Mengjuan Li, Lei Niu^*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 263-284, 2023, DOI:10.32604/cmc.2023.041193

Abstract In the era of artificial intelligence, cognitive computing, based on cognitive science; and supported by machine learning and big data, brings personalization into every corner of our social life. Recommendation systems are essential applications of cognitive computing in educational scenarios. They help learners personalize their learning better by computing student and exercise characteristics using data generated from relevant learning progress. The paper introduces a Learning and Forgetting Convolutional Knowledge Tracking Exercise Recommendation model (LFCKT-ER). First, the model computes studentsʼ ability to understand each knowledge concept, and the learning progress of each knowledge concept, and the model consider their forgetting behavior… More >

K. Abhirami^1,*, M. K. Kavitha Devi²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1127-1144, 2022, DOI:10.32604/csse.2022.020013

Abstract With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The quality of learning can be… More >