# Teaching Multiple Concepts to a Forgetful Learner

arXiv: https://arxiv.org/abs/1805.08322 · HTML: https://mlsanity.com/paper/1805.08322/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 May 2018.

## Built on by (most cited first, 17 of 17)

- [Replay in Deep Learning: Current Approaches and Missing Biological Elements](https://mlsanity.com/paper/2104.04132/) (2021)
- [Teaching Humans When To Defer to a Classifier via Exemplars](https://mlsanity.com/paper/2111.11297/) (2021)
- [Interactive Teaching Algorithms for Inverse Reinforcement Learning](https://mlsanity.com/paper/1905.11867/) (2019)
- [Counterfactual Temporal Point Processes](https://mlsanity.com/paper/2111.07603/) (2021)
- [Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints](https://mlsanity.com/paper/1906.00429/) (2019)
- [Teaching an Active Learner with Contrastive Examples](https://mlsanity.com/paper/2110.14888/) (2021)
- [Iterative Teaching by Label Synthesis](https://mlsanity.com/paper/2110.14432/) (2021)
- [Curriculum Design for Teaching via Demonstrations: Theory and Applications](https://mlsanity.com/paper/2106.04696/) (2021)
- [Nonparametric Iterative Machine Teaching](https://mlsanity.com/paper/2306.03007/) (2023)
- [From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks](https://mlsanity.com/paper/2205.01265/) (2022)
- [Iterative Teaching by Data Hallucination](https://mlsanity.com/paper/2210.17467/) (2022)
- [Nonparametric Teaching for Multiple Learners](https://mlsanity.com/paper/2311.10318/) (2023)
- [Do Your Best and Get Enough Rest for Continual Learning](https://mlsanity.com/paper/2503.18371/) (2025)
- [Improving Artificial Teachers by Considering How People Learn and Forget](https://mlsanity.com/paper/2102.04174/) (2021)
- [KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students](https://mlsanity.com/paper/2402.12291/) (2024)
- [Visual Knowledge Tracing](https://mlsanity.com/paper/2207.10157/) (2022)
- [One-shot Machine Teaching: Cost Very Few Examples to Converge Faster](https://mlsanity.com/paper/2212.06416/) (2022)

## Abstract (arXiv)

How can we help a forgetful learner learn multiple concepts within a limited time frame? While there have been extensive studies in designing optimal schedules for teaching a single concept given a learner's memory model, existing approaches for teaching multiple concepts are typically based on heuristic scheduling techniques without theoretical guarantees. In this paper, we look at the problem from the perspective of discrete optimization and introduce a novel algorithmic framework for teaching multiple concepts with strong performance guarantees. Our framework is both generic, allowing the design of teaching schedules for different memory models, and also interactive, allowing the teacher to adapt the schedule to the underlying forgetting mechanisms of the learner. Furthermore, for a well-known memory model, we are able to identify a regime of model parameters where our framework is guaranteed to achieve high performance. We perform extensive evaluations using simulations along with real user studies in two concrete applications: (i) an educational app for online vocabulary teaching; and (ii) an app for teaching novices how to recognize animal species from images. Our results demonstrate the effectiveness of our algorithm compared to popular heuristic approaches.