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Tetsuo Tanaka; Ryo Horiuchi; Mari Ueda – International Association for Development of the Information Society, 2024
We evaluate the effectiveness of reading aloud a program code in learning programming from a neuroscientific perspective by measuring brain activity using a near-infrared spectroscopy device. The results show that when reading aloud and then reading silently, brain activity increases during reading aloud; a similar trend is observed when the…
Descriptors: Oral Reading, Programming, Coding, Neurosciences
Ma, Yingbo; Katuka, Gloria Ashiya; Celepkolu, Mehmet; Boyer, Kristy Elizabeth – International Educational Data Mining Society, 2022
Collaborative learning is a complex process during which two or more learners exchange opinions, construct shared knowledge, and solve problems together. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. If intelligent systems could predict…
Descriptors: Middle School Students, Cooperative Learning, Prediction, Peer Relationship
Tanaka, Tetsuo; Ueda, Mari – International Association for Development of the Information Society, 2023
In this study, the authors have developed a web-based programming exercise system currently implemented in classrooms. This system not only provides students with a web-based programming environment but also tracks the time spent on exercises, logging operations such as program editing, building, execution, and testing. Additionally, it records…
Descriptors: Scores, Prediction, Programming, Artificial Intelligence
Marwan, Samiha; Shi, Yang; Menezes, Ian; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2021
Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…
Descriptors: Expertise, Models, Feedback (Response), Identification
Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
Orr, J. Walker; Russell, Nathaniel – International Educational Data Mining Society, 2021
The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…
Descriptors: Programming Languages, Feedback (Response), Units of Study, Computer Science Education
Imai, Yoshiro; Imai, Masatoshi; Moritoh, Yoshio – International Association for Development of the Information Society, 2013
This paper presents trial evaluation of a visual computer simulator in 2009-2011, which has been developed to play some roles of both instruction facility and learning tool simultaneously. And it illustrates an example of Computer Architecture education for University students and usage of e-Learning tool for Assembly Programming in order to…
Descriptors: Computer Simulation, Teaching Methods, Cooperative Learning, Programming
Lane, Forrest C.; Henson, Robin K. – Online Submission, 2010
Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…
Descriptors: Quasiexperimental Design, Research Methodology, Educational Research, Scores
Zhang, Yanwei; Breithaupt, Krista; Tessema, Aster; Chuah, David – Online Submission, 2006
Two IRT-based procedures to estimate test reliability for a certification exam that used both adaptive (via a MST model) and non-adaptive design were considered in this study. Both procedures rely on calibrated item parameters to estimate error variance. In terms of score variance, one procedure (Method 1) uses the empirical ability distribution…
Descriptors: Individual Testing, Test Reliability, Programming, Error of Measurement
Myers, J. Paul, Jr.; Munsinger, Brita – 1996
This paper investigates the relationship between learning style and programming achievement in two paradigms: imperative and functional. An imperative language achieves its effect by changing the value of variables by means of assignment statements while functional languages rely on evaluation of expressions rather than side-effects. Learning…
Descriptors: Achievement Gains, Cognitive Style, Computer Science Education, Correlation