The Online Pivot: Lessons Learned from Teaching a Text and Data Mining Course in Lockdown, Enhancing online Teaching with Pair Programming and Digital Badges (2021)

Abstract: In this paper we provide an account of how we ported a text and data mining course online in summer 2020 as a result of the COVID-19 pandemic and how we improved it in a second pilot run. We describe the course, how we adapted it over the two pilot runs and what teaching techniques we used to improve students’ learning and community building online. We also provide information on the relentless feedback collected during the course which helped us to adapt our teaching from one session to the next and one pilot to the next. We discuss the lessons learned and promote the use of innovative teaching techniques applied to the digital such as digital badges and pair programming in break-out rooms for teaching Natural Language Processing courses to beginners and students with different backgrounds.

## introduction it was spring 2020 and it felt like we were in crisis mode. we wanted to teach a text and data mining (tdm) pilot course but because of social distancing measures we could not do it in a physical classroom. we had to learn new ways of interacting online and using a multitude of different technologies and we needed to do it fast. we had been planning this course for a while before covid-19 hit. we were designing a tdm for humanities and social science students but because of the situation we had to adapt the way we delivered it. rather than hybrid teaching as intended, accommodating in-classroom, online synchronous and online asynchronous students, we had to fully commit to online methods in a matter of a few weeks. we decided to plunge headlong into the digital teaching world. the easiest way would have been to post videos of a traditional style lectures -it is very tempting to take this approach. we felt, however, that it was important that we maintained what is good about teaching when everyone is in the same room, the collaboration, its social aspects, the feedback, all of which you lose when a student sits on their own in a room watching a pre-recorded lecture. we decided to run a tdm boot camp to virtually test our new course which we were planning as part of the edinburgh futures institute (efi) postgraduate programme. 1 we wanted to not only teach fundamental methods for text mining corpora to programming novices but also teach ourselves how to become better practitioners in teaching in an online world. in this paper, we will describe our methods and experience for porting an in-person tdm course into the online world. in the next section we will present related publications on teaching natural language processing or tdm courses. we then describe the academic backgrounds of the teaching team (section 3.1) and provide an overview of our course (section 3.2). sections 3.3 and 3.4 explain how we taught and adapted it in two online pilot runs delivered in june and september 2020. we provide information on how we collected relentless feedback during and after each course and include a detailed account of one participant of the first pilot and how it has affected her teaching (section 4). finally, we summarise what we learned from these experiences (section 5) and lay out future plans for our tdm course (section 6). ## related work there are two aspects that we consider of importance in relation to this work, the course content, natural language processing (nlp), and the environment, teaching online during a pandemic. in this section we explore both topics. nlp educators choose which aspects to teach based on multiple constraints such as class length, student experience, recent advancements, program focus, and even personal interest. our tdm course is fundamentally designed to be cross-disciplinary as we are teaching nlp and coding to students from multiple schools and backgrounds including linguistics, social sciences and business. @xcite point out that nlp courses are designed to reflect, amongst other things, the background and experience of the students. @xcite explains that in courses such as these the majority of students, who he calls "newbies in computer science", have never programmed before. he highlights that we can increase experience through homework tasks which we did both before the course and in-between each session. @xcite states that in these circumstances it is not important to place too much emphasis on the theoretical underpinnings of nlp but to focus on providing instructions for students on what is possible and how they can use it on their own in the future. we based our approach on using the nltk foot_1 and spacy foot_2 python libraries as well as used examples inspired by @xcite . we aim to explain how text analysis works step-bystep using clear and simple examples. we thereby aspire to develop and broaden humanities and social science students' data-driven training and give them an understanding of how things work inside the box, something for which there is still a significant need in their core disciplines @xcite . teaching text analysis to non-computer scientists has been explored in texts such as @xcite . for our course we had to consider the variety of backgrounds and experiences that this would encompass and needed to use a pre-course learning task and office hours to provide a more level knowledge starting point. we also had to design the course to keep more advanced students engaged while not intimidating learners who may find it more challenging. we used core material to explain principle concepts (such as tokens, tokenisation, and partof-speech (pos) tagging etc.) but with a hands-on approach. we avoided too much technical detail and put the material in the context of projects we have worked on ourselves to demonstrate how each analysis step becomes useful in practice. as we taught our tdm course online in the context of a worldwide pandemic, we also report on related work in the area of online teaching, and with respect to the challenges in which we are teaching. massive open online courses (mooc) generally focus on providing online access to learning resources to a large number and wide range of participants. this has led to a desire to automate teaching and innovate digital interaction techniques in order to engage with large numbers of students. whilst our intention was to teach a limited number of students, we hoped to use and draw upon innovation in this area in order to improve the experience for our students. e-learning and technology should not be seen as an attempt to replace or automate human teaching, although this can often be a fear articulated by teachers. in a discussion of automation within teaching @xcite argues that we can design online teaching and still place human communication at the centre with technology enhancing the learning of the student. bayne suggests that the human teacher, the student and the technology can be intertwined. we asked students to engage with digital objects and the technology to enhance their learning journey. as teachers we do not merely support the digital learner but we remain at the centre of teaching the course. @xcite point out that online