Kappa Learning: A New Method for Measuring Similarity Between Educational Items Using Performance Data. - Tanya Nazaretsky; Sara Hershkovitz; Giora Alexandron (CoRR, 2018)

Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response Data. - Tanya Nazaretsky; Sara Hershkovitz; Giora Alexandron (EDM, 2019)

First Steps Towards NLP-based Formative Feedback to Improve Scientific Writing in Hebrew. - Moriah Ariely; Tanya Nazaretsky; Giora Alexandron (EDM, 2020)

Empowering Teachers with AI: Co-Designing a Learning Analytics Tool for Personalized Instruction in the Science Classroom. - Tanya Nazaretsky; Carmel Bar; Michal Walter; Giora Alexandron (LAK, 2022)

An Instrument for Measuring Teachers' Trust in AI-Based Educational Technology. - Tanya Nazaretsky; Mutlu Cukurova; Giora Alexandron (LAK, 2022)

Teachers' trust in AI-powered educational technology and a professional development program to improve it. - Tanya Nazaretsky; Moriah Ariely; Mutlu Cukurova; Giora Alexandron (Br. J. Educ. Technol., 2022)

Automated Identification and Validation of the Optimal Number of Knowledge Profiles in Student Response Data. - Brad Din; Tanya Nazaretsky; Yael Feldman-Maggor; Giora Alexandron (EDM, 2023)

Towards Automated Assessment of Scientific Explanations in Turkish using Language Transfer. - Tanya Nazaretsky; Haci Hasan Yolcu; Moriah Ariely; Giora Alexandron (EDM, 2023)

Empowering Teacher Learning with AI: Automated Evaluation of Teacher Attention to Student Ideas during Argumentation-focused Discussion. - Tanya Nazaretsky; Jamie N. Mikeska; Beata Beigman Klebanov (LAK, 2023)

Machine Learning and Hebrew NLP for Automated Assessment of Open-Ended Questions in Biology. - Moriah Ariely; Tanya Nazaretsky; Giora Alexandron (Int. J. Artif. Intell. Educ., 2023)

Navigating Self-regulated Learning Dimensions: Exploring Interactions Across Modalities. - Paola Mejia-Domenzain; Tanya Nazaretsky; Simon Schultze; Jan Hochweber; Tanja Käser (AIED (2), 2024)

Exploring the Potential of Automated and Personalized Feedback to Support Science Teacher Learning. - Jamie N. Mikeska; Beata Beigman Klebanov; Alessia Marigo; Jessica Tierney; Tricia Maxwell; Tanya Nazaretsky (AIED (2), 2024)

Explainable AI for Unsupervised Machine Learning: A Proposed Scheme Applied to a Case Study with Science Teachers. - Yael Feldman-Maggor; Tanya Nazaretsky; Giora Alexandron (CSEDU (1), 2024)

AI or Human? Evaluating Student Feedback Perceptions in Higher Education. - Tanya Nazaretsky; Paola Mejia-Domenzain; Vinitra Swamy; Jibril Frej; Tanja Käser (EC-TEL (1), 2024)

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective. - Jibril Frej; Neel Shah; Marta Knezevic; Tanya Nazaretsky; Tanja Käser (LAK, 2024)

How Instructional Sequence and Personalized Support Impact Diagnostic Strategy Learning. - Fatma Betül Güres; Tanya Nazaretsky; Bahar Radmehr; Martina A. Rau; Tanja Käser (AIED (6), 2025)

The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. - Tanya Nazaretsky; Paola Mejia-Domenzain; Vinitra Swamy; Jibril Frej; Tanja Käser (Comput. Educ. Artif. Intell., 2025)

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes. - Paola Mejia-Domenzain; Jibril Frej; Seyed Parsa Neshaei; Luca Mouchel; Tanya Nazaretsky; Thiemo Wambsganss; Antoine Bosselut; Tanja Käser (Int. J. Artif. Intell. Educ., 2025)

Evaluating Trust in AI, Human, and Co-produced Feedback Among Undergraduate Students. - Audrey Zhang; Yifei Gao; Wannapon Suraworachet; Tanya Nazaretsky; Mutlu Cukurova (CoRR, 2025)