Relevant bibliographies by topics / Intelligent tutoring systems (ITSs)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Intelligent tutoring systems (ITSs)'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Intelligent tutoring systems (ITSs)"

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Tafazoli, Dara, Elena Gómez María, and Cristina A. Huertas Abril. "Intelligent Language Tutoring System." International Journal of Information and Communication Technology Education 15, no. 3 (2019): 60–74. http://dx.doi.org/10.4018/ijicte.2019070105.

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Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to learning by assuming the role of a real teacher/expert who adapts and steers the learning process according to the specific needs of each learner. This article reviews and discusses the issues surrounding the development and use of ITSs for language le
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González, Carolina, Juan Carlos Burguillo, Martín Llamas, and Rosalía Laza. "Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 2, no. 1 (2013): 41–54. http://dx.doi.org/10.14201/adcaij2013244154.

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Intelligent Tutoring Systems (ITSs) are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR) and Multiagent systems (MAS). The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures s
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Lamia, Mahnane, and Hafidi Mohamed. "A Problem Solving Using Intelligent Social Network." International Journal of Web-Based Learning and Teaching Technologies 14, no. 3 (2019): 28–38. http://dx.doi.org/10.4018/ijwltt.2019070103.

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Nowadays, students are becoming familiar with the computer technology at a very early age. Moreover, the wide availability of the internet gives a new perspective to distance education making e-learning environments crucial to the future of education. Intelligent tutoring systems (ITSs) provide sophisticated tutoring systems using artificial intelligence techniques in computer programs to facilitate instruction. ITSs support problem solving by providing adaptive scaffolding in terms of feedback, guidance, problem selection and other types of help. Little attention has been devoted thus far to
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Lavendelis, Egons, and Janis Bicans. "Multi-Agent and Service Oriented Architectures for Intelligent Tutoring System Development." Scientific Journal of Riga Technical University. Computer Sciences 44, no. 1 (2011): 11–20. http://dx.doi.org/10.2478/v10143-011-0017-2.

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Multi-Agent and Service Oriented Architectures for Intelligent Tutoring System DevelopmentTraditional modular architecture of Intelligent Tutoring Systems (ITSs) does not provide sufficient modularity of complex ITSs. Distributed technologies like services and agents are used to increase modularity of ITSs by implementing traditional modules as sets of services or agents. The paper describes holonic agent architecture that implements each module as one or more holonic agents. It uses the lessons learned from the multi-agent architecture to propose service oriented ITS architecture.
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Hieu, Bui Trong, and Bui Thi Kim Uyen. "Data-Driven Hint Generation in Intelligent Tutoring Systems for Learning Microeconomics." European Journal of Engineering Research and Science 4, no. 9 (2019): 37–40. http://dx.doi.org/10.24018/ejers.2019.4.9.1510.

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Scientific inquiry skills is used in all educational areas. In the context of microeconomics, it is widely known that the development of scientific inquiry skills is central to the construction of ideas that enable understanding. Intelligent tutoring systems (ITSs) have been shown to be effective in supporting students' domain-level learning through guided problem solving practice. ITSs provide personalized feedback (in the form of hints) to students and improve learning at effect sizes approaching that of human tutors. However, creating an ITS to adapt to individual students requires the invo
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Bui, Hieu Trong. "Data-Driven Intelligent Tutoring Systems for STEM+C Learning and Teaching." European Journal of Engineering Research and Science 4, no. 9 (2019): 202–6. http://dx.doi.org/10.24018/ejers.2019.4.9.1553.

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It is wide known that one of the most effective ways to learn is through problem solving. In recent years, it is widely known that problem solving is a central subject and fundamental ability in the teaching and learning. Besides, problem solving is integrated in the STEM+C (Science, Technology, Engineering, and Math plus Computing, Coding or Computer Science) fields. Intelligent tutoring systems (ITSs) have been shown to be effective in supporting students' domain-level learning through guided problem solving practice. Intelligent tutoring systems provide personalized feedback (in the form of
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Tseytlin, Eugene, Faina Linkov, Melissa Castine, Elizabeth Legowski, and Rebecca S. Jacobson. "DomainBuilder: the knowledge authoring system for SlideTutor Intelligent Tutoring system." F1000Research 7 (October 31, 2018): 1721. http://dx.doi.org/10.12688/f1000research.16060.1.

