scholarly journals LEARNING STYLE DETECTION USING K-MEANS CLUSTERING

2020 ◽  
Vol 4 (3) ◽  
pp. 375-381
Author(s):  
Mubaraka Sani Ibrahim
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Learning Styles ◽  
Unsupervised Learning ◽  
Learning Style ◽  
Educational System ◽  
Learning Experience ◽  
Experimental Results ◽  
Online Learning Environment ◽  
Learning Methods

Learning theorist established the fact that learners are characterized according to their distinct learning styles. Investigating learners' learning style is important in the educational system in order to provide adaptivity and improve learning experience. Past researches have proposed various approaches to detect learning styles. Among unsupervised learning methods, the K-means clustering has emerged as a widely used method to predict patterns in data because of its simplicity. This paper evaluates the performance of K-means clustering in automatically detecting learners’ learning style in an online learning environment. The experimental results prove differences in learning thus characterizing learners based on learning style.

An Investigation of the Effect of Learning Style on Student Success in an Online Learning Environment

2000 ◽  
Vol 28 (3) ◽  
pp. 231-238 ◽  
Author(s):  
Steven R. Terrell ◽  
Laurie Dringus
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Learning Styles ◽  
Learning Style ◽  
Graduation Rate ◽  
Information Science ◽  
Demographic Data ◽  
Drop Out ◽  
Online Learning Environment ◽  
Learning Style Inventory

Ninety-eight information science students were tracked during an online masters degree program. At their initial orientation, each student completed a demographic data form and the Kolb Learning Style Inventory. Because of their major, it was hypothesized that students would fall into Kolb's Converger and Assimilator categories and these learning styles would be predictive of success in the program. Results indicated that 79.6 percent ( n = 78) of all students graduated from the program. Seventy-three students (74.5%) fell into the predicted categories and maintained an 83.6 percent ( n = 61) graduation rate. Students not falling into the predicted categories maintained a 68 percent ( n = 17) graduation rate. The implications are clear. First, the majority of students can succeed in an online learning environment regardless of their learning style. Care has to be taken, however, since a trend existed in this study for students with learning styles different from predicted to drop out in higher numbers. Institutions offering online programs should be aware of this and be prepared to address learning style issues.

scholarly journals An ESL Online Classroom Experience in Oman during Covid-19

2020 ◽  
Author(s):  
Syerina Syahrin ◽  
Abdelrahman Abdalla Salih
Keyword(s):  
Online Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Undergraduate Students ◽  
Learning Experience ◽  
Online Classroom ◽  
Learning Platform ◽  
E Learning ◽  
Learning Styles Inventory ◽  
The Relationship

This paper aimed to investigate the online learning experience of a group of ESL students at a higher learning institution in Oman during the Covid-19. The paper studied the interaction between the students’ preferred online learning style and the technologies the students experienced on the e-learning platform (Moodle) for the particular ESL course. The rationale for investigating the relationship between the students’ learning styles and the technologies the students experienced is to evaluate if the learning style and the technologies complement each other. It is also aimed to provide an evaluation of an ESL e-learning course by considering the different technologies that can be incorporated into the e-learning classroom to meet the different learning styles. Data was gathered from 32 undergraduate students by utilizing Kolb’s Learning Styles Inventory. The study included analysis of Moodle utilizing Warburton’s Technologies in Use (2007) to develop an understanding of the technologies the students experienced online. The results of the study revealed that the majority of the students’ preferred learning style is reflected in the technologies they experienced in the online classroom. As the relationship of the technology in use and the students learning style preference in the classroom complements each other, the study revealed that the emphasis of the particular skill-based pedagogy ESL classroom is on receptive skills (listening and reading). The lack of the students’ productive skills (speaking and writing) is a cause for concern to the ESL course instructors, policymakers, and the wider community.

