=Paper= {{Paper |id=None |storemode=property |title= Model for an Adaptive Tutoring System |pdfUrl=https://ceur-ws.org/Vol-920/p16-kovatcheva.pdf |volume=Vol-920 |dblpUrl=https://dblp.org/rec/conf/bci/Kovatcheva12 }} == Model for an Adaptive Tutoring System== https://ceur-ws.org/Vol-920/p16-kovatcheva.pdf 
                                              Model
                                     for an Adaptive Tutoring System
                                                                 Eugenia Kovatcheva
                                          University of Library Studies and Information Technology
                                              Tzarigradsko Shosse 119, Sofia 1784, Bulgaria
                                                              +359 882 255 075
                                                             ekovatcheva@gmail.com



ABSTRACT                                                                                   An intelligent tutoring system is educational software
Nowadays the interest to the adaptive intelligent eLearning                                 containing an artificial intelligence component.
systems increases. There are different kind of adaptations one to                          ITSs are computer-based learning systems which attempt to
the content, other to the learning process or to the assessment and                         adapt to the needs of learners.’
so on. The crucial moment for the learner motivation’s is to catch
their needs and possibilities and then to act, i.e. the respond from                   The essence of the ITS is the humanization of the learning process
the system.. The intelligent tutor (system agent(s)) has to decide                     [1]. The modelling and constructing of the ITSs is the hot topic in
the most appropriate path through the content based on the                             nowadays research. Computer Based Instruction and Training via
collected information for learner as: learning style, learner track                    e-learning platforms are the predecessors of ITSs. The ITSs has to
through the topics, learner grades and offer further steps. The                        build a complex model of the educational process, to adapt it and
intelligent agent – tutor keeps all data for every single learner,                     to control the interactions. Usually ITSs provide individualized
analyse them and offers next learner’s actions on the system.                          tutoring using four models for knowledge of: the domain,
This paper presents a constructive model based on the learning                         learners, teacher strategies and user interface. Creating of the ITSs
style of the learners and their ability and how it could be                            is based on different artificial intelligence algorithms and
implement in an intelligent eLeaning system. It should be used for                     computational architectures as: Bayesian Networks [2], Markov
self-study in formal and informal education as well as for                             Models [3], Neural Networks, Higher-Order Semantic Spaces [4,
representing the digitalized cultural and historical heritage for                      5], Fuzzy Control Systems [6, 7], Production Rules Systems,
educational purposes.                                                                  Generative Grammars [8, 9], Non-Linear Dynamical Systems,
                                                                                       External Representation [10], Concept Maps [11], Path Guidance
Categories and Subject Descriptors                                                     [12], Agents Based [13, 14], Ontology Based [15, 16, 17, 18],
                                                                                       Data Mining [19, 20, 21, 22], and etc.
H.1.2 [Models and Principles]: User/Machine Systems – Human
factors, Human information processing
                                                                                       2. CHANGE OF THE WAY OF LEARNING
General Terms                                                                          The school is no longer the sole and the most attractive source of
                                                                                       information and knowledge. Quick access to unlimited sources of
Design, Human Factors
                                                                                       information is widely available due to modern technologies. The
                                                                                       traditional concept of literacy has been gradually extended to a
Keywords                                                                               multimedia literacy referring to students' abilities to read, write,
Intelligent tutoring system, e-learning, constructive model                            and communicate with digitally encoded materials - text,
                                                                                       graphics, still and moving images, animation, sounds.
1. INTRODUCTION: THE EVOLUTION                                                         The way the people learn is changed as well. The existence of
OF E-LEARNING SYSTEMS IN SHORT                                                         non-formal learning that is not provided by an education or
Last 30 years are time for creation of the Information Society.                        training institution has been widely recognised. This type of
The education is on new stage implementing Information and                             learning does not typically lead to an official certification.
Communication Technologies in it. The human ambitions for
                                                                                       Having in mind the characteristics of non-formal learning, as well
resemblance the web-based educational systems to the face-to-
                                                                                       as the requirements of the ICT driven educational reform, a model
face education is the goal of this paper. There are different
                                                                                       of Adaptive Tutoring System has been developed. The
definitions of the Intelligent Tutoring System (ITS) some of them
                                                                                       personalized support of learners has been identified as among the
    ITSs are computer software systems that seek to mimic the                         most important functions of the system since the learning takes
     methods and dialog of natural human tutors, to generate                           place in an open and dynamic learning environment.
     instructional interactions in real time and on demand, as                         Nevertheless of changed way of people learning the learning style
     required by individual students.’                                                 is different for the people.
                                                                                       Last few years the design of learning systems is the very
BCI’12, September 16–20, 2012, Novi Sad, Serbia.                                       important part of developed web technologies.
Copyright © 2012 by the paper’s authors. Copying permitted only for private and
academic purposes. This volume is published and copyrighted by its editors.            To find the most appropriate model for the learners and to make
Local Proceedings also appeared in ISBN 978-86-7031-200-5, Faculty of Sciences,
University of Novi Sad.
                                                                                       them closer to them arose and the adaptive learning systems. They