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One of the major challenges in the development of medical Intelligent Tutoring Systems (ITS) is the development of authored content, a time-consuming process that requires participation of discipline experts. In this publication, we describe the development of software systems called DomainBuilder and TutorBuilder, designed to streamline and simplify the authoring process for general medical ITSs. The aim of these systems is to allow physicians without programming or ITSs background to create a domain knowledge base and author tutor cases in a time efficient manner. DomainBuilder combined know
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Lavendelis, Egons, and Janis Grundspenkis. "Requirements analysis of Multi-Agent Based Intelligent Tutoring Systems." Scientific Journal of Riga Technical University. Computer Sciences 38, no. 38 (2009): 37–47. http://dx.doi.org/10.2478/v10143-009-0003-0.

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Requirements analysis of Multi-Agent Based Intelligent Tutoring SystemsThe agent oriented software engineering research proposes general assumptions for agent oriented software development, while intelligent tutoring system (ITS) research proposes specific ITS architecture and other specific knowledge for ITS development. Both of these views should be taken into consideration while developing multi-agent based ITSs. Thus there is a need for specific approaches for all phases of agent based ITS development which take into consideration main ideas from both agent oriented software engineering an
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Ray, Jessica M., and John S. Barnett. "An Evolution of Tutoring and Training from Humans to Intelligent Systems: Human Factors Considerations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 53, no. 26 (2009): 1898–902. http://dx.doi.org/10.1177/154193120905302603.

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As training researchers and developers, we strive to understand and produce effective and efficient training. Research suggests the most effective form of instruction is individualized human tutoring. Yet this is rarely the most efficient form of instruction monetarily or in instructor time. Technological advances and a vision of effective, yet more efficient, computer based tutors has led to the development of sophisticated new training technologies such as Intelligent Tutoring Systems (ITSs). These systems have yet to reach their full forecast potential. In this paper we theorize that issues
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Dermeval, Diego, and Ig Ibert Bittencourt. "Co-designing Gamified Intelligent Tutoring Systems with Teachers." Revista Brasileira de Informática na Educação 28 (February 16, 2020): 73–91. http://dx.doi.org/10.5753/rbie.2020.28.0.73.

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Researchers are increasingly interested in Gamified Intelligent Tutoring Systems (ITSs) to provide adaptive instruction and to enhance engagement of students. However, although teachers are demanding to be active users of gamified ITS, they have been not considered as first-class citizens in the design of these kinds of systems. In order to contribute to the active and customized use of gamified ITS by teachers, three technical problems should be considered. First, designing ITS is very complex (i.e., considering different theories, components, and stakeholders) and including gamification may
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Dissertations / Theses on the topic "Intelligent tutoring systems (ITSs)"

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Colby, Brice R. "From Systems to Services: Changing the Way We Conceptualize ITSs -- A Theoretical Framework and Proof-of-concept." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8140.

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This dissertation consists of two articles. The first article describes an architecture for intelligent tutoring that focuses on modularity. This new architecture is based on Gibbons' layers theory for instructional design (2014). Splitting up the architecture for an intelligent tutor into layers allows different pieces to age at different rates which, in turn, allows the intelligent tutor to be adapted to new research and design theories. This architecture supports building intelligent tutoring services, nimble programs that can be assembled together to replicate the functions of intelligent
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Hall, Douglas Lee. "A Comparative Analysis of Guided vs. Query-Based Intelligent Tutoring Systems (ITS) Using a Class-Entity-Relationship-Attribute (CERA) Knowledge Base." Thesis, North Texas State University, 1987. https://digital.library.unt.edu/ark:/67531/metadc331475/.

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One of the greatest problems facing researchers in the sub field of Artificial Intelligence known as Intelligent Tutoring Systems (ITS) is the selection of a knowledge base designs that will facilitate the modification of the knowledge base. The Class-Entity-Relationship-Attribute (CERA), proposed by R. P. Brazile, holds certain promise as a more generic knowledge base design framework upon which can be built robust and efficient ITS. This study has a twofold purpose. The first is to demonstrate that a CERA knowledge base can be constructed for an ITS on a subset of the domain of Cretaceous pa
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Csizmadia, Vilmos. "Constructing an authoring tool for intelligent tutoring systems with hierarchical domain models." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-1222103-161814.

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Jupp, Dax. "The viability of an ITS for word processing in education and commerce." Thesis, University of East Anglia, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273474.

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Milik, Nancy. "Fitting Free-Form Question-Asking and Spatial Ability into ITS Development." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1215.

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Intelligent Tutoring Systems (ITSs) are problem-solving environments that provide individualised instruction and are able to adapt to the abilities and needs of each individual student in order to maximise effective learning. They provide feedback on students' actions, but a problem arises when students do not always understand the feedback they receive. Therefore, it would be beneficial for students to be able to ask for additional clarifications at any time, and to receive feedback customised to their individual differences. This research focuses on providing an additional help channel in IT
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Adenowo, Adetokunbo. "Augmented conversation and cognitive apprenticeship metamodel based intelligent learning activity builder system." Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/8238.

