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Horwitz, Paul; Reichsman, Frieda; Lord, Trudi; Dorsey, Chad; Wiebe, Eric; Lester, James – Technology, Knowledge and Learning, 2023
Studies of educational games often treat them as "black boxes" (Black and Wiliam in Phi Delta Kappan 80: 139-48, 1998; Buckley et al. in Int J LearnTechnol 5:166-190, 2010; Buckley et al. in J Sci Educ Technol 13: 23-41, 2010) and measure their effectiveness by exposing a treatment group of students to the game and comparing their…
Descriptors: Educational Games, Genetics, Middle School Students, High School Students
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Henderson, Nathan; Acosta, Halim; Min, Wookhee; Mott, Bradford; Lord, Trudi; Reichsman, Frieda; Dorsey, Chad; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2022
Stealth assessment in game-based learning environments has demonstrated significant promise for predicting student competencies and learning outcomes through unobtrusive data capture of student gameplay interactions. However, as machine learning techniques for student competency modeling have increased in complexity, the need for substantial data…
Descriptors: Evaluation Methods, Game Based Learning, Educational Environment, Learning Strategies
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Mutch-Jones, Karen; Boulden, Danielle C.; Gasca, Santiago; Lord, Trudi; Wiebe, Eric; Reichsman, Frieda – Educational Technology Research and Development, 2021
Research on the use of digital games suggests they can enhance students' learning; however, teachers often play an important role in mediating gameplay and a game's educational goals. The purpose of the study was to investigate implementation approaches of nine biology teachers using an immersive digital game in their science classes, focusing on…
Descriptors: Computer Games, Game Based Learning, Teaching Methods, Science Instruction
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Min, Wookhee; Frankosky, Megan H.; Mott, Bradford W.; Rowe, Jonathan P.; Smith, Andy; Wiebe, Eric; Boyer, Kristy Elizabeth; Lester, James C. – IEEE Transactions on Learning Technologies, 2020
A distinctive feature of game-based learning environments is their capacity for enabling stealth assessment. Stealth assessment analyzes a stream of fine-grained student interaction data from a game-based learning environment to dynamically draw inferences about students' competencies through evidence-centered design. In evidence-centered design,…
Descriptors: Game Based Learning, Student Evaluation, Artificial Intelligence, Models
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Henderson, Nathan; Kumaran, Vikram; Min, Wookhee; Mott, Bradford; Wu, Ziwei; Boulden, Danielle; Lord, Trudi; Reichsman, Frieda; Dorsey, Chad; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2020
In recent years, game-based learning has shown significant promise for creating engaging and effective learning experiences. Developing models that can predict whether students will struggle with mastering certain concepts could guide adaptive support to assist students with mastering those concepts. Game-based learning environments offer…
Descriptors: Competency Based Education, Game Based Learning, Student Evaluation, Evaluation Methods
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Rachmatullah, Arif; Reichsman, Frieda; Lord, Trudi; Dorsey, Chad; Mott, Bradford; Lester, James; Wiebe, Eric – Journal of Science Education and Technology, 2021
This study examined students' genetics learning in a game-based environment by exploring the connections between the expectancy-value theory of achievement motivation and flow theory. A total of 394 secondary school students were recruited and learned genetics concepts through interacting with a game-based learning environment. We measured their…
Descriptors: Models, Secondary School Students, Genetics, Game Based Learning