Adaptive Instructional Systems. Adaptation Strategies and Methods: Third International Conference, AIS 2021, Held as Part of the 23rd HCI ... II (Lecture Notes in Computer Science, 12793)

Description

This two-volume set LNCS 12774 and 12775 constitutes the refereed proceedings of the 12th International Conference on Social Computing and Social Media, SCSM 2021, held as part of the 23rd International Conference, HCI International 2021, which took place in July 2021. Due to COVID-19 pandemic the conference was held virtually. The total of 1276 papers and 241 poster papers included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The regular papers of AIS 2021, Part II, focus on Learner Modelling and State Assessment in AIS. Foreword HCI International 2021 Thematic Areas and Affiliated Conferences Contents – Part II Contents – Part I Learner Modelling and State Assessment in AIS Helping Instructor Pilots Detect and Respond to Engagement Lapses in Simulations 1 Introduction 1.1 Supporting Instructors with Adaptive Learning 1.2 Exemplar Use Case: Pilot Training Next 2 Models of Engagement 2.1 General Model of Engagement 2.2 VR Influences on Engagement Metrics 3 Machine Learning Model Design and Training 3.1 Machine Learning Models 3.2 Model Training 4 Supporting Instructors: Adaptive Recommendations 4.1 Adaptive Recommendations Model 4.2 Adaptive Recommendation Methods 5 Model Performance 6 Conclusions and Future Work References Dynamic Analytics for the Detection of Quality and Alignment Issues in an Online Hybrid Adaptive Instructional and Assessment System 1 Introduction 2 Hybrid Adaptive Instruction and Assessment System 2.1 Instructional Module 2.2 Mastery Quiz Assessment 2.3 Progress Check Assessment 2.4 Screener Adaptive Diagnostic Assessment 3 Psychometric Methods for Detecting Misalignment of Instruction and Assessment and Checking Item Quality 4 Empirical Example 4.1 Data and Cleaning Rules 4.2 Application Procedure 4.3 Workflow Process from Data Analysis to Result Reporting 5 Conclusion References Predicting Literacy Skills via Stealth Assessment in a Simple Vocabulary Game 1 Introduction 1.1 iSTART 1.2 iSTART Games 1.3 Literacy Assessment for Personalized Training 1.4 Current Study 2 Methods 2.1 Participants 2.2 Procedure, Materials, and Measures 2.3 Statistical Analyses 3 Results 3.1 Principal Component Analysis 3.2 Descriptive Statistics of Predictor and Predicted Variables 3.3 Hierarchical Linear Regressions 4 Discussion References Skill Mastery Measurement and Prediction to Adapt Instruction Strategies 1 Introduction 1.1 Background and Related Work 1.2 Current Study 2 Design of an Automated VACR Training Support System 2.1 Description of Different Candidate Tutors 2.2 Dynamic Bayesian Network (DBN) Algorithm to Track Aircraft Mastery 2.3 Study Aim and Research Questions 3 Method 3.1 Participants 3.2 Procedure 4 Results and Discussion 5 Conclusions 6 Future Work References Measuring Flow, Immersion and Arousal/Valence for Application in Adaptive Learning Systems 1 Introduction 2 Literature Review 2.1 Presence 2.2 Immersion 2.3 Flow 3 A Combined Model of Flow and Immersion 4 Measuring Flow and Immersion 4.1 Study Design 4.2 Physiological Measurements 4.3 Study and Results 5 Extending the Combined Flow/Immersion Model with Arousal/Valence 5.1 Measuring Intensity (Arousal)/Valence 6 Future Work References Modelling and Quantifying Learner Motivation for Adaptive Systems: Current Insight and Future Perspectives 1 Introduction 2 Research Background 2.1 Motivation 2.2 Persuasive Technology 3 Modelling of Motivation to Learn in Intelligent Tutoring Systems 3.1 Techniques for Learners’ Motivational States Diagnosis in ITSs 3.2 Strategies and Features for Adapting to Learner Motivation 4 Proposed Architecture for Integrating Motivation Modelling into ITSs 5 Conclusion References Competency-Based Experiential-Expertise and Future Adaptive Learning Systems 1 Introduction 2 Discussion 2.1 Competency 2.2 Experiential-Expertise 3 Method 4 Conclusion and Recommendation