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Design and Development of Adaptive Learning Systems
  • HASANOV AZIZ
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dc.contributor.advisorTae-Sun Chung-
dc.contributor.authorHASANOV AZIZ-
dc.date.issued2024-08-
dc.identifier.other34219-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/38820-
dc.description학위논문(박사)--컴퓨터공학과,2024. 8-
dc.description.abstractThe era of pervasive computing has driven the development of Adaptive Context-Aware Learning Environments (ACALEs), which detect learner context and deliver adaptive learning services accordingly. Despite the existence of numerous standalone educational systems tailored for specific adaptive scenarios, there is a growing demand for a unified framework to facilitate the development of ACALEs. In response, we introduce Lightlore, an adaptation framework designed to support various adaptive learning services across formal and informal learning settings. Leveraging Scenario-Based Design (SBD), we crafted a conceptual model for Lightlore based on educational scenarios identified through a comprehensive literature review, which highlighted the limitations of existing ACALEs in terms of interoperability and extensibility. The design and development methodology included the formulation of a reference architecture and a proof-of-concept implementation featuring a hypermedia system for learning data structures using Lightlore’s adaptation service. The formative evaluation involved 25 expert reviewers with backgrounds in computer engineering and educational technology, ensuring a diverse and knowledgeable assessment panel. Their feedback was gathered through a structured survey and qualitative analysis, focusing on the framework’s clarity, adaptability, extensibility, and interoperability. Evaluation results revealed that Lightlore’s conceptual model and reference architecture are highly clear and comprehensible, with most experts rating them very positively. The framework was praised for its effective separation of the adaptation engine from application logic, its extensibility, and its interoperability with external systems. Experts noted the framework’s robustness in addressing essential components of adaptive learning environments and its strong support for modular scalability. Implications of these findings suggest that Lightlore significantly enhances the development and deployment of adaptive, context-aware educational services. By integrating seamlessly with existing learning environments through the Experience API (xAPI) and Learning Record Store (LRS), Lightlore offers substantial benefits to learners, educators, developers, and educational technology researchers, fostering continuous improvement and innovation in adaptive learning environments.-
dc.description.tableofcontents1 Introduction 1_x000D_ <br> 1.1 Background 1_x000D_ <br> 1.2 Motivation 2_x000D_ <br> 1.3 Problem Statement 3_x000D_ <br> 1.4 Research Objectives and Questions 4_x000D_ <br> 1.5 Contributions of the Study 6_x000D_ <br> 1.6 Significance of the Study 6_x000D_ <br> 1.7 Thesis Outline 7_x000D_ <br>2 Background 8_x000D_ <br> 2.1 Context, Context-awareness 8_x000D_ <br> 2.2 Adaptive Learning 9_x000D_ <br> 2.3 Adaptive Context-Aware Learning Environments 10_x000D_ <br> 2.3.1 Adaptive Hypermedia System (AHS) 10_x000D_ <br> 2.3.2 Intelligent Tutoring System (ITS) 11_x000D_ <br> 2.3.3 Collaborative Adaptive Learning