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use knowledge representation and domain models, consider the                 The ITS model consists five elements set  for the
student knowledge as a means for providing adaptivity [23]. The              identification of learner where:
overview identifies five main features used for maintaining
adaptivity:                                                                             L – Learning style,

         student goals,                                                                E – an Evaluation vector –for learner assessment during
                                                                                         the educational process,
         student knowledge and familiarity with the domain,
                                                                                        T – learner Time spend on the system,
         student qualification (how quickly he or she acquires
          knowledge),                                                                   A – the learner interaction with the system – type of
                                                                                         Actions,
         experience in the hyperspace and
                                                                                        P – control Points for learning process.
         personal preferences.
                                                                             The Intelligent Tutoring System consists of few modules: Admin,
                                                                             Expert, Domain, Learner, Assessment, Learning Style and
3.  Model                                                            Learner Interface as it is shown on figure 1.
In the previous work [24, 25] the author went deep in student
knowledge- the most important student characteristic in the                  The Expert module includes pedagogical perspectives and lessons
majority of the current adaptive systems.                                    planner – connected to the Domain module (the concept map
                                                                             approach in combination with ontology is used in domain
The presented constructive research model deals with the learning            module). The Learning Style module is based on the Homey and
style, student knowledge, the domain of knowledge, the learner               Mumford’s model
interaction with the learning system (time on the ITS and type of
activities) and the intelligent tutor. The ITS is adapted to the             The learner bahviour on the system is described with these five
learner style, the achieved learning results- learner ability and the        elements where the learning style L could be identifying on each
way of access to the learning materials. The ITS introduces and              student interaction with the system. The time T spent on one
responds the appropriate materials to the learner - a thorough               action A and evaluation E on the control point return the style L.
answer and kind of material. The intelligent tutor (system                   On the other hand the system keeps information for the learner
agent(s)) has to makes decision on each learner action and the               way through the learning materials.
collected learner’s data.

                                                                Assessment /
                                                                 Feedback




                       Admin




                                                             Learning        Style


                                                                                                                          Learner Interface
         Expert Module                                       Learner
                                                       student goals,
                                                       student knowledge
                                                       student qualification
                                                       experience in the hyperspace
                                                       personal preferences.



            Domain Module                                                                      Learner Module


                                            Figure 1:  intelligent tutoring system.



