• Ashcraft, M. H. (1978). Property norms for typical and atypical items from 17 categories: A description and discussion. Memory & Cognition, 6(3), 227-232. https://doi.org/10.3758/BF03197450.
• Ausubel, D., Novak, J., & Hanesian, H. (1986). Educational psychology: A cognitive view (2 ed.). New York: Holt, Rinehart and Winston.
• Bahar, M., & Hansell, M. H. (2000). The relationship between some psychological factors and their effect on the performance of grid questions and word association tests. Educational Psychology, 20(3), 349-364. https://doi.org/10.1080/713663739.
• Bahar, M., Johnstone, A. H., & Sutcliffe, R. G. (1999). Investigation of students’ cognitive structure in elementary genetics through word association tests. Journal of Biological Education, 33(3), 134-141. https://doi.org/10.1080/00219266.1999.9655653.
• Baker, O. (1993). How constructivist theory and research inform educational policy. Paper presented at the Annual Meeting of the American Educational Research Association, Atlanta, Georgia.
• Barão, A. (2014). Gephi plugin: Network Splitter 3D.
• Bell, E. C., Willson, M. C., Wilman, A. H., Dave, S., & Silverstone, P. H. (2006). Males and females differ in brain activation during cognitive tasks. NeuroImage, 30(2), 529-538. https://doi.org/10.1016/j.neuroimage.2005.09.049.
• Bird, L. (2010). Logical reasoning ability and student performance in general chemistry. Journal of Chemical Education, 87(5), 541-546. https://doi.org/10.1021/ed8001754.
• Bodner, G. M. (1986). Constructivism: A theory of knowledge. Journal of Chemical Education, 63(10). https://doi.org/10.1021/ed063p873.
• Cambridge, D. (2012). The relationship between student’s quantitative skills, application of math, science courses, and science marks at single-sex independent high schools. (Ed.D.), St. Joseph’s University, Ann Arbor, United States. Retrieved from https://eric.ed.gov/? ProQuest Dissertations & Theses A&I database.
• Cavallo, A. M. J. P., Wendell H.; Rozman, Michelle. (2004). Gender differences in learning constructs, shifts in learning constructs, and their relationship to course achievement in a structured inquiry, yearlong college physics course for life science majors. School Science and Mathematics, 104(6). https://doi.org/10.1111/j.1949-8594.2004.tb18000.x.
• Clauser, B. E. (2007). The life and labors of Francis Galton: A review of four recent books about the father of behavioral statistics. [Francis Galton: Pioneer of Heredity and Biometry, M. Bulmer; Extreme Measures: The Dark Visions and Bright Ideas of Francis Galton, M. Brookes; The Biographer’s Tale, A. S. Byatt; A Life of Sir Francis Galton: From African Exploration to the Birth of Eugenics, N. W. Gillham]. Journal of Educational and Behavioral Statistics, 32(4), 440-444. https://doi.org/10.3102/1076998607307449.
• Forster, P. (1999). Applying constructivist theory to practice in a technology-based learning environment. Mathematics Education Research Journal, 11(2), 81-93. https://doi.org/10.1007/BF03217062.
• Garskof, B. E., & Houston, J. P. (1963). Measurement of verbal relatedness: An idiographic approach. Psychological Review, 70(3), 277. https://doi.org/10.1037/h0041879.
• Gulacar, O., & Bowman, C. R. (2014). Determining what our students need most: exploring student perceptions and comparing difficulty ratings of students and faculty. Chemistry Education Research and Practice, 15(4), 587-593. https://doi.org/10.1039/C4RP00055B.
• Gulacar, O., Sinan, O., Bowman, C. R., & Yildirim, Y. (2015). Exploring the changes in students’ understanding of the scientific method using word associations. Research in Science Education, 45(5), 717-726. https://doi.org/10.1007/s11165-014-9443-9.
• Hoffmann, R., & Laszlo, P. (1991). Representation in chemistry. Angewandte Chemie, 30(1), 1-16. https://doi.org/10.1002/anie.199100013.
• Johnstone, A. H. (1982). Macro- and microchemistry. School Science Review, 64, 377-379.
• Johnstone, A. H. (2006). Chemical education research in Glasgow in persepctive. Chemistry Education Research and Practice, 7(2), 49-63. https://doi.org/10.1039/B5RP90021B.
• Jung, C. G. (1910). The association method. American Journal of Psychology, 21(2), 219-269. https://doi.org/10.2307/1413002.
• Kempa, R., & Nicholls, C. E. (1983). Problem‐solving ability and cognitive structure‐an exploratory investigation. European Journal of Science Education, 5(2), 171-184. https://doi.org/10.1080/0140528830050205.
• Kilner, W. C. (2014). The Chem-Math Project: Enhancing Success in General Chemistry through the Integration of Mathematics, Problem-Solving and Conceptual Understanding. An Action-Research Study. Retrieved from ERIC database https://search.proquest.com/docview/1720061323?accountid=14505.
• Kostova, Z. R., Blagovesta. (2008). Word association test for studying conceptual structures of teachers and students. Bulgarian Journal of Science and Education Policy, 2(2), 209-231.
• Kounios, J., & Holcomb, P. J. (1992). Structure and process in semantic memory: Evidence from event-related brain potentials and reaction times. Journal of Experimental Psychology, 121(4), 459-479. https://doi.org/10.1037/0096-3445.121.4.459.
