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Open AccessJournal ArticleDOI

Design of an Intelligent Tutoring System to Create a Personalized Study Plan Using Expert Systems

Vladimír Bradáč, +3 more
- 19 Jun 2022 - 
- Vol. 12, Iss: 12, pp 6236-6236
TLDR
A model of an intelligent tutoring system to control learning by accentuating the individual needs of a student is proposed and is oriented on the study of the English language, where each student receives a unique study plan, which is continuously adapted based on achieved results.
Abstract
The article is devoted to the issue of the construction of an intelligent tutoring system which was created by our university for implementing distance learning and combined forms of studies. Significantly higher demand for such tools occurred during the COVID-19 pandemic when distance learning was used by students in their full-time studies. Current Learning Management Systems (LMS) do not address students' individuality regarding their various levels of input knowledge and skills or their different learning styles, which, in our case, are based on sensory preferences. Therefore, this article proposes a model of an intelligent tutoring system to control learning by accentuating the individual needs of a student. The foundation stones of this system are an expert system and adaptation mechanisms. The expert system acts as a tool for the identification of students’ needs from the point of view of input knowledge and sensory preferences. Sensory preferences influence the student’s learning style. The implemented adaptation mechanisms control the progress of the student through a study unit. The model was implemented in the LMS Moodle environment. Regarding the focus of the research content, our model is oriented on the study of the English language, where each student receives a unique study plan, which is continuously adapted based on achieved results. We consider the focus on the individuality of the student to be an innovative approach that can be achieved automatically on a mass scale.

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Citations
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A Smart Testing Model Based on Mining Semantic Relations

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Journal ArticleDOI

A Smart Testing Model Based on Mining Semantic Relations

- 01 Jan 2023 - 
TL;DR: In this paper , an intelligent model which considers the personalized student characteristics in exploring the student learning styles variation, then considering this variation in building the student exam is proposed to ensure the compatibility of the conducted exam with the student's capabilities as well as the course Intended Learning Outcomes (ILO) coverage.
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Systematic Review of Literature on Expert System in Education.

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References
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The SAGE Handbook of E-learning Research

TL;DR: The new edition of The SAGE Handbook of E-Learning Research retains the original effort of the first edition by focusing on research while capturing the leading edge of e-learning development and practice.
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Research Trends of Flipped Classroom Studies for Medical Courses: A Review of Journal Publications from 2008 to 2017 Based on the Technology-Enhanced Learning Model.

TL;DR: It was found that a great number of studies adopted instructional videos uploaded on online learning systems or used existing online videos to conduct before-class teaching in the before- class stage of the flipped classroom, while little attention was paid to developing learners’ higher order thinking skills.
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A study exploring the impact of lecture capture availability and lecture capture usage on student attendance and attainment

TL;DR: In this paper, the authors examined the impact of lecture capture introduction and usage in a compulsory second year research methods module in a undergraduate BSc degree and found that attendance substantially dropped in three matched lectures after capture became available.
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Self-Explanation and Reading Strategy Training (SERT) Improves Low-Knowledge Students’ Science Course Performance

TL;DR: The authors showed that self-explanation in combination with instruction and practice using comprehension strategies helps students to overcome their knowledge deficits in an introductory biology course, and showed that low-knowledge students who received self-explain and use comprehension strategies performed more poorly than high knowledge students.
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Motivating Students by “Personalizing” Learning Around Individual Interests: A Consideration of Theory, Design and Implementation Issues

TL;DR: The theoretical, design, and implementation issues to consider when creating interventions that utilize context personalization to enhance motivation are discussed, and potential drawbacks of personalization are explored, considering research on seductive details, desirable difficulties, and authenticity of connections to prior knowledge.
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Intelligance tutoring system for personalized learning?

The paper proposes a model of an intelligent tutoring system that focuses on the individual needs of students for personalized learning.