mlsanityData to 14 Oct 2026

A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategies

arXiv 2602.20527 ↗First posted 24 Feb 2026cs.LG cs.AIcited by 2

On the map: Deep reinforcement learning methods → RL training of language and agent models

Abstract (arXiv)

Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) have advanced rapidly in recent years and have been successfully applied to e-learning environments like intelligent tutoring systems (ITSs). Despite great success, the broader application of DRL to educational technologies has been limited due to major challenges such as sample inefficiency and difficulty designing the reward function. In contrast, Apprenticeship Learning (AL) uses a few expert demonstrations to infer the expert's underlying reward functions and derive decision-making policies that generalize and replicate optimal behavior. In this work, we leverage a generalized AL framework, THEMES, to induce effective pedagogical policies by capturing the complexities of the expert student learning process, where multiple reward functions may dynamically evolve over time. We evaluate the effectiveness of THEMES against six state-of-the-art baselines, demonstrating its superior performance and highlighting its potential as a powerful alternative for inducing effective pedagogical policies and show that it can achieve high performance, with an AUC of 0.899 and a Jaccard of 0.653, using only 18 trajectories of a previous semester to predict student pedagogical decisions in a later semester.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in RL training of language and agent models, one of 15 directions in Deep reinforcement learning methods. Builds on 18 of its 54 references that are in the map. First posted on arXiv 24 Feb 2026.

Builds on

18 of 54 references.

References · 18

  1. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,920
  2. 2016Concrete Problems in AI Safetycited by 1,642
  3. 2016Generative Adversarial Imitation Learningcited by 1,597
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  10. 2017Continuous State-Space Models for Optimal Sepsis Treatment - a Deep Reinforcement Learning Approachcited by 68
  11. 2017Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Netscited by 64
  12. 2021Scalable Bayesian Inverse Reinforcement Learningcited by 56
6 more
  1. 2020Strictly Batch Imitation Learning by Energy-based Distribution Matchingcited by 54
  2. 2017Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Datacited by 47
  3. 2019Truly Batch Apprenticeship Learning with Deep Successor Featurescited by 27
  4. 2016HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewardscited by 15
  5. 2024A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategiescited by 2
  6. 2023Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learningcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Hierarchical Apprenticeship Learning from Imperfect Demonstrations with Evolving Rewardscited by 0
  2. 2026Pedagogical Safety in Educational Reinforcement Learning: Formalizing and Detecting Reward Hacking in AI Tutoring Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Rewarding How Models Think Pedagogically: Integrating Pedagogical Reasoning and Thinking Rewards for LLMs in Education
  2. 2026PEARL: Training Socratic Tutors with Pedagogically Aligned Reinforcement Learning
  3. 2026MC-CPO: Mastery-Conditioned Constrained Policy Optimization for Pedagogically Safe Intelligent Tutoring Systems
  4. 2025UCO: A Multi-Turn Interactive Reinforcement Learning Method for Adaptive Teaching with Large Language Models
  5. 2022Teacher-student curriculum learning for reinforcement learning
  6. 2025From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning
  7. 2025Evolutionary Reinforcement Learning based AI tutor for Socratic Interdisciplinary Instruction
  8. 2026Adaptive Scaffolding for Cognitive Engagement in an Intelligent Tutoring System