Big Five Personality in Online Learning and Games

2016 ◽  
Vol 7 (3) ◽  
pp. 33-46 ◽  
Author(s):  
Peter Krátky ◽  
Jozef Tvarožek ◽  
Daniela Chudá
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Learning Style ◽  
Individual Student ◽  
Online Learning Environment ◽  
Big Five Personality ◽  
Effective Learning ◽  
Learning Content ◽  
Student’S Performance ◽  
Programming Courses

Online learning gives promise of effective learning for masses. Personalized learning experiences tailored for individual needs and preferences of each student are key ingredients in making online learning successful. Current approaches to adaptive and personalized online learning use student's personality profile and preferred learning style to adapt learning content and activities in order to provide the best possible experience to each individual student. Research has shown that effects on different types of learning activities in various settings may be different. This study analyses how personality affects student's performance in an online learning environment for programming exercises and how the student's personality can be estimated unobtrusively using a casual online game. The data used to evaluate were collected from an online learning environment used in university programming courses over the course of several years. The activity indicators show significant correlations with overall academic results of students and particularly with personality traits.

scholarly journals Factors affecting student behavioural engagement in an inquiry-based online learning environment

2021 ◽  
Author(s):  
Md Abdullah Al Mamun ◽  
Gwen Lawrie
Keyword(s):  
Online Learning ◽  
Student Engagement ◽  
Learning Environment ◽  
Learning Environments ◽  
Learning Experience ◽  
Independent Study ◽  
Online Learning Environment ◽  
Online Environment ◽  
Inquiry Based Learning ◽  
Behavioural Engagement

Abstract The technological innovations and changing learning environments are influencing student engagement more than ever before. These changing learning environments are affecting the constructs of student behavioural engagement in the online environment and require scrutiny to determine how to facilitate better student learning outcomes. Specifically, the recent literature is lacking in providing insights into how students engage and interact with online content in the self-regulated environment, considering the absence of direct teacher support. This paper investigates how instructional design, informed by the factors relating to behavioural engagement, can influence the student-content interaction process within the fabric of inquiry-based learning activities. Two online learning modules on introductory science topics were developed to facilitate students’ independent study in an asynchronous online environment. The study revealed that students showed high commitment to engage and complete the tasks that required less manipulative, pro-active effort during the learning process. The findings also revealed that instructional guidance significantly improved the behavioural engagement for student groups with prior learning experience and technology skills. This study highlights several issues concerning student engagement in a self-directed online learning environment and offers possible suggestions for improvement. The findings might contribute to informing the practice of teachers and educators in developing online science modules applicable to inquiry-based learning.

Smart ProFlexLearn

2004 ◽  
pp. 66-83 ◽  
Author(s):  
Claude Ghaoui ◽  
W. A. Janvier
Keyword(s):  
Online Learning ◽  
World Wide Web ◽  
Learning Environment ◽  
Real World ◽  
World Wide ◽  
Learning Experience ◽  
Online Learning Environment ◽  
Virtual University ◽  
The World ◽  
Real World Learning

This chapter is based on the authors’ vision that “A virtual university should be, to the learner, a distance or online learning environment that can be transmitted via the World Wide Web by an intelligent tool that is intuitive to use, a simulation of the real-world learning experience and, at all stages, interacts with the learner’s changing profile.”

Successful Strategies in the Online Learning Environment Based on Theories, Styles, and Characteristics

2010 ◽  
pp. 451-468
Author(s):  
Leane B. Skinner
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Learning Styles ◽  
Curriculum Design ◽  
Effective Model ◽  
Online Learning Environment ◽  
Online Student ◽  
Continuous Increase ◽  
Decision Styles ◽  
The Impact

With the continuous increase in online student enrollment, it is important to examine the learning/teaching process in the online learning environment in order to develop the most effective model in this unique environment. This chapter will explore various e-learner and e-educator styles and teaching strategies in the online environment. Theories and an evaluation of their appropriateness in an online learning environment will be presented. The impact of learning styles, social styles, decision styles, and generational styles in the online learning environment will be analyzed. Additionally, there will be a discussion of the characteristics and traits of the successful e-learner, successful e-educator, and successful course and curriculum design model based on specific theories and styles.

Sign in / Sign up

Export Citation Format

Share Document