- Year 2023
- NSF Noyce Award # 1660728
- First Name Melanie
- Last Name Pivarski
- Discipline Life Sciences
Neil Voss, Byoung Sug Kim
The surge of remote learning has highlighted threats to the integrity of online assessments, such as widespread question sharing on platforms like Chegg. YAML Integrity provides a solution to this issue and eases the task of creating unique, high-quality questions, thereby enhancing assessment quality, fairness, and efficiency.
1. How can we mitigate the effect of question sharing on the integrity of online assessments in STEM education? 2. In what ways does the automated generation of a diverse question pool contribute to assessment integrity, reduce question sharing, and enhance instructor efficiency? 3. What are the potential impacts of an automated question generation tool on academic honesty in online learning environments?
YAML Integrity utilizes Python scripts and YAML files to generate diverse assessments. Educators can supply either true/false statements or pairs of matching terms and definitions, YAML Integrity produces a range of consistent yet unique questions. This approach undermines question-sharing practices that rely on questions repeating from student to student. This platform-independent tool allows for adaptation across various online learning environments.
YAML Integrity is anticipated to significantly reduce question sharing, improve teaching efficiency, and enable to the creation of diverse, comprehensive assessments. The deliverables include the Python tool itself, compatibility with various learning platforms, and a robust solution to a common problem in STEM education. Future initiatives will concentrate on refining YAML Integrity, expanding its question-generation capabilities, expanding its library of STEM assessment content, and adding compatibility with other learning platforms.
YAML Integrity aims to influence STEM education by enhancing the reliability and integrity of online assessment practices. It provides STEM educators an efficient, reliable means to create unique assessments and reduce academic misconduct. Implications for teacher education programs include a shift in focus from assessment crafting to actual teaching. Future steps will explore YAML Integrity’s effectiveness across diverse STEM fields and add compatibility to more learning management systems.