Education has a substantial impact and influences on almost all sectors in modern society. Different computer-supported educational systems have been developing for many decades to support and make easier teaching and learning processes on all levels of education. Influences of rapid development of Information Communication Technologies and other related disciplines on design and implementation of intelligent, sophisticated educational systems are evident. Nowadays intensive development and wide applications of Artificial Intelligent techniques significantly affect the development of intelligent tutoring systems, smart learning environments that incorporate virtual and augmented reality and robots.
Artificial Intelligence has the potential to address some of the biggest challenges in education today, but also in the future in order to establish innovative teaching and learning practices facilitated by powerful educational datamining and learning analytics.This book presents a collection of 17 chapters that bring interesting aspects of the state-of-the-art of application of intelligent techniques in different educational processes and settings. We believe that the works presented in the book will be of great interest to readers and that will motivate them to try to enhance presented approaches and propose better and more advanced solutions.
Author(s): Mirjana Ivanović, Aleksandra Klašnja-Milićević, Lakhmi C. Jain
Series: Learning and Analytics in Intelligent Systems, 29
Publisher: Springer
Year: 2022
Language: English
Pages: 398
City: Cham
Preface
Contents
About the Editors
1 Current Trends in AI-Based Educational Processes—An Overview
1.1 Introduction
1.2 Different Roles and Applications of AI in Education
1.3 Some Characteristic Educational Systems Based on AI Techniques
1.3.1 Adaptive Personalization Systems and Intelligent Tutoring Systems
1.3.2 Assessment and Evaluation
1.3.3 Intelligent Interfaces in Educational Systems
1.3.4 EDM and LA: The Benefits and the Challenges in Educational Processes
1.4 Concluding Remarks
References
2 Digitalization of Education
2.1 Introduction
2.2 Digitalization of Education
2.3 Conclusions
References
3 Remote Teaching and Learning Math in English Through CLIL
3.1 Introduction and Methodology
3.2 Main Pillars of CLIL
3.3 A Dialogic Vision of Teaching Mathematics: The Added Value of CLIL
3.4 Remote and Hybrid Educational Scenarios for CLIL
3.5 Remote and Hybrid Mathematics
3.6 Case Examples of Remote CLIL in Math
3.7 A Case Example of Remote CLIL in Math at Primary School Level
3.8 Discussion
3.9 Conclusions
References
4 The Potential of Artificial Intelligence for Assistive Technology in Education
4.1 Introduction
4.2 Learners with Visual Impairment
4.3 Learners with Hearing Impairments
4.4 Learners with Speech or Communication Disabilities
4.5 Learners with Intellectual Disabilities
4.6 Learners with Cognitive Disabilities
4.7 Learners with Mobility Disabilities
4.8 Futuristic Assistive Technologies and Neural Implants
4.9 Conclusions
References
5 Adaptive and Intelligent Web-Based Learning and Control Technologies
5.1 Introduction
5.2 Competency-Based Vocational Education
5.3 Conclusions
References
6 Exemplar Use-Cases for Training Teachers on Learning Analytics
6.1 Introduction
6.2 A Use Case for Hypothesis Testing
6.2.1 Method
6.2.2 Are Students Interested in Higher Education?: An Example of Hypothesis Testing
6.2.3 Use-Cases of Hypothesis Testing from Literature
6.3 Use-Case for ANOVA
6.3.1 An Example: Does the Choice of Reference Material Affect student’s Performance?
6.3.2 Use-Cases of ANOVA from Literature
6.4 A Use-Case for Correlation Relation
6.4.1 An Example: Does a Student’s Performance in a Course Depend on a Pre-requisite Course?
6.4.2 Use-Cases of Correlation Analysis from Literature
6.5 Use-Case for Linear Regression Analysis
6.5.1 Predicting the Students Performance from Pre-requisite Courses
6.5.2 Use-Cases of Regression Analysis from Literature
6.6 Conclusion
Appendix: A Primer on Statistical Terms and Definitions
References
7 Impact of Lesson Planning on Students’ Achievement Using Learner Profile System
7.1 Introduction
7.1.1 Research Questions and the Associated Hypotheses
7.2 Literature Review
7.3 Methodology
7.3.1 Learning Profile System—The Web Portal
7.3.2 Instrumentation for LPS
7.3.3 Pilot Study
7.3.4 Research Design
7.4 Results and Discussion
7.5 Conclusions
References
8 Towards an Understanding of Student Digital Ecosystems for Education
8.1 Introduction
8.2 Literature Review
8.3 Methodology
8.3.1 Participants
8.3.2 Procedure
8.3.3 Research Design
8.4 Results and Discussion
8.4.1 Access Read and Post
8.5 Conclusion
References
9 Computational Argumentation for Supporting Learning Processes: Applications and Challenges
9.1 Introduction
9.2 Argumentation in a Nutshell
9.3 Argument-Based Recommendation in Learning Environments
