scholarly journals A STUDY ON LEARNING STYLES AND THEIR POSSIBLE EFFECT ON ACADEMIC PERFORMANCE AMONG UNIVERSITY STUDENTS IN GLASGOW

2018 ◽  
Vol 4 (2) ◽  
pp. 27-44
Author(s):  
Ma Li ◽  
◽  
Ahmed Alduais ◽  
2019 ◽  
Author(s):  
Harry Minas

Abstract Objective: There has been increased attention in recent years to mental health, quality of life, stress and academic performance among university students, and the possible influence of learning styles. Brief reliable questionnaires are useful in large-scale multivariate research designs, such as the largely survey-based research on well-being and academic performance of university students. The objective of this study was to examine the psychometric properties of a briefer version of the 39-item Adelaide Diagnostic Learning Inventory. Results: In two survey samples - medical and physiotherapy students - a 21-item version Adelaide Diagnostic Learning Inventory - Brief (ADLIB) was shown to have the same factor structure as the parent instrument, and the factor structure of the brief instrument was found to generalise across students of medicine and physiotherapy. Sub-scale reliability estimations were in the order of magnitude of the parent instrument. Sub-scale inter-correlations, inter-factor congruence coefficients, and correlations between ADLIB sub-scale scores and several external measures provide support support for the construct and criterion validity of the instrument.


Author(s):  
Jorge Muñoz-Mederos ◽  
Elizabeth Acosta-Gonzaga ◽  
Elena Fabiola Ruiz-Ledesma ◽  
Aldo Ramírez-Arellano

Author(s):  
Marta Nieves Espericueta-Medina ◽  
Lilia Sánchez-Rivera ◽  
Blanca Margarita Villarreal-Soto ◽  
Vivian Ortíz-Torres

The present investigation, Learning Styles in different dimensions will be addressed according to The Inventory Learning Processes (ILP), (Schmeck et al., 1977; Schmeck and Ribich, 1978). The objective is to know the factors that make up the axes: academic performance and learning styles of the university students of the Mexican Republic, in addition to the attributes that make them up. We worked with a sample of 253 subjects. The information was processed by means of the descriptive analysis from frequencies and percentages, comparative with Student's t-test for independent groups and with integrative, exploratory factor analysis.It is an exploratory and descriptive quantitative, synchronous and transversal investigation t is indicated that the characteristics that identify young people such as: gender, age, city, state, institution, career, average, among others, influence the academic performance of students. In this way, the factors that affect student learning are presented. A summarized panorama of the research is presented: One of the conclusions is that, in trend, university students have a good academic performance, according to the study method, being the population of women with the most significant opinion. Likewise, it is observed that the variables that have greater objectivity which will give an educational innovation through factors. Finally, the innovative strategies that have emerged through the study phenomenon will be presented.


2020 ◽  
Author(s):  
Harry Minas

Abstract Objective: There has been increased attention in recent years to mental health, quality of life, stress and academic performance among university students, and the possible influence of learning styles. Brief reliable questionnaires are useful in large-scale multivariate research designs, such as the largely survey-based research on well-being and academic performance of university students. The objective of this study was to examine the psychometric properties of a briefer version of the 39-item Adelaide Diagnostic Learning Inventory. Results: In two survey samples - medical and physiotherapy students - a 21-item version Adelaide Diagnostic Learning Inventory - Brief (ADLIB) was shown to have the same factor structure as the parent instrument, and the factor structure of the brief instrument was found to generalise across students of medicine and physiotherapy. Sub-scale reliability estimations were in the order of magnitude of the parent instrument. Sub-scale inter-correlations, inter-factor congruence coefficients, and correlations between ADLIB sub-scale scores and several external measures provide support support for the construct and criterion validity of the instrument.


This paper describes how to improve the academic performance of engineering university students through an Adaptive Educational Hypermedia System (AEHS). The psychological basis, learning styles and MOOMH methodology for the development of the system are exposed, which with its implementation achieves adaptability and works for students as an “intelligent tutor”, allowing them to guide their education as academic tutor. Not only shows its content that meets the needs of the student, but it is also represented in elements such as color adaptation, work tools and even academic recommendations based on the interactions that the user makes within the system, the system recognizes its pattern of use, and when the student is logged in again, it presents a friendlier interface that the student prefers use, it is wider in content and, above all, easy to use and understand. In addition, the AEHS allows to extend education allowing the assignment of more domain areas, in the field of engineering, that is, the SHAE can be adapted to various engineering specialties such as: industrial, software, telecommunications, mechanics and other.


2019 ◽  
Vol 9 (2) ◽  
pp. 184 ◽  
Author(s):  
Gilbert Magulod

In order to better prepare university students as proficient, versatile and productive information and industrial technologists in the 21st century, the need to implement instructional strategies and activities naturally align with their predispositions will make them better learners. This study examined the learning style preferences, study habits and level of academic achievement of students enrolled in applied science courses of Cagayan State University at Lasam, Philippines.  The study employed descriptive correlational research design to a total of seventy-five respondents who were purposively sampled. Two sets of standardized instruments were utilized by the researcher. Results of the study revealed that the students of applied sciences courses preferred visual, group and kinesthetic as major learning styles while they manifest a moderate level of study habits. They also have a good level of academic achievement. Test of difference revealed that academic performance, father's occupation and type of high school graduated from spelled significant differences in their perceptual learning styles. They also spelled differences in their study habits when grouped according to academic standing in high school, writing skills, mothers’ education, and test anxiety. Finally, there were significant relationships between learning styles, study habits and academic performance of students in applied science courses. The implications of the study can guide instructors plan and deliver suitable instructional interventions.


This paper describes how to improve the academic performance of engineering university students through an Adaptive Educational Hypermedia System (AEHS). The psychological basis, learning styles and MOOMH methodology for the development of the system are exposed, which with its implementation achieves adaptability and works for students as an “intelligent tutor”, allowing them to guide their education as academic tutor. Not only shows its content that meets the needs of the student, but it is also represented in elements such as color adaptation, work tools and even academic recommendations based on the interactions that the user makes within the system, the system recognizes its pattern of use, and when the student is logged in again, it presents a friendlier interface that the student prefers use, it is wider in content and, above all, easy to use and understand. In addition, the AEHS allows to extend education allowing the assignment of more domain areas, in the field of engineering, that is, the SHAE can be adapted to various engineering specialties such as: industrial, software, telecommunications, mechanics and other.


2015 ◽  
pp. 103-115 ◽  
Author(s):  
Lucky Sibanda ◽  
Chux Gervase Iwu ◽  
Olumide Henrie Benedict

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