Fen Eğitiminde Tahmin-Gözlem-Açıkla Stratejisinin Akademik Başarıya Etkisi: Bir Meta Analiz Çalışması

Öz

Tahmin gözlem açıklama (TGA) uzun bir süredir fen eğitiminde kullanılan bir stratejidir. Özellikle fen alanındaki kavramların yapılandırıldığı deneylerde kullanılan bu stratejinin ne kadar etkili olduğunun belirlenmesi önem teşkil etmektedir. Bu araştırmada TGA stratejisinin öğrencilerin fen başarısı üzerindeki etkisi meta-analiz yöntemiyle incelenmiştir. Belirlenen anahtar kelimeler ile veri tabanlarında çeşitli taramalar gerçekleştirilmiş, dâhil edilme kriterlerini sağlayan 35 çalışma (6 tez, 29 makale) elde edilmiştir. Etki büyüklüklerinin hesaplanmasında Hedges’s g ve analizlerde rastgele etkiler modeli tercih edilmiştir. Analiz sonucunda ortalama etki büyüklüğü (g=0.979, 95% CI:0.771-1.188, p<0.001) sınıflamaya göre yüksek düzey bulunmuştur. Buna göre, TGA stratejisi öğrencilerin fen başarısını artırmakla birlikte yüksek düzeyde etkilemektedir. Çalışmalar arasındaki farklılıklar analog ANOVA ve meta-regresyon analizleri ile belirlenmiştir. TGA stratejisinin öğrencilerin fen başarısı üzerindeki etkisi bilim alanı ve öğretim kademesi moderatörlerine göre anlamlı farklılıklar gösterirken, uygulanma şekli moderatörüne göre anlamlı bir farklılık göstermemiştir. Uygulama süresi ve yayın yılı moderatörlerinin TGA stratejisinin fen başarısı üzerindeki etkisinin anlamlı birer yordayıcıları olmadığı ortaya koyulmuştur. Bu sonuçlardan yola çıkarak araştırmacı ve uygulayıcılara bazı önerilerde bulunulmuştur.

Anahtar Kelimeler

• Tahmin-gözlem-açıkla
• fen eğitimi
• akademik başarı
• meta-analiz

Effect of the Predict-Observe-Explain (POE) Strategy on Achievement in Science Education: A Meta-Analysis Study

Öz

Predict-observe-explain (POE) is a strategy that has been used in science education for several decades. It is important to determine how effective this strategy is, especially when used in the constructing scientific concepts. In this study, the effect of the POE strategy on students’ science achievement was examined in a meta-analysis. Databases were searched using specific keywords and 35 studies (6 theses and 29 articles) that met the inclusion criteria were found. Hedges’ g and the random effects model were used to calculate effect sizes. As a result, the average effect size (g=0.979, 95% CI: 0.771-1.188, p<0.001) was found to be high. The POE strategy was found to increase students’ science achievement with a high-level effect. The differences between studies were determined by analog to the ANOVA and meta-regression moderator analyses. While the effect of POE on students’ science achievement differed significantly according to the moderators of field of science and level of education, it did not differ significantly according to the moderator of implementation type. The moderators of implementation time and year of publication were similarly not found to be significant predictors of the effect of POE on science achievement. Based on these results, suggestions are made for researchers and practitioners.

Anahtar Kelimeler

• Predict-observe-explain
• science education
• academic achievement
• meta-analysis

Kaynakça

1. Acar Şeşen, B. (2013). Diagnosing pre-service science teachers’ understanding of chemistry concepts by using computer-mediated predict-observe-explain tasks. Chemistry Education Research and Practice, 14(3), 239-246. https://doi.org/10.1039/C3RP20143K
2. *Akpınar, E. (2014). The use of interactive computer animations based on POE as a presentation tool in primary science teaching. Journal of Science Education and Technology, 23(4), 527-537. https://doi.org/10.1007/s10956-013-9482-4
3. Atasoy, B. (2004). Science learning and teaching. Asil Yayıncılık.
4. *Ayvacı, H. Ş., & Durmuş, A. (2016). Effect of laboratory activities based on “predict-observe- explain (POE)” method on pre-service science teachers’ academic achievement on “heat and temperature” subject. Pamukkale University Journal of Education, 39(39), 101-118. http://dx.doi.org/10.9779/PUJE742
5. *Banawi, A., Sopandi, W., Kadarohman, A., & Solehuddin, M. (2019). Prospective primary school teachers’ conception change on states of matter and their changes through predict-observe explain strategy. International Journal of Instruction, 12(3), 359-374. https://doi.org/10.29333/iji.2019.12322a
6. *Bilen, K., & Köse, S. (2012). An effective concept teaching strategy: Prediction-observation explanation (POE) "growth and development in plant". Pamukkale University Journal of Education, 31(31), 123-136.
7. *Bolat, A., & Karamustafaoğlu, S. (2021). Teaching mass and weight concepts: Prediction observation-explain. Milli Eğitim Dergisi, 50(230), 663-687. https://doi.org/10.37669/milliegitim.702128
8. Borenstein, M., Hedges, L., Higgins, J., & Rothstein, H. (2014). Comprehensive meta-analysis (Version 3.3.070) [Computer software]. Biostat. https://www.metaanalysis.com

9. Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2021). Introduction to meta analysis (2nd ed.). John Wiley & Sons. https://doi.org/10.1016/b978-0-12-2090059.50005-9
10. *Bulunuz, N., & Bulunuz, M. (2017). Effect of formative assessment-based instruction on high school students’ conceptual understanding of balance and torque. Journal of Inquiry Based Activities, 7(1), 21-33.
11. Card, N. A. (2012). Applied meta-analysis for social science research. The Guilford Press.
12. *Chen, C. H., Huang, K. & Liu, J. H. (2020). Inquiry-enhanced digital game-based learning: Effects on secondary students’ conceptual understanding in science, game performance, and behavioral patterns. The Asia-Pacific Education Researcher, 29(4), 319-330. https://doi.org/10.1007/s40299-019-00486-w
13. *Chen, J. C. (2022). Developing a cycle-mode POED model and using scientific inquiry for a practice activity to improve students’ learning motivation, learning performance, and hands-on ability. Interactive Learning Environments, 30(7), 1252-1264. https://doi.org/10.1080/10494820.2020.1716023
14. *Chen, Y. L., Pan, P. R., Sung, Y. T., & Chang, K. E. (2013). Correcting misconceptions on electronics: Effects of a simulation based learning environment backed by a conceptual change model. Educational Technology & Society, 16(2), 212-227.
15. Coe, C. W. M. (1993). Predict-observe-explain science activities in the junior high classroom: A qualitative inquiry [Master’s thesis, St. Mary’s University]. ProQuest Dissertations & Theses Global.
16. Cohen, L., Manion, L., & Morrison, K. (2002). Research methods in education. Routledge. https://doi.org/10.4324/9780203224342
17. Cooper, H., Hedges. L. V., & Valentine, J. C. (Eds.). (2009). The handbook of research synthesis and meta-analysis (2nd ed.). Russell Sage Publication.
18. *Coştu, B. (2008). Learning science through the pdeode teaching strategy: Helping students make sense of everyday situations. Eurasia Journal of Mathematics, Science & Technology Education, 4(1), 3-9. https://doi.org/10.12973/ejmste/75300
19. *Coştu, F. (2021). Investigation of the predict-explain-obseve discuss-explain based laboratory activities on pre-service science teachers’ achievement, conceptual understanding and science process skills [Doctoral dissertation, Marmara University]. Council of Higher Education Thesis Center.
20. *Çalış, S., & Özkan, M. (2022). The effect of science teaching based on POE strategy on the academic achievement and attitudes of fifth-grade students in the distance education process. Mimbar Sekolah Dasar, 9(3), 381-395. https://doi.org/ 10.53400/mimbarsd.v9i3.45472
21. *Çıngıl Barış, Ç. (2022). The effect of the ‘predict-observe-explain (POE)’ strategy in teaching photosynthesis and respiration concepts to pre-service science teachers. Journal of Biological Education. https://doi.org/10.1080/00219266.2022.2047097
22. *Çinici, A., Sözbilir, M., & Demir, Y. (2011). Effect of cooperative and individual learning activities on students’ understanding of diffusion and osmosis. Eurasian Journal of Educational Research, 43, 19-36.
23. Delen, I., & Şen, S. (2023). Effect of design-based learning on achievement in K-12 education: A meta-analysis. Journal of Research in Science Teaching, 60(2), 330-356. https://doi.org/10.1002/tea.21800
24. Dickersin, K. (2005). Publication bias: Recognizing the problem, understanding its origins and scope, and preventing harm. In H. R. Rothstein, A. J. Sutton, & M. Borenstein (Eds.), Publication bias in meta-analysis: Prevention, assessment and adjustments (pp.11-33). John Wiley & Sons.
25. Duval, S., & Tweedie, R. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455-463. https://doi.org/10. 1111/j.0006-341X.2000.00455.x
26. Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315, 629-634. https://doi.org/10.1136/bmj.315.7109.629
27. *Erdem Özcan, G., & Uyanık, G. (2022). The effects of the “predict-observe-explain (POE)” strategy on academic achievement, attitude and retention in science learning. Journal of Pedagogical Research, 6(3), 103-111. https://doi.org/10.33902/JPR.202215535
28. Evangelou, F., & Kotsis, K. (2019). Real vs virtual physics experiments: comparison of learning outcomes among fifth grade primary school students. A case on the concept of frictional force. International Journal of Science Education, 41(3), 330-348, https://doi.org/10.1080/09500693.2018.1549760