                                                                        17
The definition of set  describes the learner from                    Honey and Mumford have been developed tests for identifying
different point of view. It gives an approximation to the intelligent        the learning styles. The learning is more effective when the
tutoring system for further learner actions on the system. It will           learners use appropriate (for their learning style) resources and
improve the possibility for knowing the learner. This user profile           actions and they can apply what they know in the efficient way.
constructive model is an attempt at comprise all learner                     The implementation of the possibilities for style recognition into
characteristics as knowledge and as human factor.                            the tutoring systems will support the learners and give the
                                                                             flexibility to the learners.
The visualization of the module is like a sphere. The expert
module, learner module, domain, learning style and learning
interface are angels of one pentagram - the circumference from               4.2 Computer Adaptive Tests
each angle answers for one of the modules. The Assessment                    Computer Adaptive Tests (CAT) base on the Item Respond
module observes the learner behavior on the systems supported by             Theory for identification of student ability under the knowledge
the expert. The modeled intelligent system assures appropriate               domain in each step of the process. CAT successively selects
and ease of use learning materials and environment for each                  questions so as to maximize the precision of the exam based on
learner. It is prerequisite for effective learning.                          what is known about the examinee from previous questions. From
                                                                             the examinee's perspective, the difficulty of the exam seems to
The technology pawns the repository structured by topics,                    tailor itself to his or her level of ability.
learning styles and difficulties as well as the assessment pool. The
main problem could be in front of content providers to develop               The psychometric technology that allows equitable scores to be
appropriate learning material to fill in.                                    computed across different sets of items is item response theory
                                                                             (IRT). IRT is also the preferred methodology for selecting
Knowing of students’ ability and learning style is a premise for             optimal items which are typically selected on the basis of
students’ engagement and involvement in mastering of knowledge               information rather than difficulty, per se.
and skills. This type of systems is very suitable for self-learning
and distance education. The learner could be monitored at each               The learning system control points are the tests for self-evaluation
moment by set .                                                      not only for the different topics and with additional items
                                                                             describing the learner ability and motivation. One possibility for
                                                                             these tests is to be constructed the Computer Adaptive Test (CAT)
4. TOOL SUPPORT FOR                                                  based on Item Response Theory, [27]. The constructive research
                                                                             identify that the results from the CAT better describe the user
4.1 Learning Style
                                                                             comparing the fixed tests. The use of CAT presumes the well
Learning styles are various approaches or ways of learning. They
                                                                             structured metadata for describing the test items and the tool for
involve educating methods, particular to an individual, that are
                                                                             developing and pool for store the items according Thissen, &
presumed to allow that individual to learn best. Most people
                                                                             Mislevy [28]
prefer an identifiable method of interacting with, taking in, and
processing stimuli or information. Based on this concept, the idea           The basic computer-adaptive testing method is an iterative
of individualized "learning styles" originated in the 1970s, and             algorithm with the following steps:
acquired "enormous popularity".
                                                                                  1.   The pool of available items is searched for the optimal
Proponents say that teachers should assess the learning styles of                      item, based on the current estimate of the examinee's
their students and adapt their classroom methods to best fit each                      ability
student's learning style, which is called the 'meshing hypothesis.
                                                                                  2.   The chosen item is presented to the examinee, who then
The basis and efficacy for these proposals are extensively                             answers it correctly or incorrectly
criticized. Although children and adults express personal
preferences, there is no evidence that identifying a student's                    3.   The ability estimate is updated, based upon all prior
learning style produces better outcomes, and there is significant                      answers
evidence that the widespread "meshing hypothesis" (that a student                 4.   Steps 1–3 are repeated until a termination criterion is
will learn best if taught in a method deemed appropriate for the                       met
student's learning style) is invalid. Allegedly well-designed
studies "flatly contradict the popular meshing hypothesis". One of           Nothing is known about the examinee prior to the administration
it is of Honey and Mumford [26]. They distinguished four                     of the first item, so the algorithm is generally started by selecting
learning styles. It is one qualification and never appears in pure           an item of medium, or medium-easy, difficulty as the first item.
form:                                                                        As a result of adaptive administration, different examinees receive
         Reflector - prefers to learn from activities that allow            quite different tests [29].
          them to watch, think, and review what has happened.
         Theorist - prefers to think problems through in a step-            4.3 Intelligent Agents
          by-step manner.                                                    Intelligent Agents serve the Learner and Tutor module. They

         Pragmatist - prefers to apply new learning to actual                        keep tracks of the learner
          practice to see if they work.                                               interaction user between user and system
         Activist - prefers the challenges of new experiences,                       tutor’s emotions return the feedback
          involvement with others, assimilations and role-playing.




