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Zoran Budimac - One of the best experts on this subject based on the ideXlab platform.
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ontology based architecture with recommendation strategy in java Tutoring System
Computer Science and Information Systems, 2013Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:The aim of Semantic Web is to provide distributed information with well-defined meaning, understandable for humans as well as machines. E-learning is an important domain which can be benefited from the Semantic Web technology. Ontologies, as a building structure of Semantic Web, will fundamentally change the way in which e-learning Systems are constructed. The explicit conceptualization of System components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration among System components, and construction of intensive and expressive Systems. In previous research, we implemented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning basic concepts of Java programming language. Protus uses principles of learner style identification and content recommendation for course personalization. The new version of the System called Protus 2.0, supported by several ontologies, as well as examples of its usage for performing personalization are presented in this paper. Architecture of new System extends the usage of Semantic Web concepts, where the representation of each Protus 2.0 component is made by a specific ontology, making possible a clear separation of the Tutoring System components and explicit communication among them.
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protus 2 0 ontology based semantic recommendation in programming Tutoring System
Expert Systems With Applications, 2012Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:With the development of the Semantic web the use of ontologies as a formalism to describe knowledge and information in a way that can be shared on the web is becoming common. The explicit conceptualization of System components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive Systems. Semantic web provides huge potential and opportunities for developing the next generation of e-learning Systems. In previous work, we presented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning the essence of Java programming language. It uses principles of learning style identification and content recommendation for course personalization. This paper presents new approach to perform effective personalization highly based on Semantic web technologies performed in new version of the System, named Protus 2.0. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. Functionality, structure and implementation of a Protus 2.0 ontology as well as syntax of SWRL rules implemented for on-the-fly personalization will be presented in this paper.
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rule based reasoning for altering pattern navigation in programming Tutoring System
International Conference on System Theory Control and Computing, 2011Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:Semantic Web technologies seem to be a promising technological foundation for the next generation of e-learning Systems. Although ontologies have a set of basic implicit reasoning mechanisms derived from the description logic which they are typically based on (such as classification, relations, instance checking, etc.), they need rules to make further inferences and to express relations that cannot be represented by ontological reasoning. In our previous work, we presented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning Java programming basics. One of the most important features of Protus is the adaptation of the presentation and navigation System of a course based on the level of particular learner knowledge. It uses principles of adaptive hypermedia and content recommendation for course personalization. There can be different sequence of resources that depends on navigational sequence determined for particular learner. In this paper we present set of proposed SWRL rules for altering navigation sequences.
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Intelligent Tutoring System as multiagent System
1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335), 1Co-Authors: Mihal Badjonski, Mirjana Ivanović, Zoran BudimacAbstract:Intelligent Tutoring Systems are important educational tools. They can be built using different methodologies and tools. In this paper a generic architecture for intelligent Tutoring System as a multiagent System is presented. The agents in the architecture are programmed with AGLess-a specialized agent-oriented environment, This approach has been compared to an object-oriented approach based on object-oriented language, Less.
Yasmin Hernandez Perez - One of the best experts on this subject based on the ideXlab platform.
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Knowledge-Based System in an Affective and Intelligent Tutoring System
Current Trends on Knowledge-Based Systems, 2017Co-Authors: Ramón Zatarain Cabada, María Lucía Barrón Estrada, Yasmin Hernandez PerezAbstract:This book chapter presents an affective and intelligent Tutoring System called Fermat that integrates emotion or affective states with an Intelligent Learning Environment. The System applies Knowledge Space Theory to implement the knowledge representation in the domain and student modules and Fuzzy Logic to implement a new knowledge tracing algorithm, which is used to track student’s pedagogical and affective states. The Intelligent Learning Environment was implemented with two main components: an affective and intelligent Tutoring System for elementary mathematics and an educational social network. The Tutoring System generates math exercises by using a fuzzy System that is fed with cognitive and effective values. Emotion recognition was implemented by two methods: one for feature extraction of the face and one for feature classification using back-propagation neural networks. In addition to recognizing the emotional state of the user, our System gives emotional support through a pedagogical agent. Furthermore, an architecture of software is presented where the emotion recognizer collaborates with the affective and intelligent Tutoring System inside a social network. Finally, we present a real-time evaluation with third-grade students in two different schools.
