Personalized Education at Scale

Tailoring the presentation of information to the needs of individual students leads to massive gains in student outcomes~\cite{bloom19842}. This finding is likely due to the fact that different students learn differently, perhaps as a result of variation in ability, interest or other factors~\cite{schiefele1992interest}. Adapting presentations to the educational needs of an individual has traditionally been the domain of experts, making it expensive and logistically challenging to do at scale, and also leading to inequity in educational outcomes. Increased course sizes and large MOOC enrollments provide an unprecedented access to student data. We propose that emerging technologies in reinforcement learning (RL), as well as semi-supervised learning, natural language processing, and computer vision are critical to leveraging this data to provide personalized education at scale.

• Publication year

  2018

• Venue

  arXiv.org

• Publication date

  2018-09-24

• Fields of study

  Mathematics, Computer Science, Education

• Identifiers
  arXiv 1809.10025
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Online Decision-Making for Scalable Autonomous Systems

  2017cited by this paper
• Where to Add Actions in Human-in-the-Loop Reinforcement Learning

  2017cited by this paper
• Faster Teaching by POMDP Planning

  2011cited by this paper
• Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies

  2011cited by this paper
• Planning to see: A hierarchical approach to planning visual actions on a robot using POMDPs

  2010cited by this paper
• Learning teaching strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning

  2009cited by this paper
• Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting

  2009cited by this paper
• Cognitive Computer Tutors: Solving the Two-Sigma Problem

  2001cited by this paper
• Force concept inventory

  1992cited by this paper
• Interest as a predictor of academic achievement: A meta-analysis of research.

  1992cited by this paper
• The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring

  1984cited by this paper

• How to cite in APA

  year unknowncites this paper