Mehak Maniktala Maniktala, M., Chi, M., & Barnes, T. (2022, August 3). Enhancing a student productivitymodel for adaptive problem-solving assistance. USER MODELING AND USER-ADAPTED INTERACTION. https://doi.org/10.1007/s11257-022-09338-7 Ausin, M. S., Maniktala, M., Barnes, T., & Chi, M. (2022, November 28). The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION. https://doi.org/10.1007/s40593-022-00312-3 Maniktala, M., Cody, C., Barnes, T., & Chi, M. (2021, March). Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor (September, 10.1007/s40593-020-00213-3, 2020). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, Vol. 31, pp. 154–155. https://doi.org/10.1007/s40593-020-00232-0 Ausin, M. S., Maniktala, M., Barnes, T., & Chi, M. (2021). Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 356–368. https://doi.org/10.1007/978-3-030-78292-4_29 Cody, C., Maniktala, M., Lytle, N., Chi, M., & Barnes, T. (2021, May 21). The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION. https://doi.org/10.1007/s40593-021-00237-3 Maniktala, M., Cody, C., Barnes, T., & Chi, M. (2020). Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 30(4), 637–667. https://doi.org/10.1007/s40593-020-00213-3