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Qi Wang; Shengquan Yu – Interactive Learning Environments, 2024
Learning resources are quite important for online learning while resource provision based on algorithms could not address learners' ubiquitous needs well. Moreover, the structure and content of resources are pre-defined which makes the "Structure" and "Content" coupled closely and could not easily adjust when learners' needs…
Descriptors: Electronic Learning, Educational Resources, Automation, Models
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Silvia Wen-Yu Lee; Jyh-Chong Liang; Chung-Yuan Hsu; Meng-Jung Tsai – Interactive Learning Environments, 2024
While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…
Descriptors: Student Attitudes, Beliefs, Computer Science Education, Programming
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Hwang, Wu-Yuin; Hariyanti, Uun; Chen, Nian-Shing; Purba, Siska Wati Dewi – Interactive Learning Environments, 2023
The purpose of this study is to develop and validate an authentic contextual learning framework with six constructs to model the relationships among essential factors of authentic contextual learning. In particular, this framework explores the relationships across six constructs, i.e. learning by applying, healthy learning, collaborative learning,…
Descriptors: Authentic Learning, Models, Experiential Learning, Cooperative Learning
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Poitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science Instruction
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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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Clark, Douglas B.; Sengupta, Pratim – Interactive Learning Environments, 2020
This paper situates a critical review of studies that we have conducted within the broader research literature to analyze the affordances of integrating modeling within disciplinarily-integrated games from computational thinking and science as practice perspectives. Across the studies, the analyses pursue two themes: (a) the role of agent-based…
Descriptors: Game Based Learning, Thinking Skills, Computer Games, Science Education
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Hong, Jon-Chao; Hwang, Ming-Yueh; Liu, Yeu-Ting; Lin, Pei-Hsin; Chen, Yi-Ling – Interactive Learning Environments, 2016
Educational games can be viewed in two ways, "learning to play" or "playing to learn." The Chinese Idiom String Up Game was specifically designed to examine the effect of "learning to play" on the interrelatedness of players' gameplay interest, competitive anxiety, and perceived utility of pre-game learning (PUPGL).…
Descriptors: Educational Games, Prediction, Anxiety, Competition
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Blau, Ina; Peled, Yehuda; Nusan, Anat – Interactive Learning Environments, 2016
One-to-one (1X1) laptop initiatives become prevalent in schools aiming to enhance active learning and assist students in developing twenty-first-century skills. This paper reports a qualitative investigation of all 7th graders and their 15 teachers in a junior high-school in Northern Israel gradually implementing 1X1 model. The research was…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Qualitative Research, Access to Computers
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Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Kuo, Yen-Chun – Interactive Learning Environments, 2016
Consequential reasoning relevant to moral development has not been effectively practised in elementary schools in Taiwan. The present study designed a "To Do or Not To Do" website for students to explore moral dilemma situations and exercise consequence-based moral reasoning. Effective data from 160 fifth-grade students were collected…
Descriptors: Foreign Countries, Grade 5, Elementary School Students, Web Sites
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Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design