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Showing 1 to 15 of 25 results Save | Export
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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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Morales-Trujillo, Miguel Ehecatl; Galster, Matthias; Gilson, Fabian; Mathews, Moffat – IEEE Transactions on Education, 2022
Background: Peer evaluation in software engineering (SE) project courses enhances the learning experience of students. It also helps instructors monitor and assess both teams and individual students. Peer evaluations might influence the way individual students and teams work; therefore, the quality of the peer evaluations should be tracked through…
Descriptors: Undergraduate Students, Computer Software, Programming, Peer Evaluation
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Kim, ChanMin; Vasconcelos, Lucas; Belland, Brian R.; Umutlu, Duygu; Gleasman, Cory – International Journal of Educational Technology in Higher Education, 2022
It is critical to teach all learners to program and think through programming. But to do so requires that early childhood teacher candidates learn to teach computer science. This in turn requires novel pedagogy that can both help such teachers learn the needed skills, but also provide a model for their future teaching. In this study, we examined…
Descriptors: Programming, Error Correction, Student Behavior, Early Childhood Teachers
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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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Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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Chou, Chih-Yueh; Chang, Chun-Ho – Educational Technology & Society, 2021
Help-seeking is an important self-regulated learning strategy and skill for effective learning. Studies have found that some students have poor help-seeking behaviors and that this leads to poor learning performance. Some researchers have developed help-seeking regulation mechanisms to detect and regulate students' poor help-seeking behaviors.…
Descriptors: Help Seeking, Computer Assisted Instruction, Student Behavior, Technology Uses in Education
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Garcia, Victor; Conesa, Jordi; Perez-Navarro, Antoni – Journal of Science Education and Technology, 2022
Videos created with the hands of teachers filmed have been perceived as useful educational resource for students of Physics in undergraduate courses. In previous works, we analyzed the students' perception about educational videos by asking them about their experiences. In this work, we analyze the same facts, but from a learning analytics…
Descriptors: Physics, Science Instruction, Teaching Methods, Video Technology
Olivares, Daniel Michael – ProQuest LLC, 2019
The 2012 report by the US President's Council of Advisors on Science and Technology (PCAST) predicts a deficit in the workforce for science, technology, engineering, and mathematics (STEM) in the following decade and emphasizes the importance of addressing this shortfall. According to the report, less than half of the three million students…
Descriptors: Intervention, Computer Science Education, Programming, Social Behavior
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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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Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior
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Akcapinar, Gokhan; Bayazit, Alper – Turkish Online Journal of Distance Education, 2018
The deep and surface learning approaches are closely related to the students' interaction with learning content and learning outcomes. While students with a surface approach have a tendency to acquire knowledge without questioning and to try to pass courses with minimum effort, students with a deep learning approach tend to use more skills such as…
Descriptors: Video Technology, Student Behavior, Technology Uses in Education, Interaction
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Angrave, Lawrence; Zhang, Zhilin; Henricks, Genevieve; Mahipal, Chirantan – Grantee Submission, 2019
Lecture material of a sophomore large-enrollment (N=271) system programming 15-week class was delivered solely online using a new video-based web platform. The platform provided accurate accessible transcriptions and captioning plus a custom text-searchable interface to rapidly find relevant video moments from the entire course. The system logged…
Descriptors: Outcomes of Education, Student Behavior, Learning Analytics, Video Technology
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