Pedagogical Principles in the Online Teaching of Text Mining: A Retrospection

Autor: Pedro Alonso, György Kovács, Rajkumar Saini, Oluwatosin Adewumi, Mohamadreza Faridghasemnia, Marcus Liwicki, Hamam Mokayed, Sumit Rakesh
Rok vydání: 2021
Předmět:
Zdroj: Proceedings of the Fifth Workshop on Teaching NLP.
DOI: 10.18653/v1/2021.teachingnlp-1.1
Popis: The ongoing COVID-19 pandemic has brought online education to the forefront of pedagogical discussions. To make this increased interest sustainable in a post-pandemic era, online courses must be built on strong pedagogical foundations. With a long history of pedagogic research, there are many principles, frameworks, and models available to help teachers in doing so. These models cover different teaching perspectives, such as constructive alignment, feedback, and the learning environment. In this paper, we discuss how we designed and implemented our online Natural Language Processing (NLP) course following constructive alignment and adhering to the pedagogical principles of LTU. By examining our course and analyzing student evaluation forms, we show that we have met our goal and successfully delivered the course. Furthermore, we discuss the additional benefits resulting from the current mode of delivery, including the increased reusability of course content and increased potential for collaboration between universities. Lastly, we also discuss where we can and will further improve the current course design.
Databáze: OpenAIRE