A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) often suffers from "sample inefficiency" and "reward function" design difficulty, Apprenticeship Learning (AL) algorithms can overcome them.…

The number and variety of educational mathematics mobile applications (EMMAs) make it difficult to select mobile applications for mathematics learning and teaching. Therefore, in this study, multi-criteria decision-making (MCDM) techniques, which are effectively used in a wide variety of disciplines, were applied to choose among alternative…

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…

This introductory article defines and delimits expert systems. The discussion covers the concepts of artificial intelligence, the components of an expert system, and the significance of expert systems when compared to more traditional decision making tools. (CLB)

Describes the current status and limitations of expert systems, and explores the possible applications of such systems in education and training. The use of expert systems as tutors, as job aids, and as a vehicle for students to develop their own expert systems on specific topics are discussed. (40 references) (CLB)

Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)

The Computerized Decision Training (CDT) system, which focuses on improving and sharpening higher order cognitive skills in judgmental decision making, incorporates an adaptive computer program which learns the student's value structure, and uses this structure to train the student in practical decision making. The application of decision models…

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

This study compared the efficiency (time) and accuracy of two representations of instructional algorithms--list versus flow chart--for the task of using indexes to search for document numbers in the U.S. Documents Monthly Catalog. Participants were 55 undergraduates and 5 adults at the Virginia Military Institute. Two sets (flow charts and lists)…

Discrete mathematics, the mathematics of decision making for finite settings, is a topic of great interest in mathematics education at all levels. Attention is being focused on resolving the diversity of opinion concerning the exact nature of the subject, what content the curriculum should contain, who should study that material, and how that…