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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
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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
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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
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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
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