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Fen Bilgisi Öğretmen Adaylarının Kavramsal ve Algoritmik Kimya Sorularındaki Performanslarının Karşılaştırılması

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Abstract (2. Language): 
Problem Statement: Research studies have indicated that students correctly solve algorithmic questions about a concept without having a basic understanding of it. Parallel to this, in our schools, teachers have generally determined their students’ chemistry achievement by using algorithmic questions. This is an important problem for an effective chemistry education. Purpose of the Study: The purpose of the present study is to compare prospective science teachers’ performance on conceptual and algorithmic chemistry questions. Method(s): The descriptive survey model was adopted for the study. A total of 92 student teachers in first year enrolled in science teacher education department of a Faculty of Education in the eastern Blacksea region participated in the study. A test consisting of 12 questions, half of which are algorithmic and the others are conceptual, were developed and it covered six chemistry topics; acid and base, mole concept, chemical equilibrium, gases, dissolving, and finding molecular formula. The test included one conceptual question and one algorithmic question related to each topic. Students’ performances on algorithmic and conceptual questions were statistically analyzed by using independent samples t-test. Findings and Discussions: The results of t-test showed that there was a statistically significant difference between conceptual questions and graphical questions (p < 0.05). This result was consistent with results of previous studies. While 60% of students prefer algorithmic questions, 20% of them prefer conceptual questions, which is consistent with t-test findings. 50% of the students solved correctly both conceptual and algorithmic questions about all concepts under investigation. Although 27% of them solved algorithmic questions correctly, they cannot solve conceptual questions in same topics. While 14% of students solved conceptual questions correctly, they cannot solve algorithmic questions. 9% of the students cannot solve both conceptual and algorithmic questions. Conclusions and Recommendations: Most of the students showed higher performance on solving algorithmic questions requiring mathematical calculations than conceptual questions. This difference in student performance between algorithmic and conceptual questions was found statistically significant. In a similar manner, most of the students preferred algorithmic questions rather than conceptual questions. High performance on conceptual questions could be a predictor in explaining students’ performance on algorithmic questions. Teachers and teacher educators should be awareof results of this and similar studies with in-service training programs.
Abstract (Original Language): 
Bu çalışmanın amacı, ilköğretim fen bilgisi öğretmen adaylarının kavramsal ve algoritmik kimya sorularındaki performanslarını karşılaştırmaktır. Çalışmaya, Doğu Karadeniz bölgesinde yer alan bir eğitim fakültesinin ilköğretim fen bilgisi öğretmenliği programında öğrenim gören toplam 92 birinci sınıf öğretmen adayı katılmıştır. Çalışmanın yürütülmesinde betimsel tarama modeli benimsenmiştir. Gazlar, asit-baz, molekül formülü bulma, denge, çözeltiler ve mol kavramı konularına yönelik altı kavramsal altı algoritmik toplam 12 sorudan oluşan bir test geliştirilmiştir. Testten elde edilen veriler, bağımsız örneklemeli t-testi kullanılarak karşılaştırılmıştır. Sonuçlar, öğretmen adaylarının genel olarak algoritmik sorularda kavramsal sorulardan daha yüksek başarıya sahip olduklarını göstermektedir. Kimya öğretiminde kavramsal anlamayı merkeze alan, sayısal işlemlerden ziyade kavram öğretimine ağırlık veren, öğretim yöntemlerinin ve ölçme-değerlendirme yaklaşımlarının kullanılması önerilmektedir.
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REFERENCES

References: 

