Relevant bibliographies by topics / Intelligent tutoring systems. Cognitive learning / Dissertations / Theses
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Dissertations / Theses on the topic 'Intelligent tutoring systems. Cognitive learning'

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Published: 4 June 2021
Last updated: 12 February 2022

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1

Atolagbe, Tajudeen Abayomi. "A generic architecture for interactive intelligent tutoring systems." Thesis, Brunel University, 2001. http://bura.brunel.ac.uk/handle/2438/5013.

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This research is focused on developing a generic intelligent architecture for an interactive tutoring system. A review of the literature in the areas of instructional theories, cognitive and social views of learning, intelligent tutoring systems development methodologies, and knowledge representation methods was conducted. As a result, a generic ITS development architecture (GeNisa) has been proposed, which combines the features of knowledge base systems (KBS) with object-oriented methodology. The GeNisa architecture consists of the following components: a tutorial events communication module,
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Ghemri, Lila. "Cognitive modelling in an intelligent tutoring system for second language." Thesis, University of Bristol, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386345.

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Widmer, Colin Leigh. "Explanative and Argumentative Interactions with an Intelligent Tutoring System." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1386173705.

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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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Zakharov, Konstantin. "Affect Recognition and Support in Intelligent Tutoring Systems." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1216.

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Empirical research provides evidence of strong interaction between cognitive and affective processes in the human mind. Education research proposes a model of constructive learning that relates cognitive and affective processes in an evolving cycle of affective states. Intelligent Tutoring Systems (ITSs) are capable of providing comprehensive cognitive support. Affective support in ITSs, however, is lagging behind; the in-depth exploration of cognitive and affective processes in ITSs is yet to be seen. Our research focuses on the integration of affective support in an ITS enhanced with
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Croteau, Ethan. "Evaluating predictions of transfer and analyzing student motivation." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-105752/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Dialog; Learning Gain; Web-Based Evaluations; Empirical Results; Student Motivation; Mathematics education; Model-Tracing Tutors; Tutoring Strategy Evaluation; Intelligent Tutoring. Includes bibliographical references (p. 33-34).
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Lockhart, Tony F. "Increasing motivation by adapting intelligent tutoring instruction to learner achievement goals." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39556.

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The impact of affect on learning and performance has caused many researchers in the field of cognitive psychology to acknowledge the value of motivationally supportive instruction. Goal orientation, which refers to the perceptions and behaviors of the learner in achievement situations, has been the most predominant theory in learning motivation. However, research suggests multiple components are responsible for affecting student cognitive engagement. The traditional framework distinguishes individuals who are self-motivated to master challenging tasks from those who are motivated to earn favor
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Freyberger, Jonathan E. "Using association rules to guide a search for best fitting transfer models of student learning." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-014117/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: aprior; ASAS; association rules; logistic regression; transfer models; predicting performance. Includes bibliographical references (p. 50-51).
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Nwaogu, Eze. "The Effect of Aleks on Students' Mathematics Achievement in an Online Learning Environment and the Cognitive Complexity of the Initial and Final Assessments." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/msit_diss/94.

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For many courses, mathematics included, there is an associated interactive e-learning system that provides assessment and tutoring. Some of these systems are classified as Intelligent Tutoring Systems. MyMathLab, Mathzone, and Assessment of LEarning in Knowledge Space (ALEKS) are just a few of the interactive e-learning systems in mathematics. In ALEKS, assessment and tutoring are based on the Knowledge Space Theory. Previous studies in a traditional learning environment have shown ALEKS users to perform equally or better in mathematics achievement than the group who did not use ALEKS. The pur
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Green, Derek Tannell. "INTELLIGENT TUTORING SYSTEMS FOR SKILL ACQUISITION." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/203476.

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Throughout history education has been restricted to a relatively small percentage of the world's population. The cause can be attributed to a number of factors; how- ever, it has been chiefly due to excessive cost. As we enter the information age it becomes conceivable to make education freely available to anyone, anywhere, any- time. The Intelligent Tutoring System is an automated teaching system designed to improve through experience, eventually learning to tailor its teaching to perfectly match each individual student's needs and preferences. In this dissertation we describe a template whic
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11

Gong, Yue. "Student Modeling in Intelligent Tutoring Systems." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-dissertations/403.