29. *Fateen, R. (2020). Comparing inquiry-based teaching strategies for improving and implementing computer simulation-based instruction of science concepts [Doctoral dissertation, Southern Illinois University]. ProQuest Dissertations & Theses Global.
30. Field, A. P., & Gillett, R. (2010). How to do a meta-analysis. The British Journal of Mathematical and Statistical Psychology, 63(3), 665-694. https://doi.org/10.1348/000711010X502733
31. *Furqani, D., Feranie, S., & Winarno, N. (2018). The effect of predict-observe-explain (POE) strategy on students’ conceptual mastery and critical thinking in learning vibration and wave. Journal of Science Learning, 2(1), 1-8. https://doi.org/10.17509/jsl.v2i1.12879
32. George, D., & Mallery, M. (2010). SPSS for windows step by step: A simple guide and reference, 17.0 update (10th ed.). Pearson.
33. Glass, G. V., Smith, M. L., & McGaw, B. (1981). Meta-analysis in social research. Sage.
34. Guerrero, T.A., Griffin, T.D. & Wiley, J. (2022). I think i was wrong: The effect of making experimental predictions when learning about theories from psychology textbook excerpts. Metacognition Learning 17, 337-373. https://doi.org/10.1007/s11409-021-09276-6
35. Gunstone, R. F., & White, R. T. (1981). Understanding of gravity. Science Education, 65(3), 291 299. https://doi.org/10.1002/sce.3730650308
36. Gustina, R., Hastuti, I. D., Nizaar, M., & Syaharuddin, S. (2023). Predict observe explain learning model: Implementation and its influence on students’ critical thinking ability and learning outcomes (a meta-analysis study). Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran, 9(2), 706-718. https://doi.org/10.33394/jk.v9i2.7388
37. *Harman, G., & Yenikalayci, N. (2022). The effect of prediction-observation-explanation (POE) method on learning of image formation by a plane mirror and pre-service teachers’ opinions. Journal of Educational Research and Practice, 12(1), 1-17. https://doi.org/10.5590/JERAP.2022.12.1.1
38. Hedges, L. V. (1982). Fitting categorical models to effect sizes from a series of experiments. Journal of Educational Statistics, 7(2), 119-137. https://doi.org/10.2307/1164961
39. Hedges, L. V., & Olkin, I. (1985). Statistical model of meta-analysis. Academic Press.
40. Higgins, J. P., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analysis. British Medical Journal, 327(7414), 557-560. https://doi.org/10.1136/bmj.327.7414.557
41. Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundation for the 21st century. Science Education, 88(1), 28-54. https://doi.org/10.1002/sce.10106
42. *Hsiao, H. S., Chen, J., Hong, J. C., Chen, P. H., Lu, C. C., & Chen, S. Y. (2017). A five-stage prediction-observation-explanation inquiry-based learning model to improve students’ learning performance in science courses. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 3393-3416. https://doi.org/10.12973/eurasia.2017.00735a
43. *Hsu, C. Y., Tsai, C. C., & Liang, J. C. (2011). Facilitating preschoolers’ scientific knowledge construction via computer games regarding light and shadow: The effect of the prediction observation-explanation (POE) strategy. Journal of Science Education Technology, 20(5), 482-493. https://doi.org/10.1007/s10956-011-9298-z
44. Huedo-Medina, T. B., Sánchez-Meca, J., Marín-Martínez, F., & Botella, J. (2006). Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychological Methods, 11(2), 193-206. https://doi.org/10.1037/1082-989X.11.2.193
45. IBM Corp. (2019). IBM SPSS statistics for windows (Version 26.0) [Computer software]. IBM Corp.
46. *James, N. M., Kreager, B. Z., & LaDue, N. D. (2022) Predict-observe-explain activities preserve introductory geology students’ self-efficacy. Journal of Geoscience Education, 70(2), 238-249. https://doi.org/10.1080/10899995.2021.1906593
47. *Kahraman, S. (2023). The use of dynamic computer visualizations integrated with the poe sequence: Its effect on learners’ understanding, retention, and motivation. Canadian Journal of Science, Mathematics and Technology Education, 23, 179-209. https://doi.org/10.1007/s42330-023-00284-z
48. *Karamustafaoğlu, S., & Mamlok-Naaman, R. (2015). Understanding electrochemistry concepts using the predict-observe-explain strategy. Eurasia Journal of Mathematics, Science and Technology Education, 11(5), 923-936. https://doi.org/10.12973/eurasia.2015.1364a
