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Reinforcement Learning-based Feature Selection For Developing Pedagogically Effective Tutorial Dialogue Tactics

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The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way., , , and . Int. J. Artif. Intell. Educ., 33 (4): 1031-1056 (December 2023)Meta-Cognitive Strategy Instruction in Intelligent Tutoring Systems: How, When, and Why., and . J. Educ. Technol. Soc., 13 (1): 25-39 (2010)Evolving Augmented Graph Grammars for Argument Analysis., , and . GECCO (Companion), page 65-66. ACM, (2016)Eliminating the Gap between the High and Low Students through Meta-cognitive Strategy Instruction., and . Intelligent Tutoring Systems, volume 5091 of Lecture Notes in Computer Science, page 603-613. Springer, (2008)Exploring the Impact of Worked Examples in a Novice Programming Environment., , , , , and . SIGCSE, page 98-104. ACM, (2019)Reinforcement Learning-based Feature Seleciton For Developing Pedagogically Effective Tutorial Dialogue Tactics., , , and . EDM, page 258-265. www.educationaldatamining.org, (2008)Hierarchical Reinforcement Learning for Pedagogical Policy Induction., , , , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 544-556. Springer, (2019)The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor., , , , and . CoRR, (2021)Enhancing a Student Productivity Model for Adaptive Problem-Solving Assistance., , and . CoRR, (2022)Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning towards Improved Problem Solving., , , , and . CoRR, (2022)