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"After decades of development, Intelligent Tutoring Systems (ITSs) have become a common learning environment for learners of various domains and academic levels. ITSs are computer systems designed to provide instruction and immediate feedback, which is customized to individual students, but without requiring the intervention of human instructors. All ITSs share the same goal: to provide tutorial services that support learning. Since learning is a very complex process, it is not surprising that a range of technologies and methodologies from different fields is employed. Student modeling is a
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Tong, Amelia Ka Yan. "Developing a model for tutoring strategy selection in intelligent tutoring systems." Thesis, London School of Economics and Political Science (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267977.

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Variation in tutoring strategy plays an important part in Intelligent Tutoring Systems (ITSs). The potential for providing an adaptive ITS depends initially on having a range of tutoring strategies to select from. However, in order to react effectively to the student's needs, an ITS not only has to be able to simply offer different tutoring strategies but to choose intelligently among them and determine which one is best for an individual student at a particular moment. This thesis first examines, through literature review and interactions with existing systems, the current practices of ITSs r
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Rasmussen, Kai. "Developing a Cognitive Rule-Based Tutor for the ASSISTment System." Digital WPI, 2007. https://digitalcommons.wpi.edu/etd-theses/39.

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The ASSISTment system is a web-based tutor that is currently being used as an eighth and tenth-grade mathematics in both Massachusetts and Pennsylvania. This system represents its tutors as state-based "pseudo-tutors" which mimic a more complex cognitive tutor based on a set of production rules. It has been shown that building pseudo-tutors significantly decreases the time spent authoring content. This is an advantage for authoring systems such as the ASSITment builder, though it sacrifices greater expressive power and flexibility. A cognitive tutor models a student's behavior with general log
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Lloyd, Nicholas M. "Measuring student engagement in an intelligent tutoring system." Link to electronic thesis, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-050307-134149/.

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Walonoski, Jason A. "Visual Feedback for Gaming Prevention in Intelligent Tutoring Systems." Digital WPI, 2006. https://digitalcommons.wpi.edu/etd-theses/23.

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A major issue in Intelligent Tutoring Systems is off-task student behavior, especially performance-based gaming, where students systematically exploit tutor behavior in order to advance through a curriculum quickly and easily, with as little active thought directed at the educational content as possible. The goal of this research was to explore the phenomena of off-task gaming behavior within the Assistments system, as well as to develop a passive visual indicator to deter and prevent off-task gaming behavior without active intervention via graphical feedback to the student and teachers. Trad
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Siemer, Julika. "Developing a model for remedial operations in intelligent tutoring systems." Thesis, London School of Economics and Political Science (University of London), 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294784.

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Intelligent Tutoring Systems attempt to create a relationship between a computer and the student which resembles a human-to-human tutorial situation. For successful teaching to take place an Intelligent Tutoring System has to be able to cope with any student errors that may occur during a consultation. Remedial intervention implemented in current Intelligent Tutoring Systems lacks a formal basis. The objective of this research is to formalise the process of remediation with Intelligent Tutoring Systems and to provide a framework for the implementation of remedial tutoring in Intelligent Tutori
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Jarvis, Matthew P. "Applying machine learning techniques to rule generation in intelligent tutoring systems." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0429104-112724.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Intelligent Tutoring Systems; Model Tracing; Machine Learning; Artificial Intelligence; Programming by Demonstration. Includes bibliographical references.
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Choksey, Sanket Dinesh. "Developing an affordable authoring tool for intelligent tutoring systems." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0825104-161218/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Model Tracing; Intelligent Tutoring Systems; JESS production system; Debugging Tool; Cognitive Tutor Authoring Tools. Includes bibliographical references (p. 58-60).
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Hoppe, William Charles. "Cognitive modeling and the evolution of the student model in intelligent tutoring systems." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23832.