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This research focused on a formal (theory based) approach to designing Intelligent Tutoring System (ITS) authoring tool involving two specific conventional pedagogical theories—Conversation Theory (CT) and Cognitive Apprenticeship (CA). The research conceptualised an Augmented Conversation and Cognitive Apprenticeship Metamodel (ACCAM) based on apriori theoretical knowledge and assumptions of its underlying theories. ACCAM was implemented in an Intelligent Learning Activity Builder System (ILABS)—an ITS authoring tool. ACCAM’s implementation aims to facilitate formally designed tutoring system
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Folsom-Kovarik, Jeremiah. "Leveraging Help Requests in POMDP Intelligent Tutors." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5210.

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Intelligent tutoring systems (ITSs) are computer programs that model individual learners and adapt instruction to help each learner differently. One way ITSs differ from human tutors is that few ITSs give learners a way to ask questions. When learners can ask for help, their questions have the potential to improve learning directly and also act as a new source of model data to help the ITS personalize instruction. Inquiry modeling gives ITSs the ability to answer learner questions and refine their learner models with an inexpensive new input channel. In order to support inquiry modeling, an a
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Sottilare, Robert. "Using Student Mood and Task Performance to Train Classifier Algorithms to Select Effective Coaching Strategies Within Intelligent Tutoring Systems (ITS)." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3981.

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The ultimate goal of this research was to improve student performance by adjusting an Intelligent Tutoring System's (ITS) coaching strategy based on the student's mood. As a step toward this goal, this study evaluated the relationships between each student's mood variables (pleasure, arousal, dominance and mood intensity), the coaching strategy selected by the ITS and the student's performance. Outcomes included methods to increase the perception of the intelligent tutor to allow it to adapt coaching strategies (methods of instruction) to the student's affective needs to mitigate barriers to p
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Schaf, Frederico Menine. "Arquitetura modular para ambientes virtuais de ensino de automação com suporte à realidade mista e colaboração." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/28954.

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Este trabalho apresentará estudos referentes a uma proposta de arquitetura para ambientes computacionais de suporte à colaboração para auxiliar o ensino e o treinamento em áreas multidisciplinares de engenharia de controle e automação. A motivação provém de evoluções de tecnologias da Web, redes sociais, ambientes virtuais, e mundos virtuais 3D que proporcionam sucessivas possibilidades inovadoras de emprego de tecnologia no ensino. Estas tecnologias podem ser usadas no ensino à distância ou de forma complementar (ensino híbrido) ao ensino-aprendizagem tradicional. O emprego de ambientes compu
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Mills, Nadine. "ALEKS Constructs as Predictors of High School Mathematics Achievement for Struggling Students." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5576.

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Educators in the United States (U.S.) are increasingly turning to intelligent tutoring systems (ITS) to provide differentiated math instruction to high school students. However, many struggling high school learners do not perform well on these platforms, which reinforces the need for more awareness about effective supports that influence the achievement of learners in these milieus. The purpose of this study was to determine what factors of the Assessment and Learning in Knowledge Spaces (ALEKS), an ITS, are predictive of struggling learners' performance in a blended-learning Algebra 1 course
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Books on the topic "Intelligent tutoring systems (ITSs)"

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Esma, Aïmeur, Lajoie Susanne P, Nkambou Roger 1966-, and SpringerLink (Online service), eds. Intelligent Tutoring Systems: 9th International Conference, ITS 2008, Montreal, Canada, June 23-27, 2008 Proceedings. Springer-Verlag Berlin Heidelberg, 2008.

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International, Conference on Intelligent Tutoring Systems (4th 1998 San Antonio Texas). Intelligent tutoring systems: 4th International Conference, ITS'98, San Antonio, Texas, USA, August 1998, proceedings. Springer, 1998.

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International Conference, ITS (3rd 1996 Montréal, Québec). Intelligent tutoring systems: Third International Conference, ITS '96 Montréal, Canada, June 12-14 1996, proceedings. Springer, 1996.

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Claude, Frasson, Gauthier Gilles, and McCalla Gordon, eds. Intelligent tutoring systems: Second International Conference, ITS '92, Montréal, Canada, June 10-12, 1992, proceedings. Springer-Verlag, 1992.

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C, Lester James, Vicari Rosa Maria, and Paraguaçu Fábio, eds. Intelligent tutoring systems: 7th international conference, ITS 2004, Maceió, Alagoas, Brazil, August 30-September 3, 2004 : proceedings. Springer, 2004.

