Advanced Learning Technologies Lab

Reinforcing Learning through Technology

Our Mission

Personalized Learning

Technologies that have the capability to allow learners to follow multiple trajectories through their learning experience, depending on abilities and preferences.

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Affect and Motivation

We study how to assess students’ affective states as they learn, and how to bring students back to optimal affective and motivational states for learning through a variety of Interventions.

young girl students playing educational games
a person typing on a computer keyboard


We investigate how to promote good study habits as students learn, by helping them set goals, be strategic while performing an activity, seek for help, and reflect about their performance by self-monitoring and self-evaluating their progress.

Active Physical Learning

We investigate how children can learn mathematics while exploring the physical space, getting a different understanding of math learning by gesturing, and using technology to guide them through 3D spaces.

Learn more about WearableLearning ↗

students playing educational games
animated learning companion

Intelligent Pedagogical Agents

We study how embodied characters, or learning companions, can bond with the students to deliver messages that promote motivation and develop self-regulation.

Educational Games

We investigate how Games and Game-Like Elements can promote learning and motivation, and afford a better relationship to STEM.

a young girl student using phone

Open-Tutor Platforms

We are making Tutoring Systems and Learning Environments connect with each other through Application Protocol Interfaces (APIs). MathBuds is the result of making the ASSISTments and MathSpring tutoring systems use each other, in order to make a better final product to teach middle school mathematics, capitalizing on the strengths of each other.

Learning Technologies for the Developing World

We are interested in Socio-Cultural Differences and how to create low-cost devices that could be immersed in developing countries and bring learning technologies to those in most need.

a person typing on a computer keyboard
a child raises hand in classroom

Learning Disabilities

We study how to tailor learning technologies to those who struggle most and need furthest assistance, with a cognitive psychology perspective that focuses on memory retrieval, executive functioning, and personalized learning.


ALT Lab / News

Latest news and awards

APRIL, 2023

Arroyo recognized with two distinguished awards: the PIT Fellowship and the IDS Seed Award.

The PIT Fellowship supports Arroyo's project on bilingual personalized digital tutors for mathematics learning, making the MathSpring online multimedia K-12 math tutoring platform more accessible to bilingual Latinx students. By offering MathSpring for free to Hispanic students in Holyoke, MA, the project aims to engage more Latinx students in STEM and improve their math and language skills. More information on the PIT Fellowship can be found here↗.The IDS Seed Award funds Arroyo's collaborative research with Beverly Woolf↗ and Marialuisa Di Stefano↗ on the development and testing of a new bilingual tutoring software that uses Latinx digital avatars. This innovative project focuses on addressing the needs of bilingual (Spanish and English) students, with personalized Hispanic digital avatars in early education and computer science. More information about the IDS Seed Award can be found here↗.


Brain, Body, World

Ivon Arroyo and her team innovate ways to support teachers and students using embodied learning, AI, and game design. Their work has been showcased on the University of Massachusetts Amherst Research News.

Read more here↗ and here↗.

APRIL, 2020

CAREER: Wearable Tutors in the Embodied Mathematics Classroom

Ivon Arroyo (Principal Investigator)

Read more on↗.

JUNE, 2019

IES: An Efficacy Study of the MathSpring Personalized Learning System That Responds to Student Affect (with WestEd)

Steven Schneider
Beverly Woolf
Ivon Arroyo

Read more here↗.

Developing Computational Thinking by Creating Multi-player Physically Active Math Games

Ivon Arroyo (Principal Investigator)
Gillian Smith (Co-Principal Investigator)
Erin Ottmar (Co-Principal Investigator)

Read more here↗.

INT: Collaborative Research: Detecting, Predicting and Remediating Student Affect and Grit Using Computer Vision

Ivon Arroyo (Principal Investigator)
Jacob Whitehill (Co-Principal Investigator)
Beverly Woolf (Co-Principal Investigator)

Read more here↗.

BD Spokes: Spoke: NORTHEAST: Collaborative: Grand Challenges for Data-Driven Education

Ivon Arroyo (Principal Investigator)
Neil Heffernan (Co-Principal Investigator)
Beverly Woolf (Co-Principal Investigator)

Read more here↗.

