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Showing all 12 results Save | Export
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Aakriti Kumar; Aaron S. Benjamin; Andrew Heathcote; Mark Steyvers – npj Science of Learning, 2022
Practice in real-world settings exhibits many idiosyncrasies of scheduling and duration that can only be roughly approximated by laboratory research. Here we investigate 39,157 individuals' performance on two cognitive games on the Lumosity platform over a span of 5 years. The large-scale nature of the data allows us to observe highly varied…
Descriptors: Comparative Analysis, Computational Linguistics, Learning Processes, Computer Games
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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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Aditya Anupam; Ridhima Gupta; Shubhangi Gupta; Zhendong Li; Nora Hong; Azad Naeemi; Nassim Parvin – International Journal of Designs for Learning, 2020
The abstract nature of quantum mechanics makes it difficult to visualize. This is one of the reasons it is taught in the language of mathematics. Without an opportunity to directly observe or interact with quantum phenomena, students struggle to develop conceptual understandings of its theories and formulas. In this paper we present the process of…
Descriptors: Quantum Mechanics, Science Instruction, Educational Games, Teaching Methods
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
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…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
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Lamb, Richard L. – Journal of Science Education and Technology, 2016
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the…
Descriptors: Cognitive Processes, Computation, Models, Science Laboratories
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Skewes, Joshua C; Jegindø, Else-Marie; Gebauer, Line – Autism: The International Journal of Research and Practice, 2015
Autistic people are better at perceiving details. Major theories explain this in terms of bottom-up sensory mechanisms or in terms of top-down cognitive biases. Recently, it has become possible to link these theories within a common framework. This framework assumes that perception is implicit neural inference, combining sensory evidence with…
Descriptors: Autism, Neurological Impairments, Neurology, Perception
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Proske, Antje; Roscoe, Rod D.; McNamara, Danielle S. – Educational Technology Research and Development, 2014
Achieving sustained student engagement with practice in computer-based writing strategy training can be a challenge. One potential solution is to foster engagement by embedding practice in educational games; yet there is currently little research comparing the effectiveness of game-based practice versus more traditional forms of practice. In this…
Descriptors: Educational Games, Computer Games, Student Motivation, Academic Achievement
Proske, Antje; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2014
Achieving sustained student engagement with practice in computer-based writing strategy training can be a challenge. One potential solution is to foster engagement by embedding practice in educational games; yet there is currently little research comparing the effectiveness of game-based practice versus more traditional forms of practice. In this…
Descriptors: Educational Games, Computer Games, Student Motivation, Academic Achievement
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Chaves, Rafael Oliveira; von Wangenheim, Christiane Gresse; Furtado, Julio Cezar Costa; Oliveira, Sandro Ronaldo Bezerra; Santos, Alex; Favero, Eloi Luiz – IEEE Transactions on Education, 2015
Software process modeling (SPM) is an important area of software engineering because it provides a basis for managing, automating, and supporting software process improvement (SPI). Teaching SPM is a challenging task, mainly because it lays great emphasis on theory and offers few practical exercises. Furthermore, as yet few teaching approaches…
Descriptors: Computer Software, Computer Science Education, Student Projects, Teaching Methods
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Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers