  Computational thinking (CT) and problem-solving skills are increasingly
integrated into K-8 school curricula worldwide. Consequently, there is a
growing need to develop reliable assessments for measuring students'
proficiency in these skills. Recent works have proposed tests for assessing
these skills across various CT concepts and practices, in particular, based on
multi-choice items enabling psychometric validation and usage in large-scale
studies. Despite their practical relevance, these tests are limited in how they
measure students' computational creativity, a crucial ability when applying CT
and problem solving in real-world settings. In our work, we have developed ACE,
a novel test focusing on the three higher cognitive levels in Bloom's Taxonomy,
i.e., Analyze, Evaluate, and Create. ACE comprises a diverse set of 7x3
multi-choice items spanning these three levels, grounded in elementary
block-based visual programming. We evaluate the psychometric properties of ACE
through a study conducted with 371 students in grades 3-7 from 10 schools.
Based on several psychometric analysis frameworks, our results confirm the
reliability and validity of ACE. Our study also shows a positive correlation
between students' performance on ACE and performance on Hour of Code: Maze
Challenge by Code.org.
