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Background and experience
Before starting my PhD at the University of Agder, I worked with multilingual education, English as a second language and inclusive learning environments in Sweden. I have taught and collaborated closely with students from diverse linguistic and cultural backgrounds. These experiences sparked my interest in how multilingual learners navigate school systems, how they use their languages strategically when learning and how teaching practices can be adapted to support equity and motivation.
My earlier research focused on AI-supported grammar development using personalized assignments generated by ChatGPT. In my first study (2023), I examined how individualized grammar tasks, tailored to each student’s weaknesses, could improve accuracy and efficiency in ESL classrooms. The project also highlighted how teachers’ attitudes toward AI shift from skepticism to confidence when supported through training and guided classroom use.
In my follow-up study (2024), I investigated which type of personalization works best by comparing content personalization (adapting tasks to proficiency) and topic personalization (adapting tasks to student interests). The strongest results appeared when the two were combined, leading to higher motivation, deeper engagement and more task completion. These findings inspired the development of the Personalization–Motivation Integration Framework (PMIF) (2025) The framework emphasizes that effective personalization must support autonomy, competence and relevance in order to promote inclusive learning.
In addition to linguistics and teaching, my background in philosophy and psychology has shaped my academic style. Philosophy has inspired my interest in ethics, identity, and epistemology in AI-supported learning, while psychology has strengthened my focus on motivation, cognitive engagement, learner well-being and how students understand feedback and technology. These perspectives allow me to make the connection between technological innovation and the deep understanding of the human and pedagogical dimensions of learning.
Research
My current work explores how students draw on their full linguistic repertoires when engaging with tasks and technology. This includes how translanguaging and personalized prompts influence understanding, confidence and participation. These experiences strengthened my interest in designing learning environments where multilingual students can use all their languages as cognitive and cultural resources.
In parallel, I developed a strong interest in educational technology and AI-assisted writing. I examined how digital tools can scaffold feedback, writing processes and language development and how teachers can integrate AI ethically, safely, and in a way that enhances rather than replaces meaningful learning routines. I became particularly interested in how AI changes learners’ revision strategies, decision-making and engagement.
Across my work, I have consistently been drawn to the intersection of language, identity, motivation, technology, inclusivity and how these shape students’ opportunities to learn. These experiences led naturally into my current PhD research, where I combine classroom-based pedagogy with AI-supported writing, process analytics, translanguaging, and, for smaller subsamples, physiological measures such as HRV/EEG to better understand cognitive engagement.
As an interdisciplinary researcher, I value combining classroom practice, multilingual education, learning psychology, writing analytics and emerging technologies. This blend of practical and theoretical experience forms the foundation of my PhD project.