Abstract
Multiple international organizations, in their recent reports, emphasize the need for the curricula of Higher Education Institutions to comply with the requirements established in the Education 4.0 framework by incorporating new learning approaches, such as challenge-based learning, with new competency assessment models. In the case of Science, Technology, Engineering, and Mathematics (STEM) programs, the inclusion of new technological tools helps effectively assess the mastery of transversal skills like critical thinking and creativity required by Generation Z students. This study presents the results of implementing digital platforms and natural language processing tools to evaluate active learning experiences in various engineering courses. The research was conducted using a mixed-design methodology and assessment instruments testing for lexical corpus, fluency and originality, discursive articulation, reading comprehension, technical essay writing, and specific essential learning outcomes. The results showed that a natural language toolkit could indirectly evaluate the levels of understanding of scientific concepts and the ability to develop soft the skills of creativity and critical thinking.
With the support of NOVUS Grant, 2021–2022,  Institute for the Future of Education, Tecnologico de Monterrey, Mexico.
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Acknowledgements
The authors acknowledge the financial and technical support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this work. The authors also acknowledge the financial support of the Novus Grant with PEP no. Â PHHT085-21ZZNV016, Institute for the Future of Education, Tecnologico de Monterrey, in the production of this work.
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Caratozzolo, P., Alvarez-Delgado, A., Hosseini, S. (2022). Natural Language Processing for Video Essays and Podcasts in Engineering. In: Hosseini, S., Peluffo, D.H., Nganji, J., Arrona-Palacios, A. (eds) Technology-Enabled Innovations in Education. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-19-3383-7_1
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