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Latham, Annabel; Crockett, Keeley; McLean, David; Edmonds, Bruce – Computers & Education, 2012
This paper proposes a generic methodology and architecture for developing a novel conversational intelligent tutoring system (CITS) called Oscar that leads a tutoring conversation and dynamically predicts and adapts to a student's learning style. Oscar aims to mimic a human tutor by implicitly modelling the learning style during tutoring, and…
Descriptors: Cognitive Style, Teaching Methods, Cognitive Measurement, Prediction
Huang, Eugenia Y.; Lin, Sheng Wei; Huang, Travis K. – Computers & Education, 2012
Learning style is traditionally assumed to be a predictor of learning performance, yet few studies have identified the mediating and moderating effects between the two. This study extends previous research by proposing and testing a model that examines the mediating processes in the relationship between learning style and e-learning performance…
Descriptors: Electronic Learning, Undergraduate Students, Cognitive Style, Computer Mediated Communication
Huang, Chenn-Jung; Wang, Yu-Wu; Huang, Tz-Hau; Chen, Ying-Chen; Chen, Heng-Ming; Chang, Shun-Chih – Computers & Education, 2011
Recent research indicated that students' ability to construct evidence-based explanations in classrooms through scientific inquiry is critical to successful science education. Structured argumentation support environments have been built and used in scientific discourse in the literature. To the best of our knowledge, no research work in the…
Descriptors: Electronic Learning, Feedback (Response), Persuasive Discourse, Teaching Load
Tseng, J. C. R.; Chu, H. C.; Hwang, G. J.; Tsai, C. C. – Computers & Education, 2008
Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization…
Descriptors: Cognitive Style, Instructional Design, Computer Software, Individualized Instruction
Lau, Wilfred W. F.; Yuen, Allan H. K. – Computers & Education, 2010
It has been advocated that pedagogical content knowledge as well as subject matter knowledge are important for improving classroom instructions. To develop pedagogical content knowledge, it is argued that understanding of students' mental representations of concepts is deemed necessary. Yet assessing and comparing mental model of each individual…
Descriptors: Identification, Mathematics Instruction, Pedagogical Content Knowledge, Cognitive Style
Chen, Ling-Hsiu – Computers & Education, 2011
Although conventional student assessments are extremely convenient for calculating student scores, they do not conceptualize how students organize their knowledge. Therefore, teachers and students rarely understand how to improve their future learning progress. The limitations of conventional testing methods indicate the importance of accurately…
Descriptors: Foreign Countries, Educational Technology, Cognitive Style, Self Efficacy
Schiaffino, Silvia; Garcia, Patricio; Amandi, Analia – Computers & Education, 2008
In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student's behavior while he/she is taking online courses and automatically builds the student's profile. This profile comprises the student's learning style and information about the student's performance, such…
Descriptors: Cognitive Style, Distance Education, Online Courses, Profiles
Ozpolat, Ebru; Akar, Gozde B. – Computers & Education, 2009
A desirable characteristic for an e-learning system is to provide the learner the most appropriate information based on his requirements and preferences. This can be achieved by capturing and utilizing the learner model. Learner models can be extracted based on personality factors like learning styles, behavioral factors like user's browsing…
Descriptors: Cognitive Style, Classification, Measures (Individuals), Measurement Techniques
Blake, M. Brian; Butcher-Green, Jerome D. – Computers & Education, 2009
Training individuals from diverse backgrounds and in changing environments requires customized training approaches that align with the individual learning styles and ever-evolving organizational needs. Scaffolding is a well-established instructional approach that facilitates learning by incrementally removing training aids as the learner…
Descriptors: Familiarity, Adult Learning, Simulated Environment, Trainees
Faraco, G.; Gabriele, L. – Computers & Education, 2007
Simulations make it possible to explore physical and biological phenomena, where conducting the real experiment is impracticable or difficult. The implementation of a software program describing and simulating a given physical situation encourages the understanding of a phenomenon itself. Fifty-nine students, enrolled at the Mathematical Methods…
Descriptors: Mathematical Models, Computer Software, Computer Simulation, Engineering Education

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