Loading [MathJax]/extensions/MathMenu.js
Education System based on Pre- Training with Extracted Gap-Sentences for Abstractive Summarization Sequence-to-Sequence and Bidirectional Auto-Regressive Transformers | IEEE Conference Publication | IEEE Xplore

Education System based on Pre- Training with Extracted Gap-Sentences for Abstractive Summarization Sequence-to-Sequence and Bidirectional Auto-Regressive Transformers


Abstract:

In present scenario, the traditional education system has criticized for its one-size-fits-all approach, failing to provide to individual students' needs. The advent of t...Show More

Abstract:

In present scenario, the traditional education system has criticized for its one-size-fits-all approach, failing to provide to individual students' needs. The advent of technology has brought about opportunities to revolutionize education that aims to investigate the feasibility of developing an education system by addressing the existing challenges that overreliance on technology, inadequate teacher training, unequal access to digital resources existing inequalities and academic challenges. To overcome those drawbacks, this paper proposed a robust educational system by harnessing effective methods. Initially, preprocessing techniques like tokenization, stop word removal, stemming, and lemmatization are applied to the data. The processed data is then fed into the Extended Technology Acceptance Model (ETAM), which extracts optimal attributes like academic performance and grades. Leveraging these extracted parameters to an education system for developing advanced text generation models, Pre-Training with Extracted Gap-Sentences for Abstractive Summarization Sequence- To-Sequence (PEGASUS) and Bidirectional and Auto-Regressive Transformers (BART). This proposed model enables the generation of high-quality educational content, facilitating personalized learning experiences by combining these cutting-edge techniques. The performance of proposed model Pegasus-BART evaluated with the various metrics such accuracy with value of (96.56%), Precision is (94.63%), Recall is (96.04%), and F1 score is (95.77%) respectively.
Date of Conference: 22-23 November 2024
Date Added to IEEE Xplore: 05 February 2025
ISBN Information:
Conference Location: Kalaburagi, India
References is not available for this document.

I. Introduction

Education system has undergone dynamical transformation in its whole history and played crucial role in the domain of education. In olden days, the education focused on important skills like writing, mathematics and reading whereas in Middle Ages it was controlled by the different institutions of education [1]. The Renaissance marked a significant shift towards humanism in education, and by the 19th century, emergence of laws for compulsory education were imposed. During the time of difficulty faced during COVID-19 had revolutionized the complete education system as it had made everybody suffer for teaching and learning. The unpredictable quarantines and lockdowns led to mitigating the pandemic effect forcing for adjusting priorities and lifestyles for different people [2]. These modifications were also made in the field of education impacting for online conduction of classes rather than face-to-face physical interaction [3]. The education system was not possible without problems that undermined its quality, availability and relevance today [4]. Poor access to education facilities, regions especially rural or backward entities, was a big issue having large populations of school children unable to perform well due to lack of infrastructure and other resources. Further, the system suffered from structural asymmetries where poor children were less well educated compared to their wealthy corresponding people due to their poorer accessing to technology and extra- curricular activities [5]. Additionally, existing educational programs did not encounter present-day necessities because most educational institutions stressed on repetition learning which did not troubled their students with the requirement of critical and analytic thinking or the gaining technical skills required for surviving in present atmosphere.