• Kurt, H., Ekici, G., Aktas, M., & Aksu, O. (2013). Determining biology student teachers’ cognitive structure on the concept of “diffusion” through the free word-association test and the drawing-writing technique. International Education Studies, 6(9). https://doi.org/10.5539/ies.v6n9p187.
• Lee, K.-W. L. (1985). Cognitive variables in problem solving in chemistry. Research in Science Education, 15(1), 43-50. https://doi.org/10.1007/BF02356524.
• Lee, K.-W. L., & Fensham, P. J. (1996). A general strategy for solving high school electrochemistry problems. International Journal of Science Education, 18(5), 543-555. https://doi.org/10.1080/0950069960180504.
• Lee, K.-W. L., Goh, N. K., Chia, L. S., & Chin, C. (1996). Cognitive variables in problem solving in chemistry: A revisited study. Science Education, 80(6), 691-710. https://doi.org/10.1002/(SICI)1098-237X(199611)80:6<691::AID-SCE4>3.0.CO;2-E.
• Murphy, K., Holme, T., Zenisky, A., Caruthers, H., & Knaus, K. (2012). Building the ACS exams anchoring concept content map for undergraduate chemistry. Journal of Chemical Education, 89(6), 715-720. https://doi.org/10.1021/ed300049w.
• Nakiboglu, C. (2008). Using word associations for assessing non major science students’ knowledge structure before and after general chemistry instruction: the case of atomic structure. Chemistry Education Research and Practice, 9(4), 309-322. https://doi.org/10.1039/b818466f.
• Noss, R., & Hoyles, C. (2017). Constructionism and Microworlds. In E. Duval, M. Sharples, & R. Sutherland (Eds.), Technology Enhanced Learning: Research Themes (pp. 29-35). Cham: Springer International Publishing.
• Petrucci, R. H., Herring, F. G., Madura, J. D., & Bissonnette, C. (2011). General chemistry: Principles and modern applications (10th ed.). Toronto: Pearson.
• Pinarbasi, T., & Canpolat, N. (2003). Students’ understanding of solution chemistry concepts. Journal of Chemical Education, 80(11), 1328-1332. https://doi.org/10.1021/ed080p1328.
• Richardson, V. (1997). Constructivist teacher education: Building a world of new understandings. London: Routledge/Falmer.
• Rixse, J. S., & Pickering, M. (1985). Freshman chemistry as a predictor of future academic success. Journal of Chemical Education, 62(4), 313. https://doi.org/10.1021/ed062p313.
• Schvaneveldt, R. W. (1990). Proximities, networks, and schemata. In R. W. Schvaneveldt (Ed.), Pathfinder associative networks: Studies in knowledge organization (pp. 135-148). Norwood, NJ: Ablex.
• Shavelson, R. J. (1972). Some aspects of the correspondence between content structure and cognitive structure in physics instruction. Journal of Educational Psychology, 63(3), 225-234. https://doi.org/10.1037/h0032652.
• Shibley Jr, I. A., Milakofsky, L. M., Bender, D. S., & Patterson, H. O. (2003). College chemistry and Piaget: An analysis of gender difference, cognitive abilities, and achievement measures seventeen years apart. Journal of Chemical Education, 80(5). https://doi.org/10.1021/ed080p569.
• Smilkstein, R. (1991). A natural teaching method based on learning theory. Gamut, 12-15.
• Speck, O., Ernst, T., Braun, J., Koch, C., Miller, E., & Chang, L. (2000). Gender differences in the functional organization of the brain for working memory. NeuroReport, 11(11), 2581-2585. https://doi.org/10.1097/00001756-200008030-00046.
• Spekkink, W. (2015a). MDS Layout.
• Spekkink, W. (2015b). MDS Statistics.
• Taber, K. S. (2013). Revisiting the chemistry triplet: drawing upon the nature of chemical knowledge and the psychology of learning to inform chemistry education. Chemistry Education Research and Practice, 14(2), 156-168. https://doi.org/10.1039/c3rp00012e.
• Tai, R. H., Ward, B. R., & Sadler, P. M. (2006). High school chemistry content background of introductory college chemistry students and its association with college chemistry grades. Journal of Chemical Education, 83(11), 1703-1711. https://doi.org/10.1021/ed083p1703.
• Talanquer, V. (2011). Macro, submicro, and symbolic: The many faces of the chemistry “triplet”. International Journal of Science Education, 33(2), 179-195. https://doi.org/10.1080/09500690903386435.
• Von Glasersfeld, E. (1990). An exposition of constructivism: Why some like it radical. In R. B. Davis, C. A. Mayer, & N. Noddings (Eds.), Constructivist view on the teaching and learning of mathematics (pp. 19-29). Reston, VA: National Council of Teachers of Mathematics.
• Wagner, W., Valencia, J., & Elejabarrieta, F. (1996). Relevance, discourse and the ‘hot’ stable core social representations—A structural analysis of word associations. British Journal of Social Psychology, 35(3), 331-351. https://doi.org/10.1111/j.2044-8309.1996.tb01101.x.
• Yücel, E. Ö., & Özkan, M. (2015). Determination of secondary school students’ cognitive structure, and misconception in ecological concepts through word association test. Educational Research and Reviews, 10(5), 660. https://doi.org/10.5897/ERR2014.2022.

