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Abarkan, Ali; BenYakhlef, Majid – Education and Information Technologies, 2022
Learning to code is far from an easy task, it is a promising approach that underscores the use of the video game culture of students to motivate them to invest their time in the practice of programming. The students in this discipline are often discouraged by the amount of information to remember and the complex and constraining syntaxes.…
Descriptors: Programming Languages, Educational Games, Computer Games, Learning Motivation
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Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
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Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
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Mashood, K. K.; Khosla, Kamakshi; Prasad, Arjun; V., Sasidevan; Ashefas CH, Muhammed; Jose, Charles; Chandrasekharan, Sanjay – Physical Review Physics Education Research, 2022
Recent educational policies advocate a radical revision of science curricula and pedagogy, to support interdisciplinary practices, a distinguishing feature of contemporary science. Computational modeling (CM) is a core methodology of interdisciplinary science, as such models allow intertwining of data and theoretical perspectives from multiple…
Descriptors: Teaching Methods, Undergraduate Students, Science Instruction, Science Curriculum
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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
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Molina, Ana I.; Arroyo, Yoel; Lacave, Carmen; Redondo, Miguel A. – British Journal of Educational Technology, 2018
The incorporation of advanced information and communication technologies into the field of education has made the design and deployment of courses and instructional units more and more complicated. In order to support such complex task, methods and techniques have been proposed in the last years for the standardization, formalization and modelling…
Descriptors: Programming Languages, Models, Cooperative Learning, Learning Processes
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Maruyama, Ryoga; Ogata, Shinpei; Kayama, Mizue; Tachi, Nobuyuki; Nagai, Takashi; Taguchi, Naomi – International Association for Development of the Information Society, 2022
This study aims to explore an educational learning environment that supports students to learn conceptual modelling with the unified modelling language (UML). In this study, we call the describing models "UML programming." In this paper, we show an educational UML programming environment for science, technology, engineering, art, and…
Descriptors: Case Studies, Programming Languages, Learning Processes, Models
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Knauf, Rainer; Sakurai, Yoshitaka; Tsuruta, Setsuo; Jantke, Klaus P. – Journal of Educational Computing Research, 2010
University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…
Descriptors: Prerequisites, College Instruction, Educational Experiments, Cognitive Style
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Najjar, Mehdi – International Journal of Distance Education Technologies, 2008
Despite a growing development of virtual laboratories which use the advantages of multimedia and Internet for distance education, learning by means of such tutorial tools would be more effective if they were specifically tailored to each student needs. The virtual teaching process would be well adapted if an artificial tutor can identify the…
Descriptors: Scaffolding (Teaching Technique), Virtual Classrooms, Prompting, Teaching Methods
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Rodriguez-Artacho, Miguel; Verdejo Maillo, M. Felisa – Educational Technology & Society, 2004
This paper presents a reference framework to describe educational material. It introduces the PALO Language as a cognitive based approach to Educational Modeling Languages (EML). In accordance with recent trends for reusability and interoperability in Learning Technologies, EML constitutes an evolution of the current content-centered…
Descriptors: Learning Processes, Standards, Teaching Methods, Instructional Materials