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A, Cerri Stefano, Gouardères Guy, and Paraguaçu Fábio, eds. Intelligent tutoring systems: 6th International Conference, ITS 2002, Biarritz, France and San Sebastián, Spain, June 2-7, 2002 : proceedings. Springer, 2002.

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International Conference, ITS (4th 1998 San Antonio, Tex.). Intelligent tutoring systems: 4th International Conference, ITS '98, San Antonio, Texas, USA, August 16-19, 1998 : proceedings. Springer, 1998.

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Gauthier, Gilles. Intelligent Tutoring Systems: 5th International Conference, ITS 2000 Montréal, Canada, June 19 23, 2000 Proceedings. Springer-Verlag Berlin Heidelberg, 2000.

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International Conference on Intelligent Tutoring Systems (2nd 1992 Montréal). Intelligent tutoring systems: Second international conference, ITS '92, Montréal, Canada, June 10-12, 1992 : proceedings. Springer, 1992.

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J, Clancey William, Papadourakis Giorgos, Panourgia Kitty, and SpringerLink (Online service), eds. Intelligent Tutoring Systems: 11th International Conference, ITS 2012, Chania, Crete, Greece, June 14-18, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Intelligent tutoring systems (ITSs)"

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du Boulay, Benedict. "Can We Learn from ITSs?" In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45108-0_3.

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Díaz-Ilarraza, A., J. A. Elorriaga, I. Fernández-Castro, J. Gutiérrez-Serrano, and J. A. Vadillo-Zorita. "User modeling and architecture in industrial ITSs." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55606-0_76.

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Matsuda, Noboru, and Toshio Okamoto. "Parallel computing model for problem solver towards ITSs." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61327-7_120.

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Suraweera, Pramuditha, Antonija Mitrovic, and Brent Martin. "The Role of Domain Ontology in Knowledge Acquisition for ITSs." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30139-4_20.

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Ainsworth, Shaaron, and Shirley Grimshaw. "Are ITSs Created with the REDEEM Authoring Tool More Effective than “Dumb” Couresware?" In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47987-2_88.

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Lehman, Blair, Caitlin Mills, Sidney D’Mello, and Arthur Graesser. "Automatic Evaluation of Learner Self-Explanations and Erroneous Responses for Dialogue-Based ITSs." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30950-2_70.

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Virvou, Maria, and Maria Moundridou. "Modelling the Instructor in a Web-Based Authoring Tool for Algebra-Related ITSs." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45108-0_67.

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Taub, Michelle, Nicholas V. Mudrick, Ramkumar Rajendran, Yi Dong, Gautam Biswas, and Roger Azevedo. "How Are Students’ Emotions Associated with the Accuracy of Their Note Taking and Summarizing During Learning with ITSs?" In Intelligent Tutoring Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91464-0_23.

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Srisethanil, Chaisak, and Nelson C. Baker. "ITS-Engineering: A domain independent its for building engineering tutors." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61327-7_168.

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Hirashima, Tsukasa, Akihiro Kashihara, and Jun'ichi Toyoda. "Providing problem explanation for ITS." In Intelligent Tutoring Systems. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55606-0_11.

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Conference papers on the topic "Intelligent tutoring systems (ITSs)"

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Karvonen, H., T. Kujala, and P. Saariluoma. "In-Car Ubiquitous Computing: Driver Tutoring Messages Presented on a Head-Up Display." In 2006 IEEE Intelligent Transportation Systems Conference. IEEE, 2006. http://dx.doi.org/10.1109/itsc.2006.1706800.

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Patel, Ashok, Kinshuk NA, David Russell, and R. Oppermann. "Intelligent Tutoring Systems: Confluence of Information Science and Cognitive Science." In 2001 Informing Science Conference. Informing Science Institute, 2001. http://dx.doi.org/10.28945/2387.

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The advent of Internet as a global communication medium has brought a new focus on an area of research in designing Intelligent Tutoring System (ITS) that has not been adequately considered so far. In the main, this has been due to the localised nature of most academic environments limiting the sources of information and an implicit assumption that information and knowledge are synonymous. These factors have led to overemphasis on learner modelling in the traditional ITS research, which seeks to enhance the interaction between the ITS as the provider and the learner as the consumer of knowledg
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Sottilare, Robert A. ""A hybrid machine learning approach to Automated Scenario Generation (ASG) to support adaptive instruction in virtual simulations and games"." In The 8th International Defence and Homeland Security Simulation Workshop. CAL-TEK srl, 2018. http://dx.doi.org/10.46354/i3m.2018.dhss.009.

