We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…

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.…

Educational leaders are faced with multi-faceted dilemmas that place decision-making at the heart of their day-to-day work. For support, they often turn to collaborative networks of experienced educators, such as Project ECHO, for solutions to address challenges they encounter while working in the field. The availability of generative AI…

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…

Generic competency development activities (GCDAs) help students develop critical thinking, problem-solving, innovation, creativity, communication and social skills. This study evaluated students' acceptance of a machine learning-assisted recommendation system (MARS) developed to recommend GCDAs for students in a higher education institution. This…

Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less…

The approach to problem solving which is presented has two components--closeness and reformulation. The closeness measure is a cognitively-based heuristic function. It incorporates the notion of what cognition notices as the structural difference between two situations. The problem-solver attempts to close the structural gap, and once this is done…

In order to investigate the use of strategies in a game-playing computer program, "Gammon," a computer program that plays Backgammon, was developed. It focuses on the play of a given strategy, as well as the process of strategy selection, and examines the concept of strategy as an integrating and driving force in the play of a game. A…

Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

Describes a programming environment called Tinker, in which a beginning programmer presents examples to the machine, distinguishing accidental and essential aspects of the examples. Examples of programming in Tinker are presented in which programmers demonstrate how to handle specific examples and the machine formulates a procedure for handling…

The role of artificial intelligence expert systems in administrative issues in special education is examined. Mandate Consultant (MC) is one such system designed to provide a second opinion on the consistency of school officials' actions in implementing the Individualized Education Program team process. MC employs rules based on the Education For…

The paper describes the use of expert systems technology in translating test and observational data into objectives for Individualized Education Programs (IEPs) with handicapped students. The Math Test Interpreter (MTI) is designed to combine student information, results from the Key Math Diagnostic Arithmetic Test and additional program generated…

Presents findings from study of design activities among 26 novice instructional designers which investigated prevalence of initial generation of more than one design solution; basis on which solutions are accepted or rejected; constraints encountered in proceeding with design; way in which designers know design is finished. Twelve references are…