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Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Kaiiali, Mustafa; Ozkaya, Armagan; Altun, Halis; Haddad, Hatem; Alier, Marc – IEEE Transactions on Learning Technologies, 2016
M-learning has enhanced the e-learning by making the learning process learner-centered. However, enforcing exam security in open environments where each student has his/her own mobile/tablet device connected to a Wi-Fi network through which it is further connected to the Internet can be one of the most challenging tasks. In such environments,…
Descriptors: Electronic Learning, Computer System Design, Computer Security, Confidentiality
Malandrino, Delfina; Manno, Ilaria; Palmieri, Giuseppina; Scarano, Vittorio; Tateo, Luca; Casola, Daniele; Ferrante, Ivan; Foresta, Francesco – IEEE Transactions on Learning Technologies, 2015
The widespread use of mobile devices is leading towards their adoption in the learning process, even if some pedagogical challenges are still not fully addressed when integrating mobile-assisted activities into regular curricula activities. In this paper, we first define some guidelines to design a general, tailorable, and platform-independent…
Descriptors: Telecommunications, Handheld Devices, Guidelines, Web Based Instruction