Dr Jemma König
Postdoctoral Fellow (Computer Science)
PhD (Computer Science) Waikato
BCMS (Hons) Waikato
Jemma is a Postdoctoral Fellow in the Department of Computer Science at the University of Waikato. She is working on the Tini o te Hakituri project under Associate Professor Annika Hinze and Dr Judy Bowen. Hakituri is a project funded by the Ministry of Business, Innovation and Employment (MBIE) investigating technology uses in hazardous work environments.
Jemma started her undergraduate study at the University of Waikato in 2012, graduating with a Bachelor of Computing and Mathematical Sciences with first class honors. After this she undertook a Ph.D. in Computer Science, which she completed in 2019.
Jemma’s PhD research explored a computational approach to vocabulary testing, language tools, and text enrichment. More specifically focusing on corpus analysis, pseudoword generation, automated vocabulary testing, and tracking learners' interaction with online written language.
Jemma's postdoctoral research is part of a larger MBIE-funded project called Tini o te Hakituri. Hakituri is centered on investigating technology uses in hazardous work environments. As part of this research, Jemma’s postdoctoral fellowship is centered on using wearable technology to identify and prevent fatigue in the forestry industry.
Dylan Exton "Utilizing IoT in Hazardous Environments"
Master of Science (Research) in Computer Science
Konig, J., Hinze, A., & Bowen, J. (2021). Identifying worker fatigue in the New Zealand forestry industry: Computer Science Working Paper Series (03/2021). University of Waikato. Open Access version: https://hdl.handle.net/10289/14145
Bowen, J., Hinze, A., Konig, J., & Exton, D. (2021). Supporting safer work practice through the use of wearable technology. In R. Charles, & D. Golightly (Eds.), Ergonomics and Human Factors 2021 (pp. 8 pages). Online, London.
Konig, J. (2020). Automating vocabulary tests and enriching online courses for language learners (PhD abstract). IEEE Intelligent Informatics Bulletin, 20, 42. Retrieved from http://www.ieee-iib.org/2020/IIB2020_Final.pdf
Fitzgerald, A., Konig, J., & Witten, I. H. (2019). F-Lingo: Integrating lexical feature identification into MOOC platforms for learning professional and academic English. In Proc 2019 IEEE Learning With MOOCS (LWMOOCS 2019) (pp. 101-104). Milwaukee, WI. doi:10.1109/LWMOOCS47620.2019.8939658 Open Access version: https://hdl.handle.net/10289/13574
Find more research publications by Jemma König