Environment (CALE) 11_x000D_ <br> 2.4 Learning Styles Models 12_x000D_ <br> 2.4.1 Honey and Mumford's Learning Style Model 12_x000D_ <br> 2.4.2 Kolb's Learning Style Inventory (LSI) 12_x000D_ <br> 2.4.3 Felder and Silverman's Learning Style Model (FSLSM) 13_x000D_ <br> 2.5 Educational Technology Standards 13_x000D_ <br> 2.5.1 SCORM (Sharable Content Object Reference Model) 14_x000D_ <br> 2.5.2 QTI (Question and Test Interoperability) 14_x000D_ <br> 2.5.3 LTI (Learning Tools Interoperability) 14_x000D_ <br> 2.5.4 xAPI (Experience API) 15_x000D_ <br>3 Methodology 17_x000D_ <br> 3.1 Literature Review 17_x000D_ <br> 3.1.1 Research Design 17_x000D_ <br> 3.1.2 Data Collection 18_x000D_ <br> 3.1.3 Data Analysis and Synthesis 19_x000D_ <br> 3.2 Lightlore Design and Development 19_x000D_ <br> 3.3 Evaluation Methodology 21_x000D_ <br>4 Literature Review and Analysis of ACALEs 25_x000D_ <br> 4.1 Literature Review 25_x000D_ <br> 4.1.1 Overview 26_x000D_ <br> 4.1.2 Context-awareness 29_x000D_ <br> 4.1.3 Adaptation 35_x000D_ <br> 4.1.4 Pedagogy 40_x000D_ <br> 4.1.5 Trend analysis 42_x000D_ <br> 4.2 Analysis of ACALEs 44_x000D_ <br> 4.2.1 Technical Approaches for Context-Awareness and Adaptation 44_x000D_ <br> 4.2.2 Pedagogical Approaches in ACALEs 48_x000D_ <br> 4.2.3 Relations between taxonomies 49_x000D_ <br> 4.2.4 Current and future trends 50_x000D_ <br> 4.2.5 Limitations 52_x000D_ <br>5 The Lightlore Framework 53_x000D_ <br> 5.1 Scenario-based Development Process 53_x000D_ <br> 5.2 Conceptual Model 55_x000D_ <br> 5.3 Reference Architecture 58_x000D_ <br> 5.3.1 Context Management Module 60_x000D_ <br> 5.3.2 Adaptation Engine 62_x000D_ <br> 5.4 xAPI Profile 65_x000D_ <br>6 Proof-of-Concept 66_x000D_ <br> 6.1 Implementation without Adaptation 66_x000D_ <br> 6.2 Adaptation to Learning Style 67_x000D_ <br> 6.3 Proof of Concept Operation 70_x000D_ <br> 6.4 Integration of xAPI 72_x000D_ <br>7 Formative Evaluation 74_x000D_ <br>8 Discussion 78_x000D_ <br> 8.1 Common Vocabulary 78_x000D_ <br> 8.2 Essential Components and Architecture of Lightlore 79_x000D_ <br> 8.3 Leveraging xAPI for Interoperability and Personalization 80_x000D_ <br> 8.4 Implications 81_x000D_ <br> 8.5 Future Directions of Adaptive Context-Aware Learning 82_x000D_ <br> 8.6 Ecosystem, Roles, and Potential Use Cases 83_x000D_ <br> 8.7 Limitations 86_x000D_ <br> 8.8 Related Work 87_x000D_ <br>9 Conclusion and Future Work 90_x000D_ <br>Bibliography 94_x000D_ <br> A List of Publications 113_x000D_ <br> A.1 SCI/SCIE Journal Papers 113_x000D_ <br> A.2 Conference Papers 114_x000D_ <br> B An overview of ACALEs 115_x000D_ <br> C Context-awareness in ACALEs 120_x000D_ <br> D Adaptation in ACALEs 124_x000D_ <br> E Pedagogy in ACALEs 130_x000D_ <br> F Lightlore xAPI Profile 135_x000D_ <br> G Evaluation Questionnaire 138_x000D_ <br> H Evaluation Tutorial 144_x000D_ <br> I Lightlore Requirements Document 160-
dc.language.isoeng-
dc.publisherThe Graduate School, Ajou University-
dc.rights아주대학교 논문은 저작권에 의해 보호받습니다.-
dc.titleDesign and Development of Adaptive Learning Systems-
dc.typeThesis-
dc.contributor.affiliation아주대학교 대학원-
dc.contributor.department일반대학원 컴퓨터공학과-
dc.date.awarded2024-08-
dc.description.degreeDoctor-
dc.identifier.urlhttps://dcoll.ajou.ac.kr/dcollection/common/orgView/000000034219-
dc.subject.keywordadaptive learning-
dc.subject.keywordcontext-awareness-
dc.subject.keywordlightlore-
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