Names, Nicknames, and Spelling Errors: Protecting Participant Identity in Learning Analytics of Online Discussions

Autor: Elaine Farrow, Johanna D. Moore, Dragan Gasevic

Publikováno v: Farrow, E, Moore, J & Gasevic, D 2023, Names, Nicknames, and Spelling Errors: Protecting Participant Identity in Learning Analytics of Online Discussions . in Proceedings of the 13th International Conference on Learning Analytics and Knowledge (LAK23) . vol. LAK23, Association for Computing Machinery (ACM), pp. 145-155, The 13th International Learning Analytics and Knowledge Conference, 2023, Arlington, Texas, United States, 13/03/23 . https://doi.org/10.1145/3576050.3576070

Messages exchanged between participants in online discussion forums often contain personal names and other details that need to be redacted before the data is used for research purposes in learning analytics. However, removing the names entirely make

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f786be85c2e858ea02be1801f0c9512
https://doi.org/10.1145/3576050.3576070

A network analytic approach to integrating multiple quality measures for asynchronous online discussions

Autor: Elaine Farrow, Johanna D. Moore, Dragan Gašević

Publikováno v: LAK

Asynchronous online discussions within a community of learners can improve learning outcomes through social knowledge construction, but the depth and quality of student contributions often varies widely. Approaches to assessing critical discourse typ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::352dbd20e3fd2d3fc6f29b2d85a14821
https://doi.org/10.1145/3448139.3448163

Dialogue attributes that inform depth and quality of participation in course discussion forums

Autor: Dragan Gašević, Johanna D. Moore, Elaine Farrow

Publikováno v: Farrow, E, Moore, J & Gašević, D 2020, Dialogue attributes that inform depth and quality of participation in course discussion forums . in LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge . Association for Computing Machinery (ACM), pp. 129-134, The 10th International Learning Analytics & Knowledge Conference, Frankfurt, Germany, 23/03/20 . https://doi.org/10.1145/3375462.3375481
LAK

This paper describes work in progress to answer the question of how we can identify and model the depth and quality of student participation in class discussion forums using the content of the discussion forum messages. We look at two widely-studied

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f052d436f43c032c0c7e290104983c45
https://hdl.handle.net/20.500.11820/693e122b-491f-43f8-967f-d58fbe4983b4

Automatic coding of occupation and cause-of-death records

Autor: Beatrice Alex, Richard Tobin, Elaine Farrow, Claire Grover

Publikováno v: International Journal of Population Data Science, Vol 4, Iss 3 (2019)
Tobin, R, Farrow, E, Grover, C & Alex, B 2019, ' Automatic coding of occupation and cause-of-death records ', International Journal of Population Data Science, vol. 4, no. 3 . https://doi.org/10.23889/ijpds.v4i3.1202

The Digitising Scotland project aims to digitise 24 million Scottish vital event records of births, marriages and deaths from 1856 to 1973. To use these records effectively for large-scale research they must not only be made machine-readable, but als

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7b62beef9e8bd2bf52232e2663ebe12
https://ijpds.org/article/view/1202

BEETLE II: Deep Natural Language Understanding and Automatic Feedback Generation for Intelligent Tutoring in Basic Electricity and Electronics

Autor: Johanna D. Moore, Myroslava O. Dzikovska, Elaine Farrow, Natalie Steinhauser, Gwendolyn E. Campbell

Publikováno v: Dzikovska, M, Steinhauser, N, Farrow, E, Moore, J & Campbell, G 2014, ' BEETLE II: Deep Natural Language Understanding and Automatic Feedback Generation for Intelligent Tutoring in Basic Electricity and Electronics ', International Journal of Artificial Intelligence in Education, vol. 24, no. 3, pp. 284-332 . https://doi.org/10.1007/s40593-014-0017-9

Within STEM domains, physics is considered to be one of the most difficult topics to master, in part because many of the underlying principles are counter-intuitive. Effective teaching methods rely on engaging the student in active experimentation an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc49edb218f92199f09135252ac023b4
https://doi.org/10.1007/s40593-014-0017-9