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

Tlili, Ahmed; Sun, Tianyue; Denden, Mouna; Kinshuk, Kinshuk; Graf, Sabine; Fei, Cheng; Wang, Huanhuan

doi:10.3389/fpsyg.2023.1071985

Cited by 4 publications

(1 citation statement)

References 71 publications

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“…Intimately connected to the qualms of students rationale of familiarity to a significant education cultural community in online and mixed education communities is the qualms of student's observation of their self-learner personality (Dennen and Arslan, 2022). Based on Tlili (2023), the establishment of learner personality is engrossed in with agency and emotions of being in authority stemming from emotions of familiarity to an education cultural community. They additionally assert that the growth of a robust and imperative online personality plays a significant functional function for student reservation and inducement in online education programs.…”

Section: Social Spaces Education Cultural Community and Student Socia...mentioning

confidence: 99%

Sociology of E-Learning: A Social Observational Trek at Universities in Freetown, Sierra Leone

Bangura

2024

EJCEEL

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Social e-learning is acquiring several solid grounds in University enlightenment right through the universe and Sierra Leone not an exception. Recently, a generous amount of universities globally promote social e-learning in divergent shapes. Despite this extensive embracement of social e-learning in university tutelage, sociological inquiry on social e-learning approbation proposes that it has not accomplished its maximum implicit. This sociological inquiry converses the privileges that prevail and demurrers that obstruct the thriving embracement of social e-learning automation as a social norm of tutelage at designated universities in Freetown, Sierra Leone. The sociological verdicts and observations accommodated are anticipated to reinforce universities evolve their social e-learning approaches. The respondents of this inquiry are university lecturers who are commencing to utilize social e-learning. The resultants denote that social e-learning at greater of the universities is still at its conception pulpit. This sociological inquiry unmasks a multitude of considerations or rationales for the restricted attainments, which are associated to architectural growth, advance and didactical reflections for e-learning. Universities are financing further and upgrading organizational operating system at the cost of Erudition Oversight Customs (EOC) operating system that bolsters instruction and education or scholarship. This sociological inquiry proposes that competent advancement or businesslike programs with underscore on e-learning didactics besides the formulation of social e-learning facilitate constructions should be championed.

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Section: Social Spaces Education Cultural Community and Student Socia...mentioning

confidence: 99%

Sociology of E-Learning: A Social Observational Trek at Universities in Freetown, Sierra Leone

Bangura

2024

EJCEEL

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Impact of ML-LA feedback system on learners’ academic performance, engagement and behavioral patterns in online collaborative learning environments: A lag sequential analysis and Markov chain approach

Yildiz Durak

2024

Educ Inf Technol

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Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing online learning behaviors, it is unclear how the effectiveness of this feedback translates into online learning experiences. The current study aims to compare the behavioral patterns of online system engagement of students who receive and do not receive machine learning-based temporal learning analytics (ML-LA) feedback, to identify the differences between student groups in terms of learning performance, online engagement, and various system usage variables, and to examine the behavioral patterns change over time of students regarding online system engagement. The current study was conducted with the participation of 49 undergraduate students. The study defined three engagement levels using system usage analytics and cluster analysis. While t-test and ANCOVA were applied to pre-test and post-test scores to evaluate students’ learning performance and online engagement, lag sequential analysis was used to analyze behavioral patterns, and the Markov chain was used to examine the change of behavioral patterns over time. The group receiving ML-LA feedback showed higher behavior and cognitive engagement than the control group. In addition, the rate of completing learning tasks was higher in the experimental group. Temporal patterns of online engagement behaviors across student groups are described and compared. The results showed that both groups used all stages of the system features. However, there were some differences in the navigation rankings. The most important behavioral transitions in the experimental group are task and discussion viewing and posting, task posting updating, and group performance viewing. In the control group, the most important behavioral transitions are the relationship between viewing a discussion and making a discussion, then this is followed by the sequential relationship between viewing individual performance and viewing group performance. The results showed that students’ engagement behaviors transitioned from light to medium and intense throughout the semester, especially in the experimental group. For learning designers and researchers, this study can help develop a deep understanding of environment design.

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Opening up the gamification black box: effects of students’ personality traits and perception of game elements on their engaged behaviors in a gamified course

Denden,

Tlili,

Salha

et al. 2023

Tech Know Learn

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

Cited by 4 publications

References 71 publications

Sociology of E-Learning: A Social Observational Trek at Universities in Freetown, Sierra Leone

Sociology of E-Learning: A Social Observational Trek at Universities in Freetown, Sierra Leone

Impact of ML-LA feedback system on learners’ academic performance, engagement and behavioral patterns in online collaborative learning environments: A lag sequential analysis and Markov chain approach

Opening up the gamification black box: effects of students’ personality traits and perception of game elements on their engaged behaviors in a gamified course

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