References Early Prediction of At-Risk Students in a Virtual Learning Environment Using Deep Learning Techniques 1 Introduction 2 Literature Study 3 Research Questions and Objectives 4 Methodology 5 Experimentation 5.1 OULA Dataset 5.2 Preprocessing of Dataset 5.3 Convolutional Neural Networks 6 Results and Discussions 7 Conclusion References An Experiential Competency Application Framework 1 Overview 1.1 Ecaf 2 Terms and Definitions 3 The State Model 3.1 Assertion Scores 3.2 Practice 3.3 Skill Decay 3.4 Spaced Repetition 3.5 ECAF State Function Calculation 4 Predictive Models 5 Training Model 6 ECAF Implementations 7 Analysis of Intelligent Tutoring Systems 8 Closing Remarks and Further Research References Individual Differences in the Relationship Between Emotion and Performance in Command-and-Control Environments 1 Introduction 1.1 Background 1.2 Hypotheses 2 Methodology 2.1 Sample Description 2.2 Experimental Task 2.3 Variables 2.4 Statistical Analysis 3 Results 3.1 Expected Results 3.2 Observed Results 4 Discussion 4.1 Individual Differences in the Relationship of Emotional Valence and Performance 4.2 The Importance of Multifactorial Detection of Emotional Arousal 4.3 Methodological Reasons 5 Conclusions References Using Principled Assessment Design and Item Difficulty Modeling to Connect Hybrid Adaptive Instructional and Assessment Systems: Proof of Concept 1 Introduction 1.1 Achievement Level Descriptors 1.2 Learning Progressions 1.3 Adaptive Systems 1.4 Evaluation of the Validity Framework 2 Purpose 3 Methods 4 Results 5 Conclusion and Discussion References Dynamic Cognitive Modeling for Adaptive Serious Games 1 Introduction 2 Related Work 3 Cognitive Architectures and E-Learning 4 Concept for User Modeling and Artificial Intelligence (UMAI) 5 Software Architecture, Implementation 6 Application and Results 6.1 Serious Game: Exercise Trainer (EXTRA) 6.2 Application of UMAI 7 Conclusion References Staying Ahead of the Curve: Selecting Students for Newly Arising Tasks 1 Introduction 2 Constructing a Data Set 2.1 The Students 2.2 The Tasks 2.3 Data Generation 2.4 Labelling the Students and Tasks 3 Student Selection Methods 3.1 Matrix Factorization 3.2 Neighborhood Model 3.3 Random Forest Regression 3.4 Baseline Recommenders 4 Method 5 Results 5.1 Global Split Results 5.2 Item Split Results 6 Discussion and Related Work References Designing a Learner Model for Use in Training Analysts in a Social Media Practice Environment 1 Introduction 2 Learner Modeling Background 2.1 Learner Assessment Characteristics 3 GLAsE Component Overview 3.1 Curriculum Model 3.2 Analysis Products Comparator 3.3 Learner Modeler 4 Proficiency Scoring 4.1 Proficiency Example 5 Mapping User Actions to Expert Plans 6 Conclusion and Next Steps References Measuring Cognitive Load for Adaptive Instructional Systems by Using a Pressure Sensitive Computer Mouse 1 Introduction 2 Materials and Methods 2.1 Participants 2.2 Materials 2.3 Experimental Design 2.4 Hypotheses 2.5 Procedure 2.6 Data Analysis 3 Results 3.1 Pressure 3.2 Click Duration 3.3 Click Frequency 3.4 NASA-TLX 3.5 Summary and Discussion 4 Conclusion References Measuring and Integrating Facial Expressions and Head Pose as Indicators of Engagement and Affect in Tutoring Systems 1 Introduction 2 Related Work 2.1 Affect-Aware and Gaze-Reactive Intelligent Tutoring System 2.2 Facial Expression Recognition 2.3 Head Pose Estimation 3 Tutoring System's Response to Students' Head Pose 3.1 Method to Detect Student Head Pose 3.2 Experiment to Measure Student Head Pose 4 Teacher Dashboard to Inform Teachers 4.1 Method to Develop the Teacher Dashboard 4.2 Usability Study for the Teacher Dashboard 5 Discussion and Future Work 6 Conclusion References Enhancing Personalization by Integrating Top-Down and Bottom-Up Approaches to Learner Modeling 1 Introduction 2 Learner Modeling Approaches 3 Evidence Identification and Aggregation 4 Making Sense of Process Data 5 Improving Interpretability of Learner Models 6 Discussion 7 Future Work References Author Index