learning is a key growth area in higher education, which is even more true since the pandemic started, but that it is harder to form relationships in online courses. therefore, we saw it as important to develop online dialogue between students in order to form communities which can improve these relationships. building a community online can be harder but it is possible. we tried to achieve this through using a combination of traditional learning such as lectures and task-based learning such as pair programming exercises. online learning tends to be interrupted as we are in our homes or elsewhere and have responsibilities that can take us away from the online space, bandwidth issues, dropping children at school, flatmates interrupting, phone calls, even the door bell ringing. our teaching practices needed to be accepting of and adapted to this context. @xcite discuss the issues of presence and distance in online learning. interruptions in students' concentration are a common event when learning online and we must use resilience strategies to maintain a 'nearness' to our students. this includes recognising that these events are normal and that engaging is an effort, identifying affinities and creating a socialness, valuing that distraction can change our perspective and this is helpful and designing openings, events that allow and encourage student to come together and engage. whilst designing the course we kept these ideas in focus in order to allow us to develop and enhance our online relationships and our students' learning. ## lessons learned despite on-the-whole positive comments, we still found teaching in an online environment quite odd. we felt that we lost the sense of whether the students were engaged, learning and enjoying the experience because most participants had their cameras switched off so we could not see their faces or body language. the feedback did help, even simply asking students to 'raise your hand if you can hear me', but it still remains odd to us to talk to a blank screen without seeing everyone. we did not get everything right. the technology did not always work but luckily one teaching team member is quite experienced in fixing softwarerelated issues. we would have struggled without it. initially we also did not give enough thought to accessibility; we just assumed the software would deal with that -it did not. we learned that we have to ask all students before the course if they might have issues in accessing course materials or video calls and make time to deal with any technical issues that could arise as a result. we learned that students can be shy when it comes to talking to each other and putting on their webcams. we found ice breaker questions upfront, can be answered playfully on a whiteboard, very helpful for putting students at ease and have some fun. we used some simple things that made a lot of difference. we played music in the room before the class so when students joined, they knew we were there and that their speakers were on. we made extensive use of the virtual whiteboard to gather anonymous feedback really fast in addition to frequent short surveys (see figure 4 ). we also included questions in the notebooks that buddies had to work on together to encourage discussion. the notebooks contained essential tdm coding tasks and more complex tasks for the curious. this allowed some students to extend their learning without others feeling they were left behind. we also found that the amount of content that we could cover grew as the course went on. there were initial issues with the technology which needed fixing and as we were all getting used to the new way of teaching. the conversation also became more natural as time went on. at first it was quite odd to drop into the break-out rooms but by the second session this became easier and we were all chatting a lot more. the majority of students really liked the pair programming, they liked the flexibility and the content. they really felt they were part of the course in a way that is not always experienced online. as instructors, we found that teaching in this way, switching between modes, lecturing, answering the chat, live coding and responding to issues is really cognitively challenging. it is hard work and cannot easily be done by one individual. the technologies we use are complex and can fail but they are for the most part intuitive and provide a wide range of ways to teach and interact. we learned that online teaching is exhausting but done right it can still be really rewarding. we all enjoyed the interactions and felt part of a little community. after the course we did a debriefing and each wrote down three things we liked about the course and something we wished we could have achieved (see page appendix on 11). we, the tdm course teachers on this paper, have, in the same way as the author who participated in the course, benefited immensely from what we learned through these pilots before delving into our online teaching in the first term of 2020/21. ## summary and future work in this paper, we have reflected of how we ported a tdm course online as a result of the global pandemic caused by covid-19. we described the content of the course and how we adapted it over two pilot runs. we particularly found different features of blackboard collaborate useful for teaching, especially the use of a virtual whiteboard and dividing the class up into break-out rooms. students responded positively to learning in pairs and to course materials broken down into digital badges. finally, the relentless feedback we collected throughout each session and after the course helped us as teachers to improve the course and how we teach it. to make a course like this a good learning experience, it is really important to build community and get students to talk not just to the teachers but to each other as they would in a classroom. being caught in lockdown encouraged us to innovate, and our experience demonstrates what is possible to achieve virtually despite the limitations. experiencing the learning in a classroom is difficult to replicate online, however, we are confident that these types of virtual environments will play a role in education beyond this pandemic, to complement and enhance traditional learning. going forward we would like to experiment with teaching this course in different ways: asynchronously to students joining from different time zones, to much larger groups to understand where the limits are in terms of number of participants given staff capacity, or in a writer-retreat type setup where the instructors touch base with students several times during the day. we will also look at how this course can be pivoted back to on-campus teaching for students who can join in person and once the current pandemic slows down, lockdown restrictions are relaxed and on-campus teaching resumes. we are pleased to announce that this course will be part of the post-graduate programme taught at efi. would also like to thank siobhan dunn and her colleagues at efi for managing the registration for our courses and marco rossi at the university of edinburgh business school's student development team for offering the course to their students.