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Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
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Yang, Yanxia; Wang, Xiangling – Interactive Learning Environments, 2023
Machine translation post-editing (MTPE) has become a common practice in translation industry, which calls much attention in academia. However, little research has been carried out to investigate students' cognitive and motivational individual differences in MTPE. The purpose of the present study was to examine the predictive effects of…
Descriptors: Translation, Computational Linguistics, Second Languages, Language Usage
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Doyle, Elaine; Buckley, Patrick – Interactive Learning Environments, 2022
While research and practice centred around students and academics working together to co-create in the higher level sector has increased, co-creation in assessment remains relatively rare in a higher education context. It is acknowledged in the literature that deeper comprehension of content can be realised when students author their own questions…
Descriptors: Multiple Choice Tests, Student Participation, Test Construction, Academic Achievement
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Kwon, Kyungbin; Shin, Suhkyung; Brush, Thomas A.; Glazewski, Krista D.; Edelberg, Thomas; Park, Su Jin; Khlaif, Zuheir; Nadiruzzaman, Hamid; Alangari, Husa – Interactive Learning Environments, 2018
This study examined the types of learning behaviors students demonstrated while performing inquiry tasks. It also explored the relationship between the learning behaviors and students' domain knowledge. We observed fourteen students in five groups during a ninth-grade biology course. Three types of learning behaviors (inquiry, collaborative, and…
Descriptors: Inquiry, Problem Based Learning, Cooperative Learning, Grade 9
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Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse – Interactive Learning Environments, 2016
Well-designed game-based learning can provide students with an innovative environment that may enhance students' motivation and engagement in learning and thus improve their learning performance. The purpose of this study was to examine the relationships among elementary school students' flow experience and learning performances. We also…
Descriptors: Foreign Countries, Elementary School Students, Educational Games, Learning Processes
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Camacho-Miñano, María-del-Mar; del Campo, Cristina – Interactive Learning Environments, 2016
Many university lecturers are encouraged to implement innovative teaching tools and methodologies such as clickers in order to create an interactive learning environment and improve student learning, but its performance must be evaluated. The aim of this paper is to test empirically the impact of the use of clickers on students' learning…
Descriptors: Audience Response Systems, Student Motivation, Classroom Techniques, Feedback (Response)
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Cheng, Kun-Hung; Hou, Huei-Tse; Wu, Sheng-Yi – Interactive Learning Environments, 2014
In the social interactions among individuals of learning communities, including those individuals engaged in peer assessment activities, emotion may be a key factor in learning. However, research regarding the emotional response of learners in online peer assessment activities is relatively scarce. Detecting learners' emotion when they make…
Descriptors: Online Courses, Electronic Learning, Peer Evaluation, Emotional Response
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Shin, Dong-Hee; An, Hyeri; Kim, Jang Hyun – Interactive Learning Environments, 2016
The use of a second screen can enhance information processing and the execution of search tasks within a given period. In this study, we examined the learner's attentional shift (AS) between two screens and controlled secondary tasks (STs) in the media multitasking setting and its effect on the learning process. In particular, we analyzed how…
Descriptors: Cognitive Processes, Search Strategies, Attention Control, Learning Processes
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Joo, Young Ju; Joung, Sunyoung; Kim, Jiyeon – Interactive Learning Environments, 2014
Learning persistence in a cyber-learning environment is not only an index determining the success or failure of individual learners but also a source of important information to establish the management direction of educational programs in an organization. Accordingly, learners need to be motivated to continue to grow in order to ensure both…
Descriptors: Virtual Universities, Online Courses, Independent Study, Satisfaction
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Tirado, Ramón; Hernando, Ángel; Aguaded, José Ignacio – Interactive Learning Environments, 2015
Interactive relationships in online learning communities can influence the process and quality of knowledge building. The aim of this study is to empirically investigate the relationships between network structures and social knowledge building in an asynchronous writing environment through discussion forums in a learning management system. The…
Descriptors: Foreign Countries, Educational Technology, Electronic Learning, Computer Assisted Instruction
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Shute, Valerie J.; Glaser, Robert – Interactive Learning Environments, 1990
Presents an evaluation of "Smithtown," an intelligent tutoring system designed to teach inductive inquiry skills and principles of basic microeconomics. Two studies of individual differences in learning are described, including a comparison of knowledge acquisition with traditional instruction; hypotheses tested are discussed; and the…
Descriptors: Artificial Intelligence, Cluster Analysis, Comparative Analysis, Computer Assisted Instruction