Sustainability and Scalability of AI-Based Solutions in ESL Education
DOI:
https://doi.org/10.59367/vfd42a16Abstract
The integration of Artificial Intelligence (AI) into educational systems is revolutionizing the way learning occurs, particularly in the realm of English as a Second Language (ESL) education. AI-based adaptive learning solutions offer the promise of personalized, efficient, and effective education tailored to the unique needs of each learner. However, the adoption of these technologies raises significant questions about their sustainability and scalability, particularly across diverse educational settings such as urban, rural, and international contexts. This essay explores these dimensions, examining the challenges and opportunities associated with the implementation of AI-driven adaptive learning systems in ESL education.
References
P William, Narendar Chinthamu, Indradeep Kumar, Manish Gupta, Anurag Shrivastava, Arun Pratap Srivastava, Schema Design with Intelligent Multi Modelling Edge Computing Techniques for Industrial Applications, 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN).
P William, Narendar Chinthamu, Indradeep Kumar, Manish Gupta, Anurag Shrivastava, Arun Pratap Srivastava, Schema Design with Intelligent Multi Modelling Edge Computing Techniques for Industrial Applications, 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN).
Kuldeep Chouhan, Abhishek Singh, Anurag Shrivastava, Structural Support Vector Machine for Speech Recognition Classification with CNN Approach, 2021 9th International Conference on Cyber and IT Service Management (CITSM).
A Deepak, P William, Rajat Dubey, Shilpa Sachdeva, C Vinotha, Sunny Masand, Anurag Shrivastava, Impact of Artificial Intelligence and Cyber Security as Advanced Technologies on Bitcoin Industries, International Journal of Intelligent Systems and Applications in Engineering, Vol-12, Issue-3.
J. Prakash Arul Jose, Anurag Shrivastava, Prem Kumar Soni, N. Hemalatha, An Analysis of the Effects of Nanofluid-Based Serpentine Tube Cooling Enhancement in Solar Photovoltaic Cells for Green Cities, Hindawi, Journal of Nanomaterials Volume 2023,
Pooja Bagane, Susheel George Joseph, Abhishek Singh, Anurag Shrivastava, B Prabha, Amit Shrivastava, Classification of Malware using Deep Learning Techniques, 2021 9th International Conference on Cyber and IT Service Management (CITSM)
Rakesh Kumar Godi, Mule Shrishail Basvant, A Deepak, Arun Pratap Srivastava, Manoj Kumar, Akhil Sankhyan, Anurag Shrivastava, Sentiment Analysis on Omicron Tweets Using Hybrid Classifiers with Multiple Feature Extraction Techniques and Transformer Based Models, International Journal of Intelligent Systems and Applications in Engineering, Vol-12, 15-S.
Ayan Banik, Jarabala Ranga, Anurag Shrivastava, Subash Ranjan Kabat, AVGA Marthanda, S Hemavathi, Novel Energy-Efficient Hybrid Green Energy Scheme for Future Sustainability, 2021 International Conference on Technological Advancements and Innovations (ICTAI)
Ajay Rana, Virender Khurana, Amit Shrivastava, Durgaprasad Gangodkar, Deepika Arora, Anil Kumar Dixit, A ZEBRA Optimization Algorithm Search for Improving Localization in Wireless Sensor Network, 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)
Balbir Singh, Manjush Tatiya, Anurag Shrivastava, Devvret Verma, Arun Pratap Srivastava, Ajay Rana, Detection of Alzheimer's Disease Using Deep Learning, Blockchain, and IoT Cognitive Data, 2022 2nd International Conference on Technological Advancements in Computational Sciences, ICTACS
Bikash Chandra Saha, Anurag Shrivastava, Sanjiv Kumar Jain, Prateek Nigam, S Hemavathi, On-Grid solar microgrid temperature monitoring and assessment in real time, Materials Today: Proceedings, Volume 62, Part 7, 2022.
