Investigating Engineering Student Learning Style Trends by Using Multivariate Statistical Analysis

Abdelhadi, Abdelhakim; Ibrahim, Yasser E.; Nurunnabi, Mohammad

doi:10.3390/educsci9010058

Cited by 10 publications

(14 citation statements)

References 24 publications

(28 reference statements)

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“…This questionnaire lists the Course Learning Outcomes (CLOs) that the students have to utilize to assess their predefined CLOs. 15 Online learning overlaps with the concept of distance learning, which uses earlier technologies such as educational television and videoconferencing. Previous studies of distance learning concluded that these technologies were not significantly different from regular classroom learning in effectiveness.…”

Section: Significance For Public Healthmentioning

confidence: 99%

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Effect of COVID-19 pandemic on academic accreditation

Abdelhadi¹

2020

J Public Health Res

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Background: Higher education quality is an essential measurement for any country’s development, since education is a significant source of new sciences and its applications. This importance works as one of the cornerstones toward public health. The sudden change from traditional classroom teaching and learning to online education and learning process did not give educators the time to adjust the teaching material or, for that matter, did not give the program administrators the time to prepare for the needed documents toward the accreditation. This situation creates a dilemma for all members involved in certification. This research is addressing this issue from the accreditation point of view. Design: Brainstorming methodology is used to study the effect of COVID-19 pandemic on the academic/health accreditation. Methods: Cause and effect diagram (Fishbone diagram) is used to present the ideas presented by institutional participants related to the effect of COVID-19 on the accreditations processes. Conclusions: The study shows that COVID-19 pandemics have dramatic influence on accreditation processes, which may lead to change and/or adjust the rules and the requirements of the educational institutions due to changes in the fulfillment of the accreditation by the institutions during this period.

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Section: Significance For Public Healthmentioning

confidence: 99%

“…This questionnaire lists the Course Learning Outcomes (CLOs) that the students have to utilize to assess their predefined CLOs. 15 …”

Section: Introductionmentioning

confidence: 99%

Effect of COVID-19 pandemic on academic accreditation

Abdelhadi¹

2020

J Public Health Res

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“…FSLSM has been used to date in several studies involving learner behavior modeling in LMS such as Aissaoui et al. (2018) , Abdelhadi et al. (2019) , and Ferreira et al.…”

Section: Introductionmentioning

confidence: 99%

Identifying learning styles and cognitive traits in a learning management system

Lwande

Muchemi

Oboko

2021

Heliyon

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Investigating learner behavior is an increasingly important research topic in online learning. Learning styles and cognitive traits have been the subjects of research in this area. Although learning institutions use Learning Management Systems such as Moodle, Claroline, and Blackboard to facilitate teaching, the platforms do not have features for analyzing data and identifying behavior such as learning styles and cognitive traits. Instead, they only produce certain statistical reports from the daily access records. Even though complex models have been proposed in the literature, most studies are based on a single behavior such as learning styles or cognitive traits but not both. Only a few have investigated a combination of cognition-based theories such as working memory capacity and psychology-based ones such as learning styles. Thus, this study sought to answer the research question of whether it was possible to establish a methodology for the estimation of learning styles and cognitive traits from a learning management system. The study combined the Felder-Silverman Learning Style Model and Cognitive Trait Model as theoretical frameworks to identify behavior in a Learning Management System. This study designed a model for extracting records from Learning Management Systems access records to estimate learning style and cognitive traits. From this, a prototype was developed to estimate the learning style and cognitive traits for each student. The model was evaluated by administering manual tools to students in a classroom environment then comparing the results gathered against those estimated by the model. The results analyzed using Kappa statistics demonstrated the interrater reliability results were moderately in agreement. Taken together, these results suggest that it is possible to estimate the learning styles and cognitive traits of a learner in a Learning Management System. The information generated by the model can be used by tutors to provide a conducive online learning environment where learners with similar behavior ask each other for help. This can reduce the teaching load for online tutors because learners themselves act as a teaching resource. Information on learning styles and cognitive styles can also facilitate online group formation by isolating the individual factors that contribute to team success.

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“…Despite this, most of the research, which explored the effect of cognitive styles on individual performance, was focused on human resource implications within organizations, such as team performance, productivity, adaptability, and entrepreneurial attitude, to mention a few [12][13][14]. Cognitive style studies in engineering education are scarce and seem to focus on the student's cognitive level [15], cognitive operations [16], personality traits and mental skills [17], and learning styles [18]. Less at-tention was given to the role of a student's cognitive styles in their academic performance, especially in engineering education.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Styles, Gender, and Student Academic Performance in Engineering Education

Alalouch

2021

Education Sciences

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Cognitive styles affect the learning process positively if tasks are matched to the cognitive style of learners. This effect becomes more pronounced in complex education, such as in engineering. We attempted to critically assess the effect of cognitive styles and gender on students’ academic performance in eight engineering majors to understand whether a cognitive style preference is associated with certain majors. We used the Cognitive Style Indicator (CoSI) with a sample of n = 584 engineering students. Multiple standard statistical tests, regression tree analysis, and cluster analysis showed that none of the three cognitive styles was exclusively associated with better performance. However, students who had a stronger preference for a cognitive style were more likely to perform better. Gender, the major, and students’ clarity about their cognitive style were shown to be the best predictors of academic performance. Female students performed better and were clearer about their preferred cognitive style, whereas male students were more capable of adapting to different learning tasks. Furthermore, certain engineering majors were shown to be associated with certain cognitive styles. We concluded the study with theoretical and practical implications for engineering education and suggestions for further research.

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Investigating Engineering Student Learning Style Trends by Using Multivariate Statistical Analysis

Cited by 10 publications

References 24 publications

Effect of COVID-19 pandemic on academic accreditation

Effect of COVID-19 pandemic on academic accreditation

Identifying learning styles and cognitive traits in a learning management system

Cognitive Styles, Gender, and Student Academic Performance in Engineering Education

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