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This innovative practice WIP paper describes our ongoing development and deployment of an online robotics education platform that highlighted a gap in providing an interactive, feedback-rich learning environment essential for mastering pro-gramming concepts in robotics, which they were not getting with the traditional code→ simulate→turn-in workflow. Since teaching resources are limited, students would benefit from feedback in real-time to find and fix their mistakes in the programming assignments. To integrate such automated feedback, this paper will focus on creating a system for unit testing while integrating it into the course workflow. We facilitate this real-time feedback by including unit testing in the design of programming assignments so students can understand and fix their errors on their own and without the prior help of instructors/TAs serving as a bottleneck. In line with the framework's personalized student-centered approach, this method makes it easier for students to revise and debug their programming work, encouraging hands-on learning. The updated course workflow, which includes 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.
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Improving Wikidata with Student-Generated Concept Maps
Wikidata is a publicly available, crowdsourced knowledge base that contains interlinked concepts structured for use by intelligent systems. While Wikidata has experienced rapid growth, it is far from complete and faces challenges that prevent it from being used to its full potential. In this paper, we propose a novel method for improving Wikidata by engaging undergraduate students to contribute previously missing knowledge via concept mapping assignments. Rather than allow students to edit Wikidata directly, we describe a workflow in which knowledge is constructed by students and then reviewed by an expert. We present a case study in which we deployed a workflow in a large undergraduate course about sustainability, and find that it was able to contribute a substantial number of high quality statements that persisted in and contributed previously missing knowledge to Wikidata. This work provides a preliminary workflow for improving Wikidata based on classroom assignments, as well as recommendations for how future educational projects could continue to improve Wikidata or other public knowledge bases.
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- Award ID(s):
- 2121572
- PAR ID:
- 10356169
- Date Published:
- Journal Name:
- Proceedings of the International AAAI Conference on Web and Social Media (ICWSM 22)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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