A Literature Review on Intelligent Services Applied to Distance Learning

Distance learning has assumed a relevant role in the educational scenario. The use of Virtual Learning Environments contributes to obtaining a substantial amount of educational data. In this sense, the analyzed data generate knowledge used by institutions to assist managers and professors in strategic planning and teaching. The discovery of students’ behaviors enables a wide variety of intelligent services for assisting in the learning process. This article presents a literature review in order to identify the intelligent services applied in distance learning. The research covers the period from January 2010 to May 2021. The initial search found 1316 articles, among which 51 were selected for further studies. Considering the selected articles, 33% (17/51) focus on learning systems, 35% (18/51) propose recommendation systems, 26% (13/51) approach predictive systems or models, and 6% (3/51) use assessment tools. This review allowed for the observation that the principal services offered are recommendation systems and learning systems. In these services, the analysis of student profiles stands out to identify patterns of behavior, detect low performance, and identify probabilities of dropouts from courses.info:eu-repo/semantics/publishedVersio

COMPUTATIONAL ANALYSIS OF KNOWLEDGE SHARING IN COLLABORATIVE DISTANCE LEARNING

The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. This technology supports structured, on-line learning activities, and provides facilities for assessment and collaboration. Structured collaboration, in the classroom, has proven itself a successful and uniquely powerful learning method. Online collaborative learners, however, do not enjoy the same benefits as face-to-face learners because the technology provides no guidance or direction during online discussion sessions. Integrating intelligent facilitation agents into collaborative distance learning environments may help bring the benefits of the supportive classroom closer to distance learners.In this dissertation, I describe a new approach to analyzing and supporting online peer interaction. The approach applies Hidden Markov Models, and Multidimensional Scaling with a threshold-based clustering method, to analyze and assess sequences of coded on-line student interaction. These analysis techniques were used to train a system to dynamically recognize when and why students may be experiencing breakdowns while sharing knowledge and learning from each other. I focus on knowledge sharing interaction because students bring a great deal of specialized knowledge and experiences to the group, and how they share and assimilate this knowledge shapes the collaboration and learning processes. The results of this research could be used to dynamically inform and assist an intelligent instructional agent in facilitating knowledge sharing interaction, and helping to improve the quality of online learning interaction

Interface Engineering and Design: Adaptibility Problems

* The research work reviewed in this paper has been carried out in the context of the Russian Foundation for Basic Research funded project “Adaptable Intelligent Interfaces Research and Development for Distance Learning Systems”(grant N 02-01-81019). The authors wish to acknowledge the co-operation with the Byelorussian partners of this project.The paper describes some investigation’s problems intended to construct user model via psychological assessment for further interface adaptation. The proposed concept of user model comprises formal representation of demographic, professional, physiological and psychological data about the user with stress put on psychological features. Essential users physiological, communicative and cognitive peculiarities are in the center of view in the research theoretical part. The presented research develops flexible user- centered approach as a unity of two main investigation directions – user modeling and adaptive interface’s design. The adaptation engineering procedure is investigated via special interface modeling approach. The targeted implementation is distance learning process. Special software tool InterTrivium for interactive questionnaire presentation is described

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

The NURAXI web-based learning environment architecture

The fast evolution of today world impels corporations to provide their employees just-in-time training, adapted training and more generally continuous education. To be able to satisfy this demand, authors need means to specify once didactic material and then to reuse, select, adapt and distribute it to different users in different contexts. Since September 1998, Mediatech is developing the NURAXI multimedia research platform aimed at the design, generation, deployment, management and use of intelligent distance learning environments. NURAXI interacts with the user on the basis of the competency assessment (initial, on-going progress and final), the individual learning style and collaborative learning. Our solution is departing from a document type based organization of courses and training material towards a functionality and competency based model. We consider models and structures for information, knowledge and competencies more appropriate to the new on-line delivery environment than the document-based old one (html-based or not). From a technological point of view, this was made possible by the recent arrival of XML technology, coupled with Java and Web application technology

Developing e-Examination Voice interface for Visually Impaired students in Open and Distance Learning Context

Voice-based systems allow users access to information on the internet over a voice interface. Prior studies on Open and Distance Learning (ODL) eexamination systems that make use of voice interface do not sufficiently exhibit intelligent form of assessment, which diminishes the rigour of examination. The objective of this paper is to improve on the achievements of previous studies by providing a framework that will guide the development of a voice-based e-examination expert system for the visually impaired students in ODL. The study employs a combination of technologies such as system design, server side scripting, voice-based system development, data management and rule-based reasoning in developing the system. The system was evaluated to determine the level of usability. The results of the usability evaluation showed that the developed application has an ‘average usability’ rating of 3.48 out of 5 scales. The findings show that the voice-based e-examination system will not only be of immense benefit to the visually impaired students in ODL in respective of distance, but will also complement the existing web-based method for online examination

An open learner model for trainee pilots

This paper investigates the potential for simple open learner models for highly motivated, independent learners, using the example of trainee pilots. In particular we consider whether such users access their learner model to help them identify their current knowledge level, areas of difficulty and specific misconceptions, to help them plan their immediate learning activities; and whether they find a longer‐term planning aid useful. The Flight Club open learner model was deployed in a UK flight school over four weeks. Results suggest that motivated users such as trainee pilots will use a system with a simple open learner model, and are interested in consulting their learner model information both to facilitate planning over time, and to understand their current knowledge state. We discuss the extent to which our findings may be relevant to learners in other contexts