Temporal perspective on the gender-related differences in online learning behaviour

Wang, Huanhuan; Tlili, Ahmed; Lämsä, Joni; Cai, Zhenyu; Zhong, Xiaoyu; Huang, Ronghuai

doi:10.1080/0144929x.2022.2039769

Cited by 5 publications

(2 citation statements)

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“…It estimates the probability of a given behavior to occur, as well as its successive behavior (Bakeman and Gottman, 1997). This can help researchers examine behavior patterns (e.g., Yang et al, 2015;Kucuk and Sisman, 2017;Wang et al, 2022) and understand how a given user might behave in a given context. Therefore, LSA was used in this study to understand how learners with different personalities might behave in an online course.…”

Section: Research Gap and The Purpose Of The Studymentioning

confidence: 99%

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Impact of personality traits on learners’ navigational behavior patterns in an online course: a lag sequential analysis approach

et al. 2023

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Personality is considered as the internal factor that defines a person’s behavior. Therefore, providing adaptive features and personalized support in online learning by considering learners’ personalities can improve their learning experiences and outcomes. In this context, several research studies have investigated the impact of personality differences in online learning. However, little is known about how personality differences affect learners’ behavior while learning. To fill this gap, this study applies a lag sequential analysis (LSA) approach to understand learners’ navigational behavior patterns in an online three-months course of 65 learners based on their personalities. In this context, the five factor model (FFM) model was used to identify learners’ personalities. The findings revealed that learners with different personalities use different strategies to learn and navigate within the course. For instance, learners high in extraversion tend to be extrinsically motivated. They therefore significantly navigated between viewing the course module and their personal achievements. The findings of this study can contribute to the adaptive learning field by providing insights about which personalization features can help learners with different personalities. The findings can also contribute to the field of automatic modeling of personality by providing information about differences in navigational behavior based on learners’ personalities.

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Section: Research Gap and The Purpose Of The Studymentioning

confidence: 99%

“… Tlili et al (2021) also applied LSA to examine the behavioral pattern differences among learners from either China, Tunisia or Serbia who enrolled in an online six-week course. Wang et al (2022) further applied LSA to investigate how gender might moderate learners’ online learning behavioral patterns.…”

Section: Introductionmentioning

confidence: 99%

Impact of personality traits on learners’ navigational behavior patterns in an online course: a lag sequential analysis approach

et al. 2023

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Pre-service student teachers’ metacognition in an online learning community: An epistemic network analysis

Zhao,

Wang,

2024

Educ Inf Technol

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Exploring the Effects and Inquiry Process Behaviors of Fifth-Grade Students Using Predict-Observe-Explain Strategy in Virtual Inquiry Learning

Zheng,

Bai,

Yang

et al. 2024

J Sci Educ Technol

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Temporal perspective on the gender-related differences in online learning behaviour

Abstract: Temporal perspective on the gender-related differences in online learning behaviour. Behaviour and Information Technology, Early online.

Cited by 5 publications

References 47 publications

Impact of personality traits on learners’ navigational behavior patterns in an online course: a lag sequential analysis approach

Impact of personality traits on learners’ navigational behavior patterns in an online course: a lag sequential analysis approach

Pre-service student teachers’ metacognition in an online learning community: An epistemic network analysis

Exploring the Effects and Inquiry Process Behaviors of Fifth-Grade Students Using Predict-Observe-Explain Strategy in Virtual Inquiry Learning

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