                                                                        18
4.4 Concept Map                                                              [6] Lombardi, M.M. (2007) Authentic Learning for the 21st
A concept map is a way of representing relationships between                     Century: An Overview, ELI Paper 1: 2007 May 2007,
ideas, images, or words in the same way that a sentence diagram                  EDUCAUSE
represents the grammar of a sentence, a road map represents the              [7] Suraweera, P., Mitrovic A.and Martin, B. A Knowledge
locations of highways and towns, and a circuit diagram represents                Acquisition System for Constraint-based Intelligent Tutoring
the workings of an electrical appliance. In a concept map, each                  Systems
word or phrase is connected to another and linked back to the
                                                                             [8] Contreras, W.F., Galindo, E.G., Caballero E.M., and
original idea, word or phrase. Concept maps are a way to develop
                                                                                 Caballero, G.M. (2006) An Intelligent Tutoring System for a
logical thinking and study skills by revealing connections and
                                                                                 Virtual E-learning Center, Current Developments in
helping students see how individual ideas form a larger whole.
                                                                                 Technology-Assisted Education, © FORMATEX 2006
Concept Maps ensure the categorization into the domain module.               [9] Salgueiro, F., Costa, G., Cataldi, Z., Lage, F., Martínez,
They in combination with Artificial Neural Networks are in used                  R.G. (2005) Redefinition of Basic Modules of an Intelligent
for knowledge representation and organization and Knowledge                      Tutoring System: The Tutor Module, Proceedings VII
map as self-training and adjustable tool.                                        Workshop Argentine Computer Science Reaserchers. pp.
                                                                                 444–448, 2005
4.5 Bayesian Network                                                         [10] Williams, B., The Role of External Representations in
Bayesian network [2] or belief network model or directed acyclic                  Intelligent System authoring: Supporting localised decision
graphical model is a probabilistic graphical model (a type of                     complex and evolving global context, AI-ED 2001
statistical model) that represents a set of random variables and                  Workshop, External Representations in AIED: Multiple
their conditional dependencies via a directed acyclic graph. the                  Forms and Multiple Roles, San Antonio, Texas, Sunday 20th
Bayesian networks could be support the analysis of the data for                   May 2001
huge about of learner and return visualized feedback to the tutor
                                                                             [11] Martins,W, Cortez, J.P., Nalini, L.E.G. Gomes, V.M. The
and administration.
                                                                                  Use of Conceptual Maps in a Hybrid Intelligent Tutoring
                                                                                  System
5. CONCLUSION                                                                [12] Hong, C-M., Chen, C-M ,Chang, M-H, and Chen, S-C
The presented constructive research model deals with the learning
                                                                                  (2007) Intelligent Web-based Tutoring System with
style, student knowledge, the domain of knowledge, the learner
                                                                                  Personalized Learning Path Guidance, Seventh IEEE
interaction with the learning system (time on the ITS and type of
                                                                                  International Conference on Advanced Learning
activities) and the intelligent tutor. The ITS is adapted to the
                                                                                  Technologies (ICALT 2007)
learner style, the achieved learning results- learner ability and the
way of access to the learning materials. The ITS introduces and              [13] Hospers, M., Kroezen, E. Nijholt, A. den Akker R.& Heylen,
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The researcher’s participation in the conference was financially                  pedagogical roles, Current Developments in Technology-
supported by the Research Foundation at Sofia University “St. K.                  Assisted Education, © FORMATEX 2006
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