View all past awards on↗

Students and Staff

ALT Lab / Students and Staff

Meet our staff

Danielle Allessio

Postdoc Researcher

Francisco Castro

Postdoc Researcher

Frank Sylvia

Software Engineer

Matthew Micciolo

Software Engineer

Current students

Allison Poh

Research Assistant

Boming Zhang

Research Assistant

Hannah Smith

Research Assistant @WPI

Injila Rasul

Research Assistant

Krishna Chaitanya Rao Kathala

Research Assistant

Mohammad Hadi Nezhad

Research Assistant

Sai Gattupalli

Research Assistant

Will Lee

Research Assistant

Will Rebelsky

Research Assistant

Former students

Grace Seiche

Teacher and Lab Specialist

Lada Kvasyuk

Project Assistant

Laura Cintrón García

Project Assistant

Olivia Bogs

Project Assistant

Nick Caccamo

Research Assistant

Luisa Perez Lacera

Research Assistant

Xinyue Zuo

Research Assistant

Anastasiya Kvasyuk

Project Assistant

Erik Erickson

Research Assistant


ALT Lab / Faculty

Meet the faculty

A true hybrid across disciplines, Ivon Arroyo specializes in learning sciences, computer science, and educational/cognitive psychology. Her expertise is in the design of novel technologies for learning and assessment for K-12 students studying mathematics.Arroyo's team creates adaptive personalized learning technologies that automatically assess students' math changing abilities, affective states and metacognitive states, respond to students on the spot, and report strengths and weaknesses to the teacher--in real time, as students are working on computers or mobile devices.Her group also works on wearable learning and computational thinking, including the use of mobile electronic devices for students to design, develop and play multiplayer physically active embodied math games.Professor Arroyo enjoys teaching at the graduate and undergraduate level because of the opportunity to impart knowledge and skills to students, as well as the opportunity to mentor a new generation of learning scientists that have dual strengths in computation and core learning sciences--allowing for an invaluable combination of technological innovation with theoretical knowledge of how people learn.

Background and Profile

Ed.D. in Math and Science Education
University of Massachusetts Amherst
M.S. in Computer Science
University of Massachusetts Amherst
B.S. in Computer Science
(Licenciatura en Informática)
Universidad Blas Pascal, Cordoba, Argentina

COMPSCI 590ED: Educational Data Mining and Learner Analytics
Spring 2021
EDUC 618C - Computer Programming for Educators I
Fall 2022, Spring 2020
EDUC 597S - EDUC 597S: Service Learning & Computational Media
Spring 2020
EDUC 463 - Principles and Methods of Teaching Mathematics pre-K-6SS 590 - Educational Data Mining
Fall 2014
PSY 520 - Metacognition, Motivation and Affect
Fall 2013
PSY 1401 - Cognitive Psychology
Fall 2014
PSY 502 - Learning Environments in Education
Spring 2013

Beverly Park Woolf PhD is a Research Professor in the Computer Science Department of the University of Massachusetts Amherst. She is the Director of the Center for Knowledge Communication. Many of the three-dimensional graphics and multimedia classes at the University of Massachusetts owe their beginning to Dr. Woolf's efforts to offer students the opportunity to expand both intellectual and practical skills.Dr. Woolf's research focuses on building systems to train, explain, and advise users effectively. Extended multimedia capabilities are integrated with knowledge about the user, domain, and dialogue to produce real-time performance support and on-demand advisory and tutoring systems. The tutoring systems use intelligent interfaces, inferencing mechanisms, cognitive models, and modifiable software to improve a computer's communicative abilities. These systems have been tested with learners, trainers, and other client bases, deployed in education and industry and demonstrated in more than 50 American industrial, military and academic sites and 15 foreign countries.Her most recent book is Building Intelligent Interactive Tutors, Student-Centered Strategies for Revolutionizing E-Learning, Published by Elsevier & Morgan Kaufmann, 2008.

Neena Thota is Senior Teaching Faculty at the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. Her research interests are in Computing Education Research, Educational Technologies, Learning and Assessment Taxonomies, and Methodological Frameworks for Research.Dr. Thota is Co-PI for the NSF supported project for Computational Thinking Funds of Knowledge: A Culturally-Relevant Assessment for Early Elementary Students Children. The project is developing equitable computational thinking (CT) assessments for historically marginalized Black and Hispanic students in the early grades. She is also Co-PI for the NSF supported CyberTraining workshops for the Center for Parallel and Distributed Computing Curriculum Development and Educational Resources PDC Curriculum Early Adopter Grant and Summer Training Program, that prepare instructors to offer experimental courses with an updated Parallel and Distributed Curriculum.She is the director of the Early Research Scholar Program at CICS that provides a structured and scalable research experience for undergraduate students. In her role as Sloan Faculty Fellow, she participates in the Sloan Student Fellows Program - a research mentoring program welcoming Black, Latine/Hispanic, and Indigenous (BLI) undergraduate students.Contact her if you are interested in pursing Independent Studies or Honors Thesis projects.