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an intelligent and affective Tutoring System within a social network for learning mathematics
Ibero-American Conference on Artificial Intelligence, 2012Co-Authors: Maria Lucia Barronestrada, Ramon Zataraincabada, Yasmin Hernandez PerezAbstract:In this paper we present an intelligent and affective Tutoring System designed and implemented within a social network. The Tutoring System evaluates cognitive and affective aspects and applies fuzzy logic to calculate the exercises that are presented to the student. We are using Kohonen neural networks to recognize emotions through faces and voices and multi-attribute utility theory to encourage positive affective states. The social network and the intelligent Tutoring System are integrated into a Web application. We present preliminary results with different groups of students using this software tool.
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IBERAMIA - An Intelligent and Affective Tutoring System within a Social Network for Learning Mathematics
Lecture Notes in Computer Science, 2012Co-Authors: María Lucía Barrón-estrada, Ramón Zatarain-cabada, Yasmin Hernandez PerezAbstract:In this paper we present an intelligent and affective Tutoring System designed and implemented within a social network. The Tutoring System evaluates cognitive and affective aspects and applies fuzzy logic to calculate the exercises that are presented to the student. We are using Kohonen neural networks to recognize emotions through faces and voices and multi-attribute utility theory to encourage positive affective states. The social network and the intelligent Tutoring System are integrated into a Web application. We present preliminary results with different groups of students using this software tool.
Kurt Vanlehn - One of the best experts on this subject based on the ideXlab platform.
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Teaching Algebraic Model Construction: A Tutoring System, Lessons Learned and an Evaluation
International Journal of Artificial Intelligence in Education, 2020Co-Authors: Kurt Vanlehn, Chandrani Banerjee, Fabio Milner, Jon WetzelAbstract:An algebraic model uses a set of algebra equations to precisely describe a situation. Constructing such models is a fundamental skill required by US standards for both math and science. It is usually taught with algebra word problems. However, many students still lack the skill, even after taking several algebra courses in high school and college. We are developing a short, intensive course in algebraic model construction. The course combines human teaching with a Tutoring System. This paper describes the lessons learned during the iterative development process. Starting from an existing theory of model construction, we gradually acquired a completely different view of the skills required as we modified the Tutoring System and the instruction. We close by describing encouraging results from a quasi-experimental study.
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AIED - Porting an Intelligent Tutoring System across Domains
2007Co-Authors: Min Chi, Kurt VanlehnAbstract:One possible approach to reducing the cost of developing an intelligent Tutoring System (ITS) is to reuse the components of an existing ITS. We used this approach to develop an Andes probability Tutoring System by modifying the declarative knowledge of the Andes physics Tutoring System. We claim that if we cluster various educational domains into groups based on their problem-solving methods [2], then it will be more efficient to port an existing ITS to a new domain in the same cluster than to build a new ITS from scratch.
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the andes physics Tutoring System five years of evaluations
Artificial Intelligence in Education, 2005Co-Authors: Kurt Vanlehn, Collin F Lynch, Kay G Schulze, Joel A Shapiro, Robert Shelby, Linwood Taylor, Don Treacy, Anders Weinstein, M C WintersgillAbstract:Andes is a mature intelligent Tutoring System that has helped hundreds of students improve their learning of university physics. It replaces pencil and paper problem solving homework. Students continue to attend the same lectures, labs and recitations. Five years of experimentation at the United States Naval Academy indicates that it significantly improves student learning. This report describes the evaluations and what was learned from them.
