Research Article

Developing a game-based test to assess middle school sixth-grade students’ algorithmic thinking skills

Volume: 11 Number: 1 March 16, 2024
TR EN

Developing a game-based test to assess middle school sixth-grade students’ algorithmic thinking skills

Abstract

This study was carried out to develop a test to assess algorithmic thinking skills. To this end, the twelve steps suggested by Downing (2006) were adopted. Throughout the test development, 24 middle school sixth-grade students and eight experts in different areas took part as needed in the tasks on the project. The test was given to 252 students attending the sixth grade who were selected through purposeful sampling. The content validity of the test was ensured by means of obtaining expert opinion, whereas the construct validity was ensured by performing an independent sample t-test on the difference between the lower and upper groups. As a result, the algorithmic thinking skills assessment test was finalized with 22 main items and 2 sample items, totalling 24 items. The KR-20 reliability analysis proved a quite reliable test based on the reliability coefficient of 0.83. As mentioned earlier, the independent sample t-test was applied to the difference of lower and upper groups for construct validation of the test. It was seen that the test items are significant in discriminating the students in the lower and upper groups (p<0.01).

Keywords

Ethical Statement

Trabzon University, 13.08.2021, E-81614018-000-704.

References

  1. Altakrouri, B., & Schrader, A. (2012, September). Towards dynamic natural interaction ensembles. In the 26th BCS Conference on Human Computer Interaction 26 (pp. 1-10). http://dx.doi.org/10.14236/ewic/HCI2012.0
  2. Anderson, M.L. (2003). Embodied cognition: A field guide. Artificial intelligence, 149(1), 91-130. https://doi.org/10.1016/S0004-3702(03)00054-7
  3. Apostolellis, P., Stewart, M., Frisina, C., & Kafura, D. (2014). RaBit EscAPE: A board game for computational thinking. In Proceedings of the 2014 conference on Interaction design and children (pp. 349-352). http://dx.doi.org/10.1145/2593968.2610489
  4. Ayala, N.A.R., Mendívil, E.G., Salinas, P., & Rios, H. (2013). Kinesthetic learning applied to mathematics using kinect. Procedia Computer Science, 25, 131 135. https://doi.org/10.1016/j.procs.2013.11.016
  5. Aytekin, A., Çakır, F.S., Yücel, Y.B., & Kulaözü, İ. (2018). The place and importance of algorithms in our lives. Eurasian Journal of Social and Economic Studies, 5(7), 143 150. https://dergipark.org.tr/tr/pub/asead/issue/41013/495619
  6. Başol, G. (2019). Measurement and evaluation in education. Pegem Citation Index, 001-307.
  7. Baykul, Y., Gelbal, S., & Kelecioğlu, H. (2003). Measurement and evaluation in education for Anatolian teacher high schools. National Education Printing House.
  8. Bayrakçeken, S. (2015). Test development. E. Karip (Ed.), In Measurement and Evaluation (s. 292-322). Pegem Academy.

Details

Primary Language

English

Subjects

Measurement and Evaluation in Education (Other)

Journal Section

Research Article

Early Pub Date

March 13, 2024

Publication Date

March 16, 2024

Submission Date

July 13, 2023

Acceptance Date

January 10, 2024

Published in Issue

Year 2024 Volume: 11 Number: 1

APA
Zengin, E., & Karal, Y. (2024). Developing a game-based test to assess middle school sixth-grade students’ algorithmic thinking skills. International Journal of Assessment Tools in Education, 11(1), 88-108. https://doi.org/10.21449/ijate.1327082

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