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Ward, W.; Cole, R.; Bolanos, D.; Buchenroth-Martin, C.; Svirsky, E.; Van Vuuren, S.; Weston, T.; Zheng, J.; Becker, L. – Grantee Submission, 2011
This paper describes My Science Tutor (MyST), an intelligent tutoring system designed to improve science learning by students in 3rd, 4th and 5th grades (7 to 11 years old) through conversational dialogs with a virtual science tutor. In our study, individual students engage in spoken dialogs with the virtual tutor Marni during 15 to 20 minute…
Descriptors: Elementary School Science, Elementary School Students, Science Education, Intelligent Tutoring Systems
Lee, Young-Jin – Journal of Educational Technology Systems, 2011
In the last decades, many education researchers have been trying to use computerized learning environments to enhance student learning. Without proper instructional supports and guidance, however, students often failed to acquire knowledge from computer-based learning activities. The objective of this study was to demonstrate how research-based…
Descriptors: Learning Activities, Formative Evaluation, Physics, Misconceptions
Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia – Journal of Educational Technology Systems, 2011
LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms…
Descriptors: Foreign Countries, Web Based Instruction, Distance Education, Intelligent Tutoring Systems
Ting, Choo-Yee; Phon-Amnuaisuk, Somnuk – Computers & Education, 2009
There has been an increasing interest in employing decision-theoretic framework for learner modeling and provision of pedagogical support in Intelligent Tutoring Systems (ITSs). Much of the existing learner modeling research work focuses on identifying appropriate learner properties. Little attention, however, has been given to leverage Dynamic…
Descriptors: Decision Support Systems, Computer Simulation, Intelligent Tutoring Systems, Computer Interfaces
Lane, H. Chad; Hays, Matthew Jensen; Core, Mark G.; Auerbach, Daniel – Journal of Educational Psychology, 2013
In the context of practicing intercultural communication skills, we investigated the role of fidelity in a game-based, virtual learning environment as well as the role of feedback delivered by an intelligent tutoring system. In 2 experiments, we compared variations on the game interface, use of the tutoring system, and the form of the feedback.…
Descriptors: Feedback (Response), Fidelity, Intercultural Communication, Communication Skills
Arroyo, Ivon; Burleson, Winslow; Tai, Minghui; Muldner, Kasia; Woolf, Beverly Park – Journal of Educational Psychology, 2013
We provide evidence of persistent gender effects for students using advanced adaptive technology while learning mathematics. This technology improves each gender's learning and affective predispositions toward mathematics, but specific features in the software help either female or male students. Gender differences were seen in the students' style…
Descriptors: Gender Differences, Educational Technology, Technology Uses in Education, Mathematics Instruction
Wang, Ya-huei; Liao, Hung-Chang – British Journal of Educational Technology, 2011
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is…
Descriptors: Cognitive Style, Learning Motivation, Learning Processes, Individualized Instruction
Klinkenberg, S.; Straatemeier, M.; van der Maas, H. L. J. – Computers & Education, 2011
In this paper we present a model for computerized adaptive practice and monitoring. This model is used in the Maths Garden, a web-based monitoring system, which includes a challenging web environment for children to practice arithmetic. Using a new item response model based on the Elo (1978) rating system and an explicit scoring rule, estimates of…
Descriptors: Test Items, Reaction Time, Scoring, Probability
Pavlik, Philip, Jr.; Toth, Joe – Online Submission, 2010
The plethora of different subfields in intelligent tutoring systems (ITS) are often difficult to integrate theoretically when analyzing how to design an intelligent tutor. Important principles of design are claimed by many subfields, including but not limited to: design, human-computer interaction, perceptual psychology, cognitive psychology,…
Descriptors: Intelligent Tutoring Systems, Interdisciplinary Approach, Design, Computer Interfaces
Chi, Min; VanLehn, Kurt – Educational Technology & Society, 2010
Certain learners are less sensitive to learning environments and can always learn, while others are more sensitive to variations in learning environments and may fail to learn (Cronbach & Snow, 1977). We refer to the former as high learners and the latter as low learners. One important goal of any learning environment is to bring students up…
Descriptors: Intelligent Tutoring Systems, Physics, Probability, Tutoring
Nugent, Rebecca; Ayers, Elizabeth; Dean, Nema – International Working Group on Educational Data Mining, 2009
In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of mastering. As the number of examinees, items, and skills increases, the estimation of even simple cognitive diagnosis models becomes difficult. We adopt a faster, simpler approach:…
Descriptors: Data Analysis, Students, Skills, Cluster Grouping
Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C. – Cognition, 2009
Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…
Descriptors: Intelligent Tutoring Systems, Animal Behavior, Reinforcement, Models
He, Yulan; Hui, Siu Cheung; Quan, Tho Thanh – Computers & Education, 2009
Summary writing is an important part of many English Language Examinations. As grading students' summary writings is a very time-consuming task, computer-assisted assessment will help teachers carry out the grading more effectively. Several techniques such as latent semantic analysis (LSA), n-gram co-occurrence and BLEU have been proposed to…
Descriptors: Semantics, Intelligent Tutoring Systems, Grading, Computer Assisted Testing
Pardos, Zachary A.; Dailey, Matthew D.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
The well established, gold standard approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pre-test and post-test design. RCTs have been used in the intelligent tutoring community for decades to determine which questions and tutorial feedback work best. Practically speaking, however,…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Pretests Posttests, Educational Research
Lee, Sungjin; Noh, Hyungjong; Lee, Jonghoon; Lee, Kyusong; Lee, Gary Geunbae; Sagong, Seongdae; Kim, Munsang – ReCALL, 2011
This study introduces the educational assistant robots that we developed for foreign language learning and explores the effectiveness of robot-assisted language learning (RALL) which is in its early stages. To achieve this purpose, a course was designed in which students have meaningful interactions with intelligent robots in an immersive…
Descriptors: Second Language Learning, Robotics, Speech Skills, Listening Skills

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