DESIGN OF THE PEDAGOGICAL MODULE FOR AN EMOTIONALLY INTELLIGENT TUTORING SYSTEM / PEDAGOGINIO MODULIO EMOCIJAS SUPRANTANČIAI MOKYMO SISTEMAI KŪRIMAS

Since 1970-ties the research is being carried out for the development of intelligent tutoring systems (ITS) that aretrying to imitate human-teachers and their teaching methods. However, over the last decade researchers inspired by the closerelationship between emotions and learning have been working on the addition of an emotional component to human-computerinteraction. This has led to creation of a new generation of intelligent tutoring systems – emotionally intelligent tutoring systems(EITS). Despite the research carried out so far, a problem how to adapt tutoring not only to a student’s knowledge state butalso to his/her emotional state has been disregarded. The paper presents study on how to use the determined student’s emotionalstate further in order to change behaviour of the intelligent tutoring system looking from the pedagogical point of view and toimplement this as a part of the pedagogical module. The architecture of the planned tutoring system that adapts the tutoring bothto student’s emotions and knowledge is also described in the paper. Straipsnyje nagrinėjami klausimai, susiję su informacijos apienustatytą studento emocinę būklę taikymu sumaniosios mokymosistemos elgsenai keisti, taip pat emocinės būklės poveikis mokymoprocesui pedagoginiu požiūriu. Siūlomas pedagoginiamsaspektams įgyvendinti specializuotas informacinės sistemosmodulis. Parodoma pedagoginio modulio vieta sumaniosiosmokymo sistemos, pritaikančios mokymo procesą konkretausstudento žinių ir emociniam lygmenims, architektūroje.

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Intelligent Tutoring Systems

Journal of Intelligent Systems ◽

10.1515/jisys-2015-0144 ◽

2017 ◽

Vol 26 (4) ◽

pp. 717-727 ◽

Cited By ~ 3

Author(s):

Vladimír Bradáč ◽

Kateřina Kostolányová

Keyword(s):

Intelligent Tutoring Systems ◽

Technological Development ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Point Of View ◽

Tertiary Sector ◽

Tutoring Systems ◽

Number Of Ends ◽

E Learning ◽

Education Of Students

AbstractThe importance of intelligent tutoring systems has rapidly increased in past decades. There has been an exponential growth in the number of ends users that can be addressed as well as in technological development of the environments, which makes it more sophisticated and easily implementable. In the introduction, the paper offers a brief overview of intelligent tutoring systems. It then focuses on two types that have been designed for education of students in the tertiary sector. The systems use elements of adaptivity in order to accommodate as many users as possible. They serve both as a support of presence lessons and, primarily, as the main educational environment for students in the distance form of studies – e-learning. The systems are described from the point of view of their functionalities and typical features that show their differences. The authors conclude with an attempt to choose the best features of each system, which would lead to creation of an even more sophisticated intelligent tutoring system for e-learning.

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Tutoring Process in Emotionally Intelligent Tutoring Systems

Psychology and Mental Health ◽

10.4018/978-1-5225-0159-6.ch046 ◽

2016 ◽

pp. 1094-1110 ◽

Cited By ~ 1

Author(s):

Sintija Petrovica

Keyword(s):

Intelligent Tutoring Systems ◽

Emotional State ◽

Intelligent Tutoring ◽

Point Of View ◽

Research Groups ◽

Tutoring Systems ◽

Knowledge States ◽

Close Relationship ◽

Emotionally Intelligent ◽

Selection Of

Research has shown that emotions can influence learning in situations when students have to analyze, reason, make conclusions, apply acquired knowledge, answer questions, solve tasks, and provide explanations. A number of research groups inspired by the close relationship between emotions and learning have been working to develop emotionally intelligent tutoring systems. Despite the research carried out so far, a problem how to adapt tutoring not only to a student's knowledge state but also to his/her emotional state has been disregarded. The paper aims to examine to what extent the tutoring process and tutoring strategies are adapted to students' emotional and knowledge states in these systems. It also presents a study on how to influence student's emotions looking from the pedagogical point of view and provides general guidelines for selection of tutoring strategies to influence and regulate student's emotions.