ALT Lab / Publications

Our most recent work

This section was last updated in September, 2023. For latest research, visit our Google Scholar.

Arroyo, I. Euredjian, A., Perez-Lacera, L., Allessio, D., Woolf, B.P. (2023, April) Localizing a Mathematics Tutoring System to Spanish in Latin-America. In Proceedings of the International Conference on Information Technology & Systems. Cuzco, Peru. Rocha, A., Ferrás, C. and Ibarra, W., Eds. LNNS 691. Springer.

Rasul, I., Castro, F., & Arroyo, I. (2023, May). Towards Embodied Wearable Intelligent Tutoring Systems. Augmented Intelligence and Intelligent Tutoring Systems. Proceedings of the 19th International Conference, ITS 2023, Corfu, Greece, June 2–5, 2023, (pp. 298-306). Springer Cham.

Rasul. I., Crabtree, D., Castro, F., Poh, A., Gattupalli, S., Kathala, K., Arroyo, I. (2023) WearableLearning: Developing Computational Thinking through Modeling, Simulation and Computational Problem Solving. In Proceedings of the 17th International Conference of the Learning Sciences-ICLS 2023. International Society of the Learning Sciences.

Castro, F., Raipura, S., Conboy, H., Haas, P., Osterweil, L., & Arroyo, I. (2023, March). Piloting an Interactive Ethics and Responsible Computing Learning Environment in Undergraduate CS Courses. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (pp. 659-665).

Woolf, B.P., Betke, M., Yu, H., Bargal, S.A., Arroyo, I., Magee, J., Allessio, D., Rebelsky, W. (2023) Face Readers: The Frontier of Computer Vision and Math Learning. In Proceedings of the Workshop “Towards the Future of AI-Augmented Human Tutoring in Math Learning”. In conjunction with the International Conference on Artificial Intelligence in Education 2023. Tokyo, Japan.

Gattupali, S., Lee, W., Allessio, D., Crabtree, D., Arroyo, I., Woolf, B.P. (2023) Exploring Pre-Service Teachers' Perceptions of Large Language Models-Generated Hints in Online Mathematics Learning. In Proceedings of the Workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation. In conjunction with the International Conference on Artificial Intelligence in Education 2023. Tokyo, Japan.

Ruiz, N., Yu, H., Allessio, D. A., Jalal, M., Joshi, A., Murray, T., ... & Betke, M. (2022). ATL-BP: a student engagement dataset and model for affect transfer learning for behavior prediction. IEEE Transactions on Biometrics, Behavior, and Identity Science.

Lee, W., Allessio, D., Rebelsky, W., Satish Gattupalli, S., Yu, H., Arroyo, I., ... & Woolf, B. P. (2022, June). Measurements and Interventions to Improve Student Engagement Through Facial Expression Recognition. In Adaptive Instructional Systems: 4th International Conference, AIS 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26–July 1, 2022, Proceedings (pp. 286-301). Cham: Springer International Publishing.

Arroyo, I., Closser, A. H., Castro, F., Smith, H., Ottmar, E., & Micciolo, M. (2022). The WearableLearning Platform: A Computational Thinking Tool Supporting Game Design and Active Play. Technology, Knowledge and Learning, 1-10.

Castro, F. (2022). Exploring the Use of Finite-State Machines and Game Creation to Teach Computational Thinking in Middle Schools. In Proceedings of the Innovation and Technology in Computer Science Education Conference. Dublin, Ireland (2022).

Gattupalli, S., Castro, F., Arroyo, I., Bogs, O., Seiche, G. (2022). Exploring Cross-cultural Differences in Educational Math Game Creation using the WearableLearning Platform. Proceedings of the International Conference of the Learning Sciences 2022.

Arroyo, I., Closser, A. H., Castro, F., Smith, H., Ottmar, E., Micciolo, M. (2022) The Wearable Learning Platform: A Computational Thinking Tool Supporting Game Design and Active Play. Technology, Knowledge and Learning. Springer Nature.

Closser, A. H., Erickson, J. A., Smith, H., Varatharaj, A., & Botelho, A. F. (2022). Blending learning analytics and embodied design to model students’ comprehension of measurement using their actions, speech, and gestures. International Journal of Child-Computer Interaction’s special issue on Learning Analytics and Embodied Design.

Arroyo, I., Castro, F., Smith, H., Harrison, A., Ottmar, E. (2021). Augmenting Embodied Mathematics Classrooms with Mobile Tutors. AERA 2021.