Shamita Chakaborty, Yogini Dilip Borole, Archana S Nanoty, Anurag Shrivastava, Sanjiv Kumar Jain, Moti Lal Rinawa, Smart Remote Solar Panel Cleaning Robot with Wireless Communication, 2021 9th International Conference on Cyber and IT Service Management (CITSM)
Shrivastava, A., Chakkaravarthy, M., Shah, M.A..A Novel Approach Using Learning Algorithm for Parkinson’s Disease Detection with Handwritten Sketches. In Cybernetics and Systems, 2022
Shrivastava, A., Chakkaravarthy, M., Shah, M.A., A new machine learning method for predicting systolic and diastolic blood pressure using clinical characteristics. In Healthcare Analytics, 2023, 4, 100219
Shrivastava, A., Chakkaravarthy, M., Shah, M.A.,Health Monitoring based Cognitive IoT using Fast Machine Learning Technique. In International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(6s), pp. 720–729
Shrivastava, A., Rajput, N., Rajesh, P., Swarnalatha, S.R., IoT-Based Label Distribution Learning Mechanism for Autism Spectrum Disorder for Healthcare Application. In Practical Artificial Intelligence for Internet of Medical Things: Emerging Trends, Issues, and Challenges, 2023, pp. 305–321
Boina, R., Ganage, D., Chincholkar, Y.D., .Chinthamu, N., Shrivastava, A., Enhancing Intelligence Diagnostic Accuracy Based on Machine Learning Disease Classification. In International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(6s), pp. 765–774
Shrivastava, A., Pundir, S., Sharma, A., ...Kumar, R., Khan, A.K. Control of A Virtual System with Hand Gestures. In Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 1716–1721
Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., & Mané, D. (2016). Concrete problems in AI safety. arXiv preprint arXiv:1606.06565.
Beam, A. L., & Kohane, I. S. (2018). Big data and machine learning in health care. JAMA, 319(13), 1317-1318.
Che, Z., Purushotham, S., Khemani, R., & Liu, Y. (2016). Interpretable deep models for ICU outcome prediction. AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2016, 371.
ALMahadin, Ghayth, Yassine Aoudni, Mohammad Shabaz, Anurag Vijay Agrawal, Ghazaala Yasmin, Esraa Saleh Alomari, Hamza Mohammed Ridha Al-Khafaji, Debabrata Dansana, and Renato R. Maaliw. "VANET Network Traffic Anomaly Detection Using GRU-Based Deep Learning Model," IEEE Transactions on Consumer Electronics (2023).
Al-Khafaji, Hamza MR, Esraa S. Alomari, and Hasan S. Majdi. "Review of Analytics Tools on Traffic for IoT and Cloud Based Network Environment," In 2020 3rd International Conference on Engineering Technology and its Applications (IICETA), pp. 73-77. IEEE, 2020.
Al-Khafaji, Hamza Mohammed Ridha, Esraa Saleh Alomari, and Hasan Shakir Majdi. "Secured environment for cloud integrated fog and mist architecture," In 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech), pp. 112-116. IEEE, 2019.
Nuiaa, Riyadh Rahef, Selvakumar Manickam, Ali Hakem Alsaeedi, and Esraa Saleh Alomari. "Enhancing the Performance of Detect DRDoS DNS Attacks Based on the Machine Learning and Proactive Feature Selection (PFS) Model," IAENG International Journal of Computer Science 49, no. 2 (2022).
Alomari, Esraa Saleh. "Soft computing-based cluster head selection for secured energy aware routing in flying ad hoc networks (FANET)," Indian J. Public Health Res. Dev 9 (2018): 1993.
Al Ogaili, Riyadh Rahef Nuiaa, Esraa Saleh Alomari, Manar Bashar Mortatha Alkorani, Zaid Abdi Alkareem Alyasseri, Mazin Abed Mohammed, Rajesh Kumar Dhanaraj, Selvakumar Manickam, Seifedine Kadry, Mohammed Anbar, and Shankar Karuppayah. "Malware cyberattacks detection using a novel feature selection method based on a modified whale optimization algorithm," Wireless Networks (2023): 1-17.
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