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Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
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Michailidis, Nikolaos; Kapravelos, Efstasthios; Tsiatsos, Thrasyvoulos – Interactive Learning Environments, 2022
Students' skilful use of self-regulatory learning strategies is becoming fundamental to the advent of blog-based learning. Moreover, the use of Interaction Analysis (IA) in studying the learning dynamics in Computer-Supported Collaborative Learning (CSCL) activities is on the increase, particularly aiming to support participants by means of IA…
Descriptors: Interaction Process Analysis, Student Motivation, Learning Strategies, Electronic 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