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"This paper examines machine learning methods to automatically generate a large number of child scenarios from a small number of parent scenarios in support of adaptive instruction conducted in virtual simulations and game-based platforms. Adaptive instructional systems (AISs) include Intelligent Tutoring Systems (ITSs), intelligent mentors, recommender systems, personal assistants, and intelligent instructional media. AISs attempt to tailor instruction for individuals and teams based on their learning needs (e.g., knowledge or skill deficiencies), goals, and preferences. This often requires m
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Kim, Yong Se, Hyun Jin Cha, Tae Bok Yoon, and Jee-Hyoung Lee. "A Perspective Projection Tutoring System With Motivation Diagnosis and Planning." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35432.

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Motivation is a paramount factor to student success. Although it is well known that the learner’s motivation and emotional state in educational contexts are very important, they have not been fully addressed in intelligent tutoring systems (ITS). In this paper, a method for integrated motivation diagnosis and motivational planning is described in a manner applied to an operable system. For the motivational diagnosis rules, three different channels of data (performance from interaction with the system, verbal communication, and feedbacks) are combined. For the motivational planning rules, four
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Zouhair, Abdelhamid, El Mokhtar En-Naimi, Benaissa Amami, Hadhoum Boukachour, Patrick Person, and Cyrille Bertelle. "Intelligent tutoring systems founded of incremental dynamic case based reasoning and multi-agent systems (ITS-IDCBR-MAS)." In 2013 International Conference on Advanced Logistics and Transport (ICALT). IEEE, 2013. http://dx.doi.org/10.1109/icadlt.2013.6568482.

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Jurado, Francisco, Miguel Ángel Redondo, and Manuel Ortega. "Fuzzy algorithm representation for its application in intelligent tutoring systems for the learning of programming." In the 2007 Euro American conference. ACM Press, 2007. http://dx.doi.org/10.1145/1352694.1352728.

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Katuk, Norliza, Abdolhossien Sarrafzadeh, and Farhad Dadgostar. "Effective ways of encouraging teachers to design and use ITS: feature analysis of intelligent tutoring systems authoring tools." In 2009 International Conference on Innovations in Information Technology (IIT). IEEE, 2009. http://dx.doi.org/10.1109/iit.2009.5413784.

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"About ITSS." In 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015). IEEE, 2015. http://dx.doi.org/10.1109/itsc.2015.482.

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Grover, Ishaan, Hae Won Park, and Cynthia Breazeal. "A Semantics-based Model for Predicting Children's Vocabulary." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/188.

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Intelligent tutoring systems (ITS) provide educational benefits through one-on-one tutoring by assessing children's existing knowledge and providing tailored educational content. In the domain of language acquisition, several studies have shown that children often learn new words by forming semantic relationships with words they already know. In this paper, we present a model that uses word semantics (semantics-based model) to make inferences about a child's vocabulary from partial information about their existing vocabulary knowledge. We show that the proposed semantics-based model outperform
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Meshref, Hossam, and Isbudeen Noor Mohamed. "Intelligent tutoring systems." In the International Conference. ACM Press, 2012. http://dx.doi.org/10.1145/2345396.2345585.

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Reports on the topic "Intelligent tutoring systems (ITSs)"

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Burmester, George M., Dick Stottler, and John L. Hart. Embedded Training Intelligent Tutoring Systems (ITS) for the Future Combat Systems (FCS) Command and Control (C2) Vehicle. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada438495.

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Shute, Valerie J., and Joseph Psotka. Intelligent Tutoring Systems: Past, Present, and Future. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada280011.

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Di Eugenio, Barbara. Natural Language Dialogue for Intelligent Tutoring Systems. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada470806.

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Porter, Bruce. An Interactive, Intelligent Tutoring Systems for Prediction Tasks. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada300063.

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Steuck, Kurt, and J. L. Fleming. Intelligent Tutoring Systems: A Taxonomy of Evaluation Issues. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada222090.

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Ong, James, and Sowmya Ramachandran. An Intelligent Tutoring System Approach to Adaptive Instructional Systems. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada437533.

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Sottilare, Robert A. Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada614161.

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Richardson, J. J., and Martha C. Polson. Proceedings of the Air Force Forum for Intelligent Tutoring Systems. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada207096.

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Martinak, R., Anthony E. Kelly, D. Sleeman, J. Moore, and R. D. Ward. Diagnosis and Remediation in the Context of Intelligent Tutoring Systems. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada199024.

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Stottler, Richard H. A Case-Based Reasoning Approach to Internet Intelligent Tutoring System (ITS) Authoring. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada337189.

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