace data",

author = "Jelena Jovanovi{\'c} and Shane Dawson and Dragan Ga{\v s}evi{\'c} and Alexander Whitelock-Wainwright and Abelardo Pardo",

year = "2019",

doi = "10.1145/3303772.3303782",

language = "English",

series = "ACM International Conference Proceeding Series",

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

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editor = "Christopher Brooks and Rebecca Ferguson and Ulrich Hoppe",

booktitle = "Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19)",

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Jovanović, J, Dawson, S, Gašević, D, Whitelock-Wainwright, A & Pardo, A 2019, Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load. in C Brooks, R Ferguson & U Hoppe (eds), Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19): Learning Analytics to Promote Inclusion and Success. ACM International Conference Proceeding Series, Association for Computing Machinery (ACM), New York NY USA, pp. 511-520, International Learning Analytics & Knowledge Conference 2019, Tempe, Arizona, United States of America, 4/03/19. https://doi.org/10.1145/3303772.3303782

Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load. / Jovanović, Jelena; Dawson, Shane; Gašević, Dragan et al.
Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19): Learning Analytics to Promote Inclusion and Success. ed. / Christopher Brooks; Rebecca Ferguson; Ulrich Hoppe. New York NY USA: Association for Computing Machinery (ACM), 2019. p. 511-520 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Introducing meaning to clicks

T2 - International Learning Analytics & Knowledge Conference 2019

AU - Jovanović, Jelena

AU - Dawson, Shane

AU - Gašević, Dragan

AU - Whitelock-Wainwright, Alexander

AU - Pardo, Abelardo

N1 - Conference code: 9th

PY - 2019

Y1 - 2019

N2 - The use of learning trace data together with various analytical methods has proven successful in detecting patterns in learning behaviour, identifying student profiles, and clustering learning resources. However, interpretation of the findings is often difficult and uncertain due to a lack of contextual data (e.g., data on student motivation, emotion or curriculum design). In this study we explored the integration of student self-reports about cognitive load and self-efficacy into the learning process and collection of relevant students' perceptions as learning traces. Our objective was to examine the association of traced measures of relevant learning constructs (cognitive load and self-efficacy) with i) indicators of the students' learning behaviour derived from trace data, and ii) the students' academic performance. The results indicated the presence of association between some indicators of students' engagement with learning activities and traced measures of cognitive load and self-efficacy. Correlational analysis demonstrated significant positive correlation between the students' course performance and traced measures of cognitive load and self-efficacy.

AB - The use of learning trace data together with various analytical methods has proven successful in detecting patterns in learning behaviour, identifying student profiles, and clustering learning resources. However, interpretation of the findings is often difficult and uncertain due to a lack of contextual data (e.g., data on student motivation, emotion or curriculum design). In this study we explored the integration of student self-reports about cognitive load and self-efficacy into the learning process and collection of relevant students' perceptions as learning traces. Our objective was to examine the association of traced measures of relevant learning constructs (cognitive load and self-efficacy) with i) indicators of the students' learning behaviour derived from trace data, and ii) the students' academic performance. The results indicated the presence of association between some indicators of students' engagement with learning activities and traced measures of cognitive load and self-efficacy. Correlational analysis demonstrated significant positive correlation between the students' course performance and traced measures of cognitive load and self-efficacy.

KW - Cognitive load

KW - Learning analytics

KW - Perceived difficulty

KW - Self-efficacy

KW - Self-reports

KW - Trace data

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U2 - 10.1145/3303772.3303782

DO - 10.1145/3303772.3303782

M3 - Conference Paper

AN - SCOPUS:85062791797

T3 - ACM International Conference Proceeding Series

SP - 511

EP - 520

BT - Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19)

A2 - Brooks, Christopher

A2 - Ferguson, Rebecca

A2 - Hoppe, Ulrich

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

Y2 - 4 March 2019 through 8 March 2019

ER -

Jovanović J, Dawson S, Gašević D, Whitelock-Wainwright A, Pardo A. Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load. In Brooks C, Ferguson R, Hoppe U, editors, Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK'19): Learning Analytics to Promote Inclusion and Success. New York NY USA: Association for Computing Machinery (ACM). 2019. p. 511-520. (ACM International Conference Proceeding Series). doi: 10.1145/3303772.3303782

Introducing meaning to clicks: towards traced-measures of self-efficacy and cognitive load

Abstract

Publication series

Conference

Keywords

Access to Document

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