A study of learning styles and computer-assisted instruction (original) (raw)
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Journal of Physics: Conference Series, 2019
This study aims at identifying student learning styles in the Faculty of Communication and Informatics. Web-based applications are built as a system to determine visual, auditory, read/write, or kinesthetic (VARK) learning styles. The Version 7.1 questionnaire has been applied as a basic instrument. Test data was obtained from a sample of 230 students. System performance is tested by applying black-box testing and testing the validity of alpha-beta on each system module. Meanwhile, the survey method is used to assess the feasibility of application design. Based on a series of observations, tests, and analysis it can be concluded that of 230 students, 27% had visual learning styles, 16% hearing, 14% reading and writing, and 43% kinesthetic. Based on the results of this study, it can be concluded that students have diverse learning style preferences so that educators must adjust learning strategies by providing appropriate learning media and learning instruments in teaching classes.
A model for the evaluation of learning styles design effectiveness
Assessing the customized system of a formative path, on the basis of cognitive styles, needs two fundamental requirements: a) the choice of a strong learning design model, built on conceptual maps, didactic objective trees and observable behaviours taxonomies (Bloom, Anderson, Romiszowski and Marzano); b) the utilisation of the Kolb Learning Style Inventory to evaluate the preferences individuals show in the learning context.
The purpose of this study is to calculate the effect size, by running a meta-analysis, of the experimental studies carried out in Turkey between 2004 and 2014 that investigate the effect of learning styles on academic achievement, attitude, retention, and to define whether the academic achievement shows a significant difference in terms of learning styles model, experimental design and course type. For this purpose, a metaanalytical review method was employed to combine the outcome of the independent experimental studies. The studies included in this review were collected from CoHE National Thesis Archive (2015), ULAKBIM (2015), Google Academic (2015), ERIC (2015) and EBSCO (2015) databases. As a result of the searching process, 402 studies were assessed according to the inclusion criteria and 30 experimental studies were included in this study. Cohen' s d coefficient was calculated for the effect size in this study. Because there was a high amount of heterogeneity (Q > x 2 , p < .05) among the effect sizes of the studies, the common effect size was calculated according to the random effect model. As a result of meta-analysis, it was determined that the instructional designs based on the learning styles model had a large effect on the academic achievement (d = 1.029), attitude (d = 1.113) and retention (d = 1.290). Moreover, the academic achievement did not show any significant difference according to learning style model, course type and experimental design.
A Psychometric Study of the Index of Learning Styles©
Journal of Engineering Education, 2007
A study was conducted on the Felder-Soloman Index of Learning Styles © (ILS) to assess reliability, factor structure, and construct validity as well to determine whether changing its dichotomous response scale to a five-option response scale would improve reliability and validity. Data collected in this study had internal consistency reliability ranging from 0.55 to 0.77 across the four learning style scales of the ILS. Factor analysis revealed that multiple factors were present within three of the learning style scales, which correspond to known aspects of the scale definitions. The factor analysis and direct feedback from students on whether they felt their scores accurately represented their learning preferences provide evidence of construct validity for the ILS. Changing the response scale improved reliability, but it did not change the factor structure substantially nor did it affect the strength of the evidence for construct validity based on student feedback.
Learning Style Instruments: Implications of Content
International Journal of Sustainable Energy Development, 2017
Research into the use of information technology in computing-based education has indicated that students have different abilities, needs and learn in different ways. Following a review of learning styles. This study depends on new learning style instrument, which was constructed using Visual and Active forms of information such as figures, charts and equations rather than depending only on textual information. In a sample of six Masters Students, the learning style of participants was measured twice, once by the VARK questionnaire and once by the developed instrument, which uses both visual and active forms of information. The results of both approaches were compared and an interview with each participant has been conducted to further investigate the outcomes. The results of this study showed that there were significant differences among student preferences of learning. They also revealed that using visual and active content for constructing the learning style instruments has a significant effect on the measured preferred learning style of students.
A Validity and Reliability of Learning Style Instruments Using e-LeS Online Web Based System
wseas.us
The reliability of an instrument developed to measure the learning styles is essential to find out learners' learning styles ability. An electronic learning style (e-LeS) was developed to measure students' individual learning styles (LeS). The purpose of this research was to produce empirical evidence of validity and reliability by using Rasch Model of 6 learning styles constructs; Competitive, Collaborative, Avoidant, Participative, Dependent and Independent. A survey was conducted to 185 postgraduate students from a Malaysian Institute of Teachers Training (ITT). Statistical analysis using Winsteps software was selected to measure the validity and reliability of the 60 items and the results showed the reliability of LeS items was between 0.96 and 0.99. Results from the analysis showed that the separation index items were all above 2 and values of the polarity items indicated all positive values. Infit and Outfit MNSQ ranged 0.6 to 1.4 were produced for the purpose of removing and retaining items. Finally Rasch Model analysis has dropped 7 items from the 60 items. The Rasch Measurement Model has proven highest degree of validity and reliability in measuring LeS items of learning styles.
learning styles followed by the methodology used in this study in section 3. The evaluation of the survey and the discussion of the model are given in sections 4 and 5 respectively. The section 6 provides information on the proposed model and section 7 provides the limitations of the model. Finally the section 8 concludes the paper with general recommendation on the Influences of Learning Styles on Learners in E-Learning Environments Abstract— E-learning tools as an emerging technology has changed the process of higher education dramatically influencing learners' learning style in various ways. Learning styles is the ways of people learn and it has become an important topic for researchers recently. The main purpose of this research is to analyze influences of learning styles in e-learning environment at universities. This paper will provide an overview of learning styles of different learners based on the knowledge of Felder and Silverman learning style model based on the survey conducted using the different type of learners in the university E-learning environment. Further, this paper proposes a developed framework of the E-learning environment of higher education students. II. LEARNING STYLE " Learning style " can be defined in a variety of ways. Keefee (1979) defines learning style as typical psychological and affective behavior that serve as a reasonably stable indicator of how individuals perceive, respond to and interact with learning environment [5], Reid 1995 characterized learning style as favored way of taking in processing and maintaining new information and skills [1]. Riechmann and Grasha (1974) defined learning style as a personal quality that influences a student's ability to perceive information, to work with peers and teachers [7]. Felder and Silverman defined learning style as grouping student according to the number of scales relating to the ways they receive and process information [8] [1]. Many researchers have developed learning style models with their own assessment instruments in the forms of questionnaires that include various types of question on learner personality, attitude and behavior. For example, Kolb learning style consists of 12 items to rank 12 sentences describing how the learner best learns [8]. The learning style model chosen in this study is Felder-Silverman learning style (FSLS)[9]. Felder and Silverman's index of learning styles is one of the best learning style models about learners' learning styles, the model is commonly used in most of the research related to this area.