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Shiyi Liu; Juan Zheng; Tingting Wang; Zeda Xu; Jie Chao; Shiyan Jiang – AERA Online Paper Repository, 2024
This study introduces a novel approach for predicting student engagement levels in a language-based AI curriculum. The curriculum was integrated into English Language Arts classrooms, in which 106 students from five classes participated five web-based machine learning and text mining modules for 2 weeks. Sentiment and categorical analyses,…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Language Arts
Zeitlin, Benjamin D.; Sadhak, Nishanth D. – Education and Information Technologies, 2023
Computer-based learning applications and mobile technology have transformed many aspects of the educational experience over the last decade, producing software aimed at improving learning efficiency and streamlining the presentation of course materials. One such class of software, purpose-created to take advantage of spaced learning and spaced…
Descriptors: Student Attitudes, Foreign Students, Educational Technology, Electronic Learning
Chen, Jihe; Zhou, Ying; Lv, Litian – Education and Information Technologies, 2023
This study aims to explore the significant variables affecting online knowledge-sharing and the hierarchical structure, from the perspective of online learners. To comprehensively discuss the relationship between these variables, binary logit regression and interpretative structural model (ISM) was used. Based on literature analysis, the data of…
Descriptors: Students, Electronic Learning, Sharing Behavior, Knowledge Level
Ford, Robyn; Broadway, Susan; Mason, Diana – Journal of Science Education and Technology, 2023
Contributed data reflective of students' compliance in doing electronic homework (e-HW) exercises when asked to choose when required e-HW assignments are due are evaluated using a quasi-experimental format with non-equivalent groups to determine if first-semester general chemistry (Chem I) students (N = 273) will academically benefit from improved…
Descriptors: Students, Homework, Electronic Learning, Chemistry
Moya, Sofia; Camacho, Mar – Technology, Knowledge and Learning, 2023
Learning innovation for future education often includes digital approaches to enhance learning and to contribute to the development of twenty-first-century skills. There is evidence that mobile learning provides positive outcomes. However, there is a recognized lack of research in the field of frameworks and models that contributes to highlighting…
Descriptors: Electronic Learning, Sustainable Development, Educational Technology, Technology Uses in Education
Playfoot, David – Teaching of Psychology, 2023
Background: The flipped classroom method requires that students engage with homework before coming to the classroom so that class time can be spent on active and collaborative learning exercises. Research has demonstrated that this can improve student performance versus traditional lecturer-led teaching methods. Objective: During the COVID-19…
Descriptors: Flipped Classroom, Undergraduate Students, Statistics Education, Outcomes of Education
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
Dendir, Seife – Journal of Education for Business, 2023
This study investigates whether online homework improves learning in principles of microeconomics. It contributes to the related literature in two dimensions. First, it tests whether there is a positive association between students' performances on homework and exams. Importantly, it measures learning through exams that were given shortly after…
Descriptors: Electronic Learning, Homework, In Person Learning, Microeconomics
Zhou, Yizhuo; Zhao, Jin; Zhang, Jianjun – Interactive Learning Environments, 2023
On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…
Descriptors: Electronic Learning, Prediction, Dropouts, Student Behavior
Raviolo, Paolo; Messina, Salvatore; Mauro, Irene; Rondonotti, Marco – Research on Education and Media, 2023
The paper focuses on the topic of e-tutoring within the context of Higher Education. The research target is a framework for e-tutor role and skills in a higher education environment. The research began with a systematic review of the scientific literature with the aim of having a vision on the scientific landscape about the approach of…
Descriptors: Electronic Learning, Tutoring, Tutors, Foreign Countries
Fischer, Gerhard; Lundin, Johan; Lindberg, Ola J. – International Journal of Information and Learning Technology, 2023
Purpose: The main argument behind this paper is learning in the digital age should not be restricted to creating digital infrastructures for supporting current forms of learning nor taking schools in their current form as God-given, natural entities, but changing current forms of education by developing new frameworks and socio-technical…
Descriptors: Electronic Learning, Lifelong Learning, Transformative Learning, Educational Change
Okubo, Fumiya; Shiino, Tetsuya; Minematsu, Tsubasa; Taniguchi, Yuta; Shimada, Atsushi – IEEE Transactions on Learning Technologies, 2023
In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are…
Descriptors: Learning Management Systems, Student Evaluation, Automation, Artificial Intelligence
Joo, Hyungchul; Choi, Yoonso – Asia Pacific Education Review, 2023
This study aims to explore educational and political efforts for PE teachers to implement ICT-based PE class by analyzing three significant phases (PE teacher, the curriculum, and teaching environment). To reach the goal of this study, we conducted AHP and IPA analysis to find out the priorities in order to implement ICT-based PE class. As a…
Descriptors: Physical Education, Educational Technology, Physical Education Teachers, Curriculum
Eckley, Darrell; Allen, Andrew; Millear, Prudence; Rune, Karina Tirsvad – Social Psychology of Education: An International Journal, 2023
The novel coronavirus SARS-CoV-2 (COVID-19) has accentuated the role and interplay of numerous educational factors, inviting pedagogical research concerning online education. Using self-determination theory's basic psychological needs and fundamental learning theories, identified educational factors were integrated into three pathways: (1)…
Descriptors: COVID-19, Pandemics, Electronic Learning, Learning Processes
Akbari, Morteza; Danesh, Mozhgan; Rezvani, Azadeh; Javadi, Nazanin; Banihashem, Seyyed Kazem; Noroozi, Omid – Education and Information Technologies, 2023
Over the last decades, using e-learning systems as an alternative format of education for traditional classroom has been growing in higher education and due to COVID-19 pandemic, this transition has been unprecedently accelerated. Although there is a large body of research on e-learning, little is known about the extent to which innovative and…
Descriptors: College Students, Electronic Learning, Identification (Psychology), Interpersonal Relationship