Lab Members
Scientific Director
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Earl Woodruff
Dr. Earl Woodruff is a scholar in learning sciences whose work explores how emotion, cognition, and artificial intelligence interact to create meaningful learning experiences. He previously served as Chair of the Department of Applied Psychology and Human Development at the University of Toronto (2015–2024).
Dr. Woodruff’s research focuses on computer-supported learning environments, AI-enhanced education, and the real-time dynamics of engagement. Through the ELO initiative, he explores how knowledge-related emotions such as confusion, curiosity, and interest influence attention, perceptions of relevance, and conceptual change during learning. His laboratory combines multimodal data (such as facial expression analytics, behavioural traces, and interactions with language models) using machine learning to identify phases of understanding as they occur. By modelling the connection between emotional states and cognitive processes, ELO detects moments of productive struggle, disengagement, and shifts towards deeper insight. This research aids the development of adaptive AI systems that respond to learners’ emotional and cognitive needs in real time.
Dr. Woodruff’s broader theoretical work explores goal-oriented behaviour, the realization of relevance, and the conditions under which human–AI collaboration enhances knowledge development. His research seeks to revolutionize education by helping learners regulate emotion, sustain productive confusion, and engage in knowledge-building that is both intrinsically motivating and intellectually rigorous.
ORCID: https://orcid.org/0000-0002-0958-8379
Dr. Woodruff’s research focuses on computer-supported learning environments, AI-enhanced education, and the real-time dynamics of engagement. Through the ELO initiative, he explores how knowledge-related emotions such as confusion, curiosity, and interest influence attention, perceptions of relevance, and conceptual change during learning. His laboratory combines multimodal data (such as facial expression analytics, behavioural traces, and interactions with language models) using machine learning to identify phases of understanding as they occur. By modelling the connection between emotional states and cognitive processes, ELO detects moments of productive struggle, disengagement, and shifts towards deeper insight. This research aids the development of adaptive AI systems that respond to learners’ emotional and cognitive needs in real time.
Dr. Woodruff’s broader theoretical work explores goal-oriented behaviour, the realization of relevance, and the conditions under which human–AI collaboration enhances knowledge development. His research seeks to revolutionize education by helping learners regulate emotion, sustain productive confusion, and engage in knowledge-building that is both intrinsically motivating and intellectually rigorous.
ORCID: https://orcid.org/0000-0002-0958-8379
Graduate Students
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Milan Lazic
Milan is a 4th year PhD student in the DPE program. His thesis explores how physiology and machine learning can be leveraged to track understanding as both a cognitive process and affective experience.
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Ana Zdravkovic
Ana is a PhD Student in the Developmental Psychology & Education Program. She obtained her bachelors degree in Psychology from McGill University, and completed her Master of Arts (MA) in Developmental Psychology & Education program at OISE in 2019. She is interested in studying 1) the pattern of real time emotions associated with math anxiety in populations of children 2) how we can reduce the development of math anxiety in young children using technology as possible intervention.
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Qiyuan Zheng
Qiyuan Zheng, is a Ph.D. student in the Department of Applied Psychology and Human Development at the University of Toronto. She completed her thesis-based M.A. in Educational Psychology and Learning Sciences at McGill University. Her research interests include:
1. Investigating the interrelation between students’ emotions, motivation, and interest development;
2. Capturing students’ real-time physiological responses during states of interest or boredom, and across various levels of engagement;
3. Exploring how external contributors, such as teachers and parents, support children’s and emerging adults’ emotion regulation, mental health, and well-being.
1. Investigating the interrelation between students’ emotions, motivation, and interest development;
2. Capturing students’ real-time physiological responses during states of interest or boredom, and across various levels of engagement;
3. Exploring how external contributors, such as teachers and parents, support children’s and emerging adults’ emotion regulation, mental health, and well-being.
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Teresa Orbillo-Villaruz
Teresa is a 3rd year PhD student in the Developmental Psychology and Education (DPE) program. She graduated from her HBSc at UofT in 2017 with a double major in Psychology, Exceptionality in Human Learning and a minor in Biology. She graduated from her MEd in DPE in 2023. Teresa is a board certified neurofeedback practitioner, and has been practicing for 9 years. She specializes in helping youth with neurodiversities. She is also working as a Program Evaluation and Implementation Specialist at a non-profit organization. Teresa’s research interest lies in the interplay between physiology and environment, particularly in the resulting behavioral output.
