CTAT: Computational Thinking in AI Training Test¶
Product or Programme · All products and programmes
Evidence · 6 claims (6 for) · 1 study (1 design),q3· 0 of 1 report an effect size · 6 claims rest on one study
Description¶
A validated multiple-choice assessment developed by Shile Zhang et al. for measuring higher-education CS and AI students’ computational-thinking concepts and practices in AI-training contexts.
Components¶
- CTAT: Computational Thinking in AI Training Test: CTAT is a validated multiple-choice assessment of computational thinking in AI training contexts for higher education CS/AI students, developed using Evidence-Centered Design. The article states: "In this study, 34 multiple-choice items were developed across four scenarios: (1) Data, (2) Conditionals, (3) Loops, and (4) Testing and Debugging." After pilot testing one item was deleted, leaving 33 items used in the main study. Items use a notebook-style Python interface with schematic diagrams and visual symbols to reduce literacy and code-comprehension barriers, and combine AI model training tasks with text-based programming. (Shile Zhang et al. (2026))
Claims¶
- CTAT shows robust psychometric properties for higher education CS/AI students, with reliable internal consistency and adequate IRT item parameters [+W]
- No significant gender differences in CTAT performance within either educational pathway [+W]
- College students scored significantly higher on CTAT than vocational school students [+W]
- Students struggle with the 'not' operator and logical operator precedence when evaluating conditional statements [+W]
- Students have difficulty distinguishing between for loops and while loops [+W]
- Higher education students struggle to identify appropriate data representations for AI model training [+W]
Related Products and Programmes¶
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Key Sources¶
- Shile Zhang and Shuhan Zhang. (2026). Integrating AI into computational thinking: development and validation of an assessment tool for higher education students. International Journal of STEM Education. https://doi.org/10.1186/s40594-026-00623-0
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
ctat-computational-thinking-in-ai-training-test |
title |
CTAT: Computational Thinking in AI Training Test |
description |
A validated multiple-choice assessment developed by Shile Zhang et al. |
status |
review |
product_kind |
assessment |
generated |
by process:settle-candidates on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
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