Adaptive instructional systems : 4th international conference, AIS 2022, held as part of the 24th HCI international conference, HCII 2022, virtual event, June 26 - July 1, 2022 : proceedings

This book constitutes the refereed proceedings of the 4th International Conference on Adaptive Instructional Systems, AIS 2022, held as part of the 23rd International Conference, HCI International 2022, which was held virtually in June/July 2022. The total of 1271 papers and 275 posters included in the HCII 2022 proceedings was carefully reviewed and selected from 5487 submissions. The AIS 2022 proceedings were organized in the following topical sections: Learner Modeling and State Assessment for Adaptive Instructional Decisions; Adaptation Design to Individual Learners and Teams; Design and Development of Adaptive Instructional Systems; Evaluating the Effectiveness of Adaptive Instructional Systems . Foreword HCI International 2022 Thematic Areas and Affiliated Conferences List of Conference Proceedings Volumes Appearing Before the Conference Preface 4th International Conference on Adaptive Instructional Systems (AIS 2022) HCI International 2023 Contents Learner Modeling and State Assessment for Adaptive Instructional Decisions Heart Rate Variability for Stress Detection with Autistic Young Adults 1 Introduction 2 System Design 2.1 Methods 2.2 Data Analysis 3 Results 4 Discussion and Conclusion References Bayesian Cognitive State Modeling for Adaptive Serious Games 1 Introduction 2 Related Work 3 Concept for a Cognitive User Model 3.1 Observable Variables 3.2 Cognitive User Models for Serious Games 3.3 A Hierarchical Bayesian User Model 4 Evaluation 5 Conclusion and Outlook References Player State and Diagnostics in Adaptive Serious Games. Suggestions for Modelling the Adversarial Contradiction 1 Introduction 2 Premises in Theories of Adaptive Serious Games 3 Premise Analysis 4 Performative Retorsion 5 Adaptivity 6 Adaptive Serious Games References Adaptive Learner Assessment to Train Social Media Analysts 1 Introduction 2 Background 2.1 Student Modeling in an Intelligent Tutoring System 2.2 Social Media Analysis 3 GLAsE: Learner Assessment for Twiner 4 GLAsE Model and Component Overview 4.1 Curriculum Model 4.2 Learner Model 4.3 Learner Modeler 4.4 Plan Recognizer 4.5 Critic 4.6 Curriculum Element Scorer 4.7 Advisor/Hint Generator 5 GLAsE Implementation Details 6 Conclusions References A Review of Automatic Detection of Learner States in Four Typical Learning Scenarios 1 Introduction 2 Review Method 3 Learning States 3.1 Affect 3.2 Engagement 3.3 Attention/Mind Wandering 3.4 Cognitive Load 4 Typical Learning Scenarios 4.1 Computer-Based Learning 4.2 Mobile Learning 4.3 Traditional Classroom-Based Learning 4.4 Individual Computer-Free Learning 5 Discussion References Learner Modeling in Conversation-Based Assessment 1 Introduction 2 Evidence from Dialogue Systems 3 Evidence in CBAs 3.1 Integrating Process and Response Data 3.2 Interpretability of Learner Models 4 Discussion 5 Future Work References Adaptation Design to Individual Learners and Teams Adaptively Adding Cards to a Flashcard Deck Improves Learning Compared to Adaptively Dropping Cards Regardless of Cognitive Ability 1 Introduction 1.1 Overview 1.2 Flashcard-Based Learning 1.3 Adaptive Mastery-Based Approaches to Flashcard-Based Learning 1.4 Cognitive Ability and Flashcard-Based Learning 1.5 Present Study 2 Method 2.1 Participants and Design 2.2 Materials 2.3 Procedure 3 Results 3.1 Online Versus In-Person Session Comparison 3.2 Learning Performance 4 Discussion 4.1 Overview 4.2 When Should Flashcard-Based Learning Be Adaptive? 