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Moussa, Nahla Mohamed Aly – ProQuest LLC, 2015
Today, adoption of innovative technology is an important subject for research and work. Recent research discussed the importance of integrating modern technology into teaching and learning environments in higher education settings (Aucoin, 2014; Fisher, Worley & Fernandez, 2012; Kajuna, 2009). Learning styles of individuals also play an…
Descriptors: Cognitive Style, Student Attitudes, Computer Attitudes, Technology Integration
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Huang, Yong-Ming – Australasian Journal of Educational Technology, 2015
The use of collaborative technologies in learning has received considerable attention in recent years, but few studies to date have examined the factors that affect sequential and global learners' intention to use such technologies. Previous studies have shown that the learners of different learning styles have different needs for educational…
Descriptors: Technology Uses in Education, Intention, Performance Factors, Sequential Learning
Bhrommalee, Panu – ProQuest LLC, 2011
Online learning provides learners with more convenient and flexible ways of learning than does a traditional learning environment. Many Thai universities have implemented online learning for their students despite a lack of knowledge and understanding about students' attitudes toward and behavioral intention to using the system. The purpose of…
Descriptors: Electronic Learning, Cognitive Style, Student Attitudes, Online Courses
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Zhang, Li-Fang; He, Yunfeng – Journal of Educational Computing Research, 2003
In the present study, the thinking styles as defined in Sternberg's theory of mental self-government are tested against yet another domain relevant to student learning. This domain is students' knowledge and use of as well as their attitudes toward the use of computing and information technology (CIT) in education. One hundred and ninety-three (75…
Descriptors: Foreign Countries, Educational Technology, Cognitive Style, Student Attitudes
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Moldafsky, Neil I; Kwon, Ik-Whan – Computers in Human Behavior, 1994
Reviews current literature about personal, demographic, situational, and cognitive attributes that affect computer-aided decision making. The effectiveness of computer-aided decision making is explored in relation to decision quality, effectiveness, and confidence. Studies of the effects of age, anxiety, cognitive type, attitude, gender, and prior…
Descriptors: Age, Cognitive Style, Computer Anxiety, Computer Attitudes
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Houle, Philip A. – Journal of Educational Computing Research, 1996
Describes a study that examined various characteristics of undergraduate students enrolled in a computer skills course. Variables considered include gender, college major, high school computer courses, other prior computer experience, computer self-efficacy, computer attitude, computer anxiety, and cognitive style. (Author/LRW)
Descriptors: Cognitive Style, Comparative Analysis, Computer Anxiety, Computer Attitudes
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Ross, Craig M.; Lukow, Jennifer E. – Journal of Scholarship of Teaching and Learning, 2004
The purpose of this study was to explore the relationship between learning styles and students' attitudes towards the use of technology in a leisure study curriculum. All 422 subjects completed the Kolb learning style inventory (LSI) and a computer attitudes survey (CAS) developed by the authors. The LSI is a standardized assessment utilized to…
Descriptors: Cognitive Style, Electronic Mail, Student Attitudes, Computer Attitudes
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Contreras, Carlos L. M. – Quarterly Review of Distance Education, 2004
Demographic and personality variables and computer use were used to predict computer self-confidence with a sample of students enrolled in online college-credit classes. Computer self-confidence was measured with one 10-choice question. Demographic variables included age, annual income, geographic region, gender, and ethnicity. Computer use was…
Descriptors: Income, Age Differences, Ethnic Groups, Gender Differences