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Learning Behavior Feature Fused Deep Learning Network Model for MOOC Dropout Prediction
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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
'Instructor in Action': Co-Design and Evaluation of Human-Centred LA-Informed Feedback in MOOCs
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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
System Architecture of Big Data in Massive Open Online Courses (BD-MOOCs System Architecture)
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Khajonmote, Withamon; Chinsook, Kittipong; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jansawang, Natchanok; Jantakoon, Thada – Journal of Education and Learning, 2022
The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…
Descriptors: MOOCs, Data Collection, Student Behavior, Computer Software
Evaluating a Learning Analytics Dashboard to Detect Dishonest Behaviours: A Case Study in Small Private Online Courses with Academic Recognition
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Jaramillo-Morillo, Daniel; Ruipérez-Valiente, José A.; Burbano Astaiza, Claudia Patricia; Solarte, Mario; Ramirez-Gonzalez, Gustavo; Alexandron, Giora – Journal of Computer Assisted Learning, 2022
Background: Small private online courses (SPOCs) are one of the strategies to introduce the massive open online courses (MOOCs) within the university environment and to have these courses validates for academic credit. However, numerous researchers have highlighted that academic dishonesty is greatly facilitated by the online context in which…
Descriptors: Learning Analytics, Cheating, Integrated Learning Systems, Intervention
Log Mining for Course Recommendation in Limited Information Scenarios
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Sanguino, Juan; Manrique, Rubén; Mariño, Olga; Linares-Vásquez, Mario; Cardozo, Nicolas – International Educational Data Mining Society, 2022
Recommender systems in educational contexts have proven effective to identify learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In current recommendation techniques, and in particular, in…
Descriptors: Data Analysis, Learning Analytics, Student Interests, Student Needs
Proceedings of the 18th Latin American Conference on Learning Technologies (LACLO 2023). Lecture Notes in Educational Technology
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Santiago Berrezueta Ed. – Lecture Notes in Educational Technology, 2023
The proceedings of the 18th edition of Latin American Conference on Learning Technologies (LACLO) demonstrates the developments in the research of learning science, learning resources, challenges and solutions. This Proceedings book showcases a collection of quality articles that explores and discusses trending topics in education in the upcoming…
Descriptors: Educational Technology, Active Learning, Design, Telecommunications