4.3 Cognitive Ability and Flashcard-Based Learning 4.4 Conclusion References AIS Challenges in Evaluating the Selection of Learner Interventions 1 Introduction to Adaptive Instruction 2 Learning Effect Model (LEM) 2.1 Assessment of Learner Domain Competency 2.2 Assessment of Learner Real-Time Performance 2.3 Selection of Optimal Learner Interventions 2.4 Execution of Selected Learner Interventions 2.5 Evaluation of Intervention Effect on Learning 3 Additional Recommendations References Iterative Refinement of an AIS Rewards System 1 Introduction 2 Methods 2.1 Platform 2.2 Data Collection 2.3 Overview of Design Iterations 3 Analysis and Results 3.1 V0 to V1 Design Change Impact 3.2 V1 to V2 Design Change 3.3 V2 to V3 Design Change 4 Discussion and Conclusions References Examining Two Adaptive Sequencing Approaches for Flashcard Learning: The Tradeoff Between Training Efficiency and Long-Term Retention 1 Introduction 1.1 Retrieval Practice with Flashcards 1.2 Adaptive Training and Adaptive Flashcards 1.3 Two Adaptive Sequencing Approaches 1.4 Current Research and Hypotheses 2 Method 2.1 Participants and Design 2.2 Materials 2.3 Procedure 3 Results 4 Discussion 4.1 Implications and Limitations 4.2 Future Research 4.3 Conclusion References Design and Development of Adaptive Instructional Systems Development of AIS Using Simulated Learners, Bayesian Networks and Knowledge Elicitation Methods 1 Introduction 2 Problem Statement 3 Bayesian Networks for Learner and Tasks Models 4 Expert Tutors Knowledge Elicitation 4.1 Semi-structured Interviews 4.2 Simulation Exercises 4.3 Data to Inform and Optimize Export Tutors 5 Simulated Learners and Tutors for Exploring AIS Design Options 5.1 ACT-R Cognitive Architecture 5.2 Learners and Tutors Cognitive Models 6 Summary References Promoting Equity and Achievement in Real-Time Learning (PEARL): Towards a Framework for the Formation, Creation, and Validation of Stackable Knowledge Units 1 Introduction 2 Literature Review 2.1 Cognitive Ability 2.2 Affective Skills 2.3 Domain/Industry Knowledge 3 Problem Based Learning, Competency-Based Education, and Stackable Knowledge Units 4 The Artificial Intelligence Learning Approach 4.1 Adaptive Learning in Educational Settings 4.2 Opportunities 4.3 Challenges 5 The PEARL Approach 6 Earl in Practice 6.1 Illustrative Healthcare-Related PBL Scenario 6.2 Acceptance and Implementation Perspectives Regarding PEARL 6.3 Learner’s Preparation and Readiness for PBL 6.4 Learning, Scaffolding, and Technology Integration 7 Conclusions and Future Research References SatisfAI: A Serious Tabletop Game to Reveal Human-AI Interaction Dynamics 1 Introduction 2 Background 2.1 Human Needs Models 2.2 Dimensions of AI Systems 3 Game Design 3.1 Prototype Gameplay 4 Data Collection Design and Approach 4.1 Data Collection 4.2 Assumptions and Risks 5 Play Testing and Evaluation Approach 5.1 Evaluating Data Collection 6 Conclusions References A Framework for the Design and Development of Adaptive Agent-Based Simulations to Explore Student Thinking and Performance in K-20 Science 1 Introduction and Motivation 2 Instruction and Assessment for 3D Science Learning 2.1 Developing and Using Models in K-20 Science Education 2.2 The Importance of Making Models for Science Learning 3 Framework for Agent-Based Adaptive Learning in Science 3.1 Agent-Based Models and Simulations 3.2 Intelligent Tutoring Systems and Simulation 3.3 FABALS Architecture 3.4 ABMS Design and Development with FABALS 3.5 Framework Application 3.6 Areas for Future Development 4 Conclusions References Adaptive Instructional System for Complex Equipment Trainings in the Post-covid Era: Breaking the Ice of Time-Consuming Tasks 1 Introduction 2 Material and Methods 2.1 Participants and Equipment 2.2 Training Quality Evaluation 2.3 Pre-training Form 2.4 Instructor and Trainee Feedback