Learning style detection in E-learning systems using machine learning techniques

Rasheed, Fareeha; Wahid, Abdul

doi:10.1016/j.eswa.2021.114774

Cited by 93 publications

(55 citation statements)

References 36 publications

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“…Finally, the pink clusters showed searches related to artificial intelligence, machine learning, and deep learning. The researcher can also take these subfields as topics for research in e-learning, especially the last cluster, which formed a recent research trend for many scholars ( Bhardwaj et al, 2021 ; Kashive et al, 2021 ; Rasheed and Wahid, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

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E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis

et al. 2022

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This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within “e-learning in higher education.” E-learning as a concept has been widely used in the academic and professional communities and has been approved as an educational approach during COVID-19. This article starts with a literature review of e-learning. Diverse subjects have appeared on the topic of e-learning, which is indicative of the dynamic and multidisciplinary nature of the field. These include analyses of the most influential authors, of models and networks for bibliometric analysis, and progress towards the current research within the most critical areas. A bibliometric review analyzes data of 602 studies published (2020–2021) in the Web of Science (WoS) database to fully understand this field. The data were examined using VOSviewer, CiteSpace, and KnowledgeMatrix Plus to extract networks and bibliometric indicators about keywords, authors, organizations, and countries. The study concluded with several results within higher education. Many converging words or sub-fields of e-learning in higher education included distance learning, distance learning, interactive learning, online learning, virtual learning, computer-based learning, digital learning, and blended learning (hybrid learning). This research is mainly focused on pedagogical techniques, particularly e-learning and collaborative learning, but these are not the only trends developing in this area. The sub-fields of artificial intelligence, machine learning, and deep learning constitute new research directions for e-learning in light of COVID-19 and are suggestive of new approaches for further analysis.

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Section: Resultsmentioning

confidence: 99%

“…Finally, using artificial intelligence, machine learning, and deep learning to transform the e-learning Industry, this final sub-field formed a recent research trend for many scholars ( Bhardwaj et al, 2021 ; Kashive et al, 2021 ; Rasheed and Wahid, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis

et al. 2022

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“…With the development of digital technology today, it is easier and more accessible for students to connect to unlimited communication teacherstudent interaction equipped with internet support facilities (Pennings et al, 2018;Blaschke & Hase, 2019;Malhotra et al, 2020). With the use of technology in learning can facilitate student learning according to student characteristics Every student has different characteristics and types of learning styles (Lwande et al, 2021;Rasheed & Wahid, 2021). There are three kinds of learning styles, but each student's percentage is not the same, starting from the visual learning style, auditory and kinesthetic (Costa et al, 2020;Sari, 2014).…”

Section: Discussionmentioning

confidence: 99%

Mobile Counselling Online an Alternative Counselling Guidance System For Millennial Era Student

Fahyuni

Taurusta

Hariastuti

et al. 2021

j.of education technology

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This study analyses the counselling service system during the COVID-19 pandemic on introducing potential and preparation of learning strategies for junior and senior high school in the Sidoarjo district. This research design is a mixed-method with quantitative and qualitative approaches using exploratory factor analysis and further research and development (R&D) to produce products in online counselling guidance services. The results of the exploratory factor analysis qualitatively reveal various problems experienced and needed by students during the COVID-19 pandemic. In contrast, quantitatively, shows that eight forms of Counselling guidanceservices, the strengthening of skill skor 0.999 is the highest. Its effect on increasing students' self-efficacy and achievement motivation. The findings of this study indicate that students need online counselling services in recognizing their learning potential and problems. Hereafter, online counselling guidance must three factors: understanding the potential for effective learning, designing and developing learning strategies, and building students' internal and external motivation. The innovation of online counselling guidance must consider the factors of convenience, convenience, and user confidentiality services that are adaptive, flexible and unlimited in the millennial era.

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“…Every child has different characteristics (Duman, 2010;Lwande et al, 2021). Learning is carried out by paying attention to the differences in characteristics that an individual has (Mahasneh et al, 2021;Rasheed & Wahid, 2021).…”

Section: Discussionmentioning

confidence: 99%

English as a Foreign Language Lesson Plans During Covid-19 Pandemic in The Senior High School

Jayantari

Agustini

2021

JPBI

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Teachers have difficulties in preparing lesson plans that are adapted to online learning. This has resulted in students having difficulty learning English as a foreign language (EFL) through Google Classroom during the Covid-19 pandemic. The purpose of this study was to analyze the abilities and difficulties of teachers in preparing lesson plans and the difficulties of students in learning English as a foreign language (EFL) through Google Classroom during the Covid-19 pandemic. The design used in this research is the Embedded Mix Method design. The technique used to collect data is a questionnaire. The instrument used to collect data is a questionnaire. The population of this study found 10 teachers and 55 students. The ability of teachers to prepare lesson plans for EFL through Google Classroom is measured and described quantitatively. Meanwhile, the difficulties of teachers and students were described and analyzed qualitatively. The study results are the teacher's ability to prepare EFL lesson plans through Google Classroom, which is 67.50. It can be said that EFL teachers are less able to choose learning procedures or steps, choose learning media and evaluate learning. Students also have difficulty learning EFL through Google Classroom.

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Learning style detection in E-learning systems using machine learning techniques

Cited by 93 publications

References 36 publications

E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis

E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis

Mobile Counselling Online an Alternative Counselling Guidance System For Millennial Era Student

English as a Foreign Language Lesson Plans During Covid-19 Pandemic in The Senior High School

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