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Tutoring Process in Emotionally Intelligent Tutoring Systems

International Journal of Technology and Educational Marketing ◽

10.4018/ijtem.2014010106 ◽

2014 ◽

Vol 4 (1) ◽

pp. 72-85 ◽

Cited By ~ 1

Author(s):

Sintija Petrovica

Keyword(s):

Intelligent Tutoring Systems ◽

Emotional State ◽

Intelligent Tutoring ◽

Point Of View ◽

Research Groups ◽

Tutoring Systems ◽

Knowledge States ◽

Close Relationship ◽

Emotionally Intelligent ◽

Selection Of

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Implementing Multiple Tutoring Strategies in an Intelligent Tutoring System for Music Learning

Journal of Information Technology ◽

10.1177/026839629501000107 ◽

1995 ◽

Vol 10 (1) ◽

pp. 52-62

Author(s):

Marios C. Angelides ◽

Amelia K.Y. Tong

Keyword(s):

Music Theory ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Individual Student ◽

Tutoring System ◽

Music Learning ◽

Tutoring Systems

Variation in tutoring strategies plays an important part in intelligent tutoring systems. The potential for providing an adaptive intelligent tutoring system depends on having a range of tutoring strategies to select from. In order to react effectively to the student's needs, an intelligent tutoring system has to be able to choose intelligently among the strategies and determine which strategy is best for an individual student at a particular moment. This paper describes, through the discussion pertaining to the implementation of SONATA, a music theory tutoring system, how an intelligent tutoring system can be developed to support multiple tutoring strategies during the course of interaction. SONATA has been implemented using a hypertext tool, HyperCard II. 1.

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Student Modeling in an Intelligent Tutoring System

Intelligent Tutoring Systems in E-Learning Environments ◽

10.4018/978-1-61692-008-1.ch011 ◽

2011 ◽

pp. 208-236 ◽

Cited By ~ 1

Author(s):

Mingyu Feng ◽

Neil Heffernan ◽

Kenneth Koedinger

Keyword(s):

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Student Modeling ◽

Tutoring System ◽

Tutoring Systems ◽

Fine Grained ◽

Knowledge States ◽

Complex Models ◽

Cognitively Diagnostic

Student modeling and cognitively diagnostic assessment are important issues that need to be addressed for the development and successful application of intelligent tutoring systems (its). Its needs the construction of complex models to represent the skills that students are using and their knowledge states, and practitioners want cognitively diagnostic information at a finer grained level. This chapter reviews our effort on modeling student’s knowledge in the ASSISTment project. Intelligent tutors have been mainly used to teach students. In the ASSISTment project, we have emphasized using the intelligent tutoring system as an assessment system that provides instructional assistance during the test. Usually it is believed that assessment get harder if students are allowed to learn during the test, as its then like try to hit a moving target. So our results are surprising that by providing tutoring to students while they are assessed we actually prove the assessment of students’ knowledge. Additionally, in this article, we present encouraging results about a fine-grained skill model with that system that is able to predict state test scores. We conclude that using intelligent tutoring systems to do assessment seems like a reasonable way of dealing with the dilemma that every minute spent testing students takes time away from instruction.

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Designing an Intelligent Tutoring System Interface to Account for Personality Differences

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129403801302 ◽

1994 ◽

Vol 38 (13) ◽

pp. 789-792

Author(s):

Pauline K. Cushman

Keyword(s):

Subject Matter ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Tutoring System ◽

Tutoring Systems ◽

Personality Differences ◽

The Way

Intelligent Tutoring Systems have been designed for a variety of purposes. Much of the design effort has been aimed at the actual subject matter. Often ignored has been the critical nature of the interface. If the way people interact with computers is directly related to their personality, then systems should respond differently to different people. This paper describes the design of an interface for an Intelligent Tutoring System that, given the student's personality, will make adjustments in the style of interaction.