Forms 2.5 Software Architecture of MicroAssistant Platform 2.6 MicroAssistant UI Design 2.7 MicroAssistant Recommendation System 3 Results 3.1 Assessing the Difficulty of AIS Adaptation for Core Facilities 3.2 RQ1: Different Tools to Overview and Intervene Training Sessions Reduces the Active Presence of the Instructor During Trainings with MicroAssistant 3.3 RQ1: Modular Design of Database of Training Content Decreases the Time for Preparation of Autonomous Trainings for Other Equipment 3.4 RQ1: Introducing Simultaneous Trainings as a New Way to Increase Cost-Efficiency of Adaptation of Automatic Training Solution for Equipment Trainings in CFs 3.5 Cost-Efficiency of AIS Training Solution for Equipment Trainings in CF 3.6 RQ2: Modular Design Allows Rapid Customization of Training Session 3.7 RQ2: Recommendation System Increases Engagement of Trainees During Autonomous Trainings 3.8 Feedback-Based Evaluation of the System 4 Discussion 5 Limitations 6 Conclusion and Future Directions References Learning Support and Evaluation of Weight-Shifting Skills for Novice Skiers Using Virtual Reality 1 Introduction 2 Related Research 3 Development of a Ski Learning Support System 4 Evaluation Experiment 4.1 Measurement Methods 4.2 Participants 4.3 Verification Method 4.4 Evaluation 4.5 Result 5 Discussion 5.1 Findings 5.2 Contribution 5.3 Limitation 6 Conclusion References ILoveEye: Eyeliner Makeup Guidance System with Eye Shape Features 1 Introduction 2 Related Work 2.1 Eye Features 2.2 Guidance System 2.3 Makeup Guidance 3 System Overview 3.1 Eye Detection 3.2 System Workflow 3.3 Eye Features Analysis 4 Makeup Guidance 4.1 Eyeliner Styles 4.2 Merging Types 4.3 User Interface 5 System Evaluation 5.1 Experiment Procedure 5.2 Evaluation Method 6 Results 6.1 Subjective Evaluation 6.2 Objective Evaluation 7 Discussion 8 Conclusion References Evaluating the Effectiveness of Adaptive Instructional Systems Lessons Learned from Creating, Implementing and Evaluating Assisted E-Learning Incorporating Adaptivity, Recommendations and Learning Analytics 1 Introduction 2 Requirements 2.1 Organizational Requirements 2.2 Methodological Requirements 2.3 Didactical Requirements 2.4 Content Requirements 2.5 Technical Requirements 3 Requirements Engineering Tailored to Our Users Needs 4 AI Supported Functionalities for Learners and Teachers 4.1 Learning Recommender System 4.2 Chatbot 4.3 Adaptive Tasks 4.4 Learning Analytics Dashboard for Instructors 5 Evaluation 5.1 Evaluation Results 6 Discussion and Lessons Learned 7 Conclusion and Further Research References Development of the Assessment Toolkit for Leader Adaptability Skills (ATLAS) 1 Introduction 1.1 Cognitive Framework of Adaptability 1.2 ATLAS Simulation Environment 1.3 ATLAS Measure Scoring 2 Field Test Validation 3 Current and Future Implications with Automated Adaptability Measures 3.1 Adaptability Performance Feedback 3.2 Adaptability Throughout Training and Education 4 Conclusion References Measurements and Interventions to Improve Student Engagement Through Facial Expression Recognition 1 Introduction 2 Related Work 3 Research Questions 4 Methods 4.1 Intelligent Tutors 4.2 Facial Expression Recognition (FER) 4.3 Design 4.4 Data 5 Results 5.1 Exploratory Analysis 5.2 Re-engagement Interventions Analysis 6 Discussions 7 Conclusions References Assessing the Social Agency of Pedagogical Agents in Adaptive Training Systems 1 Introduction 1.1 Adaptive Training – Feedback Strategies 1.2 Learning with Pedagogical Agents 1.3 Theoretical Background: How Do Pedagogical Agents Influence Learning? 1.4 Experimental Extensions of Social Agency Theory 2 Scale Development 3 The Present Study 4 Method 5 Results 6 Applications and Extensions References Author Index