Kamila Misiejuk er forsker ved Senter for vitenskapelig læring og teknologi (SLATE), Universitetet i Bergen.

Hennes Ph.D. forskning fokusert på kollegavurdering og læringsanalyse.

Hun leder International Society for Quantitative Ethnography Resources Committee (ISQE-RC) og er studentmedlem i International Society for Quantitative Ethnography (ISQE)-styret.

PRESENTASJONER:

10.02.23 How has feedback from learning analytics dashboards helped students’ learning? (PhD prøveforelesning), Universitetet i Bergen.

05.12.22 Peer assessment and learning analytics: Potential and challenges, ENVISION Project Multiplier Event, Online

01.02.21 Incorporating sentiment analysis with epistemic network analysis to enhance discourse analysis of Twitter data, 2nd International Conference on Quantitative Ethnography, Online.

02.12.20 DigiTrans: Learning design in online courses, Læringsmiljøutvalget i Bergen.

26.03.19 Measuring learning in the age of big data, Bergen Artificial Intelligence and Machine Learning Symposium i Bergen.

13.03.19 Exploring peer assessment with learning analytics, PeergradeCon i København, Danmark. 

11.09.18 Challenges in using learning analytics to explore peer assessment data, 4th International Association for Educational Assessment Annual Conference i Oxford, Storbritannia.

21.06.16 Presensjon av den State-of-the-field on Learning Analytics and Knowledge (SoF LAK) prosjektet, åpning av den Centre for the Science of Learning & Technology (SLATE) i Bergen.

12.04.16 Web analytics (gjesteforelesning), Bachelorkurs INFO262 Interaction Design ved Universitetet i Bergen.

PANELER / SYMPOSIER:

02.02.21 Symposium: Challenges and Solutions to Examining Twitter Data: Reflections from QE-COVID19 Data Challenge, Woodson Hobbs, Rogers Kaliisa, Kamila Misiejuk, Melanie Pfeffer, David Sanchez, Jennifer Scianna, Mamta Shah, Hamideh Talafian, Karl Vachuska, Yeyu Wang, Susie Wnag, Monique Woodard og Szilvia Zorgo ved den andre International Conference on Quantitative Ethnography 2020, Online.

02.02.21 Women in QE, Golnaz Arastoopour Irgens, Mamta Shah, Danielle Espino og Kamila Misiejuk ved den andre International Conference on Quantitative Ethnography 2020, Online.

21.10.19 Teaching Quantitative Ethnography, Brendan Eagan, Eric Hamilton og Kamila Misiejuk ved den første International Conference on Quantitative Ethnography 2019, Madison, Wisconsin, USA.

24.10.22 Misiejuk, K. & Misfeldt, M. LA research methods 3: Quantitative Ethnography. PhD-kurs, INFO900: Introduction to Learning Analytics. Online

29.03.21 Misiejuk, K. Introduction to Epistemic Network Analysis. University of Eastern Finland, Online

31.01.21 Misiejuk, K., Porter, C. & Eagan, B. Introduction to Epistemic Network Analysis. 2nd International Conference on Quantitative Ethnography. Online

24.03.20 Misfeldt, M., Spikol, D., Bruun, J., Saqr, M., Kaliisa, R., Ruis, A., Eagan., B. and Misiejuk, K. Quantitative ethnography as a framework for network analysis - A discussion of the foundations for network approaches to learning analysis. 10th International Learning Analytics and Knowledge Conference i Frankfurt, Tyskland

20.10.19 Misiejuk, K. & Eagan, B. Introduction to Epistemic Network Analysis. 1st International Conference on Quantitative Ethnography i Madison, USA

18.10.19 Misiejuk, K. Introduction to Epistemic Network Analysis. Carnegie Mellon University i Pittsburgh, USA

11.07.19 Rose, C., Liat, Y., Misiejuk, K., Hu, X., Mu, S., and Jingjing., Z. Approaches and Tools for Learning Analytics. Learning Design, Technology and the Learning Sciences: A Research Colloquium, Beijing Normal University i Beijing, Kina

07.06.19 Misiejuk, K. Introduction to Epistemic Network Analysis. 15th EATEL Summer School on Technology Enhanced Learning 2019, Bari, Italia

29.08.18 Misfeldt, M. & Misiejuk, K. Epistemic Network Analysis - Quantitative Ethnography, An Open Source Workshop. 2nd LASI-NORDIC Learning Analytics Summer Institute, København, Danmark

