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Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki – International Association for Development of the Information Society, 2015
An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…
Descriptors: Adaptive Testing, Bayesian Statistics, Networks, Computer Assisted Instruction
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Achumba, Ifeyinwa E.; Azzi, Djamel; Stocker, James – International Journal of Virtual and Personal Learning Environments, 2010
The laboratory component of undergraduate engineering education poses challenges in resource constrained engineering faculties. The cost, time, space and physical presence requirements of the traditional (real) laboratory approach are the contributory factors. These resource constraints may mitigate the acquisition of meaningful laboratory…
Descriptors: Cost Effectiveness, Engineering Education, Web Based Instruction, Computer Simulation
Tennyson, Robert – Journal of Instructional Development, 1984
Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…
Descriptors: Artificial Intelligence, Bayesian Statistics, Computer Assisted Instruction, Feedback