Creating Assessments Using Artificial Intelligence
An Introduction to the Teach-SAN-TA Model
Bibliographic Data
| ID | 21557063 |
|---|---|
| Authors | Thomas Trendowski (0000-0002-3722-9250, corresponding author) |
| Year | 2026 |
| Volume | 97 |
| Issue | 4 |
| Pages | 43-51 |
| Publication date | 2026-05-04 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Physical Education Recreation & Dance (JOURNAL) |
| Journal identifiers | ISSN: 0730-3084 • E-ISSN: 2168-3816 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07303084.2026.2619968 |
| OpenAlex | W7151538757 |
| Language | EN |
| Citations received | 2 |
| References cited | 9 |
In physical education (PE), a variety of technologies have been introduced to support instructors’ creativity and efficiency. Language learning models (LLMs), a type of artificial intelligence (e.g., ChatGPT, Gemini, and Copilot) are resources. These systems can generate unique replies by analyzing vast amounts of text data. The purpose of this article is to examine effective prompt writing for psychomotor domain evaluations based on best practices. Using the TEACH-SAN-TA approach, educators can create effective assessments using LLMs
Educational Assessment and Pedagogy · Intelligent Tutoring Systems and Adaptive Learning · Online Learning and Analytics
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |