Dimension of Learning Styles and Students’ Academic Achievement

Omar, Norasyikin; Mohamad, Mimi Mohaffyza; Paimin, Aini Nazura

doi:10.1016/j.sbspro.2015.08.130

Cited by 38 publications

(34 citation statements)

References 2 publications

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“…Araştırmalar, e-öğrenme ortamlarında öğrencilerin bireysel farklılıklarına ve öğrenme özelliklerine dikkat ederek sınıf içi etkinlikleri düzenlemenin, öğrenmenin kalitesini ve öğrencilerin akademik başarılarını artırmada önemli bir rol oynadığını ortaya koymuştur (Jahanbakhsh, 2012;Omar, Mohamad, & Paimin, 2015;Veznedaroğlu & Özgür, 2005). Tulbure (2011), öğrencilerin öğrenme stillerine göre hazırlanmış bir öğretimin akademik başarıyı arttırdığını ve öğrencilerin öğrenme sonuçlarını, derse karşı tutumlarını, öğrenmeye ilişkin güdülenmelerine katkı sağladığını belirtmektedir.…”

Section: Introductionunclassified

E-öğrenme Ortamlarında Öğrenme Stilleri ve Akademik Başarı Arasındaki İlişkinin İncelenmesi

Ergün

Kurnaz

2019

Kuramsal Eğitimbilim

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In this study, the effects of students learning styles on academic achievement was investigated in elearning environments and the answer for the question "are e-learning style, participation in online course and watching the lecture videos offline predictors of academic achievement?" is tried to examined. E-Learning Style Scale (Gülbahar and Alper, 2014) and Achievement Test were applied 501 (350 female and 151 male) students who received pedagogical formation education in e-learning environment during the 2016-2017 academic year. The research was carried out online with learning management systems in the measurement and assessment course for 14 weeks. The certificate of pedagogical formation was given to students at the end of the course. The Achievement Test developed by researchers. This test was tested in another group similar to the study group and found reliable and valid results. The scores obtained from this test were accepted as a measure of academic achievement. Data were analyzed by stepwise multiple regression analyses. According to the results, participation in online course, watching video recordings, active learning style and independent learning style were found as predictors of students' academic achievement. These four variables account for 7% of the total variance in academic achievement.

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Section: Introductionunclassified

E-öğrenme Ortamlarında Öğrenme Stilleri ve Akademik Başarı Arasındaki İlişkinin İncelenmesi

Ergün

Kurnaz

2019

Kuramsal Eğitimbilim

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“…In addition, numerous hypotheses and multiple taxonomies attempting to describe how people reason and learn have been proposed, arranging individuals into distinct groups. Moreover, as indicated by Omar et al [8], different learning style instruments to research and pedagogical purposes have been produced. From FSLSM theory, there are four dimensions that describe learning styles: processing, perception, input, and understanding.…”

Section: Learning Styles Model Selectionmentioning

confidence: 99%

Use of Deep Multi-Target Prediction to Identify Learning Styles

2020

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Featured Application: Our results can be applied to identifying of students' learning style providing adaptation to e-learning systems.Abstract: It is possible to classify students according to the manner they recognize, process, and store information. This classification should be considered when developing adaptive e-learning systems. It also creates a comprehension of the different styles students demonstrate while in the process of learning, which can help adaptive e-learning systems offer advice and instructions to students, teachers, administrators, and parents in order to optimize students' learning processes. Moreover, e-learning systems using computational and statistical algorithms to analyze students' learning may offer the opportunity to complement traditional learning evaluation methods with new ones based on analytical intelligence. In this work, we propose a method based on deep multi-target prediction algorithm using Felder-Silverman learning styles model to improve students' learning evaluation using feature selection, learning styles models, and multiple target classification. As a result, we present a set of features and a model based on an artificial neural network to investigate the possibility of improving the accuracy of automatic learning styles identification. The obtained results show that learning styles allow adaptive e-learning systems to improve the learning processes of students.

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“…The findings show that excellent and weak students have different learning habits. Meanwhile, the results obtained by (Omar, Mohamad, & Paimin, 2015) show that the various factors of the study program affect the student learning style. However, in this study, researchers are more focused on large areas of mechanical engineering with four small programs in them.…”

Section: Problem Statementmentioning

confidence: 99%

Relationship between motivation, learning habit and overall results of polytechnic mechanical engineering student

Khathri

Daud

2018

JCET

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Motivation and learning habit generally play an important role in influential the results of a student's exam. This study aims to determine the relationship between motivations, learning habit and overall achievement in the second semester of Mechanical Engineering students at Terengganu Polytechnic. The study also aims to identify the differences in learning by gender at early achievement in the previous semester. To achieve this goal, the method of survey is conducted. Samples consisted of 196 students in second semester out of four programs in Mechanical Engineering Department. The study instrument used was Selmes Learning Inventory which presented four learning styles, namely deep-style, surface-style, well-organized style and diligent. The fifth style of learning, motivational style has been modified to measure the internal and external motivation. Data collected were analyzed descriptively and inferred using SPSS software. The results of the descriptive analysis found that students had high internal motivation as compared to external motivation as well as practicing surface style and deeper style than planned and diligent style. Inferential analysis results found that the overall achievement of the second semesters had a relationship with the in-depth learning style, effort and planning. There is a significant relationship between deep learning style and internal motivation. There was no significant difference in learning habit by gender and early achievement. The implication of this study is that motivation plays an important role in determining the choice of learning methods practiced by the students.

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Dimension of Learning Styles and Students’ Academic Achievement

Cited by 38 publications

References 2 publications

E-öğrenme Ortamlarında Öğrenme Stilleri ve Akademik Başarı Arasındaki İlişkinin İncelenmesi

E-öğrenme Ortamlarında Öğrenme Stilleri ve Akademik Başarı Arasındaki İlişkinin İncelenmesi

Use of Deep Multi-Target Prediction to Identify Learning Styles

Relationship between motivation, learning habit and overall results of polytechnic mechanical engineering student

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