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Kseibat, Dawod. "Adaptive intelligent tutoring for teaching modern standard Arabic." Thesis, University of Bedfordshire, 2010. http://hdl.handle.net/10547/134371.

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The aim of this PhD thesis is to develop a framework for adaptive intelligent tutoring systems (ITS) in the domain of Modern Standard Arabic language. This framework will comprise of a new approach to using a fuzzy inference mechanism and generic rules in guiding the learning process. In addition, the framework will demonstrate another contribution in which the system can be adapted to be used in the teaching of different languages. A prototype system will be developed to demonstrate these features. This system is targeted at adult English-speaking casual learners with no pre-knowledge of the
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Razzaq, Leena. "Investigating Learning in an Intelligent Tutoring System through Randomized Controlled Experiments." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-dissertations/370.

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"In the United States, many students are doing poorly on new high-stakes standards-based tests that are required by the No Child Left Behind Act of 2002. Teachers are expected to cover more material to address all of the topics covered in standardized tests, and instructional time is more precious than ever. Educators want to know that the interventions that they are using in their classrooms are effective for students of varying abilities. Many educational technologies rely on tutored problem solving, which requires students to work through problems step-by-step while the system provides hi
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Weerasinghe, A. "A General Model of Adaptive Tutorial Dialogues for Intelligent Tutoring Systems." Thesis, University of Canterbury. Computer Science and Software Engineering, 2013. http://hdl.handle.net/10092/8732.

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Adaptive tutorial dialogues have been successfully employed by ITSs to facilitate deep learning of conceptual domain knowledge. But none of the approaches used for generating dialogues have been used across instructional domains and tasks. The objective of this project was twofold: (i) to propose a general model that provides adaptive dialogue support in both well- and ill-defined instructional tasks (ii) to explore whether adaptive tutorial dialogues are better than non-adaptive dialogues in acquiring domain knowledge. Our model provides adaptive dialogue support by identifying the concepts
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Livak, Thomas Michael. "Collaborative warrior tutoring." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0824104-152548/.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Collaborative tutoring; Intelligent tutoring; Computer generated forces; Cognitive modeling. Includes bibliographical references (p. 29-31).
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Amaral, Luiz A. "Designing intelligent language tutoring systems for integration into foreign language instruction." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1179979688.

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Razzaq, Leena M. "Tutorial dialog in an equation solving intelligent tutoring system." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0107104-155853.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: cognitive model; model-tracing; intelligent tutoring system; tutoring; artificial intelligence. Includes bibliographical references (p. 55-57).
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26

Joyner, David A. "Metacognitive tutoring for inquiry-driven modeling." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53498.

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Over the past several decades, many K-12 classes have moved to use open, inquiry-based approaches to science instruction; research has shown some benefits from these approaches. However, there also exist significant challenges in teaching scientific modeling and inquiry, some based on their nature as metacognitive skills and others based on the general difficulty in providing guided instruction in open-ended exploratory learning contexts. To address these challenges, this dissertation presents a metacognitive tutoring system that teaches students an authentic process of inquiry-driven scientif
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Upalekar, Ruta Sunil. "Tools to help build models that predict student learning." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050206-154628/.

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28

Palitawanont, Nanta. "An Investigation into the Effectiveness of Intelligent Tutoring on Learning of College Level Statistics." Thesis, University of North Texas, 1989. https://digital.library.unt.edu/ark:/67531/metadc331166/.

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The present research incorporated the content of basic statistics into the Artificial Intelligence Physics Tutor (ARPHY), which was used as the expert system shell, and investigated the effects of the Artificial Intelligent Statistics Tutor (ARSTAT) as a supplement to learning statistics at the college level. Two classes of an introductory educational statistics course in the Department of Educational Foundations, University of North Texas, were used in the study. The daytime class was used as the experimental group and the evening class was used as the control group. The experimental group's
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Liu, Hairong. "Student modeling in e-learning environments /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1420936.

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Brawner, Keith. "Modeling Learner Mood in Realtime through Biosensors for Intelligent Tutoring Improvements." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5774.