Ashmore, A. D., Frazer, M. J. & Casey, R. J. (1979). Problem
solving and problem solving networks in chemistry.
Journal of Chemical Education, 56, 377-379.
Bilgin, İ. (2006). The effects of pair problem solving technique
incorporating Polya’s problem solving strategy on
undergraduate students’ performance in chemistry.
Journal of Science Education, 7(2), 101-106.
Overton T. L. & Potter N. M. (2011). Investigating students’
success in solving and attitudes towards context-rich openended
problem solving in chemistry. Chemistry Education
Research and Practice, 12, 294-302.
St Clair-Thompson H. L., Overton T. & Bugler, M. (2012).
Mental capacity and working memory in chemistry:
algorithmic versus open-ended problem solving.
Chemistry Education Research and Practice, 13, 484-
489.
Boujaoude, S., Salloum, S. & Abd-El-Khalick, F. (2004).
Relationships between selective cognitive variables and
students’ ability to solve chemistry problems.
International Journal of Science Education, 26, 63-84.
Camacho, M. & Good, R. (1989). Problem-solving and chemical
equilibrium: successful versus unsuccessful performance.
Journal of Research in Science Teaching, 26, 251-272.
Chiu, M.H. (2001). Algorithmic problem solving and conceptual
understanding of chemistry by students at a local high
school in Taiwan. Proceedings of National Science
Council, ROC (D) 11(1), 20–38.
Coştu, B. (2007). Comparison of students’ performance on
algorithmic, conceptual and graphical chemistry gas
problems. Journal of Science Education Technology, 16,
379–386.
Demircioğlu, G. & Baykan, F. (2011). Kimya ve fen bilgisi
öğretmen adayları ile lise 11.sınıf öğrencilerinin kimyasal
bağlanma kavramına yönelik algılamalarının
karşılaştırılması, 2nd International Conference on New Trends in Education and Their Implications, 27-29 April,
Antalya.
Demircioğlu, H., Demircioğlu, G., Ayas, A. & Kongur, S.
(2012). Onuncu sınıf öğrencilerinin fiziksel ve kimyasal
değişme kavramları ile ilgili teorik ve uygulama
bilgilerinin karşılaştırılması. Türk Fen Eğitimi Dergisi,
9(1), 162-181.
Frazer, M.J. & Sleet, R.J. (1984). A study of students’ attempts
to solve chemical problems. Europian Journal of Science
Education, 6, 141–152.
Gabel, D., Sherwood, R. & Enochs, L. (1984). Problem-solving
skills ofhigh school chemistry students. Journal of
Research in Science Teaching, 21(2), 221-233.
Larkin, J. (1981). Enriching formal knowledge: A model for
learning to solve textbook physics problems. In J. R.
Anderson (Ed.), Cognitive Skills and their Acquisition.
Hillsdale, NJ: Erlbaum.
Lin, H.S., Chiu, H.L. & Chou, C.Y. (2004). Student
understanding of the natüre of science and their problemsolving
strategies. International Journal of Science
Education, 26(1), 101-112.
Lin, Q., Kirsch, P. & Turner, R. (1996). Numeric and conceptual
understanding of general chemistry at a minority
institution. Journal of Chemical Education, 73(10), 1003–
1005
Lythcott, J. (1990). Problem solving and requisite knowledge of
chemistry. Journal of Chemical Education, 67(3), 248–
252.
Mason, D. S., Shell, D. F. & Crawley, F. E. (1997). Differences
in problem solving by nonscience majors in ıntroductory
chemistry on paired algorithmic–conceptual problems.
Journal of Research in Science Teaching, 34(9), 905-923.
Morgil, İ., Yılmaz, A. & Özyalçın, Ö. (2002). Temel kimya
dersinde öğrencilerin kavramlari anlama ve sayisal
problemleri çözme başarilari arasindaki ilişki, V.Ulusal
Fen Bilimleri ve Matematik Eğitimi Kongresi, 16-18
Eylül, ODTÜ, Ankara.
Nakhleh, M. B. (1992). Why some students don’t learn
chemistry. Journal of Chemical Education, 69 (3), 191-
196.Pickering, M. (1990). Further studies on concept learning versus
problem solving. Journal of Chemical Education, 67(3),
254–255.
Sawrey, B.A. (1990). Concept learning versus problem solving:
Revised. Journal of Chemical Education, 67(3), 253–254.
Tsaparlis, G. (2005). Non algorithmic quantitative problem
solving in university physical chemistry: A correlation
study of the role of selective cognitive factors. Research in
Science & Technological Education,23, 125–148.
Tsaparlis, G., Kausathana, M. & Niaz, M. (1998). Molecularequilibrium
problems: Manipulation of logical structure
and M-demand, and their effect on students performance.
Science Education, 82:437–454.
Watkins, D. & Hattie, J. (1985). A longitudinal study of the
approaches to learning of Australian tertiary students.
Human Learning, 4, 127-141.

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