Select All
1.
Javaid Mohd, Abid Haleem, Ravi Pratap Singh, Shahbaz Khan and Ibrahim Haleem Khan, "Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system", BenchCouncil Transactions on Benchmarks Standards and Evaluations, vol. 3, no. 2, pp. 100115, 2023.
2.
C. Nagaraju, Y. Ramesh and C.K. Mohan, "A data parallel approach for distributed neural networks to achieve faster convergence", Sixteenth International Conference on Machine Vision (ICMV 2023), vol. 13072, pp. 380-389, 2024.
3.
R. Koniammal, G.P. Ramesh and G.G. Naidu, "Design a Multiband Frequency of Partial Defected Ground for Hexagonal Fractal Antenna", 2023 International Conference on Data Science and Network Security (ICDSNS), pp. 1-7, 2023.
4.
Senthil Kumar Jagatheesaperumal, Kashif Ahmad, Ala Al-Fuqaha and Junaid Qadir, "Advancing education through extended reality and internet of everything enabled metaverses: applications challenges and open issues", IEEE Transactions on Learning Technologies, 2024.
5.
P. Wang and K.L. Hemalatha, "Blockchain-Based Car Networking Data Privacy Security Assessment Model", International Conference on Big Data Analytics for Cyber-Physical System in Smart City, pp. 801-809, 2022, December.
6.
Zhang Puhong, Jingwen Sun Yinghua, Li Yuan, Li Yuewen, Sun Rong, Luo Xueqiong, et al., "An mHealth-based school health education system designed to scale up salt reduction in China (EduSaltS): A development and preliminary implementation study", Frontiers in Nutrition, vol. 10, pp. 1161282, 2023.
7.
Roy Rita, Mohammad Dawood Babakerkhell Subhodeep, Mukherjee Debajyoti Pal and Suree Funilkul, "Evaluating the intention for the adoption of artificial intelligence-based robots in the university to educate the students", IEEE Access, vol. 10, pp. 125666-125678, 2022.
8.
P. Nagaraj, K. Saiteja, K. Kalyan Ram, K. Mani Kanta, S. Krishna Aditya and V. Muneeswaran, "University recommender system based on student profile using feature weighted algorithm and KNN", 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), pp. 479-484, 2022.
9.
Teng Yusi, Jie Zhang and Ting Sun, "Data-driven decision-making model based on artificial intelligence in higher education system of colleges and universities", Expert Systems, vol. 40, no. 4, pp. e12820, 2023.
10.
Dominguez-Gil Carlota, Maria Manuela Segovia-Gonzalez and I. Contreras, "A multiplicative composite indicator to evaluate educational systems in OECD countries", Compare: A Journal of Comparative and International Education, vol. 52, no. 8, pp. 1296-1313, 2022.
11.
Yang Shangshang, Haiping Ma, Ying Bi, Ye Tian, Limiao Zhang, Yaochu Jin, et al., "An evolutionary multi-objective neural architecture search approach to advancing cognitive diagnosis in intelligent education", IEEE Transactions on Evolutionary Computation, 2024.
12.
Fatima Ahmed Al-Azazi and Mossa Ghurab, "ANN-LSTM: A deep learning model for early student performance prediction in MOOC", heliyon, vol. 9, no. 4, 2023.
13.
Cao Hong, "Entrepreneurship education-infiltrated computer-aided instruction system for college Music Majors using convolutional neural network", Frontiers in psychology, vol. 13, pp. 900195, 2022.
14.
Ahmadian Yazdi, Seyyed Javad Seyyed Mahdavi Chabok Hadis and Maryam Kheirabadi, "Dynamic educational recommender system based on improved recurrent neural networks using attention technique", Applied Artificial Intelligence, vol. 36, no. 1, pp. 2005298, 2022.
15.
Uppanapalli Lakshmi Sowjanya and R. Krithiga, "Decoding Student Emotions: An Advanced CNN Approach for Behavior Analysis Application Using Uniform Local Binary Pattern", IEEE Access, 2024.
16.
Abdulaziz Salamah Aljaloud, Diaa Mohammed Uliyan, Adel Alkhalil, Magdy Abd Elrhman, Azizah Fhad Mohammed Alogali, Yaser Mohammed Altameemi, et al., "A deep learning model to predict Student learning outcomes in LMS using CNN and LSTM", IEEE Access, vol. 10, pp. 85255-85265, 2022.
17.
Zhou Xiaohong and Jiayue Shao, "Mining and utilization of English learning resources using the Python NL TK", 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), pp. 648-652, 2023.
18.
Chernyshev Daniil and Boris Dobrov, "Investigating the pre-training bias in low-resource abstractive summarization", IEEE Access, 2024.
Contact IEEE to Subscribe

References

References is not available for this document.