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Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching

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Advances in Soft Computing (MICAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14392))

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Abstract

Student evaluations of teachings (SETs) are essential for determining the quality of the educational process. Natural Language Processing (NLP) techniques may produce informative insights into these surveys. This study aims to provide an overview of the various approaches used in NLP and sentiment analysis, focusing on identifying the top outcomes, models, and text representations used. Furthermore, we investigate NLP methods applied to a Spanish corpus of SETs, which is relatively uncommon, and discuss the application of less well-known tools in this scenario. In general, by showing the top models and text representations, especially in the case of a Spanish corpus, this study contributes to NLP and sentiment analysis. Additionally, it promotes research and interest in other languages that receive little attention.

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Data Availability Statement

The dataset used in this work may be available on request to the Institute for the Future of Education Data Hub.

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Acknowledgments

The authors would like to acknowledge the financial support and the supply of the data set to the iClassroom, a project of the Institute for the Future of Education of the Tecnologico de Monterrey.

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Authors and Affiliations

  1. Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Monterrey, Nuevo León, Mexico

    Diego Acosta-Ugalde, Santiago Enrique Conant-Pablos, Claudia Camacho-Zuñiga & Andrés Eduardo Gutiérrez-Rodríguez

Authors
  1. Diego Acosta-Ugalde
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  2. Santiago Enrique Conant-Pablos
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  3. Claudia Camacho-Zuñiga
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  4. Andrés Eduardo Gutiérrez-Rodríguez
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Corresponding author

Correspondence to Diego Acosta-Ugalde .

Editor information

Editors and Affiliations

  1. Center for Computing Research, Instituto Politécnico Nacional, Ciudad de México, Distrito Federal, Mexico

    Hiram Calvo

  2. Facultad de Ingeniería, Universidad Panamericana, Ciudad de México, Mexico

    Lourdes Martínez-Villaseñor

  3. Facultad de Ingeniería, Universidad Panamericana, Ciudad de México, Mexico

    Hiram Ponce

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Acosta-Ugalde, D., Conant-Pablos, S.E., Camacho-Zuñiga, C., Gutiérrez-Rodríguez, A.E. (2024). Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching. In: Calvo, H., Martínez-Villaseñor, L., Ponce, H. (eds) Advances in Soft Computing. MICAI 2023. Lecture Notes in Computer Science(), vol 14392. Springer, Cham. https://doi.org/10.1007/978-3-031-47640-2_3

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  • DOI: https://doi.org/10.1007/978-3-031-47640-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47639-6

  • Online ISBN: 978-3-031-47640-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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