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Xieling Chen; Di Zou; Gary Cheng; Haoran Xie – Education and Information Technologies, 2024
The rise of massive open online courses (MOOCs) brings rich opportunities for understanding learners' experiences based on analyzing learner-generated content such as course reviews. Traditionally, the unstructured textual data is analyzed qualitatively via manual coding, thus failing to offer a timely understanding of the learner's experiences.…
Descriptors: Artificial Intelligence, Semantics, Course Evaluation, MOOCs
Shiqi Liu; Sannyuya Liu; Xian Peng; Jianwen Sun; Zhi Liu – Journal of Educational Computing Research, 2025
Forum discussions in Massive Open Online Courses (MOOCs) play a crucial role in promoting learning engagement and academic achievement. In particular, discussion topics significantly influence learners' emotional and cognitive engagement. However, the complex interrelationships among these factors remain underexplored. This study introduces an…
Descriptors: MOOCs, Difficulty Level, Learner Engagement, Academic Achievement
Hanqiang Liu; Xiao Chen; Feng Zhao – Education and Information Technologies, 2024
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience. However, high dropout rate has become a prominent problem that hinders the further development of MOOCs. Therefore, the prediction of student dropouts is the key to further enhance the MOOCs platform.…
Descriptors: MOOCs, Video Technology, Behavior Patterns, Prediction
Yuan Liu; Yongquan Dong; Chan Yin; Cheng Chen; Rui Jia – Education and Information Technologies, 2024
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…
Descriptors: MOOCs, Online Courses, Models, Course Selection (Students)
Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
Lei Xie; Cixiao Wang – Interactive Learning Environments, 2024
Connectionist MOOC (cMOOC) is a type of MOOC, which can provide an online learning space for learners to sustainable connect. This study analyzed the learning behavior and motivation of repeat learners in the cMOOC "Internet + Education: a dialogue between theory and practice" to study the repeat learning needs and characteristics of…
Descriptors: Learning Analytics, Motivation Techniques, MOOCs, Sustainability
Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
MOOC Performance Prediction and Analysis via Bayesian Network and Maslow's Hierarchical Needs Theory
Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
John Stamper; Steven Moore; Carolyn P. Rosé; Philip I. Pavlik Jr.; Kenneth Koedinger – Journal of Educational Data Mining, 2024
LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…
Descriptors: Learning Analytics, Web Sites, Data Use, Educational Technology
Mohammad Khalil; Paraskevi Topali; Alejandro Ortega-Arranz; Erkan Er; Gökhan Akçapinar; Gleb Belokrys – Technology, Knowledge and Learning, 2024
The use of videos in teaching has gained impetus in recent years, especially after the increased attention towards remote learning. Understanding students' video-related behaviour through learning (and video) analytics can offer instructors significant potential to intervene and enhance course designs. Previous studies explored students' video…
Descriptors: Foreign Countries, MOOCs, Distance Education, Online Courses
Sa Li; Jingjing Dong – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to deeply analyze and evaluate the changes in the comprehensive quality of college students' sports dance, the overall idea of systematically evaluating the changes in the comprehensive quality of college students' sports dance was established. Firstly, this article uses the triangular fuzzy number method to measure the evaluation…
Descriptors: Dance Education, Teaching Methods, Evaluation Methods, Programming Languages
Karmijn van de Oudeweetering; Jeremy Knox; Mathias Decuypere – Learning, Media and Technology, 2024
This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and 'messy', the paper problematizes the model of the feedback loop that assumes that analytics dashboards 'feed back' data to instructors and/or learners…
Descriptors: MOOCs, Learning Analytics, Instructional Design, Student Role
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals