The coronavirus pandemic has challenged university teachers to design high-quality teaching without access to classrooms. Three lecturers at EFI rose to this challenge to create its first fully-online course, engage learners and enhance their teaching capabilities.
“It feels a bit like we are all in crisis mode at the moment,” says Dr Clare Llewellyn. “We want to teach, but lockdown means we need to learn new ways of interacting and using a multitude of different technologies and fast.”
In June 2020, Clare and colleagues Dr Pawel Orzechowski and Dr Beatrice Alex piloted EFI’s first fully-online course with a group of 25 University of Edinburgh staff and students. The Text and Data Mining Boot Camp, developed with the support of the Centre for Data, Culture & Society, was the latest milestone in EFI’s plans to develop a distinctive portfolio of hybrid postgraduate programmes to offer part-time students the flexibility to choose whether to study online or on campus. This teaching model also creates opportunities to build global, inclusive and diverse student cohorts, reduce the environmental impact of travel and mitigate geopolitical, health and other factors which may otherwise prevent students from studying physically in Edinburgh.
Delivered via the Business School’s Student Development team, the course taught coding novices how to analyse textual data using the Python programming language. “In our data-driven society, it is increasingly essential for people throughout the private, public and third sectors to know how to analyse the wealth of information society creates each day” explains Pawel. “The Text and Data Mining Boot Camp gives those who have very limited or no coding experience the tools they need to interrogate data.”
An online learning experience
The lecturers were already in the process of designing the course using a hybrid learning model when the coronavirus pandemic began. Following lockdown, they pivoted quickly to take it fully-online. However, they knew they had to innovate to maintain the spirit of its on-campus elements. “It would be tempting to just upload lecture videos for participants to watch, but it was important to us that we preserve the sense of collaboration and socialness that comes from being in the same classroom or lecture theatre,” says Beatrice.
Clare, Pawel and Beatrice structured the week-long course around half-day sessions on Monday, Wednesday and Friday, and an office hour on Tuesday and Thursday. Each session introduced participants to a new topic such as Python skills for reading and processing text and visualisations of large datasets, through a live video lecture. They showed students how to process and search text documents and analyse words in context. The Boot Camp also covered part of speech (PoS) tagging. This technique involves categorising and tagging words in a text by grammatical categories, such as adjective, noun or verb and using named entity recognition to identify names in text, to make it easier to analyse text document collections.
The Learn virtual learning environment (VLE) gave participants access to course materials. Collaborate video conferencing hosted immersive group sessions and a virtual whiteboard, polls, file and screen sharing. Meanwhile, the University of Edinburgh’s Notable platform provided participants with an online learning and programming environment and the open-source web application, Jupyter Notebook, allowed them to work through each day’s tasks in pairs via breakout rooms on video calls. “The course not only allowed us to test course content, but it also let us experiment with online teaching methods we are likely to use in future hybrid programmes,” Clare explains. “The pair working was a real success. As well as allowing participants to learn from each other, it also gave them much-needed social interaction, which is vital to the learning experience.”
A flexible and responsive course
The lecturers surveyed participants in the middle and the end of each session and used their live feedback to enhance the course in real-time. “The participants requested a quick recap of the first day, which we hadn’t planned on doing but it was a great way to link the sessions and get everything fresh in everyone’s minds” emphasises Pawel. “This relentless feedback loop helped us realise we could cover more content as time went on. It is one of the reasons we believe we had such a high participant retention rate.”
A measurable impact
Participants also responded positively to the pair programming, and the course’s flexibility and content. “Fantastic!” wrote one in the final feedback survey. “The pair learning is excellent! Jupiter [sic] notebooks are a great tool. The real-time interactivity is super rewarding.” Others said the three lecturers and the “humour and playfulness of the examples” made the course “really great, especially for someone completely new to coding.” While another commented they would use the skills they learned in gathering data for their undergraduate dissertation.
The lecturers found simple things that made a lot of difference to the online learning experience. “The ongoing dialogue with participants helped to overcome some of the challenges of teaching in an online environment” recalls Clare. “Asking participants to digitally ‘raise their hand’ if they could hear us and encouraging them to send chat messages helped us measure how they were learning and enjoying the experience.”
However, like most innovation, delivering The Text and Data Mining Boot Camp came with some challenges. “We didn’t get everything right” Beatrice acknowledges. “The technology didn’t always work, but thankfully Pawel had the experience to fix it. In the future, we would build in more time to address these issues and include more ice-breaking upfront to help participants get used to interacting through their webcams.”
“We also learned that online teaching is exhausting” adds Pawel. “Switching between lecturing, answering chat messages, live coding and fixing issues is cognitively challenging. However, the technology is very intuitive, and the overall experience is extremely rewarding. We all enjoyed the interaction and felt part of a little community.”
The lecturers now plan to develop the course for larger groups. “Our experience confirmed the demand for a course such as this. We were overwhelmed with interest from staff and students. With minimal advertising, we filled all the spaces overnight” notes Clare. They are also positive the experience will support EFI’s plans to launch hybrid learning programmes. “The lockdown encouraged us to innovate, and our experience demonstrates what is possible to achieve despite the limitations” Beatrice concludes. “As lecturers, it taught us valuable lessons on what works online and made us aware of the possible pitfalls. It paves the way for more hybrid models which combine the strengths of online and classroom learning.”
Dr Clare Llewellyn is Career Development Fellow at the School of Social and Political Science.
Dr Pawel Orzechowski is Senior Teaching Fellow in Programming for Business at the Business School.
Dr Beatrice Alex is a Chancellor’s Fellow and Turing Fellow and works across EFI, the School of Literatures, Languages and Cultures and the School of Informatics.
The Centre for Data, Culture & Society supports, facilitates and inspires data-led and digital research across the arts, humanities and social sciences.