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Purpose of the study

This project aims to understand and evaluate the student learning experience and identify key educational components and methodologies to derive general recommendations for the design of AI educational programs that could benefit learners across the US. These components include pedagogy, curriculum, learning modalities, technological innovations, and bespoke content and platforms. Findings of this study are expected to further guide a potential future scale up version of the current program, as well as inform development of other similar future educational programs. Research results from the past have already guided updates in the content, pedagogies and technology used in this program, both for the online and in-person activities.

Study Procedures

Your participation will involve completing two (2) electronic surveys (pre- and post-program completion) where you will be asked to discuss your experience as a student in the workshop. In the case it is considered useful and appropriate, you may also be invited to participate in an interview after the workshop completion.

Peer-reviewed publications

Overall program publications:

Bagiati A., Salazar-Gómez A.F., Bachmann A., Kennedy K.D., Breazeal C. AI for Leadership: Implementation and Evaluation of an AI Education Program. Conf. Proc. 51st SEFI Annual Conference. Dublin Ireland. 11-14 September 2023. 100-108. doi:10.21427/D96J-VQ96

Salazar-Gomez A.F., Bagiati A., Minicucci N., Kennedy K.D., Du X., Breazeal C. Designing and implementing an AI education program for learners with diverse background at scale. Conf. Proc. 2022 IEEE Frontiers in Education Conference (FIE). Uppsala, Sweden. 8-11 October 2022. 1-8

Bagiati A., Salazar-Gomez A.F., Radovan J., Kennedy K.D., Breazeal C. Learning Journeys For Scalable Ai Education: An MIT - USAF Collaboration. Conf. Proc. 50th SEFI Annual Conference. Barcelona Spain. 19-22 September 2022. 1529-1537

Learning Machines workshop publications:

 

X. Du, S. Alghowinem, M. Taylor, K. Darling and C. Breazeal, Innovating AI Leadership Education, Conf. Proc. 2023 IEEE Frontiers in Education Conference (FIE), College Station, TX, USA, 2023, pp. 1-8, doi: 10.1109/FIE58773.2023.10343238.

D. DiPaola, J. Shen, R. Hu, S. Alghowinem and C. Breazeal, DRONEscape: Designing an Educational Escape Room for Adult AI Literacy, Conf. Proc. 2023 IEEE Conference on Games (CoG), Boston, MA, USA, 2023, pp. 1-8, doi: 10.1109/CoG57401.2023.10333148.

For more information about this research study:

Professor Cynthia Breazeal, Ph.D., Principal Investigator

Aikaterina (Katerina) Bagiati, Ph.D., Principal Research Scientist

Andres Felipe Salazar Gomez, Ph.D., Research Scientist

Research team bios

Prof. Cynthia Breazeal is a Professor at the MIT Media Lab where she directs the Personal Robots Group. She is also director of the MIT initiative on Responsible AI for Social Empowerment and Education (RAISE) and is Senior Associate Dean of Open Learning. She is recognized as a pioneer of social robotics and human-robot interaction, is a fellow of the AAAI, and has commercialized personal robots for the home. She has received numerous national and global awards in design, entrepreneurship and innovation. She has spoken at numerous prestigious venues such as the World Economic Forum, the United Nations, TED, and others. Her work is covered in the media including the New York Times, The Washington Post, CNN, BBC, Wired, Fast Company, TIME, Forbers, and more. She received her doctorate from MIT in 2000 specializing in artificial intelligence and robotics. She is the lead instructor for this course and is the principal investigator of the Know-Apply-Lead AI Education Research Pilot program.

 

Dr. Sharifa Alghowinem is a research scientist at the Personal Robots Group at the MIT Media Lab, where she develops AI models that provide insights for enhanced human-robot interaction. Dr. Alghowinem earned her PhD in multimodal AI from the Australian National University in 2015, following an MSc in Software Engineering at the University of Canberra in 2010 and a BSc in Computer Applications at King Saud University in 2004. With an expertise in multimodal AI, Dr. Sharifa Alghowinem models human behaviors using advanced AI frameworks. Her research focuses on mood and behavior recognition, using speech, gaze, and body movements to detect conditions like depression, suicide risk and deception. With a teaching background at the University of Canberra and a current role as Associate Director of postgraduate programs at Prince Sultan University, she possesses eight years of experience teaching computer science topics, such as AI, to diverse age groups.

 

Dr. Katerina Bagiati is currently a Principal Research Scientist within MIT Open Learning. She has acquired a Diploma in Electrical and Computers Engineering and an Interdisciplinary Master’s Degree in Advanced Computer and Communications from the Aristotle University in Greece, followed by a PhD from the pioneer School of Engineering Education at Purdue University. She joint MIT soon thereafter working as a post-doctoral associate and then as a research scientist. Her current appointment regards research on STEM learning and educational program development (with an emphasis on the engineering and technology component) at the K-12, higher education and workplace education level, as well as on the efficacy of innovative learning technologies and state of the art pedagogical approaches and instructional design models. Thought her 12 years at MIT Dr Bagiati has been involved in numerous national and international collaboration, including research collaborations with the US Air Force and the NIH.

 

Daniella DiPaola is a Ph.D. student at the MIT Media Lab, where she studies ethics and children’s rights in the age of artificial intelligence and personal robots. As part of her work, she develops curricula to inform K-12 students about how AI will impact their lives. Her learning activities have reached hundreds of students across the world and have been featured in news outlets such as the New York Times and PopSci.

 

Dr. Anastasia K. Ostrowski is a postdoctoral associate and design researcher in the MIT Media Lab and the MIT Schwarzman College of Computing. Her work explores equitable design of robots, AI systems, and design education through co-design, participatory design, and design justice approaches, working with roboticists, co-designers, and policy thinkers. Anastasia received her PhD in media arts and sciences from MIT, focused on equitable technology design, and received her bachelor’s and master’s degrees in biomedical engineering from the University of Michigan, focused on engineering design processes and idea generation.

 

Dr. Andrés Felipe Salazar Gómez is a research scientist at MIT Open Learning where he works in the intersection of neuroscience and education studying novel pedagogical and technological approaches to learning: from academic program definition to AR/VR systems for educational training, and brain-computer interfaces (BCI) for capturing and quantifying tacit knowledge and expertise with the goal of understanding implicit learning. Andrés also works on science policy and its role in education and BCI.

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