Sojourner under Sabotage: A Serious Testing and Debugging Game
- URL: http://arxiv.org/abs/2504.19287v1
- Date: Sun, 27 Apr 2025 16:05:10 GMT
- Title: Sojourner under Sabotage: A Serious Testing and Debugging Game
- Authors: Philipp Straubinger, Tim Greller, Gordon Fraser,
- Abstract summary: Sojourner under Sabotage is a browser-based serious game that blends education with an immersive storyline.<n>A study with 79 students demonstrates that the game is a powerful tool for enhancing motivation, engagement, and skill development.
- Score: 9.856068089918555
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Teaching software testing and debugging is a critical yet challenging task in computer science education, often hindered by low student engagement and the perceived monotony of these activities. Sojourner under Sabotage, a browser-based serious game, reimagines this learning experience by blending education with an immersive and interactive storyline. Players take on the role of a spaceship crew member, using unit testing and debugging techniques to identify and repair sabotaged components across seven progressively challenging levels. A study with 79 students demonstrates that the game is a powerful tool for enhancing motivation, engagement, and skill development. These findings underscore the transformative potential of serious games in making essential software engineering practices accessible and enjoyable.
Related papers
- Teaching Software Testing and Debugging with the Serious Game Sojourner under Sabotage [9.856068089918555]
Browser-based serious game enhances learning through interactive, narrative-driven challenges.<n>Sojourner under Sabotage provides hands-on experience with the real-world testing framework JUnit.
arXiv Detail & Related papers (2025-04-27T16:10:08Z) - Examining and Comparing the Effectiveness of Virtual Reality Serious Games and LEGO Serious Play for Learning Scrum [0.40964539027092917]
This article examines and compares the effectiveness for learning Scrum and related agile practices of a serious game based on virtual reality and a learning activity based on the LEGO Serious Play methodology.
The results show that both game-based learning approaches were effective for learning Scrum and related agile practices in terms of learning performance and motivation.
arXiv Detail & Related papers (2024-06-29T06:37:25Z) - WIP: A Unit Testing Framework for Self-Guided Personalized Online Robotics Learning [3.613641107321095]
This paper focuses on creating a system for unit testing while integrating it into the course workflow.
In line with the framework's personalized student-centered approach, this method makes it easier for students to revise, and debug their programming work.
The course workflow updated to include unit tests will strengthen the learning environment and make it more interactive so that students can learn how to program robots in a self-guided fashion.
arXiv Detail & Related papers (2024-05-18T00:56:46Z) - Unit Testing Challenges with Automated Marking [4.56877715768796]
We introduce online unit testing challenges with automated marking as a learning tool via the EdStem platform.
Results from 92 participants showed that our unit testing challenges have kept students more engaged and motivated.
These results inform educators that the online unit testing challenges with automated marking improve overall student learning experience.
arXiv Detail & Related papers (2023-10-10T04:52:44Z) - Technical Challenges of Deploying Reinforcement Learning Agents for Game
Testing in AAA Games [58.720142291102135]
We describe an effort to add an experimental reinforcement learning system to an existing automated game testing solution based on scripted bots.
We show a use-case of leveraging reinforcement learning in game production and cover some of the largest time sinks anyone who wants to make the same journey for their game may encounter.
We propose a few research directions that we believe will be valuable and necessary for making machine learning, and especially reinforcement learning, an effective tool in game production.
arXiv Detail & Related papers (2023-07-19T18:19:23Z) - Giving Feedback on Interactive Student Programs with Meta-Exploration [74.5597783609281]
Developing interactive software, such as websites or games, is a particularly engaging way to learn computer science.
Standard approaches require instructors to manually grade student-implemented interactive programs.
Online platforms that serve millions, like Code.org, are unable to provide any feedback on assignments for implementing interactive programs.
arXiv Detail & Related papers (2022-11-16T10:00:23Z) - DIAMBRA Arena: a New Reinforcement Learning Platform for Research and
Experimentation [91.3755431537592]
This work presents DIAMBRA Arena, a new platform for reinforcement learning research and experimentation.
It features a collection of high-quality environments exposing a Python API fully compliant with OpenAI Gym standard.
They are episodic tasks with discrete actions and observations composed by raw pixels plus additional numerical values.
arXiv Detail & Related papers (2022-10-19T14:39:10Z) - Perceiving the World: Question-guided Reinforcement Learning for
Text-based Games [64.11746320061965]
This paper introduces world-perceiving modules, which automatically decompose tasks and prune actions by answering questions about the environment.
We then propose a two-phase training framework to decouple language learning from reinforcement learning, which further improves the sample efficiency.
arXiv Detail & Related papers (2022-03-20T04:23:57Z) - Continual Learning of Control Primitives: Skill Discovery via
Reset-Games [128.36174682118488]
We show how a single method can allow an agent to acquire skills with minimal supervision.
We do this by exploiting the insight that the need to "reset" an agent to a broad set of initial states for a learning task provides a natural setting to learn a diverse set of "reset-skills"
arXiv Detail & Related papers (2020-11-10T18:07:44Z) - Exploration Based Language Learning for Text-Based Games [72.30525050367216]
This work presents an exploration and imitation-learning-based agent capable of state-of-the-art performance in playing text-based computer games.
Text-based computer games describe their world to the player through natural language and expect the player to interact with the game using text.
These games are of interest as they can be seen as a testbed for language understanding, problem-solving, and language generation by artificial agents.
arXiv Detail & Related papers (2020-01-24T03:03:51Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.