Preface xix
Part 1: Introduction to AI Tools for Online Proctoring 1
1 AI Literacy and Online Proctoring: Educational Perspectives and Strategies 3
Prihana Vasishta, Gitanjaly Chhabra and Noosha Mehdian
1.1 Introduction 4
1.2 AI in Education — Theoretical Framework 6
1.3 AI-Assisted Educational Practices 8
1.4 Strengthening Teacher Preparation for AI Literacy in Higher Education Curricula 19
1.5 Conclusion and Implications 21
2 Next-Generation Online Education Integrating AI and IoT for Superior Management and Evaluation 27
Aniket Kumar, Rajesh Kumar, Akshay Kumar, Prashant D. Yelpale and Aman Thakur
2.1 Introduction 28
2.2 AI and IoT in Online Education Systems 31
2.3 Functional Structure of IoT System 41
2.4 Emerging Technologies in the Online Education System 45
2.5 Challenges of AI and IoT in Online Education System 54
2.6 The Future Vision of AI and IoT in Online Education Systems 562.7 Conclusion 58
Part 2: Ethics of Using AI Tools in Education 63
3 Ethical Integrity in Educational Contexts 65
C. Santhiya, Ravi Prasath S., Suriya Navaneetha Krishnan K. and Kannappan R.
3.1 Introduction 66
3.2 Types and Methods of Fake Credentials 67
3.3 Consequences of Fake Credentials 72
3.4 Challenges in Detecting and Verifying Fake Credentials 84
3.5 Role of Technology in Facilitating and Combating Fake Credentials 86
3.6 Impact on Organizational Reputation and Public Trust 90
3.7 Multi-Layered Approach to Tackling the Problem 91
3.8 Innovative Solutions and Technologies 94
3.9 Promoting Awareness and Education 96
3.10 Future Trends and Strategies 99
3.11 Conclusion 99
4 Psychological and Ethical Aspects of Using Intelligent Systems in Online Proctoring 103
Mukesh Chaware and Sreejith Alathur
4.1 Introduction 104
4.2 The Advent of AI in Online Proctoring 112
4.2.1 The Need for AI in Online Proctoring 112
4.3 The Prevailing Situation 116
4.4 Psychological Aspects 119
4.5 Ethical Aspects 124
4.6 Discussion and Recommendations 127
4.6.1 Strategies for Ethically Implementing AI in Online Proctoring 127
4.7 Conclusion 128
Part 3: State-of-the-Art AI Tools and Techniques for Online Proctoring 137
5 A Comprehensive Review of Deep Learning Models on Detecting Student Emotions in Online Education 139
Thangavel Murugan, A.M. Abirami and P. Karthikeyan
5.1 Introduction 140
5.2 Understanding Student Emotions 142
5.3 Overview of Deep Learning 143
5.4 Literature Review 144
5.5 Challenges in Detecting Student Emotions 153
5.6 Future Directions and Recommendations 158
5.7 Conclusion 159
6 Deep Learning Models for Monitoring Student's Emotion During the Class: A Comprehensive Survey 165
Vamshi Krishna B., N. Padmavathy and Ajeet Kumar
6.1 Introduction 166
6.2 Literature Survey 168
6.3 Research Background 178
6.4 Prediction Models for Tracking and Monitoring Students 193
6.5 Conclusion 197
7 Comparative Analysis of Head Pose Estimation and Eye Gaze Tracking with Machine Learning Classifiers for Proctored Online Examination 203
Rajarajeswari P., Shivagangatharani B. and Karthikeyan Jothikumar
7.1 Introduction 204
7.2 Benchmark Datasets for Head Pose and Eye Gaze Tracking 207
7.3 Apparatus for Estimating Head Pose and Tracking Eye Gaze 214
7.4 Models for Head Pose Estimation and Eye Gaze Tracking 217
7.5 Comparison of Models for Head Pose Estimation and Eye Gaze Tracking 224
7.6 Conclusion 226
8 Uni- and Multi-Modal Aspects in the Online Proctoring System: Survey 231
Diana Moses and Dainty M.
8.1 Introduction 232
8.2 AI-Based Online Proctoring System 240
8.3 Existing AI-Based Online Proctoring Frameworks 249
8.4 Challenges in AI-Based Online Proctoring Frameworks 253
8.5 Future Scope of AI-Based Proctoring Frameworks 256
8.6 Conclusion 259
9 Advancing Academic Integrity: AI and IoT in Enhancing Monitoring for Online Examination Systems 265
J. Shanthalakshmi Revathy and J. Mangaiyarkkarasi
9.1 Introduction 266
9.2 Predictive Analysis of Student Performance 267
9.3 Authentication of Students 271
9.4 Supervision of Examination 272
9.5 Challenges in Monitoring 279
9.6 Conclusion 283
10 Optimizing Academic Excellence: Leveraging Advanced AI Tools for Assessment and Evaluation in Modern Online Examination Systems 287
Manikandakumar M., Karthikeyan P., Senthamarai Kannan K., Arul V. and Vigneshwaran T.
