Past Research Collaborations with Carnegie Mellon University
Educational Technology Across Cultures
Educational technology is typically designed in western, industrialized countries and exported to other countries around the world. However, some of the design choices may not fully consider the cultural values or norms of users in all contexts. We investigate how some educational technologies are deployed around the world, understand ways that users in a variety of countries may interact with the systems, and provide recommendations to designers. These recommendations allow us to work towards promoting for all users the ability to have richer interactive experiences with technology.
- Yarzebinski, E., Ogan, A., Rodrigo, M. M. T., & Matsuda, N. (2015, June). Understanding students’ use of code-switching in a learning by teaching technology. In Proceedings of the International Conference on Artificial Intelligence in Education (pp. 504-513). Springer, Cham.
- Yarzebinski, E., Dumdumaya, C., Rodrigo, M. M. T., Matsuda, N., & Ogan, A. (2017). Regional Cultural Differences in How Students Customize Their Avatars in Technology-Enhanced Learning. In Proceedings of the International Conference on Artificial Intelligence in Education (pp. 598-601).
- Ogan, A., Yarzebinski, E., Fernández, P., & Casas, I. (2015). Cognitive Tutor Use in Chile: Understanding Classroom and Lab Culture. In Proceedings of the 17th International Conference on Artificial Intelligence in Education (pp. 318-327). Springer International Publishing.
- Uchidiuno, J., Yarzebinski, E., Vargas-Vite, E., Koedinger, K., Ogan, A. (2019). The Effectiveness of Publicly vs. Privately Assigned Group Leaders among Learners in Rural Villages in Tanzania. To appear in CSCL 2019.
Improving MOOC experiences for non-native English speakers
Many MOOC (Massive Open Online Courses – eg Coursera, edX, etc) learners are not native English speakers, yet most MOOC content is created and deployed in English. One widely assumed adaptation for these students is to translate all of the content into their mother tongue. However, we have found through interviews and observations that learners do not necessarily want this – some learners prefer to take a course in English to learn the content in English. We explore the social, economic, and geographical motivations of MOOC learners, especially those who are non-native English speakers, to discover appropriate adaptations for each of these learners that best align with their goals.
- Uchidiuno, J. O., Ogan, A., Yarzebinski, E., & Hammer, J. (2018). Going Global: Understanding English Language Learners’ Student Motivation in English-Language MOOCs. International Journal of Artificial Intelligence in Education, 28(4), 528-552.
- Uchidiuno, J., Koedinger, K., Hammer, J., Yarzebinski, E., & Ogan, A. (2018). How Do English Language Learners Interact with Different Content Types in MOOC Videos?. International Journal of Artificial Intelligence in Education, 28(4), 508-527.
Global Learning Council
In collaboration with the Global Learning Council, I am part of a team writing a white paper that will review existing research on educational technology, its design and effectiveness – at this point, about 600 papers and counting – and write our recommendations for how educational technology should move forward as a field for the next five to ten years.
- Best Practices for TEL in Global Cross-Cultural Contexts (in preparation)
The ArticuLab studies how people communicate with and through technology, particularly in areas of minority dialects and rapport-building. During my time in this lab as the Lab Manager, I also had the opportunity to contribute to some of its research projects.
- Finkelstein, S., Yarzebinski, E., Vaughn, C., Ogan, A., & Cassell, J. (2013). The effects of culturally-congruent educational technologies on student achievement. Proceedings of the International Conference on Artificial Intelligence in Education (pp 493-502). Springer. [+Best Paper Award]
The practice of learning by teaching – in which teaching a concept to someone else helps you better grasp it – underlies SimStudent. In this system, students collaborate with a virtual agent to solve algebra problems, and answer its questions along the way. The papers below cover many different classroom interventions, with a variety of experimental conditions.
- Matsuda, N., Yarzebinski, E., Keiser, V., Raizada, R., Cohen, W.W., Stylianides, G. J., & Koedinger, K. R. (2013 Nov). Cognitive anatomy of tutor learning: Lessons learned with SimStudent. Journal of Educational Psychology. Vol 105: 4.
- Matsuda, N., Yarzebinski, E., Keiser, V., Raizada, R., Cohen, W. W., Stylianides, G., & Koedinger, K.R. (2012). Shallow learning as a pathway for successful learning both for tutors and tutees. Proceedings of the Cognitive Science Society. (pp. 731-736). Austin, TX: Cognitive Science Society.