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How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
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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