Due to the empirical success of reinforcement learning, an increasing number
of students study the subject. However, from our practical teaching experience,
we see students entering the field (bachelor, master and early PhD) often
struggle. On the one hand, textbooks and (online) lectures provide the
fundamentals, but students find it hard to translate between equations and
code. On the other hand, public codebases do provide practical examples, but
the implemented algorithms tend to be complex, and the underlying test
environments contain multiple reinforcement learning challenges at once.
Although this is realistic from a research perspective, it often hinders
educational conceptual understanding. To solve this issue we introduce EduGym,
a set of educational reinforcement learning environments and associated
interactive notebooks tailored for education. Each EduGym environment is
specifically designed to illustrate a certain aspect/challenge of reinforcement
learning (e.g., exploration, partial observability, stochasticity, etc.), while
the associated interactive notebook explains the challenge and its possible
solution approaches, connecting equations and code in a single document. An
evaluation among RL students and researchers shows 86% of them think EduGym is
a useful tool for reinforcement learning education. All notebooks are available
from this https URL, while the full software
package can be installed from this https URL

通过 EduGym 这一套教育性的强化学习环境和配套的交互式笔记本，该研究旨在帮助学生更好地理解强化学习的概念和实践，通过提供特定挑战方面的环境和解决方案，从而提高教学效果。

EduGym：强化学习教育环境套件

EduGym: An Environment Suite for Reinforcement Learning Education

Artificial Intelligence (AI) is becoming more and more popular as time
passes, allowing to perform tasks that were difficult to do in the past. From
predictions to customization, AI is being used in many areas, not being
educational environments outside this situation. AI is being used in
educational settings to customize contents or to provide personalized feedback
to the students, among others. In this scenario, AI in programming teaching is
something that still has to be explored, since in this area we usually find
assessment tools that allow grading the students work, but we can not find many
tools aimed towards providing feedback to the students in the process of
creating their program. In this work we present an AI based intelligent tutor
that answers students programming questions. The tool has been tested by
university students at the URJC along a whole course. Even if the tool is still
in its preliminary phase, it helped the students with their questions,
providing accurate answers and examples. The students were able to use the
intelligent tutor easily and they thought that it could be a useful tool to use
in other courses.

本研究提出了基于人工智能的编程教学智能助教，它可以回答学生的编程问题并提供准确的答案和示例，受测试的大学生认为这个工具可以成为其他课程中有用的工具。