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Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
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Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Jeff Bender – ProQuest LLC, 2023
At an unrivaled and enduring pace, computing has transformed the world, resulting in demand for a universal fourth foundation beyond reading, writing, and arithmetic: computational thinking (CT). Despite increasingly widespread acceptance of CT as a crucial competency for all, transforming education systems accordingly has proven complex. The…
Descriptors: Addictive Behavior, Game Based Learning, Evaluation Methods, Computation
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Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
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Mao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics