Artificial Intelligence in Education Technologies: New Development and Innovative Practices: Proceedings of 2022 3rd International Conference on Artificial Intelligence in Education Technology

✍ Scribed by Eric C. K. Cheng, Tianchong Wang, Tim Schlippe, Grigorios N. Beligiannis (eds.)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 224
• Series: Lecture Notes on Data Engineering and Communications Technologies, 154
• Category: Library

✦ Synopsis

This edited book is a collection of selected research papers presented at the 2022 3rd International Conference on Artificial Intelligence in Education Technology (AIET 2022), held in Wuhan, China, on July 1–3, 2022. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems.

The book is divided into five main sections – 1) AI in Education in the Post-COVID New Norm, 2) Emerging AI Technologies, Methods, Systems and Infrastructure, 3) Innovative Practices of Teaching and Assessment Driven by AI and Education Technologies, 4) Curriculum, Teacher Professional Development and Policy for AI in Education, and 5) Issues and Discussions on AI In Education and Future Development. Through these sections, the book provides a comprehensive picture of the current status, emerging trends, innovations, theory, applications, challenges and opportunitiesof current AI in education research.

This timely publication is well aligned with UNESCO’s Beijing Consensus on Artificial Intelligence (AI) and Education. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education in the post-pandemic new norm and triggering an exponential leap toward the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.