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Online Homework versus Intelligent Tutoring Systems: Pedagogical Support for Transaction Analysis and Recording

Issues in Accounting Education ◽

10.2308/iace.2011.26.1.87 ◽

2011 ◽

Vol 26 (1) ◽

pp. 87-97 ◽

Cited By ~ 19

Author(s):

Fred Phillips ◽

Benny G. Johnson

Keyword(s):

Education Research ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Accounting Education ◽

Online Homework ◽

Learning Effects ◽

Tutoring System ◽

Tutoring Systems ◽

Transaction Analysis

ABSTRACT: Prior research demonstrates that students learn more from homework practice when using online homework or intelligent tutoring systems than a paper-and-pencil format. However, no accounting education research directly compares the learning effects of online homework systems with the learning effects of intelligent tutoring systems. This paper presents a quasi-experiment that compares the two systems and finds that students’ transaction analysis performance increased at a significantly faster rate when they used an intelligent tutoring system rather than an online homework system. Implications for accounting instructors and researchers are discussed.

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Advances in Intelligent Tutoring Systems: Problem-solving Modes and Model of Hints

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2007.1.2336 ◽

2007 ◽

Vol 2 (1) ◽

pp. 48 ◽

Cited By ~ 11

Author(s):

Alla Anohina

Keyword(s):

Problem Solving ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Tutoring System ◽

Layer Model ◽

Tutoring Systems ◽

Adaptive Support ◽

Two Layer Model ◽

Adaptive Abilities

The paper focuses on the issues of providing an adaptive support for learners in intelligent tutoring systems when learners solve practical problems. The results of the analysis of support policies of learners in the existing intelligent tutoring systems are given and the revealed problems are emphasized. The concept and the architectural parts of an intelligent tutoring system are defined. The approach which provides greater adaptive abilities of systems of such kind offering two modes of problem-solving and using a two-layer model of hints is described. It is being implemented in the intelligent tutoring system for the Minimax algorithm at present. In accordance with the proposed approach the learner solves problems in the mode which is the most appropriate for him/her and receives the most suitable hint.

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Combining Expert Systems and Multiple Intelligences in an Adaptive and Intelligent Tutoring System

International Journal of Information Technology and Web Engineering ◽

10.4018/ijitwe.2013070102 ◽

2013 ◽

Vol 8 (3) ◽

pp. 22-33

Author(s):

Hafidi Mohamed ◽

Bensebaa Taher

Keyword(s):

Expert System ◽

Expert Systems ◽

Multiple Intelligences ◽

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

The Other ◽

Tutoring System ◽

Tutoring Systems ◽

Intellectual Abilities

This paper describes an adaptive and intelligent tutoring system (AITS) based on multiple intelligences and expert system. Most of adaptive and intelligent tutoring systems based their adaptation to user’s skill level. Other learner features taken into account are background, hyperspace experience, preferences and interests. However, less attention was paid to multiple intelligences and their effects on learning. Moreover, to design AITS which can manage both different disciplinary domains and a guide for the learner is difficult. The specialization of the analysis treatments is responsible for the loss of reusability for the other disciplinary domains. To overcome these limitations, the authors will try to combine the benefits of paradigms (adaptive hypermedia, intelligent tutoring system, multiple intelligences) in order to adapt the course to the needs and intellectual abilities of each learner.

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The Challenges of Building Intelligent Tutoring Systems for Teams

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601451 ◽

2016 ◽

Vol 60 (1) ◽

pp. 1981-1985 ◽

Cited By ~ 5

Author(s):

Desmond Bonner ◽

Stephen Gilbert ◽

Michael C. Dorneich ◽

Eliot Winer ◽

Anne M. Sinatra ◽

...

Keyword(s):

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Lessons Learned ◽

Tutoring System ◽

Tutoring Systems ◽

Team Research ◽

Individual Instruction ◽

Individual Task ◽

And Training

Intelligent Tutoring Systems have been useful for individual instruction and training, but have not been widely created for teams, despite the widespread use of team training and learning in groups. This paper reviews two projects that developed team tutors: the Team Multiple Errands Task (TMET) and the Recon Task developed using the Generalized Intelligent Framework for Tutoring (GIFT). Specifically, this paper 1) analyzes why team tasks have significantly more complexity than an individual task, 2) describes the two team-based platforms for team research, and 3) explores the complexities of team tutor authoring. Results include a recommended process for authoring a team intelligent tutoring system based on our lessons learned that highlights the differences between tutors for individuals and team tutors.

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