NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Shian-Shyong Tseng; Tsung-Yu Yang; Wen-Chung Shih; Bo-Yang Shan – Interactive Learning Environments, 2024
In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…
Descriptors: Educational Games, Computer Security, Computer Science Education, Game Based Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Jiansheng; Lin, Yuyu; Sun, Mingzhu; Shadiev, Rustam – Interactive Learning Environments, 2023
This study examined whether socially shared regulation of learning (SSRL) enhances students' algorithmic thinking performance, promotes learning participation and improves students' learning attitudes through game-based collaborative learning. The students learned algorithmic knowledge and completed programing tasks using Kodu, a new visual…
Descriptors: Cooperative Learning, Game Based Learning, Educational Environment, Algorithms
Peer reviewed Peer reviewed
Direct linkDirect link
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
Jenks, Theodore G. – ProQuest LLC, 2022
The purpose of this action research was to implement a digital game development project and describe its effects on the performance and attitudes of eighth-grade students in a required computer science course at South Carolina School District Alpha. The following research questions were explored: (1) How does the game development project impact…
Descriptors: Middle School Students, Active Learning, Student Projects, 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