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Shou, Tianze; Borchers, Conrad; Karumbaiah, Shamya; Aleven, Vincent – International Educational Data Mining Society, 2023
Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…
Descriptors: Classroom Design, Accuracy, Validity, Space Utilization
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Kim, Yoon Jeon; Knowles, Mariah A.; Scianna, Jennifer; Lin, Grace; Ruipérez-Valiente, José A. – British Journal of Educational Technology, 2023
Game-based assessment (GBA), a specific application of games for learning, has been recognized as an alternative form of assessment. While there is a substantive body of literature that supports the educational benefits of GBA, limited work investigates the validity and generalizability of such systems. In this paper, we describe applications of…
Descriptors: Learning Analytics, Validity, Generalizability Theory, Game Based Learning
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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
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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Senkbeil, Martin – Education and Information Technologies, 2022
This study examined the incremental validity of different information and communication technologies (ICT)-related person characteristics over and above intelligence and and prior achievement when predicting ICT literacy across a period of three years. Relative weights analyses were performed to determine the relative contribution of each…
Descriptors: Technological Literacy, Information Technology, Validity, Individual Characteristics
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Calvo-Morata, Antonio; Rotaru, Dan Cristian; Alonso-Fernandez, Cristina; Freire-Moran, Manuel; Martinez-Ortiz, Ivan; Fernandez-Manjon, Baltasar – IEEE Transactions on Learning Technologies, 2020
Bullying is a serious social problem at schools, very prevalent independently of culture and country, and particularly acute for teenagers. With the irruption of always-on communications technology, the problem, now termed cyberbullying, is no longer restricted to school premises and hours. There are many different approaches to address…
Descriptors: Educational Games, Bullying, Computer Mediated Communication, Learning Analytics
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies