As life expectancy is mostly increasing, the incidence of many neurological disorders is also constantly growing. For improving the physical functions affected by a neurological disorder, rehabilitation procedures are mandatory, and they must be performed regularly. Unfortunately, neurorehabilitation procedures have disadvantages in terms of costs, accessibility and a lack of therapists. This paper presents Immersive Neurorehabilitation Exercises Using Virtual Reality (INREX-VR), our innovative immersive neurorehabilitation system using virtual reality. The system is based on a thorough research methodology and is able to capture real-time user movements and evaluate joint mobility for both upper and lower limbs, record training sessions and save electromyography data. The use of the first-person perspective increases immersion, and the joint range of motion is calculated with the help of both the HTC Vive system and inverse kinematics principles applied on skeleton rigs. Tutorial exercises are demonstrated by a virtual therapist, as they were recorded with real-life physicians, and sessions can be monitored and configured through tele-medicine. Complex movements are practiced in gamified settings, encouraging self-improvement and competition. Finally, we proposed a training plan and preliminary tests which show promising results in terms of accuracy and user feedback. As future developments, we plan to improve the system's accuracy and investigate a wireless alternative based on neural networks.

https://www.mdpi.com/1424-8220/20/21/6045/pdf

Flexible Virtual Reality System for Neurorehabilitation and Quality of Life Improvement

This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students' characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition.

Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

Abstract Background The application of artificial intelligence (AI) in STEM education (AI-STEM), as an emerging field, is confronted with a challenge of integrating diverse AI techniques and complex educational elements to meet instructional and learning needs. To gain a comprehensive understanding of AI applications in STEM education, this study conducted a systematic review to examine 63 empirical AI-STEM research from 2011 to 2021, grounded upon a general system theory (GST) framework. Results The results examined the major elements in the AI-STEM system as well as the effects of AI in STEM education. Six categories of AI applications were summarized and the results further showed the distribution relationships of the AI categories with other elements (i.e., information, subject, medium, environment) in AI-STEM. Moreover, the review revealed the educational and technological effects of AI in STEM education. Conclusions The application of AI technology in STEM education is confronted with the challenge of integrating diverse AI techniques in the complex STEM educational system. Grounded upon a GST framework, this research reviewed the empirical AI-STEM studies from 2011 to 2021 and proposed educational, technological, and theoretical implications to apply AI techniques in STEM education. Overall, the potential of AI technology for enhancing STEM education is fertile ground to be further explored together with studies aimed at investigating the integration of technology and educational system. 

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The application of AI technologies in STEM education: a systematic review from 2011 to 2021

Abstract There have been some hindrances in the process of programming learning. An adaptive learning system, such as ELaC, Java Guide, and Java Grader provides an adaptable learning content that can accommodate the learning styles as well as preferences of each learning individual. Moreover, an adaptive learning system can help students of different capabilities in learning programming. This study examined the outcomes of the implementation of an adaptive learning system in programming learning, as well as some finding results that were conducted according to the Systematic Literature Review framework. The research questions of this research were: problems faced during learning of programming as a background of system development, advantages and disadvantages of the system characteristics, technology, features, and effectiveness of the developed adaptive learning system. This research produced concepts that are summed up upon the related resources. The results of this study summarized whether the use of adaptive learning systems in learning programming could overcome the problems encountered during the learning process.

/pdf/enhancing-students-ability-in-learning-process-of-2i0yf1vkaj.pdf

Enhancing Students’ Ability in Learning Process of Programming Language using Adaptive Learning Systems: A Literature Review

Adaptive approaches within distance learning systems enable adapting teaching process to the needs of each learner during the learning process. This paper presents an algorithm for creating an adaptive learning process that provides knowledge and skills improvement for learners in the Java programming language. Also, it presents the application of the tool that checks the learner's knowledge through solving practical tasks from the Java programming language. The adaptive learning process in this work leads the learner through teaching materials and practical tasks where the acquired knowledge is required to be applied. Also, the algorithm, based on the measurement of knowledge and time spent on a particular part of the learning process with detailed feedback and the demonstration of observed deficiencies, directs the learner to teaching materials that allow improving the demonstrated knowledge. Teaching materials are conceived as learning objects and, as such, allow for the application of adaptive approach. An analysis of the effectiveness of the algorithm and tool for practical knowledge testing from the Java programming language was done with a test group of learners who gave their opinions and grades.

Algorithm for adaptive learning process and improving learners’ skills in Java programming language

In this paper, an approach to personalization of e-learning is proposed and implemented. This method provides different learning materials to various categories of students. The method of personalization uses fine-grained learning objects and learning processes with branching. Each learning activity uses atomic or complex learning objects. Evaluation activities measure achieved learning results and direct a student to appropriate next learning or other activity. Students also have the opportunity to choose one of offered learning or other activities, according to the overall design of a learning process. Using evaluation results, or students' choice of suggested activities, a master model of a learning process may generate different learning paths to various categories of student, providing them different teaching materials for each lesson of an online course.

Dragan Domazet

Papers

Algorithm for adaptive learning process and improving learners’ skills in Java programming language

Personalization of e-learning by using of learning processes with branching