✦ Table of Contents

Conference Committee
Preface
Contents
Machine Learning and Data Analysis in Education
Towards Effective Teacher Professional Development for STEM Education in Hong Kong K-12: A Case Study
1 Background
2 Literature Review
2.1 From Education for STEM to STEM Education
2.2 Teacher Professional Development
3 Methodology
3.1 Research Questions
3.2 Research Design
3.3 Case Selection and Research Settings
3.4 Data Analysis
4 Findings and Discussions
4.1 Cascade Model of TPD Supports Laying the Groundwork for STEM Education
4.2 The Unavailing Training Model Prompts a Revisit to TPD Content
4.3 Partnership Model of TPD Can Bring in New Knowledge, but Application Requires Sustainability and Teacher Collaboration
4.4 Action Research Model Can Encourage Innovative Practice of STEM Education, but Teachers Need Support
5 Conclusion and Implications
References
Identification and Hierarchical Analysis of Risk Factors in Primary and Secondary Schools: A Novel GT-DEMATEL-ISM Approach
1 Introduction
2 Identification of Risk Factors for School Safety
2.1 Obtaining Data
2.2 Analysis of Coding
3 Model Construction of DEMATEL-ISM
3.1 Data Collection
3.2 DEMATEL Analysis
3.3 ISM Analysis
3.4 Discussions
4 Conclusions
References
Generation of Course Prerequisites and Learning Outcomes Using Machine Learning Methods
1 Introduction
2 Related Work
3 Prerequisites Generation
3.1 Matrix Factorization
4 Outcomes Generation
4.1 Keyphrases Extraction
4.2 Similar Course's Keyphrases Recommendation
5 Results and Discussion
6 Conclusion
References
Learning Factors for TIMSS Math Performance Evidenced Through Machine Learning in the UAE
1 Introduction
2 Literature Review
3 Methodology
3.1 SHapley Additive exPlanation (SHAP)
3.2 Model Input—Learning Factors
3.3 Model Output—Student TIMSS Performance in Mathematics
3.4 Boosted Regression Tree Model
4 Results and Discussion
4.1 Model Performance
4.2 SHAP Summary Plot of Learning Factor by Importance
4.3 Discussion
5 Conclusion
5.1 Summary of Key Findings
5.2 Limitations
5.3 Future Work
Appendix
References
Educational Information Technology and E-Learning
Explainability in  Automatic Short Answer Grading
1 Introduction
2 Related Work
2.1 Explainability
2.2 Automatic Short Answer Grading
3 Methods for Explainability in Automatic Short Answer Grading
3.1 Predicted Points
3.2 Predicted Points with Confidence Scores
3.3 Predicted Points with Confidence Scores and Similar Answers
3.4 Predicted Points with Relevance of Words in the Answer
3.5 Predicted Points with Matching Positions
4 Experimental Setup
5 Experiments and Results
5.1 Trust
5.2 Informative Content
5.3 Speed
5.4 Consistency and Fairness
5.5 Fun
5.6 Comprehensibility
5.7 Applicability
5.8 Use in Exam Preparation
5.9 General Evaluation
5.10 Influence
6 Conclusion
7 Future Work
References
The Framework Design of Intelligent Assessment Tasks Recommendation System for Personalized Learning
1 Introduction
2 Related Work
3 Assessment Tasks Recommendation Framework Design
3.1 Data Processing Component
3.2 Personalized Assessment Task Generation Component
4 System Design of Intelligent Personalized Assessment Tasks Recommendation System
4.1 Data Processing Component
4.2 Personalized Assessment Tasks Recommendations Components
4.3 System Analysis
5 Conclusion
References
Assessing Graduate Academic Scholarship Applications with a Rule-Based Cloud System
1 Introduction
2 Literature Review
2.1 Graduate Scholarship
2.2 Motivation for Academic Scholarship
2.3 Rule-Based System
2.4 Cloud Computing
3 The Architecture of the Rule-Based Cloud System
4 Experiment
5 Results
6 Discussion
7 Conclusion
References
AI-Based Visualization of Voice Characteristics in Lecture Videos’ Captions
1 Introduction
2 Related Work
3 AI-Based Visualization of Voice Characteristics in Captions
4 Experimental Setup
4.1 Study Design
4.2 Participants
5 Experiments and Results
5.1 Visualization of Voice Characteristics
5.2 Preferences
5.3 Understanding the Content
5.4 Linguistic Understanding
5.5 Following the Content
5.6 Identifying Important Words
5.7 Further Applications
6 Conclusion and Future Work
References
The Intergroup Bias in the Effects of Facial Feedback on the Recognition of Micro-expressions
1 Introduction
1.1 Micro-expression and Micro-expression Recognition
1.2 Facial Feedback
1.3 Intergroup Bias
2 Overview of the Current Research
3 Method
3.1 Participants
3.2 Design
3.3 Stimuli
3.4 Manipulation of Facial Feedback
3.5 Experimental Tasks
4 Results
5 Discussion
6 Conclusion
References
Feedback on the Result of Online Learning of University Students of Health Sciences
1 Introduction
2 Material and Method
3 For data processing, a descriptive level statistical analysis was applied through the use of STUDENt's T and a regression analysis considering the regression coefficient and the standard deviation.
4 Results
5 Discussion and Conclusions
References