49. *Karpin, T., Juuti, K., & Lavonen, J. (2014) Learning to apply models of materials while explaining their properties. Research in Science & Technological Education, 32(3), 340-351. https://doi.org/10.1080/02635143.2014.944494
50. *Karslı Baydere, F. (2021). Effects of a context-based approach with prediction-observation explanation on conceptual understanding of the states of matter, heat and temperature. Chemistry Education Research and Practice, 22(3), 640-652. https://doi.org/10.1039/d0rp00348d
51. Kearney, M. (2002). Classroom use of multimedia-supported predict-observe-explain tasks to elicit and promote discussion about students’ physics concepts [Unpublished doctoral dissertation]. Curtin University of Technology.
52. Kearney, M. (2004). Classroom use of multimedia-supported predict observe-explain tasks in a social constructivist learning environment. Research in Science Education, 34(4), 427-453. https://doi.org/10.1007/s11165-004-8795-y
53. *Kibirige, I., Osodo, J., & Tlala, K. M. (2014). The effect of predict-observe-explain strategy on learners’ misconceptions about dissolved salts. Mediterranean Journal of Social Sciences, 5(4), 300-310. https://doi.org/10.5901/mjss.2014.v5n4p300
54. Konstantopoulos, S., & Hedges, L. V. (2009). Analyzing effect sizes: Fixed-effects models. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.)., The hand. of research synthesis and meta analysis, 2nd ed. (pp. 279-293). Russell Sage Foundation.
55. Li, Y. D., Ding, G. H., & Zhang, C. Y. (2021). Effects of learner-centred education on academic achievement: A meta-analysis. Educational Studies. https://doi.org/10.1080/03055698.2021.1940874
56. Liew, C. W., & Treagust, D. F. (1998). The effectiveness of predict-observe explain tasks in diagnosing students’ understanding of science and in identifying their levels of achievement (ED420715). ERIC. https://files.eric.ed.gov/fulltext/ED420715.pdf
57. Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. SAGE Publications.
58. *Lucas, L., Helikar, T., & Dauer, J. (2022) Revision as an essential step in modeling to support predicting, observing, and explaining cellular respiration system dynamics. International Journal of Science Education, 44(13), 2152-2179. https://doi.org/10.1080/09500693.2022.2114815
59. Matthews, M. R. (2002). Constructivism and science education: a further appraisal. Journal of Science Education and Technology, 11(2), 121-134.
60. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Prisma Group. (2009). Reprint-preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Physical Therapy, 89(9), 873-880. https://doi.org/10.1093/ptj/89.9.873
61. Mutlu, A., & Acar Şeşen, B. (2016). Predict-observe-explain tasks in chemistry laboratory: Pre service elementary teachers’ understanding and attitudes. Sakarya University Journal of Education, 6(2), 184-208. http://dx.doi.org/10.19126/suje.46187
62. Nurshafara, A. (2022). Meta-analysis of the effect of the predict observe explain (POE) leaming model on students’ physics leaming outcomes [Unpublished skripsi thesis]. Universitas Negeri Padang.
63. *Nyirahabimana, P., Minani, E., Nduwingoma, M., & Kemeza, I. (2023). Multimedia‑aided technologies for effective learning of quantum physics at the university level. Journal of Science Education and Technology, 32, 686-696. https://doi.org/10.1007/s10956-02310064-x
64. *Özçelik, H. (2019). Examining the effect of predict-observe-explain (poe) method supported with concept cartoons on secondary school students’ inquiry skills, sci̇ence process skills and conceptual understanding [Master’s thesis, Marmara University]. Council of Higher Education Thesis Center.
65. *Özkan, M. (2022). The effect of science teaching based on poe straregy on the academic achievement and attitudes of secondary school students in the distance education process [Master’s thesis, Bursa Uludağ University]. Council of Higher Education Thesis Center.
66. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews, 10(1), 1-11. https://doi.org/10.1186/s13643-02001552-x
67. Palmer, D. (1995). The POE in the primary school: An evaluation. Research in Science Education, 25, 323-332. https://doi.org/10.1007/BF02357405