9.4 Opinion Mining and Argumentation: Contrasting Opinions and Viewpoints on the Internet
9.5 Shared Knowledge Awareness and Argumentation
9.6 Conclusions and Related Work
References
10 Revealing Latent Student Traits in Distance Learning Through SNA and PCA
10.1 Introduction
10.2 Background: Definitions, Algorithms, and Methods
10.3 Related Work
10.4 The Hellenic Open University Dataset
10.5 Data Analysis Process
10.6 Explicit and Latent Characteristics of the Students’ Community
10.6.1 The Descriptive Features of Students’ Community
10.6.2 Social Network Analysis and Distributions
10.6.3 Correlations
10.6.4 Factor Analysis and Clustering
10.7 Conclusions
References
11 Smart Technology in the Classroom: Systematic Review and Prospects for Algorithmic Accountability
11.1 Introduction
11.2 Methodology
11.2.1 Query Design
11.2.2 Query Limitations
11.3 AI in Education
11.3.1 AI Technologies Used in the Classroom
11.3.2 Issues
11.4 Surveillance in School
11.4.1 Video Surveillance
11.4.2 Internet Surveillance
11.4.3 Biometric Surveillance
11.4.4 Psychology of School Surveillance
11.4.5 Issues
11.5 Wearables in School
11.5.1 Possibilities of Wearables in an Educational Environment
11.5.2 Issues
11.6 Algorithmic Accountability Background
11.7 Algorithmic Accountability of Smart Technology in Education
11.8 Conclusions
11.9 Appendix
References
12 Objective Tests in Automated Grading of Computer Science Courses: An Overview
12.1 Introduction
12.2 Background
12.2.1 Differences Between Assessment and Testing
12.2.2 Objective Versus Subjective Tests
12.2.3 Five Principles of Testing for Assessment
12.2.4 Online Educational Assessment
12.3 Automated Objective Tests
12.3.1 Types of Studied Objective Test Questions
12.3.2 Assembly of Automated Objective Tests
12.4 Bias in Objective Tests, Ethical Issues, Explainability
12.5 Comparison of Factual Tests and Code Testing Systems
12.6 Conclusions and Future Challenges
References
13 Correlating Universal Design of Learning and the Performance in Science at Elementary School Level
13.1 Introduction
13.1.1 Recognition Network
13.1.2 Strategic Network
13.1.3 Affective Network
13.1.4 Research Question
13.2 Literature Review
13.3 Methodology
13.3.1 Participants
13.3.2 Intervention: Time, Resources and Space
13.3.3 Instructional Objective
13.3.4 Traditional Instructional Design for Control Group
13.3.5 Instructional Design Based on UDL Framework for Experimental Group
13.3.6 Instructional Design with Respect to UDL Checkpoints
13.4 Results
13.4.1 Pre-test and Post-test Design
13.4.2 Data Analysis
13.5 Discussion
13.6 Conclusion
References
14 Facilitating Collaborative Learning with Virtual Reality Simulations, Gaming and Pair Programming
14.1 Introduction
14.2 Group Engagement as a Central Part of Collaborative Learning
14.3 Emerging Technologies as Support for Engagement in Collaborative Learning
14.4 Forestry VR Simulations in Vocational Education
14.5 Constructing and Exploring Minecraft and Vivecraft with VR Glasses
14.6 Pair Programming as Collaborative Creative Coding
14.7 Discussion
References
15 Gamification and the Internet of Things in Education
15.1 Introduction
15.2 Gamification
15.2.1 Serious and Simulation Games in Education and Training
15.2.2 Game Engines
15.3 The Internet of Things (IoT)
15.3.1 What is the IoT?
15.3.2 The Impact of IoT
15.3.3 IoT Devices and Sensors
15.3.4 Connectivity and Security
15.3.5 Industry Examples of IoT-Enabled Training and Education
15.4 Environmental Studies Gamified Tool
15.4.1 Design and Development Methodology of the Environmental Studies Gamified Tool
15.4.2 Developing the Environmental Studies Gamified Tool
15.4.3 The IoT Implementation
15.4.4 Overview of IoT-Enabled Gamification
15.4.5 Multiplayer versus IoT-Enabled Pseudo-Multiplayer
15.4.6 The Use of Environmental Studies Tool in Class
15.4.7 Student Survey and Results
15.5 Conclusions and Future Work Conclusions
References
16 Communication-Driven Digital Learning Environments: 10 years of Research and Development of the Campus Platform
16.1 Introduction
16.2 Learning as a Social Activity
16.3 Learning as a Connective Activity
16.4 Technology as (the) Learning Environment
16.5 Campus: A Social Media Platform for Learning
16.6 A Brief Overview of the Evaluation of the Platform
16.7 Conclusions
References
17 Educational Computer Games and Social Skills Training
17.1 Introduction
17.1.1 Autism Spectrum Disorders
17.1.2 Emotional Intelligence (EI)
17.1.3 Computer Game for the Development of Social Skills in Children with ASD
17.1.4 Educational Game—Framework
17.2 Game Description
17.2.1 Tasks—Mini-Game 1
17.2.2 Tasks—Mini-Game 2
17.2.3 Tasks—Mini-Game 3
17.2.4 Tasks—Mini-Game 4
17.2.5 Tasks—Mini-Game 5
17.2.6 Tasks—Mini-Game 6
17.2.7 Tasks—Mini-Game 7
17.3 Game Development
17.3.1 Pilot Testing on Two Groups of Children and Qualitative Data
17.4 Conclusions
References
