Computational Thinking Test (CTT) for Middle School Students
Author(s):
Kaan Batı (presenting / submitting)
Conference:
ECER 2017
Format:
Paper

Session Information

16 SES 11 B, Programming / Computational Thinking

Paper Session

Time:
2017-08-24
17:15-18:45
Room:
W4.21
Chair:
Carina GIrvan

Contribution

Computational thinking, formulating as well as solving problems with computers and other tools, logical logical arrangement and analysis of data, showing with abstract examples such as model and simulation of data, generating results with algorithmic thinking, showing possible solutions, analyzing and applying them, And generalizing the problem solving processes (Barr, Harrison, Conery, 2011; Wing, 2008). Computational thinking is a kind of analytical thinking. General ways of thinking mathematical thinking in solving a problem; Designing a large, complex system and thinking about it in relation to real-life situations; Intelligence, mind, and human behaviors (Wing, 2008). Computational thinking focuses on people's ways of solving problems, and it does not go into the process of trying people to think like computers (Yadav, Hong, Stephenson, 2016). It is not only software and hardware works that are physically shown and that touch one aspect of our life, but also informational concepts in problem solving, execution of life, communication and interaction with other people.

The aim of this research is to develop a valid and reliable paper item test that can be used at 8th grade (junior high school 4th grade) level and measures students' computational thinking skills. Within the scope of the study, the skills of the computational thinking defined in the literature were identified and then the problematic situations that these skills could be measured were established. Problem situations have been established in connection with subject areas of science and mathematics courses. The test, which was prepared from the prepared problem cases, was sent to five field specialists and they were asked to evaluate the validity of structure, scope and aspect. Incoming feedbacks were applied to 110 eighth-grade students from a state secondary school. CTT consists of 10 problem cases in total. While one question was asked about some problem cases, two or three questions were asked about some problem cases. For this reason, partial scoring method (Fleiss kappa) was planned for CTT scoring and the Coefficient Omega statistic is planned to be used to determine the reliability of the test. It is thought that a valid and reliable test that can be used at middle school level can be used to gain literature in the obtained findings.

Method

Weintrop, D., Beheshti, E., Horn, M.S., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2014) Collect computational thinking under four categories; These are data and information skills, modeling and simulation skills, informational problem solving skills, and systematic thinking skills. The sub-dimensions of these skills are; • Data and Information Skills: data collection, data generation, manipulation of data, analysis of data and visualization of data. • Modeling and Simulation Skills: using information processing models to understand a concept, understanding how and why information processing models work, using information processing models to find and testing solutions, creating new models and expanding existing models. • Computational Problem Solving Skills: catching and debugging errors, programming, choosing effective computational tools, measuring different approaches / solutions for a problem, developing modular information operational solutions, using problem solving strategies and creating abstracts. • Systems Management Skills: Examining a system as a whole, understanding relationships within a system, thinking in levels and visualizing systems, defining, understanding and managing complexity. CTT was based on the skills determined by Weintrop, Beheshti, Horn, Orton, Jona, Trouille and Wilensky (2014). CTT consists of 10 problem cases in total. While one question was asked about some problem cases, two or three questions were asked about some problem cases. For this reason, partial scoring method (Fleiss kappa) was planned for CTT scoring. The Coefficient Omega statistic is planned to be used to determine the reliability of the test.

Expected Outcomes

When the studies on the importance of the development and measurement of the computational thinking skills that are tried to be explained above are examined, it is seen that this area is lacking in the dimension of measurement and evaluation and it is seen that especially in our country, efforts to eliminate this opening need to be accelerated. It is especially evident that the ability to integrate computational thinking skills into more teaching programs by removing them from the context of computer programming, and integrating them primarily with science and mathematics courses. (Csernoch, Biró, Máth, Abari,2015; Jun, Han, Kim, Lee, 2014; Kim, Kim, Kim, 2013) For this reason, it can be stated that these deficiencies have been tried to be solved within the scope of this research

References

Barr, D; Harrison, J; Conery, L. (2011). Computational Thinking: A Digital Age Skill for Everyone. Learning & Leading with Technology, 38(6), p:20-23 Csernoch, M., Biró, P., Máth, J. & Abari, K. (2015) Testing Algorithmic Skills in Traditional and Non-Traditional Programming Environments. Informatics in Education, 14(2), 175–197, DOI: 10.15388/infedu.2015.11 Jun, S., Han, S. Kim, H. & Lee, W. (2014). Assessing the computational literacy of elementary students on a national level in Korea Educational Assessment, Evaluation and Accountability, 26 (4), 319–332. DOI: 10.1007/s11092-013-9185-7 Kim, B., Kim, T & Kim, J (2013). Paper-And-Pencil Programming Strategy Toward Computational Thinking For Non-Majors: Design Your Solution. J. Educational Computing Research, Vol. 49(4) 437-459. Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L. & Wilensky, U. (2016) Defining Computational Thinking for Mathematics and Science Classrooms. J Sci Educ Technol, 25: 127–147. DOI 10.1007/s10956-015-9581-5 Wing, J. M. (2008). Computational thinking and thinking about computing. Phil. Trans. R. Soc. 366, 3717–3725 Yadav, A., Hong, H. & Stephenson, C. (2016). Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms. TechTrends, 1-14 DOI 10.1007/s11528-016-0087-7

Author Information

Kaan Batı (presenting / submitting)
HACETTEPE UNIVERSITY
FACULTY OF EDUCATION
ANKARA

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