APA

Gulacar, O., Milkey, A., & McLane, S. (2019). Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry. Eurasia Journal of Mathematics, Science and Technology Education, 15(8), em1726. https://doi.org/10.29333/ejmste/106231

Vancouver

Gulacar O, Milkey A, McLane S. Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry. EURASIA J Math Sci Tech Ed. 2019;15(8):em1726. https://doi.org/10.29333/ejmste/106231

AMA

Gulacar O, Milkey A, McLane S. Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry. EURASIA J Math Sci Tech Ed. 2019;15(8), em1726. https://doi.org/10.29333/ejmste/106231

Chicago

Gulacar, Ozcan, Alexandra Milkey, and Spivey McLane. "Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry". Eurasia Journal of Mathematics, Science and Technology Education 2019 15 no. 8 (2019): em1726. https://doi.org/10.29333/ejmste/106231

Harvard

Gulacar, O., Milkey, A., and McLane, S. (2019). Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry. Eurasia Journal of Mathematics, Science and Technology Education, 15(8), em1726. https://doi.org/10.29333/ejmste/106231

MLA

Gulacar, Ozcan et al. "Exploring the Effect of Prior Knowledge and Gender on Undergraduate Students’ Knowledge Structures in Chemistry". Eurasia Journal of Mathematics, Science and Technology Education, vol. 15, no. 8, 2019, em1726. https://doi.org/10.29333/ejmste/106231