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Computer-based instructors, just like their human counterparts, should monitor the emotional and cognitive states of their students in order to adapt instructional technique. Doing so requires a model of student state to be available at run time, but this has historically been difficult. Because people are different, generalized models have not been able to be validated. As a person's cognitive and affective state vary over time of day and seasonally, individualized models have had differing difficulties. The simultaneous creation and execution of an individualized model, in real time, rep
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Andrade, Oscar Daniel. "Supporting novice application users in learning by trial and error and reading help." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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32

Kim, Sara Nan-Soon. "The role of visual concept acquisition, outcome measure, and interface design in the evaluation of a computer-based multimedia tutorial, Urinalyasis Tutor /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/7550.

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Goldstein, Adam B. "Responding to Moments of Learning." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/685.

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In the field of Artificial Intelligence in Education, many contributions have been made toward estimating student proficiency in Intelligent Tutoring Systems (cf. Corbett & Anderson, 1995). Although the community is increasingly capable of estimating how much a student knows, this does not shed much light on when the knowledge was acquired. In recent research (Baker, Goldstein, & Heffernan, 2010), we created a model that attempts to answer that exact question. We call the model P(J), for the probability that a student just learned from the last problem they answered. We demonstrated an analysi
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Sottilare, Robert. "MODELING THE INFLUENCES OF PERSONALITY PREFERENCES ON THE SELECTION OF INSTRUCTIONAL STRATEGIES ININTELLIGENT TUTORING SYSTEMS." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3790.

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This thesis hypothesizes that a method for selecting instructional strategies (specifically media) based in part on a relationship between learning style preference and personality preference provides more relevant and understandable feedback to students and thereby higher learning effectiveness. This research investigates whether personality preferences are valid predictors of learning style preferences. Since learning style preferences are a key consideration in instructional strategies and instructional strategies are a key consideration in learning effectiveness, this thesis contributes to
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Rau, Martina A. "Conceptual learning with multiple graphical representations: Intelligent tutoring systems support for sense-making and fluency-building processes." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/262.

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Most learning environments in the STEM disciplines use multiple graphical representations along with textual descriptions and symbolic representations. Multiple graphical representations are powerful learning tools because they can emphasize complementary aspects of complex learning contents. However, to benefit from multiple graphical representations, students need to engage in a number of learning processes. Educational technologies offer novel opportunities to support these learning processes by making graphical representations interactive and by providing individualized instructional suppo
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Hrubik-Vulanovic, Tatjana. "EFFECTS OF INTELLIGENT TUTORING SYSTEMS IN BASIC ALGEBRA COURSES ON SUBSEQUENT MATHEMATICS LECTURE COURSES." Kent State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=kent1373337020.

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Kelly, Kim M. "A Set of Experiments Investigating Methods to Improve Student Learning Through Self-Regulated Learning." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-dissertations/553.

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Educators and educational researchers constantly strive to find effective instructional methods that meet the needs of struggling students. There is a well-established relationship between self-regulated learning and academic achievement. Therefore, a great deal of research has been conducted examining the effectiveness of interventions designed to develop self-regulated learning sub-processes including goal setting, help-seeking behavior, self-monitoring, and causal attributions. One particular sub-process that has gained significant attention is self-motivation beliefs, which includes goal o
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38

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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Olsen, Jennifer. "Orchestrating Combined Collaborative and Individual Learning in the Classroom." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1000.

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In the classroom, teachers make use of different combinations of social planes (e.g., individual, collaborative) to support learning. However, little is known about the complementary strengths of individual and collaborative learning or how to combine them so that they are more effective than either social plane alone. One roadblock to this investigation is an ability to orchestrate, or manage, more complex, but theoretically effective, combinations of collaborative and individual learning in the classroom. Prior research has created orchestration tools that support the planning and real-time
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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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Cirett, Galan Federico M. "Using Real-Time Physiological and Behavioral Data to Predict Students' Engagement during Problem Solving: A Machine Learning Approach." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/241971.

