EngageLab
The Engagement and Learning Analytics Lab
Welcome to EngageLab, where we explore the intricacies of engagement in learning. Our focus is on understanding cognitive, emotional, and behavioral dimensions of learning through innovative multimodal analytics across digital, immersive, and AI-supported environments.
About us
EngageLab, based at Tel Aviv University, explores how people learn, think, and make decisions in health and medical contexts
We study how healthcare professionals, patients, caregivers, and members of the public engage with scientific and medical information across digital, immersive, and AI-supported environments. Our work examines learning not only in classrooms and clinical training, but also in everyday health-related situations where people encounter information, uncertainty, and decision-making challenges.
Our research uses multimodal methods, including eye-tracking, facial expression analysis, behavioral data, and AI-based measures, to better understand the cognitive, emotional, and behavioral dimensions of learning.
Through our projects, we aim to design and evaluate better ways to support health learning, professional education, public understanding, and patient engagement in a rapidly changing digital health landscape.
Current research directions
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AI literacy among healthcare professionals
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Generative AI and public health decision-making
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Virtual reality and simulation-based learning in nursing education
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Mechanistic reasoning in everyday health understanding
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Digital patient education and symptom self-management
Meet the Team
Dr. Ilana Dubovi
Head of EngageLab
Dr. Ilana Dubovi, PhD, RN, is the Head of EngageLab and a Senior Lecturer at Tel Aviv University. Her research integrates learning sciences, healthcare, and artificial intelligence to study how people learn and make decisions in digital, immersive, and AI-supported environments. Her work focuses on patient education, professional training, simulation-based learning, and multimodal learning analytics.
Current Researcher Group
Direct track Ph.D student
Revital Medenitzki
Focuses on digital health communication, public , and health decision-making in AI-supported environments.
Ph.D student
Victoria Cherniak
Focuses on digital delivery of patient education for self-management: Mapping patient engagement in learning via psycho-physiological measures.
MSN Student
Anat Kamrad
The role of the primary caregiver as a moderator in the relationship between self-efficacy and types of knowledge in oncological symptom management.
Ph.D student
Yaara Binyamin
Focuses on developing GenAi literacy with virtual reality based simulation through the perspective of learning by teaching.
MSN Student
Maayan Ziv
Engagement in Learning with Generative AI-Based Virtual Reality: The Effects of AI Literacy, Attitudes Toward AI, and Perceived Social Presence in Virtual Reality.
MSN Student
Jissel Issa
Symptom management in cancer: the impact of knowledge and self-efficacy on symptom reporting.
Ph.D student
Anat Pinko Naor
Focuses on Continuing Nursing Education (CNE) instructional processes for nurses using VR simulation, and their impact on learning engagement .
MSN Student
Alexandra Serebrinsky
Patient Interaction with GenAI in Oncology Symptom Management: The Roles of AI Literacy and AI Trust.
MSc Student
Yuval Elmaleah
The relationship between emotional aspects and driving skills during simulator-based driving among young adults with and without attention-deficit/hyperactivity disorder (ADHD).
Our Alumni
Liat Liberman
Comparing cognitive load and learning outcomes in procedural learning vs.
declarative learning in virtual reality
Liron Mosko
Computer-based simulation in distance learning:
The impact of instructional sequence, engagement and cognitive load, on
learning and knowled
Shelly Reisner
Alternative Science Perceptions: The Case of Flat Earth
Hanna Borer
Passive versus interactive guidance in childbirth education classes and their effect on the self-efficacy, attitudes, and knowledge of women with regard to mobility and upright positions during labor
Alona Haleva
The effect of shared decision-making, knowledge characteristics and anesthesia type on uncertainty and anxiety among patient before elective surgery
Eden Zelig
The impact of involvement in learning and level of expertise on mathematical anxiety,
knowledge and cognitive load
Ronen Vildshtain
Assessing the relationship between learning regulation processes, joint visual attention, and cognitive load in knowledge construction processes during the modeling of a physical phenomenon
What’s New
Stay updated on our newest news, projects, and events.
Great news! Our article on the role of generative AI in supporting clinical decision-making in nursing was recognized by Wiley as a Top Cited Article 2025 in the Journal of Advanced Nursing. The conversation is no longer only theoretical - it is already shaping practice, education, and research, with nursing playing an important role in leading this transformation.
We are honored to receive a 2025 Israel Science Foundation Grant. This support will advance our research on digital patient guidance and innovative AI approaches to improving health education and care.
A wonderful collaboration with Friederike Hendriks and Iris Tabak, jointly funded by the Lower Saxony Ministry of Science and Culture and the Volkswagen Foundation. Together, we are developing a project on deliberative engagement with science on social media and through GenAI.
Recent Publications
Contact Us
Address
Gray Faculty of Medical and Health Sciences, Tel Aviv University
55 Chaim Levanon St, Ramat Aviv.
Contact
Funding & Support
We gratefully acknowledge the financial support provided by:
