SavedAdd your journal

Journals / Journal of Turkish Science Education / 2021 / Cilt: 18 - Sayı: 3

Determination of the Contribution of Station Technique in Informal Learning Environments (STiIL) to Learning DomainS

Nevzat YİĞİT
Ebru MAZLUM GÜVEN
Ebru SİVRİKAYA
Pages
371–388
Publication Date
2022-10-18
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results showed that teaching with STiIL increases learning and retention of knowledge in the cognitive domain.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The informal learning environment and the station technique provide students with learning environments where they can be active and materialize the abstract terms.
📊
Key Findings & Data:The participants of the study are 26 eleventh-grade students.
💡
Conclusion & Impact:Results showed that teaching with STiIL increases learning and retention of knowledge in the cognitive domain.
🔬Design:Survey & Empirical Study
📍Scope:2018-2019 Verileri
⚙️Variables:Domain Parameters

Özet

The informal learning environment and the station technique provide students with learning environments where they can be active and materialize the abstract terms. With this regard, the purpose of the study was to determine the contribution of activities, which are carried out through the station technique in informal learning environments (STiIL), to the cognitive, affective, and life skills of eleventh-grade high school students. The participants of the study are 26 eleventh-grade students. The “Musculoskeletal System” topic within the scope of the study is addressed through the station technique in the 2018-2019 educational year. The data-gathering tools for the study are semi-structured questionnaires, focus group interviews, and researcher journals. Deductive and descriptive analyses were performed together on the qualitative data. Results showed that teaching with STiIL increases learning and retention of knowledge in the cognitive domain. It improves the affective skills of students in terms of eagerness to learn and makes the teaching and learning process entertaining. Self-confidence and communication skills stand out in the life skills domain.

🔖

Cite This Article

YİĞİT, N., GÜVEN, E. M., SİVRİKAYA, E. (2022). Determination of the Contribution of Station Technique in Informal Learning Environments (STiIL) to Learning DomainS. Journal of Turkish Science Education, Cilt: 18 - Sayı: 3, 371–388. https://ajindex.com/articles/568479

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (10)

  1. AAAS. (2019). Project 2061 | American Association for the Advancement of Science. https://www.aaas.org/programs/project-2061
  2. Adadan, E., Savasci, F., & Martin, R. E. (2012). An analysis of 16–17-year-old students’ understanding of solution chemistry concepts using a two-tier diagnostic instrument. International Journal of Science Education, 34(4), 513–544.
  3. Adams, D., Joo, M. T. H., Sumintono, B., & Oh, S. P. (2020). Blended Learning Engagement in Higher Education Institutions: A Differential Item Functioning Analysis of Students’ Backgrounds. Malaysian Journal of Learning and Instruction, 17(1), 133–158.
  4. Allen, M. (2014). Misconceptions in primary science. McGraw-hill education. Andrich, D. (2018). Advances in social measurement: A Rasch measurement theory. Perceived Health and Adaptation in Chronic Disease, 66–91.
  5. Arslan, H. O., Cigdemoglu, C., & Moseley, C. (2012). A Three-Tier Diagnostic Test to Assess Pre-Service Teachers’ Misconceptions about Global Warming, Greenhouse Effect, Ozone Layer Depletion, and Acid Rain. International Journal of Science Education, 34(11), 1667–1686. https://doi.org/10.1080/09500693.2012.680618
  6. Barbic, S. P., & Cano, S. J. (2016). The application of Rasch measurement theory to psychiatric clinical outcomes research: Commentary on. Screening for depression in primary care. BJPsych Bulletin, 40(5), 243–244.
  7. Bond, T. G., & Fox, C. M. (2007). Rasch modeling applied: rating scale design. Applying the Rasch Model: Fundamental Measurement in the Human Sciences (2nd Ed., Pp. 219–233).
  8. Mahwah, NJ: Lawrence Erlbaum Associates Publishers.
  9. Boone, W. J., Staver, J. R., & Yale, M. S. (2013). Rasch analysis in the human sciences. Springer. Boone, W. J., Townsend, J. S., & Staver, J. R. (2016). Utilizing multifaceted Rasch measurement through FACETS to evaluate science education data sets composed of judges, respondents, and rating scale items: An exemplar utilizing the elementary science teaching analysis matrix instrument. Science Education, 100(2), 221–238.
  10. Bradley, K. D., Peabody, M. R., Akers, K. S., & Knutson, N. (2015). Rating Scales in Survey Research: Using the Rasch model to illustrate the middle category measurement flaw. Survey Practice, 8(2). Butler, J., Mooney Simmie, G., & O’Grady, A. (2015). An investigation into the prevalence of ecological misconceptions in upper secondary students and implications for pre-service teacher education. European Journal of Teacher Education, 38(3), 300–319. https://doi.org/10.1080/02619768.20