About

I am a Learning Scientist and a User Experience (UX) researcher, exploring the theoretical and practical underpinnings of educational technology solutions that are both powered by and created for learners. I am interested in Human-AI collaboration and crowdsourcing in educational contexts and the impact of these phenomena on people’s learning. My research frequently involves conducting field experiments with adult learners in online learning environments, including Massive Open Online Courses (MOOCs). 

My dissertation delves into learnersourcing, a concept combining the principles of crowdsourcing with learning by involving students in learning activities that lead to the generation of educational content. In my first project as a PhD student, I studied the effects of learnersourcing on students’ learning outcomes, motivation, and the quality of educational content they generate. This work was awarded Best Paper at the 2021 ACM Learning at Scale Conference. Following this, I reviewed prior research on learnersourcing and contributed a theoretical framework to guide the design and deployment of novel learnersourcing systems. In this work, I highlighted the complementary relationship between learnersourcing and Artificial Intelligence (AI) and how they can be used together to enhance student learning.

I am working towards bridging learnersourcing and generative AI for optimizing educational feedback mechanisms by exploring the dynamics of student-AI collaborative feedback generation. As students, teachers, and technology platforms rapidly adopt generative AI technologies, my research seeks to understand how this adoption modifies the artifacts of the learning environment as well as students’ learning experiences.

My work has been published at peer-reviewed conferences such as Learning@Scale, SIGCSE, WWW, and AAAI. I am fortunate to have secured funding for my doctoral research from Microsoft following an internship in 2022.  Prior to my PhD, I worked at IBM Research Labs India. I graduated from the Indian Institute of Technology Delhi in 2017 with a dual master's and bachelor's degree in Mathematics and Computing.

View Anjali's CV

Selected Publications

Singh, A., Fariha, A., Brooks, C., Soares, G., Henley, A., Tiwari, A., Mahadevaswamy, C., Choi, H., & Gulwani, S. (2024, March). Investigating Student Mistakes in Introductory Data Science Programming. To Appear in Proceedings of the 55th ACM Technical Symposium on Computer Science Education.

Singh, A., Brooks, C., & Doroudi, S. (2022, June). Learnersourcing in theory and practice: synthesizing the literature and charting the future. In Proceedings of the Ninth ACM Conference On Learning@ Scale (pp. 234-245).

Singh, A., Brooks, C., Lin, Y., & Li, W. (2021, June). What's In It for the Learners? Evidence from a Randomized Field Experiment on Learnersourcing Questions in a MOOC. In Proceedings of the Eighth ACM Conference on Learning@ Scale (pp. 221-233).
(Awarded Best Paper)

Singh, A., Mittal, R. S., Atreja, S., Sharma, M., Nagar, S., Dey, P., & Jain, M. (2019, July). Automatic generation of leveled visual assessments for young learners. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, No. 01, pp. 9713-9720).