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The evaluation of an English essay is one of the most significant and difficult activities that is manually carried out by knowledgeable and capable instructors and faculty members. The advancement of science and technology has made it possible to automatically evaluate an English essay by employing techniques pertaining to natural language processing. For any given English essay, the intelligent system provides a generic evaluation as well as the topic/question correlation. This evaluation is based on the NLP multiple neural network model, which was used to build the system. The evaluation of essays according to worldwide standards is the primary contribution of this innovation. Any worldwide grading system, such as the Graduate Record Examination, the International English Language Testing System, etc., is qualified to make use of the grading standard. The algorithm gives users the opportunity to test their knowledge on a range of criteria, from the most basic to the most complicated, that are included in the scoring of an English essay.


Automatic evaluation Natural Language Processing (NLP General Assessment And Topic/Question Correlation Evaluation Method

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How to Cite
Rajest, S.S., Regin, R., T, S. and R, S. 2023. A New Natural Language Processing-Based Essay Grading Algorithm. International Journal on Integrated Education. 6, 3 (Mar. 2023), 1-22.


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  135. 135. C. R. Mahesha, R. Suprabha, Nellore Manoj Kumar, Koushik Kosanam, Harishchander Anandaram, S. C. V. Ramana Murty Naidu, M. Kalyan Chakravarthi, Venkatesan Govindarajan, "Effect of Friction Stir Welding on the Mechanical and Microstructural Behaviour of AA7075 Aluminium Alloy", Advances in Materials Science and Engineering, vol. 2022, 8 pages, 2022.
  136. 136. B. Deepa, K. Gayathiridevi, M. Kalyan Chakravarthi, A. Shajahan, B Shanti Sree, Mohammed Imran Anees, Mohammad Habeeb, ”Slow evaporation technique to grow 3 – Amino benzene sulfonic acid single crystal for Non-Linear optical (NLO) transmission”, Materials Today: Proceedings, Vol. 62, Part.4, pp.2119-2123, 2022.
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  152. 152. M. Siva Ramkumar, R. Priya, R. Felshiya Rajakumari, Prajoona Valsalan, M. Kalyan Chakravarthi, G. Charlyn Pushpa Latha, S. Mathupriya, Kavitha Rajan, "Review and Evaluation of Power Devices and Semiconductor Materials Based on Si, SiC, and Ga-N", Journal of Nanomaterials, vol. 2022, 7 pages, 2022.
  153. 153. S. Gowtham, T.Ch. Anil Kumar, N. S. M. P. Latha Devi, M. Kalyan Chakravarthi, S. Pradeep Kumar, R. Karthik, Harishchander Anandaram, N. Manoj Kumar, Kiran Ramaswamy, "A Survey on Additively Manufactured Nanocomposite Biomaterial for Orthopaedic Applications", Journal of Nanomaterials, vol. 2022, 7 pages, 2022.
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  161. 161. M. Kalyan Chakravarthi ,B.Bharath.“Dip Coated Thick Films Of Zno And Its Ethanol Sensing Properties”, IEEE, International Symposium on Mechatronics and its Applications (ISMA12), Sharjah, UAE,Pages:1-5, 2012.
  162. 162. M. Kalyan Chakravarthi, Pramod R. Watekar, “Optimization of Silica Glass Micro Fiber for Zero Dispersion Wavelength”, IJCA, ISBN: 978-93-80866-72-9, National Conference on Innovative Paradigms in Engineering & Technology (NCIPET-2012) organized by S. B. Jain Institute of technology, Nagpur.
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  178. 178. M. Kalyan Chakravarthi ,Rohit Kumar Oli, and Pramod R. Watekar,,“Design of a Furnace for Soft Glass Fiber Drawing”, National Conference on emerging trends in communications &Signal Processing echniques,SANKETA-2012, Journal of innovation in electronics and communication,ISSN:2249-9946,Volume 2,Issue 2,pp:178-179.
  179. 179. Lohith Ujjaniya, M.Kalyan Chakravarthi, “Raspberry - Pi based cost effective vehicle collision avoidance system using image processing”, ARPN Journal of Engineering and Applied Sciences, 10(7), April 2015.pp.3001-3005.