Adaptive Trainer Research Articles

Концепция адаптивного тренажера и оценка его эффективности в математическом обучении

Presented is a mathematical model of the self-learning adaptive trainer intended for adaptive learning and providing task selection. The approach in question is an alternative to the adaptive technologies based on the Item Response Theory. Possibility to take into account temporal dynamics of solution ability as well as smaller number of tasks that must be performed by a subject to provide the given results are among the features of the methods in use. To assess the effectiveness of the adaptive trainer concept under consideration, its web-implementation intended for training school students to solve mathematical tasks covered by the school curriculum was employed. The analysis performed revealed both high efficiency of the adaptive trainer (the mean test rating has increased 1.54 times owing to its use) and proven statistically significant influences of the adaptive training factor on the observed mathematical test results.

Adaptive trainer for preparing students for math exams

Due to the specificity of organizing the learning process in school classes, often students do not have enough time for a practice to solve tasks (like a math or in similar theme) under the supervision of a teacher. In this case, using the services of tutors or selftraining. In recent years, online educational services have become most popular for self-learning. This approach has some limitations, one of which is the inability to individually configure for a specific user. The presented project is aimed at automating the process of e-learning, regarding the acquisition of practical skills in solving mathematical tasks, determining the level of knowledge and reducing the duration of training by reducing the number of tasks depending on the level of training (adaptability). An adaptive testing approach has been implemented to satisfy these requirements. The created Markov models of adaptive testing became the basis for the development of an adaptive trainer for teaching nonformalized skills and abilities necessary for solving mathematical and other problems of sufficiently high complexity that require mastering both the standard technique of constructing reasoning and elements of creative thinking. A web service has been developed to demonstrate how it works. First of all, an adaptive trainer is considered the most effective in cases where it is necessary to order the knowledge and skills, such as to prepare for exams when solving non-formalized tasks (mathematical, technical, algorithmic, etc.). This service is not a substitute for a teacher, but rather complements the existing learning process, expanding the possibilities for self-study.

Модель процесса адаптивного обучения и его программная реализация

The presented project is aimed at automating the e-learning process regarding the acquisition of practical skills for solving non-formalized tasks, determining the level of knowledge and reducing the duration of training by reducing the number of tasks depending on the level of training. To meet these requirements, an adaptive testing approach was implemented and “Adaptive trainer” web-service was implemented to demonstrate how it works.

Application of Conceptual Graph Structures in the Design of an Adaptive System: An Initial Concept and Exploration

This paper presents initial work on an adaptive trainer for basic helicopter flight skills. The work was performed by Bevilacqua Research Corporation, Inc., the University of Alabama in Huntsville, and Cognitive and Behavioral Systems. The project was performed for the U. S. Army Research Institute of the Behavioral and Social Sciences, Ft. Rucker Field Unit. In this initial phase of the project, the project team: 1) created initial student conceptual models, 2) created initial instructor conceptual models, 3) identified methods to dynamically update and evaluate student models, 4) identified methods to modify instructional models in response to student behavior, and 5) developed a top-level adaptive trainer design. The conceptual models were designed using conceptual graph structures as described by Sowa (1984) and were applied as an adaptive trainer would to an example instructional sequence to prove the utility of the employed methodology.

Neuro-controllers for adaptive helicopter hover training

This paper presents an application of artificial neural networks in adaptive helicopter hover training of novice student pilots. The design of the adaptive trainer utilizes the hypothesis that novices can be trained to fly a helicopter system automatically (with no human interaction) if the helicopter system adapts to the learning curve of the student. Two different techniques based on the above approach are presented. In the first technique, the helicopter system actively enforces optimality by augmenting the novice's control inputs by amounts necessary to satisfy desired performance criteria. The second technique uses relaxed performance criteria that are not initially optimal, but approach optimality in a graded fashion, based on the learning curve of the student. Adaptive neuro-controllers, together with a critic model, are used to implement the adaptive helicopter system. The results using simulated student models verify the approach adopted, and show that the adaptive neuro-controllers allow the helicopter system to adapt to the novice's learning curve. >

Applications of simulation and artificial intelligence technology for ATC training

The authors describe how the application of artificial intelligence technologies to ATC can improve the training of individuals who plan strategic actions, as well as making it possible to interface and cooperate with geographically distributed individuals who plan tactical actions. They also show how such training can affect concerns as diverse as safety, capacity, resource limitations, and traffic system efficiency simultaneously in a real-time environment. By focusing on the learning aspect of artificial intelligence, new dimensions are added to ATC simulation for training. The authors propose the construction of a simulation-based training device, called an intelligent adaptive trainer. This device would be used to teach controllers to reconcile conflicts and simultaneously to build operational confidence within a cooperative decision-making environment. An approach for training controllers to deal with the data discontinuities that frequently occur between levels of planning and operations is discussed. >

SAKI: Twenty-five years of adaptive training into the microprocessor era

SAKI is an adaptive trainer for keyboard skills, first implemented in 1956. This paper traces the development of different generations of the machine up to its most recent microprocessor implementation.