Dr Sylwia Macinska
Head of AI Research for Learning
Sylwia is the Head of AI Research for Learning specialising in technology-enhanced learning and quantitative research methods. She leads research that informs the development of AI-based language learning and assessment products, ensuring they are grounded in evidence-based practices, with a focus on learning analytics, automated feedback, and adaptive learning. Sylwia's current work explores the potential applications of AI in education, identifying conditions necessary for their success, and evaluating their effectiveness in enhancing learning, teaching, and assessment.
Sylwia holds an MSc in Applied Data Science and has taught Research Methods and Statistic courses in Psychology at the University of Hull and Birkbeck, University of London. She also has a PhD in Psychology from the University of Hull, where she investigated the influence of emotions on implicit cognitive processes in typical development and autism spectrum disorders (ASD) using behavioural research methods and eye-tracking technology.
Macinska, S. & Pastorino-Campos, C. (2024). Integrating Process Data in AI-based Learning and Assessment: Considerations for Learners with Learning Difficulties. Paper presented at the EuroCALL. Trnava, Slovakia.
Macinska, S., Mullooly, A., Benedetto, L., Bouteba, H. & Elliott, M. (2024). Cloning Tasks with GPT Models for Automated Difficulty Estimation. Paper presented at the Language Testing Research Colloquium (LTRC). Innsbruck, Austria.
Macinska, S. & Babu-Saheer, L. (2024). Identifying predictors of dropout in mobile learning environments. Paper presented at the International Conference on Learning Analytics & Knowledge (LAK24).
Macinska, S. & Pastorino-Campos, C. (2024). Fairness considerations in integrating response process data into language assessments. Paper presented at the European Association for Language Testing and Assessment (EALTA) Equality, Diversity and Inclusion Special Interest Group (EDI SIG). Online.
Macinska, S. & Pastorino-Campos, C. (2023). Rethinking accessibility in the context of digital assessment: a review of evidence on the effectiveness of accessibility features. Paper presented at the European Association for Language Testing and Assessment (EALTA) Conference. Helsinki, Finland.
Vidal Rodeiro, C. & Macinska, S. (2022). Equal Opportunity or Unfair Advantage? The Impact of Test Accommodations on Performance in High-Stakes Assessments. Assessment in Education: Principles, Policy & Practice, 1-20.
Macinska, S., Holland, M., Glasson, N. & Galaczi, E. (2021). Aligning Assessment with Learner Needs: An Example from a Speaking Practice and Assessment App. Paper presented at the Language Testing Research Colloquium (LTRC).