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Huang, Yun; Brusilovsky, Peter; Guerra, Julio; Koedinger, Kenneth; Schunn, Christian – Journal of Computer Assisted Learning, 2023
Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives:…
Descriptors: Intelligent Tutoring Systems, Coding, Programming, Skill Development
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Arguedas, Marta; Daradoumis, Thanasis – Journal of Computer Assisted Learning, 2021
There is a lack of studies that examine the role of a pedagogical agent on student development in a specific learning situation that involves psychological and cognitive preparatory activities in high school settings. We examined the effectiveness of pedagogical agent (APT) cognitive and affective feedback on learner motivation and well-being. We…
Descriptors: High School Students, Feedback (Response), Learning Motivation, Well Being
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Wang, Dongqing; Han, Hou – Journal of Computer Assisted Learning, 2021
With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further…
Descriptors: Learning Analytics, Educational Technology, Feedback (Response), Intelligent Tutoring Systems
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Hooshyar, D.; Ahmad, R. B.; Yousefi, M.; Yusop, F. D.; Horng, S.-J. – Journal of Computer Assisted Learning, 2015
Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…
Descriptors: Flow Charts, Intelligent Tutoring Systems, Educational Technology, Teaching Methods
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Karakostas, A.; Demetriadis, S. – Journal of Computer Assisted Learning, 2011
Research on computer-supported collaborative learning (CSCL) has strongly emphasized the value of providing student support of either fixed (e.g. collaboration scripts) or dynamic form (e.g. adaptive supportive interventions). Currently, however, there is not sufficient evidence corroborating the potential of adaptive support methods to improve…
Descriptors: Open Source Technology, Intelligent Tutoring Systems, Control Groups, Computer Assisted Instruction
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Alcoholado, C.; Nussbaum, M.; Tagle, A.; Gomez, F.; Denardin, F.; Susaeta, H.; Villalta, M.; Toyama, K. – Journal of Computer Assisted Learning, 2012
Single Display Groupware (SDG) allows multiple people in the same physical space to interact simultaneously over a single communal display through individual input devices that work on the same machine. The aim of this paper is to show how SDG can be used to improve the way resources are used in schools, allowing students to work simultaneously on…
Descriptors: Foreign Countries, Educational Technology, Computer Peripherals, Computer Software
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Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P. – Journal of Computer Assisted Learning, 2010
Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…
Descriptors: Electronic Learning, Guidance, Individualized Instruction, Computer Software
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Popescu, E. – Journal of Computer Assisted Learning, 2010
Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…
Descriptors: Electronic Learning, Undergraduate Students, Cognitive Style, Individualized Instruction
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De Smet, M.; Van Keer, H.; Valcke, M. – Journal of Computer Assisted Learning, 2008
Cross-age tutors were randomly assigned to one of the three tutor training conditions distinguished for the current study: (1) the labelling experimental condition, characterized by requirements to label their tutor interventions, based on the e-moderating model of Salmon; (2) the non-labelling experimental condition, focusing on tutor's acting…
Descriptors: Self Efficacy, Discussion Groups, Tutor Training, Tutors