Vitenskapelig artikkel

• Kaliisa, Rogers; Misiejuk, Kamila; López-Pernas, Sonsoles et al. (2025). How does artificial intelligence compare to human feedback? A meta-analysis of performance, feedback perception, and learning dispositions. (ekstern lenke)
• Misiejuk, Kamila; López-Pernas, Sonsoles; Kaliisa, Rogers et al. (2025). Mapping the Landscape of Generative Artificial Intelligence in Learning Analytics: A Systematic Literature Review. (ekstern lenke)
• Misiejuk, Kamila; Bastesen, Jarle; Ershova, Tatiana (2025). How does using generative AI for essay writing impact peer assessment patterns? Insights from early adopters. (ekstern lenke)
• Kaliisa, Rogers; López-Pernas, Sonsoles; Misiejuk, Kamila et al. (2025). A Topical Review of Research in Computer-Supported Collaborative Learning: Questions and Possibilities. (ekstern lenke)
• Misiejuk, Kamila; Samuelsen, Jeanette; Kaliisa, Rogers et al. (2025). Idiographic learning analytics: Mapping of the ethical issues. (ekstern lenke)
• Misiejuk, Kamila; Kaliisa, Rogers; Scianna, Jennifer (2024). Augmenting assessment with AI coding of online student discourse: A question of reliability. (ekstern lenke)
• Misiejuk, Kamila; Ness, Ingunn Johanne; Gray, Robert et al. (2023). Changes in online course designs: Before, during, and after the pandemic. (ekstern lenke)
• Misiejuk, Kamila; Wasson, Barbara (2021). Backward evaluation in peer assessment: A scoping review. (ekstern lenke)
• Misiejuk, Kamila; Wasson, Barbara; Egelandsdal, Kjetil (2021). Using learning analytics to understand student perceptions of peer feedback. (ekstern lenke)

Doktorgradsavhandling

• Misiejuk, Kamila (2023). Using learning analytics to understand peer assessment: The importance of context data. (ekstern lenke)

Vitenskapelig foredrag

• Misiejuk, Kamila (2023). How has feedback from learning analytics dashboards helped students’ learning?. (ekstern lenke)
• Misiejuk, Kamila (2022). Peer assessment and learning analytics: Potential and challenges. (ekstern lenke)
• Misiejuk, Kamila; Wasson, Barbara (2018). Challenges in Using Learning Analytics to Explore Peer Assessment Data. (ekstern lenke)
• Misiejuk, Kamila (2018). Challenges in using learning analytics to explore peer assessment data. (ekstern lenke)

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

• Misiejuk, Kamila; Scianna, Jennifer; Kaliisa, Rogers et al. (2021). Incorporating Sentiment Analysis with Epistemic Network Analysis to Enhance Discourse Analysis of Twitter Data. (ekstern lenke)
• Kaliisa, Rogers; Misiejuk, Kamila; Irgens, Golnaz Arastoopour et al. (2021). Scoping the Emerging Field of Quantitative Ethnography: Opportunities, Challenges and Future Directions. (ekstern lenke)

Faglig foredrag

• Misiejuk, Kamila (2021). Incorporating sentiment analysis with epistemic network analysis to enhance discourse analysis of Twitter data. (ekstern lenke)
• Misiejuk, Kamila (2020). DigiTrans: Learning design in online courses. (ekstern lenke)
• Misiejuk, Kamila (2019). Exploring peer assessment with learning analytics. (ekstern lenke)
• Misiejuk, Kamila (2019). Measuring learning in the age of big data. (ekstern lenke)

Rapport

• Misiejuk, Kamila; Wasson, Barbara (2020). DigiTrans: Trends in Learning Design in Canvas Courses after Covid-19. SLATE Research Report 2020-3. (ekstern lenke)
• Misiejuk, Kamila; Wasson, Barbara (2017). State of the Field Report on Learning Analytics. (ekstern lenke)

Populærvitenskapelig bok

• Ferguson, Rebecca; Coughlan, Tim; Egelandsdal, Kjetil et al. (2019). Innovating Pedagogy 2019. Open University Innovation Report 7.. (ekstern lenke)

Poster

• Misiejuk, Kamila (2018). The Potential of Learning Analytics to Support Peer Assessment. (ekstern lenke)

Se en full oversikt over publikasjoner i Cristin

ENVISION 2027-prosjektet adresserer både det nåværende behovet for overgang fra konvensjonell klasseromsundervisning av biovitenskapsstudier til digital fjernundervisning, så vel som å forbedre dagens status for nettbasert undervisning og e-læringskursmoduler over hele Europa for fremtidige behov.

Prosjektet Remote Intelligent Access to Labs in Higher Education (RIALHE) har som mål å forbedre elevenes forståelse av vitenskapelige prosedyrer fra fjerntilgang til ekte laboratorieeksperimenter etterfulgt av samarbeidsaktiviteter ved hjelp av teknologiske plattformer.