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Goodridge, Wade H.; Lawanto, Oenardi; Santoso, Harry B. – International Education Studies, 2017
The implementation of a successful engineering program to a synchronous online curriculum is subject to many impacting factors. One such factor, that has not seen much investigation, concerns learning styles. Student learning styles may have a dramatic influence on the success of a synchronous online deliverable engineering graphics curriculum.…
Descriptors: Engineering Education, Computer Graphics, Delivery Systems, Online Courses
Kößler, Franziska J.; Nitzschner, Marco M. – Technology, Knowledge and Learning, 2015
Based on research about humor, foreign languages, and instructional design, in the current study we examined whether successful learning is related to using different types of media. We compared the comprehension of an economic concept in novices (N = 82) under three conditions: a Wikipedia article, a funny, and a serious YouTube video. The media…
Descriptors: English (Second Language), English Language Learners, Media Selection, Delivery Systems
Al-Dujaily, Amal; Kim, Jieun; Ryu, Hokyoung – Educational Technology & Society, 2013
A concern of computer-based learning system design is how to accommodate learners' individual differences during learning activities. Previous research suggests that adaptive e-learning systems can effectively address such individual differences and, consequently, they enable more directed tutoring via computer-assisted instruction. In this paper,…
Descriptors: Electronic Learning, Extraversion Introversion, Individual Differences, Learning Activities
Cimermanová, Ivana – Acta Didactica Napocensia, 2009
The article discusses the issue of e-learning courses as an alternative to traditional face-to-face courses or the support of the face-face courses. The main aim of the article is not to decide which alternative is more effective, but to find out whether there are students with particular learning style who are pre-disposed to e-learning. There…
Descriptors: Electronic Learning, Conventional Instruction, Intermode Differences, Learning Strategies
Lohman, Margaret C. – International Journal for the Scholarship of Teaching and Learning, 2007
The effects of three information distribution strategies in a course management system (CMS) on student performance and satisfaction were investigated. Analysis of the data found that the distribution of instructional materials in class resulted in significantly higher student performance on an end-of-the-semester technical knowledge test than…
Descriptors: Management Systems, Web Based Instruction, Information Dissemination, Communication Strategies

Reiff, Judith C. – Psychology: A Quarterly Journal of Human Behavior, 1986
Children were administered the Learning Style Inventory. Analysis revealed that children across sex, grade, and race had a majority of no preferences for the variables considered. The auditory approach was the least preferred learning mode by all groups. Specific diagnosis concerning modality strengths will contribute to a youngster's success in…
Descriptors: Academic Achievement, Educational Diagnosis, Elementary Education, Elementary School Students
Manochehri, Nasar; Young, Jon I. – Quarterly Review of Distance Education, 2006
This study compared the effects student learning styles with Web-based learning (WBL) and traditional instructor-based learning (ILB) on student knowledge and satisfaction. Learning methods (Web-based and instructor-based) and learning styles (Diverger, Converger, Assimilator, and Accommodator) were the independent variables. Student knowledge and…
Descriptors: Cognitive Style, Learning Strategies, Web Based Instruction, Conventional Instruction

Cordell, Barbara J. – Computers and Education, 1991
Describes study of health care employees that was designed to determine whether learning styles affect outcomes of learning with two computer-assisted instruction (CAI) design strategies, linear and branching. Use of the 4MAT Learning Styles Inventory is explained, and implications of the results for educators and courseware designers are…
Descriptors: Adult Learning, Analysis of Variance, Branching, Cognitive Style