Pedagogical Principles in the Online Teaching of Text Mining: A Retrospection (2021)

Abstract: 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.

## introduction with the covid-19 pandemic, academic institutions were pushed to moving their education online @xcite . furthermore, even institutes that still allowed students on campus were more open to online alternatives. however, in order to solidify the results attained in online education @xcite in these extraordinary circumstances, it is crucial to demonstrate that this mode of education can be a viable alternative to presential education in terms of the underlying pedagogical fundamentals and the success of practical implementation. for this, in setting up our natural language processing course, our goal was to do so based on constructive alignment and ltu's pedagogical principles. we hypothesized that adherence to both set of principles would be possible in an online version too. in this paper, by examining the design and implementation of the course and analyzing the student feedback, we will demonstrate the viability of our hypothesis. the rest of the paper is organized as follows. first, we discuss the related literature in section 1.1, followed by ltu's pedagogical principles in section 1.2. then in section 2, we present the course design. that is followed by the teaching and learning activities being discussed in section 3. next, we present the course evaluation result and the perspective of a volunteering student of the course in section 4. lastly, we conclude the paper and outline planned improvements in section 5. ## course design in this section, we examine the course design based on ltu's pedagogical principles (see section 1.2), the principle of constructive alignment, and other pedagogical considerations. we should note here that one may arrive at similar design patterns based solely on practical considerations as well. however, we consider it an integral part of our contribution that the design of the nlp course discussed here is rooted not only in pedagogical practices but also in pedagogical theories and research. ## teaching and learning activities the course is designed to maximize the intended learning outcomes. we refer to students some python programming tutorials available online to get familiarized with python. this section describes this course's teaching and learning activities, which includes delivering lectures in short videos, live sessions, lab sessions, and our learning management system. ## results the nlp course (7.5 credits) was a part of the oneyear data science masters program at ltu. there were 24 students enrolled in the nlp course. the students were from academia and industry both. most students had a background in computer science or engineering and thus had at least an introductory course in programming. some students, however, had no programming background. ## conclusion and improvements planned for the future versions of the course here, we discuss the course and the improvements we plan for the future course.