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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
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Emmanuel Burguete; Bernard Coulibaly; Vassilis Komis – Education and Information Technologies, 2025
To design and script courses, practitioners often collaboratively use simple and tangible tools such as Post-it notes. In light of this, research and development were conducted to develop Eduscript Doctor, an analogic tool that would retain the inductive potential of Post-it notes while structuring the pedagogical scripting process. This…
Descriptors: Instructional Design, Program Implementation, MOOCs, Scripts
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Juming Jiang; Luke K. Fryer – Education and Information Technologies, 2025
The number of Massive Open Online Courses' (MOOCs) participants has been increasing over the years but its completion rate is extremely low. Social support/social interaction is one of the key factors that has a huge impact on students' learning motivation in both online and offline environments, but difficult to maintain in MOOCs due to its…
Descriptors: MOOCs, Learner Engagement, Social Support Groups, Academic Persistence
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Nabila Khodeir; Fatma Elghannam – Education and Information Technologies, 2025
MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…
Descriptors: MOOCs, Computer Mediated Communication, Conferences (Gatherings), Models
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Berkan Celik; Kursat Cagiltay – Education and Information Technologies, 2024
MOOC learners come from different backgrounds, and they have various motivations and intentions for taking online courses. This study examines learner intentions with subsequent behaviors and the reasons for the intention-behavior gap in MOOCs. A total of four MOOCs from BilgeIs MOOC Portal was used in this study. This quantitative study with a…
Descriptors: Students, MOOCs, Intention, Student Behavior
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Sa'ar Karp Gershon; Ella Anghel; Giora Alexandron – Education and Information Technologies, 2024
For Massive Open Online Courses to have trustworthy credentials, assessments in these courses must be valid, reliable, and fair. Item Response Theory provides a robust approach to evaluating these properties. However, for this theory to be applicable, certain properties of the assessment items should be met, among them that item difficulties are…
Descriptors: MOOCs, Item Response Theory, Physics, Advanced Placement Programs
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Saltanat Aubakirova; Maira Kozhamzharova; Gaukhar Akhmetova; Gulzhan Artykbayeva; Zauresh Iskakova; Ramilya Zhayabayeva – Education and Information Technologies, 2024
The study aims to investigate the level of motivation and entrepreneurial competencies of students using online distance courses in entrepreneurial learning. Based on the Massive Open Online Courses (MOOCs) program, an experimental group of respondents took the course "How to Start Your Own Business" (March-May 2022), and their results…
Descriptors: MOOCs, Entrepreneurship, Student Motivation, Ability
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Anagha Ani; Ean Teng Khor – Education and Information Technologies, 2024
Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…
Descriptors: MOOCs, Classification, Artificial Intelligence, Prediction
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Ata Jahangir Moshayedi; Atanu Shuvam Roy; Zeashan Hameed Khan; Hong Lan; Habibollah Lotfi; Xiaohong Zhang – Education and Information Technologies, 2025
In this paper, a secure exam proctoring assistant 'EMTIHAN' (which means exam in Arabic/Persian/Urdu/Turkish languages) is developed to address concerns related to online exams for handwritten topics by allowing students to submit their answers online securely via their mobile devices. This system is designed with an aim to lessen the student's…
Descriptors: Computer Assisted Testing, Distance Education, MOOCs, Virtual Classrooms
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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
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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)
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Liang, Zibo; Mu, Lan; Chen, Jie; Xie, Qing – Education and Information Technologies, 2023
In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…
Descriptors: MOOCs, Artificial Intelligence, Graphs, Educational Resources
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Du, Bingxin – Education and Information Technologies, 2023
Learner satisfaction is the degree of consistency between learners' perception and expectation of learning experience. In massive online open courses, analyzing the influencing factors of learner satisfaction is of great significance to improving the quality of course development and learning experience. Taking the open course reviews as data…
Descriptors: Student Satisfaction, Expectation, Learning Experience, Curriculum Development
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Xia, Xiaona; Qi, Wanxue – Education and Information Technologies, 2023
MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to…
Descriptors: MOOCs, Learning Processes, Learning Analytics, Graphs
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Yunqing Zhang; Xinmin Zheng; Bin Shen – Education and Information Technologies, 2024
Despite the growing importance of MOOCs and their application in face-to-face classes since 2020, driven by the COVID-19 pandemic, existing literature offers limited research on the factors affecting the quality of hybrid MOOC (hMOOC) learning, particularly from a psychological perspective. Thus, based on the 3P model of teaching and learning,…
Descriptors: Student Satisfaction, MOOCs, Information Dissemination, Educational Quality
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