Abstraction plays an important role in many fields, including art and music (Kramer, 2007). In STEM, however, abstract thought is a foundational competency for the acquisition and advancement of knowledge and for problem-solving (McMaster et al., 2010). Different STEM fields have different traditions surrounding abstraction.
Abstraction plays a prominent role in the generation of scientific concepts. Scientists use abstraction to understand the empirical world and build theories that describe it. Darwish (2014) found a positive correlation between high abstract thinking levels and good scientific achievement.
Computer scientists constantly construct, manipulate, and reason with abstraction at multiple levels. Böttcher and Thurner (2023) found a positive correlation between abstract thinking skills and success in computer science-related study programs.
Abstraction in engineering is primarily represented by its modeling and representational components. Hadish et al. (2023) observed how learning at various levels of abstraction improves engineering education.
Mathematics is arguably the most abstract of all STEM disciplines, as it constantly develops higher and higher levels of abstraction from relationships among abstract objects. Darwish (2014) observed a positive correlation between abstract thinking skills and mathematical performance.
At its core, abstract thought is a long-term process of consolidation, by which constructs become more easily available (familiar) to the thinker. It is a cognitive process by which information is compressed and enriched to form and store new ideas. The repetitive use of abstraction is responsible for the acquisition of knowledge.
Empirical and reflective abstraction are tightly intertwined, working in parallel to make sense of sensory information and consolidate knowledge Our model distinguishes between six strategies of abstraction.
Each puzzle in the abstraction test, was carefully designed to test across all 6 abstraction strategies and at multiple levels of mastery. By combining 27 puzzles, we are able to gain a stable measurement of the abstraction quotient in all its dimensions.
Böttcher, A., & Thurner, V. (2023). Combining Abstract Tasks and Haptic Material to Foster Computational Thinking in Computer Science Students. Ecsee 2023 (pp. 102–109).
Darwish, A.H. (2014). The Abstract Thinking Lev- els of the Science-Education Students in Gaza Universities. Asia-Pacific Forum on Science Learning and Teaching, 15(2)
Hadish, M., Kvatinsky, S., Gero, A. (2023). Learning and Instruction that Combine Multiple Levels of Abstraction in Engi- neering: Attitudes of Students and Faculty. International Journal of Engineering Edu- cation , 39 (1), 154–162
Kramer, J. (2007). Is abstraction the key to computing? Communications of the ACM, 50(4), 36– 42
McMaster, K., Rague, B., Anderson, N. (2010). Integrating mathematical thinking, abstract thinking, and computational thinking. 40th asee/ieee (pp. S3G1–S3G6)