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combining competing language understanding approaches in an intelligent Tutoring System
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004Co-Authors: Pamela W Jordan, Maxim Makatchev, Kurt VanlehnAbstract:When implementing a Tutoring System that attempts a deep understanding of students’ natural language explanations, there are three basic approaches to choose between; symbolic, in which sentence strings are parsed using a lexicon and grammar; statistical, in which a corpus is used to train a text classifier; and hybrid, in which rich, symbolically produced features supplement statistical training. Because each type of approach requires different amounts of domain knowledge preparation and provides different quality output for the same input, we describe a method for heuristically combining multiple natural language understanding approaches in an attempt to use each to its best advantage. We explore two basic models for combining approaches in the context of a Tutoring System; one where heuristics select the first satisficing representation and another in which heuristics select the highest ranked representation.
Wintersgillmary - One of the best experts on this subject based on the ideXlab platform.
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The Andes Physics Tutoring System: Lessons Learned
International Journal of Artificial Intelligence in Education, 2005Co-Authors: Vanlehnkurt, Lynchcollin, Schulzekay, A Shapirojoel, Shelbyrobert, Taylorlinwood, Treacydon, Weinsteinanders, WintersgillmaryAbstract:The Andes System demonstrates that student learning can be significantly increased by upgrading only their homework problem-solving support. Although Andes is called an intelligent Tutoring System,...
Boban Vesin - One of the best experts on this subject based on the ideXlab platform.
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ontology based architecture with recommendation strategy in java Tutoring System
Computer Science and Information Systems, 2013Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:The aim of Semantic Web is to provide distributed information with well-defined meaning, understandable for humans as well as machines. E-learning is an important domain which can be benefited from the Semantic Web technology. Ontologies, as a building structure of Semantic Web, will fundamentally change the way in which e-learning Systems are constructed. The explicit conceptualization of System components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration among System components, and construction of intensive and expressive Systems. In previous research, we implemented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning basic concepts of Java programming language. Protus uses principles of learner style identification and content recommendation for course personalization. The new version of the System called Protus 2.0, supported by several ontologies, as well as examples of its usage for performing personalization are presented in this paper. Architecture of new System extends the usage of Semantic Web concepts, where the representation of each Protus 2.0 component is made by a specific ontology, making possible a clear separation of the Tutoring System components and explicit communication among them.
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protus 2 0 ontology based semantic recommendation in programming Tutoring System
Expert Systems With Applications, 2012Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:With the development of the Semantic web the use of ontologies as a formalism to describe knowledge and information in a way that can be shared on the web is becoming common. The explicit conceptualization of System components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive Systems. Semantic web provides huge potential and opportunities for developing the next generation of e-learning Systems. In previous work, we presented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning the essence of Java programming language. It uses principles of learning style identification and content recommendation for course personalization. This paper presents new approach to perform effective personalization highly based on Semantic web technologies performed in new version of the System, named Protus 2.0. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. Functionality, structure and implementation of a Protus 2.0 ontology as well as syntax of SWRL rules implemented for on-the-fly personalization will be presented in this paper.
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rule based reasoning for altering pattern navigation in programming Tutoring System
International Conference on System Theory Control and Computing, 2011Co-Authors: Boban Vesin, Mirjana Ivanovic, Aleksandra Klasnjamilicevic, Zoran BudimacAbstract:Semantic Web technologies seem to be a promising technological foundation for the next generation of e-learning Systems. Although ontologies have a set of basic implicit reasoning mechanisms derived from the description logic which they are typically based on (such as classification, relations, instance checking, etc.), they need rules to make further inferences and to express relations that cannot be represented by ontological reasoning. In our previous work, we presented Tutoring System named Protus (PRogramming Tutoring System) that is used for learning Java programming basics. One of the most important features of Protus is the adaptation of the presentation and navigation System of a course based on the level of particular learner knowledge. It uses principles of adaptive hypermedia and content recommendation for course personalization. There can be different sequence of resources that depends on navigational sequence determined for particular learner. In this paper we present set of proposed SWRL rules for altering navigation sequences.