Research Assistants
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Victoria Duan
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Najmeh Bordbar
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Jinkongjia Zhang
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Ying Yao
Alumni
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Zainab Razaiy
Zainab Razaiy is a 2nd year PhD student in the Developmental Psychology and Education program. She obtained her bachelors degree (HBSc) in Psychology at the University of Toronto in 2022. She completed her Master of Education (MEd) in Developmental Psychology and Education at OISE in 2023. She is currently completing her comprehensive requirement examining how poverty and education quality influence children’s learning outcomes in rural Côte d’Ivoire. Her research interests focus on exploring innovative tools and strategies to enhance Knowledge Building pedagogy within educational environments.
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Mandana Jafarian
Mandana is a 4th-year EdD Candidate in the Department of Applied Psychology and Human Development. She obtained her Master of Applied Science (MASc) in Electrical and Computer Engineering from Toronto Metropolitan University (TMU) and a Bachelor’s degree (BSc) in Computer Engineering from the University of Tehran.
With over 15 years of diverse professional experience, including software development, Mandana’s research interests lie at the intersection of psychology, education, and technology. She is particularly interested in studying how students’ emotions affect their learning and utilizing AI to enhance the learning experience. Currently, she is focused on researching Misophonia to understand the challenges it presents and identify coping strategies in academic settings.
With over 15 years of diverse professional experience, including software development, Mandana’s research interests lie at the intersection of psychology, education, and technology. She is particularly interested in studying how students’ emotions affect their learning and utilizing AI to enhance the learning experience. Currently, she is focused on researching Misophonia to understand the challenges it presents and identify coping strategies in academic settings.
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Jiaju
Jiaju is a 2nd year MEd student in the Developmental Psychology and Education Program in the Department of Applied Psychology and Human Development. He obtained his bachelor’s degree in Psychology from the University of British Columbia University in 2023. He is interested in studying emotion from the facial expressions angle and its relationship to learning.
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Ying (Sharon) Yao
Sharon was a PhD student in Applied Psychology & Human Development with a Master of Arts degree in Developmental Psychology and Education from OISE, a Bachelor’s degree in Business Administration, and a Bachelor of Arts (Honours) in Psychology from Wilfrid Laurier University. Her research interests include: 1) Children’s stress and emotional development, 2) Develop stress interventions, 3) Emotional patterns in game addictive behavior by using real time psychophysiological and emotional indicators.
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Agnes Wong
Agnes was a PhD student in the Developmental Psychology and Education program. She completed her bachelor’s degree in Applied Psychology and Master in Occupational Therapy at the Hong Kong Polytechnic University, and Master of Arts (MA) at OISE. She is a registered Occupational Therapist in Ontario and Hong Kong. She is interested in studying how the need to maintain eye contact influences physiological reactivity and cognitive performance in autism spectrum disorder.
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Stephanie Buono
Stephanie was a PhD student in the Developmental Psychology & Education program. She received her bachelor’s degree in psychology from the University of Western Ontario, and completed her Master of Arts (MA) degree in Developmental Psychology & Education at OISE. Her research interests include 1) how emotions affect children’s cognitive processes during learning 2) how children’s understanding of emotions contribute to self-regulation during learning.
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Matthew Moreno
Matthew was a student in the Department of Curriculum, Teaching, and Learning program. He has a Bachelor of Fine Arts (Music) and Bachelor of Education from York University, a Master of Education degree in Curriculum Studies & Teacher Development at OISE, and is an Ontario Certified Teacher (OCT). Using the latest multi-channel, multi-modal data collection tools, his research studies how music affects emotions, cognitive decision making, and regulatory process while learning. In addition to his research, he remains active as a lecturer and music educator.
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Rose Schnabel
Rose was a PhD student as OISE. She completed a Bachelor’s degree in Psychology at York University, a Master of Arts in Child Psychology at Laurentian University, and a Master of Social Work at New York University. She is Registered Social Worker, Registered Psychotherapist and Board Certified Biofeedback Practitioner with BCIA. Her research interests are 1) the management of emotion and stress response during optimal cognitive states and, 2) the effect of Mindfulness, Biofeedback and self-awareness on executive function tasks.
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Zhenhua Xu
Dr Zhenhua completed her PhD in the Department of Applied Psychology and Human Development. Her research focuses on examining the psychosocial determinants of students’ optimal learning pathways in complex scientific learning with advanced learning technologies. The backbone of her research is motivation and emotion in achievement settings. She aims to use person-specific process model parameters to create computational models that can be used to track students’ learning processes and provide real-time, context-aware, person-centered interventions for improving and maximizing students’ learning.