Adaptive Distance Learning Research Articles

Development managing stages of hybrid intelligent learning environment for student’s mathematics research activities

Problem and aim. The search for relevant solutions to the restructuring of the architecture of modern education, elements of a new system through the organization of an intellectual learning environment adapted to the research activities of schoolchildren on the development of complex mathematical knowledge is a research problem. Materials and methods. 52 teachers and 234 students of schools in Moscow (Russian Federation) took part in the survey. Diagnostic methods were aimed at obtaining data on the use of various digital resources and tools in everyday learning activities and the level of their intellectualization. The methods of descriptive statistics were used (variation series, histograms, measures of central tendency and scatter), as well as Pearson's χ2-test. The results of the study. About 90% of the surveyed teachers and 80% of schoolchildren spoke in favor of the idea of introducing intelligent systems into the learning process, but more than 75% of respondents cannot give examples of such systems and environments. The opinion of trainees on the introduction of digital tools into the educational process differs significantly from the opinion of their mentors (χ2 emp=33,4> χ2 cr (0,01)=2,65). The main stages of designing an intelligent learning system are presented: the development of methodological provisions for the intelligent management of the educational process; determination of personalized parameters of scientific potential that determine the structure of educational and research content; development of a database and knowledge of the subject of project activities; choice of architecture and functionality of the hybrid neural network. Conclusion. The author's methodological and technological solutions will provide scientists with a reference point for further research in the field of improving high-tech forms of e-learning, and teachers will have the opportunity to explore practical ways to implement personalized and adaptive distance learning through automated intelligent systems. Keywords: intelligent systems, research activities, teaching mathematics, complex knowledge

ПРЕДСТАВЛЕННЯ ЗНАНЬ В АДАПТИВНИХ СИСТЕМАХ ДИСТАНЦІЙНОГО НАВЧАННЯ

<p>In basis of adaptive distance learning systems ( ASDO ) laid a knowledge base. Knowledge Base ASDO - a special kind of database designed for knowledge management (metadata): collection, storage, retrieval and adaptive delivery of learning material. Model of knowledge representation ASDO includes all stages of functioning of the knowledge base.</p><p>The basis of the knowledge base of ASDO consist of frame-model of knowledge representation. But in contrast to the classical model, which reflected the final version of knowledge representation, the proposed model includes all stages of functioning of the knowledge base.</p><p>Benefits of the proposed model construction BZ: structuring knowledge, dynamic knowledge management; optionality determine all the parameters, the ability to track and manual change mode; adaptive issuing educational material.</p>

LexMeter: Validation of an Automated System for the Assessment of Lexical Competence of Medical Students as a Prerequisite for the Development of an Adaptive e-learning System

Distance learning is used in medical education, even if some recent meta-analyses indicated that it is no more effective than traditional methods. To exploit the technological capabilities, adaptive distance learning systems aim to bridge the gap between the educational offer and the learner’s need. A decrease of lexical competence has been noted in many western countries, so lexical competence could be a possible target for adaptation. The “Adaptive message learning” project (Am-learning) is aimed at designing and implementing an adaptive e-learning system, driven by lexical competence. The goal of the project is to modulate texts according to the estimated skill of learners, to allow a better comprehension. Lexmeter is the first of the four modules of the Am-learning system. It outlines an initial profile of the learner’s lexical competence and can also produce cloze tests, a test based on a completion task. A validation test of Lexmeter was run on 443 medical students of the 1st, 3rd and 6th year at the University “Sapienza” of Rome. Six cloze tests were automatically produced, with ten gaps each. The tests were different for each year and with varying levels of difficulty. A last cloze test was manually created as a control. The difference of the mean score between the easy tests and the tests with a medium level of difficulty was statistically significant for the 3rd year students but not for 1st and 6th year. The score of the automatically generated tests showed a slight but significant correlation with the control test. The reliability (Cronbach alpha) of the different tests fluctuated under and above .60, as an acceptable level. In fact, classical item analysis revealed that the tests were on the average too simple. Lexical competence is a relevant outcome and its assessment allows an early detection of students at risk. Cloze tests can also be used to assess specific knowledge of technical jargon and to train reasoning skill.

Definition and Analysis of a System for the Automated Comparison of Curriculum Sequencing Algorithms in Adaptive Distance Learning

LS-Lab provides automatic support to comparison/evaluation of the Learning Object Sequences produced by different Curriculum Sequencing Algorithms. Through this framework a teacher can verify the correspondence between the behaviour of different sequencing algorithms and her pedagogical preferences. In fact the teacher can compare algorithms outcomes over sample individual cases, represented by input student models. Such comparison can be accomplished through subjective observation of the sequences, and by evaluating the metrics computed and presented by the system. LS-Lab architecture allows extending the framework with both additional algorithms and metrics. According to the different algorithms needs, suitably varied data structures for the student models are managed. We show also the result of an experimental analysis, conducted to unveil LS-Lab usefulness, as perceived by teachers. Teacher's appreciation, acceptance of the system, and expected advantages, were analyzed through an experimental application involving 30 teachers, with 3 student models, and 3 different sequencing algorithms.

Adaptive Distance Learning Programs Based On Feedback Evaluation And Continuous Progress Assessments

This paper presents a new technological approach to the online education that will allow for individualized and personalized adaptation of the curriculum. Based on the integration with and correlation of the results of student’s self-assessment, their multi-rater 360-degree feedback evaluation and the continuous study progress checks, a modern information system can automatically determine, generate, and continuously adjust the level, the instructional flow, and the specifics of the course content. The authors present their innovative idea for integrated web-based educational system and methodology, which is currently being designed. The system will target the demands for professional development and improvement in customer service and relations with customers in the travel and tourism industries and the public administration.

Adaptive distance learning and testing system

AbstractUser models are essential to e‐learning systems, giving students learning continuity, tutors evidence of students' progress, and both a way to personalize students' learning materials to their abilities and preferences. Personalizing information has long been the motivation behind developing e‐learning systems. Adaptive educational systems attempt to maintain a learning style profile for each student and use this profile to adapt the presentation and navigation of instructional content to each student. This kind of system adapts the learning process on the basis of the student's learning preferences, knowledge, and availability. One such Web‐based tool is built at the Business School of Professional Studies in Blace (the system of intelligent evaluation using tests), which infers student knowledge using adaptive testing. The knowledge is not evaluated according to fixed standards, but it depends on individual characteristics of each student, therefore, the learning style which is the most suitable. This system is part of the integrated assessment system inside of integrated curriculum. © 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21:E2–E13, 2013