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Multazam, Muhammad; Syahrial, Zulfiati; Rusmono – Turkish Online Journal of Distance Education, 2023
Web programming courses are practical courses that can only run with the help of computer devices. The content or learning content in web programming courses is in program code directly created with a computer. The models developed include conceptual models, procedural models, and physical models. The research method used is Research and…
Descriptors: Computer Science Education, Programming, Models, Practicums
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Jyoti Wadmare; Dakshita Kolte; Kapil Bhatia; Palak Desai; Ganesh Wadmare – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper highlights an innovative and impactful online operating system algorithms e-learning tool in engineering education. Background: Common teaching methodologies make it difficult to teach complex algorithms of operating systems. This paper presents a solution to this problem by providing simulations of different complex…
Descriptors: Engineering, Science Education, Material Development, Computer Simulation
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Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
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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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Fleischer, Yannik; Biehler, Rolf; Schulte, Carsten – Statistics Education Research Journal, 2022
This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…
Descriptors: Statistics Education, Educational Research, Electronic Learning, Secondary School Students
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Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
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Schwarzenberg, Pablo; Navon, Jaime; Pérez-Sanagustín, Mar – Journal of Computing in Higher Education, 2020
The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers…
Descriptors: Models, Blended Learning, Teaching Methods, Electronic Learning
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Uto, Masaki; Nguyen, Duc-Thien; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2020
With the wide spread large-scale e-learning environments such as MOOCs, peer assessment has been popularly used to measure the learner ability. When the number of learners increases, peer assessment is often conducted by dividing learners into multiple groups to reduce the learner's assessment workload. However, in such cases, the peer assessment…
Descriptors: Item Response Theory, Electronic Learning, Peer Evaluation, Accuracy
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Wang, Lisa; Sy, Angela; Liu, Larry; Piech, Chris – International Educational Data Mining Society, 2017
Modeling student knowledge while students are acquiring new concepts is a crucial stepping stone towards providing personalized automated feedback at scale. We believe that rich information about a student's learning is captured within her responses to open-ended problems with unbounded solution spaces, such as programming exercises. In addition,…
Descriptors: Online Courses, Knowledge Level, Pedagogical Content Knowledge, Scaffolding (Teaching Technique)
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Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana – Australasian Journal of Educational Technology, 2018
This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…
Descriptors: Electronic Learning, Online Courses, Curriculum Development, Management Systems
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Sadeghi, Hamid; Kardan, Ahmad A. – Interactive Learning Environments, 2016
Group formation task as a starting point for computer-supported collaborative learning plays a key role in achieving pedagogical goals. Various approaches have been reported in the literature to address this problem, but none have offered an optimal solution. In this research, an online learning environment was modeled as a weighted undirected…
Descriptors: Foreign Countries, Cooperative Learning, Group Dynamics, Online Courses
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Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
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Cristobal, Jesus; Merino, Jorge; Navarro, Antonio; Peralta, Miguel; Roldan, Yolanda; Silveira, Rosa Maria – Interactive Technology and Smart Education, 2011
Purpose: The design, construction and deployment of a large virtual campus are a complex issue. Present virtual campuses are made of several software applications that complement e-learning platforms. In order to develop and maintain such virtual campuses, a complex software engineering infrastructure is needed. This paper aims to analyse the…
Descriptors: Electronic Learning, Engineering Education, Campuses, Programming Languages
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Miao, Yongwu; Hoppe, Heinz Ulrich – Learning, Media and Technology, 2011
Learning design is currently slanted to reflect a course-based approach to learning. This article explores whether the concept of learning design could be applied to support the informal aspects of work-based learning (WBL). It also discusses the characteristics of WBL and presents a WBL-specific learning design that highlights the key features…
Descriptors: Workplace Learning, Design Requirements, Business, Communities of Practice
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Jumaat, Nurul Farhana; Tasir, Zaidatun – Journal of Educational Computing Research, 2016
Scaffolding refers to a guidance that helps students during their learning sessions whereby it makes learning easier for them. This study aims to develop a framework of metacognitive scaffolding (MS) to guide students in learning Authoring System through Facebook. Thirty-seven master degree students who were enrolled in Authoring System course…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Programming, Computer Science Education
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