PSRE Self-assessment Approach for Predicting the Educators’ Performance Using Classification Techniques-Reference-Cited by-同舟云学术

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PSRE Self-assessment Approach for Predicting the Educators’ Performance Using Classification Techniques

Published:2022 Issue: Volume: Page:405-423
ISSN:1865-0929
Container-title:Artificial Intelligence and Speech Technology
language:
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Author:

Arora Sapna,Agarwal Manisha,Mongia Shweta,Kawatra Ruchi

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-95711-7_34

Reference43 articles.

1. Shin, J.C., Harman, G.: New challenges for higher education: global and Asia-Pacific perspectives. Asia Pacific Educ. Rev. 10, 1–13 (2009)

2. Arora, S., Agarwal, M., Kawatra, R.: Prediction of educationist’s performance using regression model. In: 7th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, pp. 88–93. IEEE (2020). https://doi.org/10.23919/INDIACom49435.2020.9083708

3. Pal, A.K., Pal, S.: Evaluation of teacher’s performance: a data mining approach. Int. J. Comput. Sci. Mob. Comput. 2(12), 359–369 (2013)

4. Maitra, S., Madan, S., Kandwal, R., Mahajan, P.: Mining authentic student feedback for faculty using Naive Bayes classifier. Procedia Comput. Sci. 132, 1171–1183 (2018)

5. Romero, C., Venture, S., Bra, P.: Knowledge discovery with genetic programming for providing feedback to courseware authors. User Model. User-Adap. Inter. 14(5), 425–464 (2004)

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