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Friðriksdóttir, Kolbrún – Research-publishing.net, 2022
This article provides evidence of critical factors of student retention in Language Massive Open Online Courses (LMOOCs). The study used multiple sources: tracked retention data (n=43,000), survey data in correlation with tracking data (n=400), and qualitative data (174 informants) from a survey (Friðriksdóttir, 2018, 2021a, 2021b). The data came…
Descriptors: Academic Persistence, MOOCs, Blended Learning, Electronic Learning
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Sa'di, Rami A.; Sharadgah, Talha A.; Abdulrazzaq, Ahmad; Yaseen, Maha S. – Electronic Journal of e-Learning, 2022
As the COVID-19 pandemic was spreading rapidly throughout the world, the most widespread reaction in many countries to curtail the disease was lockdown. As a result, educational institutions had to find an alternative to face-to-face learning. The most obvious solution was e-learning. Conventional tertiary institutions with little virtual learning…
Descriptors: COVID-19, Pandemics, Postsecondary Education, Electronic Learning
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Muhammet Demirbilek Ed.; Mahmut Sami Ozturk Ed.; Mevlut Unal Ed. – International Society for Technology, Education, and Science, 2023
"Proceedings of International Conference on Studies in Education and Social Sciences" includes full papers presented at the International Conference on Studies in Education and Social Sciences (ICSES) which took place on October 20-23, 2023, in Antalya, Turkey. The aim of the conference is to offer opportunities to share ideas, to…
Descriptors: Conferences (Gatherings), International Cooperation, Education, Social Sciences
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Nathalie Rzepka; Linda Fernsel; Hans-Georg Müller; Katharina Simbeck; Niels Pinkwart – Computer-Based Learning in Context, 2023
Algorithms and machine learning models are being used more frequently in educational settings, but there are concerns that they may discriminate against certain groups. While there is some research on algorithmic fairness, there are two main issues with the current research. Firstly, it often focuses on gender and race and ignores other groups.…
Descriptors: Algorithms, Artificial Intelligence, Models, Bias
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S. Sageengrana; S. Selvakumar; S. Srinivasan – Interactive Learning Environments, 2024
Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…
Descriptors: Electronic Learning, Dropouts, Student Behavior, Student Interests
Center for Promise, 2016
Students disengage from and leave high school without a diploma for many different reasons: academic struggles, personal and/or familial obligations, unsupportive school environments and imperceptible relevance of school to their lives and futures. The common thread that connects so many young people who leave before graduating is that the…
Descriptors: Blended Learning, Learner Engagement, At Risk Students, Dropouts
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Xing, Wanli; Du, Dongping – Journal of Educational Computing Research, 2019
Massive open online courses (MOOCs) show great potential to transform traditional education through the Internet. However, the high attrition rates in MOOCs have often been cited as a scale-efficacy tradeoff. Traditional educational approaches are usually unable to identify such large-scale number of at-risk students in danger of dropping out in…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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Su, Jian; Waugh, Michael L. – Journal of Interactive Online Learning, 2018
This paper compares the perceptions of two groups of students who participated in the first cohort of the WebIT online Master of Science Degree in Instructional Technology at the University of Tennessee at Knoxville over a two-year period. The program completers (n=11) are the students who completed and graduated from the WebIT program. The…
Descriptors: Graduate Students, Masters Programs, Online Courses, Electronic Learning
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Lewis, S.; Whiteside, A.; Garrett Dikkers, A. – International Journal of E-Learning & Distance Education, 2014
In this three-year, mixed methods case study, the benefits and challenges of online learning for at-risk high school students were examined. A key finding was that at-risk students identify the benefits and challenges of online learning to be the same. While students appreciate the opportunity to work ahead and study at their own pace, they see it…
Descriptors: High School Students, At Risk Students, Electronic Learning, Educational Benefits
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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Simonson, Michael, Ed. – Association for Educational Communications and Technology, 2012
For the thirty-fifth year, the Research and Theory Division of the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the national AECT Convention in Louisville, Kentucky. The Proceedings of AECT's Convention are published in two…
Descriptors: Educational Technology, Handheld Devices, Workplace Learning, Electronic Learning
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Stiller, Klaus D.; Bachmaier, Regine – European Journal of Open, Distance and E-Learning, 2017
High dropout rates are still a problem with online training. It is strongly suggested that learner characteristics influence the decision to persist in an online course or to drop out. The study explored the differences in domain-specific prior knowledge, motivation, computer attitude, computer anxiety, and learning skills between dropouts and…
Descriptors: Foreign Countries, Dropout Rate, Knowledge Level, Student Motivation
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