Elaine FarrowSchool of Informatics
University of Edinburgh
My focus is on learning analytics and educational technology, using natural language processing and machine learning to analyse data and convert it into actionable information, so that people can make better choices affecting their learning, their lives, and their environment.
Much of my previous work involved creating tutorial dialogue systems which use natural language interaction to support learning. Recent projects looked at how personal digital data from social media can be repackaged to tell stories; and how smart technology can help people communicate better with healthcare providers and find ways to use less gas and electricity in their homes.
Names, Nicknames, and Spelling Errors: Protecting Participant Identity in Learning Analytics of Online Discussions. Elaine Farrow, Johanna D. Moore, and Dragan Gašević. (2023).
Proceedings of the 13th International Learning Analytics and Knowledge Conference (LAK '23). pp. 145-155.
http://doi.acm.org/10.1145/3576050.3576070 [preprint pdf | bib]
The EuroPat Corpus: A Parallel Corpus of European Patent Data. Kenneth Heafield, Elaine Farrow, Jelmer van der Linde, Gema Ramírez-Sánchez and Dion Wiggins. 2022.
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). pp. 732-740.
https://aclanthology.org/2022.lrec-1.78 [bib | video]
Markers of cognitive quality in student contributions to online course discussion forums. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2022.
Journal of Learning Analytics, 9(2). pp. 38-65.
Ordering Effects in a Role-Based Scaffolding Intervention for Asynchronous Online Discussions. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2021.
Proceedings of the 22nd International Conference on Artificial Intelligence in Education (AIED). pp. 125-136.
http://doi.org/10.1007/978-3-030-78292-4_11 [preprint pdf | bib]
A network analytic approach to integrating multiple quality measures for asynchronous online discussions. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2021.
Proceedings of the 11th International Learning Analytics and Knowledge Conference (LAK '21). pp. 248-258. (nominated for best full paper award)
http://doi.acm.org/10.1145/3448139.3448163 [preprint pdf | bib]
Dialogue attributes that inform depth and quality of participation in course discussion forums. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2020.
Proceedings of the 10th International Learning Analytics and Knowledge Conference (LAK '20). pp. 129-134 (nominated for best short paper award)
http://doi.acm.org/10.1145/3375462.3375481 [preprint pdf | bib]
Modelling student participation using discussion forum data. Elaine Farrow. 2020. Companion Proceedings of the 10th International Learning Analytics and Knowledge Conference (LAK '20 DC). [pdf | poster | bib | online]
Automatic coding of occupation and cause-of-death records. Richard Tobin, Elaine Farrow, Claire Grover, Beatrice Alex. 2019.
International Journal of Population Data Science, 4(3). 1 page.
https://doi.org/10.23889/ijpds.v4i3.1202 [preprint pdf | bib]
Modelling Student Participation Using Discussion Forum Data. Elaine Farrow. 2019. Proceedings of the 14th EC-TEL Doctoral Consortium co-located with 14th European Conference on Technology Enhanced Learning. [pdf | bib]
Text mining student discussion forum data: common pitfalls and how to avoid them. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2019. Abstract presented at Advances in Data Science 2019. [pdf | bib | online]
"Why is the Doctor a Man?" Reactions of Older Adults to a Virtual Training Doctor. Aurora Constantin, Catherine Lai, Elaine Farrow, Beatrice Alex, Ruth Pel-Littel, Henk Herman Nap, Johan Jeuring. 2019.
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19). 6 pages.
https://doi.org/10.1145/3290607.3312811 [preprint pdf | bib]
Analysing discussion forum data: a replication study avoiding data contamination. Elaine Farrow, Johanna Moore, and Dragan Gašević. 2019.
Proceedings of the 9th International Learning Analytics & Knowledge Conference (LAK-19) pp. 170-179
https://doi.org/10.1145/3303772.3303779 [preprint pdf | bib]