Educational Management, Psychology and Educational Statistics
Exploration and Application of the Blended Learning Model in the “Software Engineering” Course
1 Problem Existing in the Teaching of Software Engineering
1.1 The Educational Topic is not Properly Integrated with Industry, and There is a Lack of Training for Engineering Practice
1.2 Teaching Output is Out of Sync with Societal Requirements and Disconnected from a Continuously Changing World
1.3 The Utilization Rate of Teaching Resources is Low, and the Teaching Means in Traditional Classroom Teaching Are Limited and Rigid
2 In a Software Engineering Course, Blended Teaching is Used
2.1 It Stresses the “STudent-Centered” and “Project-Driven” Teaching Concepts in Engineering Education
2.2 Reconstruction and Optimization of Curriculum Content Based on “Social Needs” + “Student Needs”
2.3 Increase the Exploitation of Teaching Materials and Develop a Smart Teaching Method
2.4 Big Data Analysis of Students’ Learning Situations, Gap Identification, and Filling, and Feedback Teaching
3 Arrangement of the Teaching Process in the Mixed Teaching Style
3.1 Bridge-In
3.2 Objective
3.3 Pre-test
3.4 Participation
3.5 Post-test
3.6 Summary
4 Teaching Outcomes in the Mixed Modality of Instruction
4.1 The Using Course Teaching Innovation
4.2 Curriculum Reform's Radiant Effect
5 Conclusion
References
Improving Learning Outcomes with Pair Teaching StrateFiggy in Higher Education: A Case Study in C Programming Language
1 Introduction
2 Literature Review
2.1 Learning Outcomes
2.2 Collaborative Strategies
3 Pair Teaching Method
4 Experiment Design
4.1 Participants
4.2 Course and Experiment Design
4.3 Data Analysis Methods
5 Results
6 Discussion
7 Conclusion
References
Foreign Language Reading Anxiety and Its Correlation with Reading Test Scores
1 Introduction
1.1 Purpose and Significance of the Research
1.2 Research Questions
2 Literature Review
2.1 Foreign Language Reading Anxiety
2.2 Foreign Language Reading Anxiety Level
2.3 FLRA and Correlates
2.4 Contributions and Gaps
3 Methodology
3.1 The Survey Design
3.2 Sample
3.3 Instrumentation
3.4 Procedures
4 Results
4.1 Research question 1: What is advanced students’ level of Foreign Language Reading Anxiety?
4.2 Research Question 2: Is There a Difference Between Foreign Language Reading Anxiety and Demographic Variables, Specifically Gender, Birthplace, and Time Spent on Reading English Texts Weekly?
4.3 Research question 3: Is there a relationship between FLRA and reading test scores?
5 Discussion
6 Conclusions
References
The Relationship between Nostalgia and Life Satisfaction in College: A Chained Mediation Model
1 Introduction
2 Theory Analysis and Research Hypothesis
2.1 The Direct Effect of Nostalgia on Satisfaction of Life
2.2 The Direct Effect of Nostalgia on Emotions
2.3 Chain Mediation Analysis of Nostalgia on Life Satisfaction
3 Subjective and Methods
3.1 Subjective
3.2 Tools
3.3 Data Processing
4 Outcomes
4.1 Validity and Common Method Bias Tests
4.2 Descriptive Statistical Analysis and Correlation Analysis
4.3 Analysis of the Role of Multiple Chain Intermediaries
5 Discussions
5.1 Discussion of the Direct Effect of Nostalgia on Life Satisfaction
5.2 Discussion on the Chain Mediating Effect of Positive Emotions and Self-esteem
5.3 Research Significance
6 Findings
References
Reform and Practice of Talent Training Model Based on Cold Chain Industry College
1 First Section
2 Ideas About the Construction of the Talent Training Model of the Cold Chain Industry College
3 “3 + 1” Talent Cultivation Operation Mechanism of Cold Chain Industry College
3.1 Theoretical Basis of the New Operating Mechanism
3.2 Organizational Leadership
3.3 Curriculum System
3.4 Key Links of the New Operating Mechanism
4 Construction of Relevant Regulations and Systems for Talent Training in Cold Chain Industry College
4.1 “3 + 1” Talent Training Organization and Management System of Cold Chain Industry College
4.2 “3 + 1” Talent Training Quality Assurance System of Cold Chain Industry College
4.3 “3 + 1” Talent Cultivation Support and Incentive System of Cold Chain Industry College
5 Practical Effect
6 Conclusion
References
Study on the Growth Pattern of Middle-Level Vocational Skills
1 Introduction
2 Analysis Process of the Growth Data of 86 Intermediate Vocational Talents
2.1 Knowledge Structure - Educational Level
2.2 Knowledge Structure - Learning and Training
2.3 Duties and Responsibilities - Passing on the Help
2.4 Competency - Organizational Management
2.5 Competency - Identify and Troubleshoot Problems
2.6 Competency - Theoretical Research
2.7 Competency - Job Competition
2.8 Honor - Access to Awards
3 The Establishment of Professional Competence Quality Model for Intermediate Vocational Skills Personnel
3.1 The Selection of Professional Competence Quality Indicators
3.2 Modeling
4 Model Validation
5 Discussion
5.1 Conclusion
References
Author Index