68. Rodriguez, J. E., Williams, D. R., & Bürkner, P. C. (2023). Heterogeneous heterogeneity by default: Testing categorical moderators in mixed-effects meta-analysis. The British Journal of Mathematical and Statistical Psychology, 76(2), 402-433. https://doi.org/10.1111/bmsp.12299
69. Rosenthal, R. (1991). Meta-analytic procedures for social research. Sage Publications.
70. Ross, B., & Munby, H. (1991). Concept mapping and misconceptions: A study of high-school students’ understandings of acids and bases. International Journal of Science Education, 13(1), 11-23. https://doi.org/10.1080/0950069910130102
71. Sarkis-Onofre, R., Catalá-López, F., Aromataris, E., & Lockwood, C. (2021). How to properly use the PRISMA Statement. Systematic Reviews, 10(1), 1-3. https://doi.org/10.1186/s1364302101671-z
72. Tao, P. K., & Gunstone, R. F. (1997). The process of conceptual change in ‘force and motion’ (ED407259). ERIC. https://files.eric.ed.gov/fulltext/ED407259.pdf
73. *Tetik, S. (2019). The effect of teaching the topic of liquids in 9. grade chemistry course with the 5E model and the tga technique (prediction-observation-explanation) on the success of students [Master’s thesis, Marmara University]. Council of Higher Education Thesis Center.
74. Thalheimer, W., & Cook, S. (2002). How to calculate effect sizes from published research: A simplified methodology. Work-Learning Research, 1, 1-9.
75. *Tokay, E. (2022). The effect of the prediction-observation-explanation (POE) method on the students’ academic achievement and motivation in the subject of ‘Acids and bases’ in the 10th grade chemistry course [Master’s thesis, Dokuz Eylül University]. Council of Higher Education Thesis Center.
76. Tüysüz, A., & Özdemir, Ö. F. (2024). An experimental study exploring the effects of predict observe-explain method supported with simulations. Research in Science & Technological Education. https://doi.org/10.1080/02635143.2023.2296458
77. UNESCO. (2012). International standard classification of education: ISCED 2011. UNESCO Institute for Statistics. https://doi.org/10.1108/S0195-6310(2013)0000030017
78. Vevea, J. L., Coburn, K., & Sutton, A. (2019). Publication bias. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (3rd ed., pp. 383-430). Russell Sage Foundation.
79. White, R., & Gunstone, R. (1992). Probing understanding. The Falmer Press.
80. White, R. T. (1988). Learning science. Basil Blackwell.
81. White, W. A. T. (1988). A meta-analysis of the effects of direct instruction in special education. Education and Treatment of Children, 11(4), 364-374. https://www.jstor.org/stable/42899084
82. *Wiyarsi A., Prodjosantoso, A. K., & Nugraheni, A. R. E. (2021). Promoting students’ scientific habits of mind and chemical literacy using the context of socio-scientific issues on the inquiry learning. Frontiers in Education, 6, 1-12. https://doi.org/10.3389/feduc.2021.660495
83. *Yaman, F., & Ayas, A. (2015). Assessing changes in high school students’ conceptual understanding through concept maps before and after the computer-based predict-observe explain (CB-POE) tasks on acid-base chemistry at the secondary level. Chemistry Education Research and Practice, 16(4), 843-855. https://doi.org/10.1039/C5RP00088B
84. Yaman, F., Ayas, A., & Çalık, M. (2019). Facilitating grade 11 students’ conceptual understanding of fundamental acid-base models. Turkish Journal of Education, 8(1), 16-32. https://doi.org/10.19128/turje.449100
85. Yang, K. H., & Chen, H. H. (2023) What increases learning retention: Employing the prediction observation-explanation learning strategy in digital game-based learning. Interactive Learning Environments, 31(6), 3898-3913. https://doi.org/10.1080/10494820.2021.1944219
86. Zacharia, Z. C., Olympiou, G., & Papaevripidou, M. (2008). Effects of experimenting with physical and virtual manipulatives on students’ conceptual understanding in heat and temperature. Journal of Research in Science Teaching, 45(9), 1021-1035. https://doi.org/10.1002/tea.20260
87. *Zhao, L., He, W., Liu, X., Tai, K. H., & Hong, J. C. (2021). Exploring the effects on fifth graders’ concept achievement and scientific epistemological beliefs: Applying the prediction observation-explanation inquiry-based learning model in science education. Journal of Baltic Science Education, 20(4), 664-676. https://doi.org/10.33225/jbse/21.20.664