Yu, H., Gupta, A., Lee, W., Arroyo, I., Betke, M., Allesio, D. & Woolf, B. P. (2021, July). Measuring and Integrating Facial Expressions and Head Pose as Indicators of Engagement and Affect in Tutoring Systems. In International Conference on Human-Computer Interaction (pp. 219-233). Springer, Cham.

Gupta, A., Menon, N., Lee, W., Rebelsky, W., Allesio, D., Murray, T. & Arroyo, I. (2021, June). Affective Teacher Tools: Affective Class Report Card and Dashboard. In International Conference on Artificial Intelligence in Education (pp. 178-189). Springer, Cham.

Arroyo, I. (2021, April). Augmenting Embodied Mathematics Classrooms with Mobile Tutors. In Annual meeting program American Educational Research Association.

Kooken, J. W., Zaini, R., & Arroyo, I. (2021). Simulating the dynamics of self-regulation, emotion, grit, and student performance in cyber-learning environments. Metacognition and Learning, 1-39.

Smith, H., Closser, A. H., Ottmar, E., & Arroyo, I. (2020). Developing mathematics knowledge and computational thinking through game play and design: A professional development program. Contemporary Issues in Technology and Teacher Education, 20(4).

Ruiz, N., Jalal, M., Ablavsky, V., Allessio, D., Magee, J., Whitehill, J., Arroyo, I., Woolf, B., Sclaroff, S., & Betke, M. (2020). Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System.
ArXiv, abs/2002.05242.

View full list of Publications on Google Scholar

Our most cited work

This section was last updated in September, 2023.

Arroyo, I., Cooper, D. G., Burleson, W., Woolf, B. P., Muldner, K., & Christopherson, R. (2009). Emotion sensors go to school. In Artificial intelligence in education (pp. 17-24). IOS press.

Woolf, B.P., Burleson, W., Arroyo, I., Dragon, T., Cooper, D.G., & Picard, R.W. (2009). Affect-aware tutors: recognising and responding to student affect. Int. J. Learn. Technol., 4, 129-164.

Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M. (2014). A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. International Journal of Artificial Intelligence in Education, 24, 387-426.

Arroyo, I.; Woolf, B.P. (2005) Inferring learning and attitudes from a Bayesian Network of log file data. Proceedings of the 12th International Conference on Artificial Intelligence in Education. C.K. Looie, G. McCalla, B. Bredeweg, and J. Breuker, editors. Amsterdam: IOS Press, 2005. pp 33-40.

Murray, T., & Arroyo, I. (2002, June). Toward measuring and maintaining the zone of proximal development in adaptive instructional systems. In International conference on intelligent tutoring systems (pp. 749-758). Springer, Berlin, Heidelberg.

Arroyo, I., Ferguson, K., Johns, J., Dragon, T., Meheranian, H., Fisher, D., ... & Woolf, B. P. (2007, June). Repairing disengagement with non-invasive interventions. In AIED (Vol. 2007, pp. 195-202).

Woolf, B. P., Arroyo, I., Muldner, K., Burleson, W., Cooper, D. G., Dolan, R. P., & Christopherson, R. (2010, June). The Effect of Motivational Learning Companions on Low Achieving Students and Students with Disabilities. In Intelligent Tutoring Systems (1) (pp. 327-337).

Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M. (2014). A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. International Journal of Artificial Intelligence in Education, 24(4), 387-426.


ALT Lab / Courses

Courses taught by the ALT faculty


Eucational Data Mining and Learner Analytics

This course provides an overview of the emerging field of educational data mining and data analytics overeducational data sets. Some of these datasets will come from student users of learning technologies, andare a reflection of students abilities and other states of mind as they learn new material. We will discussboth the application of machine learning methods to educational data, as well as classic models inspiredby cognitive theory, as well as exploring and finding patterns in data. The course will use a combinationof lectures, paper presentations, lab assignments, and projects.


Teaching Assistants as Tomorrow's Faculty

Course focuses on the TA's role in leading discussion sections, planning effective review sessions, and facilitating labs. Educational best practices that scaffold learning and create an inclusive classroom are discussed. How to balance teaching and research responsibilities is addressed as part of graduate professional development.

Projects Fall 2022↗
Instructor: Dr. Neena Thota

Projects Spring 22↗
Instructor: Dr. Ivon Arroyo

Projects Fall 2021↗
Instructor: Dr. Neena Thota

Projects Fall 2020↗
Instructor: Dr. Ivon Arroyo










Contact Us

ALT Lab / Contact

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