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Slaviša Radovic; Niels Seidel; Joerg M. Haake; Regina Kasakowskij – Journal of Computer Assisted Learning, 2024
Background: Self-assessment serves to improve learning through timely feedback on one's solution and iterative refinement as a way to improve one's competence. However, the complexity of the self-assessment process is widely recognized, as well as that students can benefit from it only if their assessment is accurate enough. Objectives: In order…
Descriptors: Self Evaluation (Individuals), Distance Education, Student Behavior, Accuracy
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Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2022
The challenge of learning programming in a MOOC is twofold: acquiring programming skills and learning online, independently. Automated testing and feedback systems, often offered in programming courses, may scaffold MOOC learners by providing immediate feedback and unlimited re-submissions of code assignments. However, research still lacks…
Descriptors: Automation, Feedback (Response), Student Behavior, MOOCs
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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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Dina A. Zekry; Gerard T. McKee – International Association for Development of the Information Society, 2023
The paper explores current learning approaches. The authors present the Trigger-Based Discussion-Oriented Continuous learning model (TbDoC) that focuses on creating a continuous learning experience over the online and off-line (on-campus) learning environments. The model aims to create a more engaging learning environment that encourages…
Descriptors: Discussion (Teaching Technique), Independent Study, Teaching Models, Electronic Learning
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Hsu, Ting-Chia; Abelson, Hal; Patton, Evan; Chen, Shih-Chu; Chang, Hsuan-Ning – International Journal of Computer-Supported Collaborative Learning, 2021
In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software…
Descriptors: Self Efficacy, Behavior Patterns, Student Behavior, Programming
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Ozan Rasit Yürüm; Soner Yildirim; Tugba Taskaya-Temizel – Interactive Learning Environments, 2023
The purpose of this study is to develop an intervention framework based on video clickstream interactions for delivering superior user experience for video lectures. Apart from existing studies on data-driven interventions, this study focuses on video clickstream interactions to identify timely interventions for creating interactive video…
Descriptors: Video Technology, Computer Assisted Instruction, Intervention, Lecture Method
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Ramos, David Brito; Ramos, Ilmara Monteverde Martins; Gasparini, Isabela; Teixeira de Oliveira, Elaine Harada – International Journal of Distance Education Technologies, 2021
This work presents a new approach to the learning path model in e-learning systems. The model uses data from the database records from an e-learning system and uses graphs as representation. In this work, the authors show how the model can be used to represent visually the learning paths, behavior analysis, help to suggest group formation for…
Descriptors: Electronic Learning, Models, Graphs, Integrated Learning Systems
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Kokoç, Mehmet; Kara, Mehmet – Educational Technology & Society, 2021
The purposes of the two studies reported in this research are to adapt and validate the instrument of the Evaluation Framework for Learning Analytics (EFLA) for learners into the Turkish context, and to examine how metacognitive and behavioral factors predict learner performance. Study 1 was conducted with 83 online learners enrolled in a 16-week…
Descriptors: Learning Analytics, Electronic Learning, Measures (Individuals), Test Validity
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Šaric-Grgic, Ines; Grubišic, Ani; Šeric, Ljiljana; Robinson, Timothy J. – International Journal of Distance Education Technologies, 2020
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would benefit from the same intervention in AC-ware Tutor, this research examined online learning…
Descriptors: Learning Analytics, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Undergraduate Students
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Tomkins, Sabina; Ramesh, Arti; Getoor, Lise – International Educational Data Mining Society, 2016
With the success and proliferation of Massive Open Online Courses (MOOCs) for college curricula, there is demand for adapting this modern mode of education for high school courses. Online and open courses have the potential to fill a much needed gap in high school curricula, especially in fields such as computer science, where there is shortage of…
Descriptors: Prediction, Pretests Posttests, Electronic Learning, Student Behavior
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Carvalho, Elizabeth Simão – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2015
Teaching object-oriented programming to students in an in-classroom environment demands well-thought didactic and pedagogical strategies in order to guarantee a good level of apprenticeship. To teach it on a completely distance learning environment (e-learning) imposes possibly other strategies, besides those that the e-learning model of Open…
Descriptors: Foreign Countries, Distance Education, Programming, Computer Science Education
Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh – International Association for Development of the Information Society, 2015
Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…
Descriptors: Foreign Countries, Cognitive Style, Electronic Learning, Student Behavior
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Mack Shelley, Editor; Omer Tayfur Ozturk, Editor – International Society for Technology, Education, and Science, 2024
"Proceedings of International Conference on Research in Education and Science" includes full papers presented at the International Conference on Research in Education and Science (ICRES) which took place on April 27-30, 2024, in Antalya, Turkey. The aim of the conference is to offer opportunities to share ideas, discuss theoretical and…
Descriptors: STEM Education, Second Language Learning, Second Language Instruction, English (Second Language)
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Auvinen, Tapio; Hakulinen, Lasse; Malmi, Lauri – IEEE Transactions on Learning Technologies, 2015
In online learning environments where automatic assessment is used, students often resort to harmful study practices such as procrastination and trial-and-error. In this paper, we study two teaching interventions that were designed to address these issues in a university-level computer science course. In the first intervention, we used achievement…
Descriptors: Student Behavior, Electronic Learning, Online Courses, Computer Assisted Testing
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Alqahtani, Maha; Mohammad, Heba – Turkish Online Journal of Educational Technology - TOJET, 2015
Mobile applications are rapidly growing in importance and can be used for various purposes. They had been used widely in education. One of the educational purposes for which mobile applications can be used is learning the right way to read and pronounce the verses of the Holy Quran. There are many applications that translate the Quran into several…
Descriptors: Electronic Learning, Handheld Devices, Participant Satisfaction, Student Attitudes
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