Identifying learning style through eye tracking technology in adaptive learning systems

Guabassi, Inssaf El; Bousalem, Zakaria; Achhab, Mohammed Al; Jellouli, Ismail; Mohajir, Badr Eddine El

doi:10.11591/ijece.v9i5.pp4408-4416

Cited by 9 publications

(8 citation statements)

References 10 publications

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“…The use of virtual reality (VR) for conventional learning methods in various domains has a positive effect on Kolb's learning style [34] improvement of the learning process is the contribution of the self-formative paradigm to change the context and attitudes associated with lifelong learning, based on self-education and e-Learning. [35] Automatic detection of learning styles is an approach that detects student learning style preferences and then adjusts learning materials using the education system automatically Student learning styles vary widely such as hearing, seeing, taking notes, imagining, and visualizing among many others (Guabassi et al, 2019). Students are easier to explore learning skills such as the ability to focus on learning, the ability to think a lot, coordinate attention using their learning style, and understanding learning styles can help learn according to their strongest abilities.…”

Section: A Approach To Learning Through Digital Mediamentioning

confidence: 99%

“…The discrepancy between digital learning design and the psychological readiness of students can hinder the learning process [12]. Research on learning styles starts from identifying and making instructions, to the strategies used [4], [13], [14]. Therefore, this article identifies the development of digital media in determining learning styles.…”

Section: Introductionmentioning

confidence: 99%

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An Integrative Review: Application of Digital Learning Media to Developing Learning Styles Preference

Nurmalisa¹,

Sunyono²,

Yulianti³

et al. 2023

IJIET

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The future of online learning or cybergogy known by several terms, such as blended learning, flipped classroom, or hybrid is something that cannot be avoided. This compelling situation is not due to the COVID-19 pandemic alone but has become a necessity for every student from school to higher education. This article aims to analyze and explain understanding in education related to the concept of "digital media", and all student responses including "learning styles", and related concepts, by reviewing, and synthesizing the literature using in an integrative review. A total of 154 qualitative and quantitative articles published between 2000 and 2020 were reviewed. Based on the inclusion analysis, 25 articles reveal things related to "digital media" and the behavior of students' "learning style" responses and what digital learning media should be. Concerning what is embedded in digital media that can result in different reactions from one another, digital learning media should be made by considering the behavioral reactions of students' "learning style" responses. Applying various digital media such as online platforms or applications in learning should directly affect different learning styles in education. Learning variations should also be offered when the learning media is created and used.

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Section: A Approach To Learning Through Digital Mediamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Integrative Review: Application of Digital Learning Media to Developing Learning Styles Preference

Nurmalisa¹,

Sunyono²,

Yulianti³

et al. 2023

IJIET

View full text Add to dashboard Cite

show abstract

“…Conceptual errors [16] can be attributed to both individual misunderstandings and the influence of societal culture. Within society and the family, certain misinterpretations and concepts are transmitted, which can contribute to the development of conceptual errors in children [17]. Some teachers who do not continuously develop their knowledge and receive appropriate training may have a misunderstanding of certain concepts.…”

Section: Misconceptions In Mathematicsmentioning

confidence: 99%

Effectiveness of Multimedia and Virtual Environments in Light of the Conflict Strategy to Reduce Misconceptions in Mathematics among First-Year University Students

Alzubi

2023

Int. J. Emerg. Technol. Learn.

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The roots of misconceptions in mathematics among first-year students at Hashemite University can be traced back to a flaw in the foundation of their previous mathematics knowledge acquired over the course of their academic years. This flaw presents a significant challenge for them during their studies. This study aimed to determine the effectiveness of multimedia and virtual environments in reducing misconceptions in mathematics among first-year students at Hashemite University, based on the conflict strategy. The study sample consisted of a random cluster sample of 109 male and female students from Hashemite University. The researcher observed the students and recorded their test scores. The researcher conducted face-to-face interviews to collect data for the study and performed statistical analysis using the t-test. The results showed that the percentage of misconceptions in mathematics among firstyear students at the Hashemite University for types 1, 2, 3, 4, and 5, respectively, amounted to 23%, 8%, 13.8%, 14.7%, and 0%. And 13.8%. The study examined the effectiveness of multimedia and virtual environments in reducing misconceptions in mathematics among first-year students at Hashemite University, based on the conflict strategy.

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“…Currently, there are several learning style models being used, including Kolb, Felder-Silverman, VARK, and others. Felder-Silverman is the most commonly used model (Guabassi et al, 2019;Rasheed and Wahid, 2021a). There are two approaches to detecting learning styles: explicit recognition and implicit recognition (Zhang et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

“…The explicit approach predominantly involves the administration of questionnaires to individuals for assessing their learning style preferences (Rajkumar and Ganapathy, 2020;Wouters and van der Meulen, 2020;Marosan et al, 2022). On the other hand, the implicit approach encompasses a diverse range of modalities, such as analyzing learning behavior patterns (Rasheed and Wahid, 2021b;Yousef et al, 2021), monitoring eye movements during learning tasks (Guabassi et al, 2019;Mu et al, 2019), utilizing facial image analysis (Gambo et al, 2018), and employing Electroencephalogram (EEG) technology to measure brain activity (Anoor et al, 2020;Zhang et al, 2021b). These methodologies are constantly developing and have been extensively embraced by researchers in the ever-changing field of learning style detection.…”

Section: Introductionmentioning

confidence: 99%

Mapping Research Themes and Future Directions in Learning Style Detection Research: A Bibliometric and Content Analysis

Wijaya,

Setiawan,

Shapiai

2023

EJEL

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This study aims to provide a comprehensive overview of the current state and potential future research in learning style detection. With the increasing number and diversity of research in this area, a quantitative approach is necessary to map out current themes and identify potential areas for future research. To achieve this goal, a bibliometric and content analysis will be conducted to map out the existing research and identify emerging topics and directions for future research. The study analyzes 1074 bibliographic sources from Scopus and visualizes the results of the bibliometric analysis through co-occurrence and thematic map analysis using VOSviewer and BibliometriX software. Content analysis is then conducted based on the results of the co-occurrence analysis. The findings reveal a significant increase in publications and citations in the field, with popular research topics including classification, adaptive learning, and MOOCs, and the most frequently used learning style models being Felder-Silverman, VARK, and Kolb. Emerging research topics include the use of EEG signals, online learning, and feature extraction. Future research may focus on classification, intelligent tutoring systems, MOOCs, online learning, adaptive learning, and deep learning. This study provides valuable insights into the current and future research trends in learning style detection, which can support the development of adaptive e-learning systems, intelligent tutoring systems, and MOOCs. By identifying popular research topics and emerging areas of study, this research can guide the design and implementation of effective online learning environments. Additionally, the study advances the field of e-learning knowledge by providing a comprehensive overview of the most frequently used learning style models and potential research areas. It sheds light on the ongoing development of learning style detection research and the potential for future advancements in the field, ultimately contributing to the growth and improvement of e-learning practices.

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Identifying learning style through eye tracking technology in adaptive learning systems

Cited by 9 publications

References 10 publications

An Integrative Review: Application of Digital Learning Media to Developing Learning Styles Preference

An Integrative Review: Application of Digital Learning Media to Developing Learning Styles Preference

Effectiveness of Multimedia and Virtual Environments in Light of the Conflict Strategy to Reduce Misconceptions in Mathematics among First-Year University Students

Mapping Research Themes and Future Directions in Learning Style Detection Research: A Bibliometric and Content Analysis

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