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The goal of this study was to evaluate whether Electroencephalography (EEG) estimates of attention and cognitive workload captured as students solved math problems could be used to predict success or failure at solving the problems. Students solved a series of SAT math problems while wearing an EEG headset that generated estimates of sustained attention and cognitive workload each second. Students also reported on their level of frustration and the perceived difficulty of each problem. Results from a Support Vector Machine (SVM) training indicated that problem outcomes could be correctly pre
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Hort, Jan. "Automatické vyhodnocování e-learningových testů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235443.

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The thesis is dealing with research of automatic evaluation of e-learning tests. That technology is useful for domain of computer aided learning and e-learning and intelligent tutoring systems. This is extending possibility of online testing the student's knowledge. This thesis is also dealing with norms for learning and intelligent tutoring systems. Briefly introduce some project of domain of intelligent tutoring systems.
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Strayer, Jeremy F. "The effects of the classroom flip on the learning environment a comparison of learning activity in a traditional classroom and a flip classroom that used an intelligent tutoring system /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1189523914.

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Schatten, Carlotta Verfasser], Lars [Akademischer Betreuer] [Gutachter] Schmidt-Thieme, and Niels [Gutachter] [Pinkwart. "Sequencing in Intelligent Tutoring Systems based on online learning Recommenders / Carlotta Schatten ; Gutachter: Lars Schmidt-Thieme, Niels Pinkwart ; Betreuer: Lars Schmidt-Thieme." Hildesheim : Universität Hildesheim, 2017. http://d-nb.info/113911798X/34.

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Schatten, Carlotta Verfasser], Lars [Akademischer Betreuer] [Schmidt-Thieme, and Niels [Gutachter] Pinkwart. "Sequencing in Intelligent Tutoring Systems based on online learning Recommenders / Carlotta Schatten ; Gutachter: Lars Schmidt-Thieme, Niels Pinkwart ; Betreuer: Lars Schmidt-Thieme." Hildesheim : Universität Hildesheim, 2017. http://d-nb.info/113911798X/34.

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46

Akers, John W. "A comparison of guided exploration and direct instruction computer tutors." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/30996.

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Baghaei, Nilufar. "A collaborative constraint-based intelligent system for learning object-oriented analysis and design using UML." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1204.

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Web-based collaborative learning is becoming an increasingly popular educational paradigm as more individuals who are geographically isolated seek higher education. As such students do not meet face to face with their peers and teachers, support for collaboration becomes extremely important. Successful collaboration means asking questions to gain a better understanding of the main concepts, elaborating and justifying opinions and sharing and explaining ideas. When group members' combined skills are sufficient to complete the learning task, effective group work can result in greater overall ach
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48

Mani, Kashani Mina. "The carbon cycle and systems thinking : Conceptualizing a visualization-based learning system for teaching the carbon cycle that supports systems thinking." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177716.

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Today, climate change, has become one of the greatest societal challenges of our time. This challenge requires an accurate understanding of climate change for making informed decisions regarding the environmental issues. The carbon cycle is one of the earth’s complicated cycles that has a critical role in the planet’s climate. Developing a thorough perception about this complex cycle uncovers how human activities impact the planet and reveals the connection between multiple environmental issues.Perceiving this complex cycle requires systems thinking skills that enable students to recognize com
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Smith, Garrett William. "Toward a general student model a framework for sharing student data across multiple computer-based learning environments /." Diss., Online access via UMI:, 2007.

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Kocabas, Efe Cem. "Uml-alf Agent Based Adaptive Learning Framework:a Case Study On Uml." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612182/index.pdf.

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As the amount of accessible and shareable knowledge increases, it is figured out that learning platforms offering the same context and learning path to all users can not meet the demands of learners. This issue brings out the necessity of designing and developing adaptive hypermedia systems. This study describes an agent-based adaptive learning framework whose goal is to implement effective tutoring system with the help of Artificial Intelligence (AI) techniques and cognitive didactic methods into Adaptive Educational Hypermedia Systems (AEHS) in the domain of Unified Modeling Language (UML).
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