10.1 Introduction 288
10.2 Role of AI in Online Examination Systems 289
10.3 Advanced AI Tools for Assessment 293
10.4 Implementing AI Tools in Online Examination Systems 308
10.5 Future Trends 310
10.6 Conclusion 311
Part 4: Case Studies: AI and IoT in Education, Online Proctoring 315
11 Evaluation of Web Design Deficiency and Anxiety Constructs, with Computer?Based Test: Use Case in India 317
Juby Thomas, Ashique Ali K.A., Vishnu Achutha Menon, Sateesh Kumar T.K. and Lijo P. Thomas
11.1 Introduction 318
11.2 Review of Literature 319
11.3 Methodology 325
11.4 Results 328
11.5 Discussions 335
11.6 Conclusion 338
12 AI for Learners' Emotions — A Perspective Approach of Analysis During Online Assessments 343
S.J. Sheeba Sharon, R. Mary Sophia Chitra and C. Santhiya
12.1 Introduction 344
12.2 Literature Survey 346
12.3 Role of Emotions in Learning 349
12.4 Challenges in Online Assessments 350
12.5 The Rise of AI in Education 351
12.6 AI Tools for Monitoring Learner Emotions 351
12.7 Methodology 353
12.8 Advantages of Using AI Tools 356
12.9 Possible Implementational Risks 357
12.10 Demerits and Future Scope 358
12.11 Conclusion 359
13 Implementing Personalized Adaptive Online Assessments through Deep Learning 365
Fawad Naseer, Noreen Sattar, Akhtar Rasool, Kamel Jebreen and Usman Khalid
13.1 Introduction 366
13.2 Literature Review 368
13.3 Methodology 370
13.4 Case Studies 378
13.5 Results and Discussion 384
13.6 Conclusion 395
14 Generative Artificial Intelligence for Online Education Systems 399
Munmi Dutta and Vinay Kumar Goyal
14.1 Introduction 400
14.2 The Types of GAI Models 401
14.3 Working of GAI 401
14.4 Use Cases of GAI 406
14.5 The Limitations of GAI 407
14.6 Adaptive Learning Platforms 408
14.7 GAI and Adaptive Learning Intersection 409
14.8 Implications for Educators and Learners 412
14.9 GAI Effect on Workforce 412
14.10 GAI Has Already Transformed Education 413
14.11 Effect on the Participation and Performance of Learners 414
14.12 The Education Sector's Challenges with GAI 415
14.13 Policymakers and Educators Need to Reconsider the Current Educational Paradigm 418
14.14 Access and Equity Comes First 418
14.15 United Nations Educational, Scientific and Cultural Organization's (UNESCO's) Policy for Reshaping Education by Using GAI 419
14.16 Conclusion 420
15 Level of Academic Misconduct During Online Unproctored Examination with Perception of Engineering Students in India 423
S. Sasikala, G. Vidyasree, C. Selvan and R. Ragunath
15.1 Introduction 424
15.2 Literature Review 425
15.3 Research Methodology 428
15.4 Conclusion 439
16 Student Activity Monitoring Using Hybrid Deep Learning Technique During Online Examinations 443
Devi Naveen, Akshitha Katkeri, Manikantha K., A.K. Sreeja and Satish Kumar V.
16.1 Introduction 444
16.2 Related Works 447
16.3 Methodology — The Theoretical Foundation of the Proposed Model 451
16.4 Experimental Results and Discussion 456
16.5 Conclusion and Future Work 460
17 Multicue Facial Emotion Expression Using Lightweight Deep Learning Models 465
S. Hemaswathi, P. Rajkumar, N. Mohan Prabhu and R. Dhivya
17.1 Introduction 466
17.2 Related Works 469
17.3 Materials and Method 472
17.4 Experimental Result Analysis 478
17.5 Conclusion 482
Part 5: Challenges and Future Scope of AI in Online Proctoring 485
18 Machine-Learning-Based Online Assessment of Students' Academic Performance in Moodle Learning Management System 487
Reshma V.K., Nisha A.K., Radhika K. Manjusha, Divya P. and Sundaraselvan S.
18.1 Introduction 488
18.2 Literature Review 491
18.3 Research Methodology 493
18.4 Results and Discussion 496
18.5 Conclusion 509
18.6 Future Research 510
19 Issues and Challenges of Using Artificial Intelligence Proctoring Tools 515
V. Senthil
19.1 Introduction 515
19.2 Literature Review 517
19.3 Issues and Challenges of Using AI Proctoring Tools 522
19.4 Case Study 524
19.5 Conclusion 527
References 529
Index 533
