Adaptive techniques in e-Learning for transnational programs

Abstract

In this article we present a set of methods and models to help the inclusion of information and communication technologies (ICTs) in transnational programs. The material that we are presenting takes advantage of several adaptive models that automatically react to students' activity. These models are extremely useful in environments where a huge number of very different students (such as those found in transnational programs) are enrolled in the courses or where the distance is a problem for face-to-face activities. We present the theoretical background, the gamification and adaptive techniques included in the model and the platform where the courses are implemented.

The Synergy Mechanism of Online-Offline Mixed Teaching Based on Teacher-Student Relationship

“…The online education platforms and online learning modes develop very rapidly in recent years, which enables teachers and students to interact more frequently and exchange the learning resources more freely, and the big data of the behaviors of teachers and students on these platforms have been accumulated at the same time [1][2][3][4][5][6]. By mining these big data, we can promote the development of smart education, and find evidence for the feasibility of implementing synergetic teaching and learning between teachers and students [7][8][9][10]. The teacher-student relationship on online education platforms is quite complex.…”

Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

“…There have been several research efforts that explored the adaptivity of the domain knowledge to students in terms of their remembering skills [15][16][17], knowledge acquisition ability [18], perceiving facts [19][20][21], incentive and appeal [22][23][24], as well as the tutoring routes [25][26][27], domain knowledge style [28,29], external resources recommendation [30,31] and sequential teaching material [32][33][34]. Concerning the technology to achieve adaptation of the learning material, the researches in the afore-presented literature utilized discrete-time stochastic control process, machine learning, weighted conceptual diagrams, ontology learning and supervised and unsupervised techniques [35,36].…”