Can We Make Definite Categorization of Student Attitudes? A Rough Set Approach to Investigate Students’ Implicit Attitudinal Typologies Toward Living Things

Aktaş H, Cagman N (2005) Bulanık ve Yaklaşımlı Kümeler, Çankaya Üniversitesi Fen-Edebiyat Fakültesi. J Arts Sci 3:13–25 Ashworth S, Boyes E, Paton R, Stanisstreet M (1995) Conservation of endangered species: what do children think? J Environ Educ Inf 14:229–244 Barney EC, Mintzes JJ, Yen C-F (2005) Assessing knowledge, attitudes, and behavior toward charismatic megafauna: the case of dolphins. J Environ Educ 36:41–55 Bjerke T, Reitan O, Kellert SR (1998) ‘Attitudes toward wolves in southeastern Norway. Soc Nat Resour 11:169–178 Bonikowaski Z (1995) Algebraic structures of rough sets, rough sets, fuzzy sets and knowledge discovery. Springer, Berlin Caro TM, Pelkey N, Grigione M (1994) Effects of conservation biology education on attitudes toward nature. Conserv Biol 8:846–852 Doignon JP, Falmagne JC (1985) Spaces for the assessment of knowledge. Int J Man-Mach Stud 23:175–196 Doignon JP, Falmagne JC (1999) Knowledge spaces. Springer, Berlin Düntsch I, Gediga G (2001) A note on the correspondence among entail relations, rough set dependencies, and logical consequence. J Math Psychol 45:393–401 Eagly AH (1992) Uneven progress: social psychology and the study of attitudes. J Pers Soc Psychol 63:693–710 Falmagne JC, Doignon JP (1988) A markovian procedure for assessing the state of a system. J Math Psychol 32:232–258 Falmagne JC, Koppen M, Villano M, Doignon JP, Johannesen L (1990) Introduction to knowledge spaces: how to build, search and test them. Psychol Rev 97:201–224 Fernandez-Manzanal R, Rogriguez-Barreiro L, Carrasquer J (2007) Evaluation of environmental attitudes: analysis and results of a scale applied to university students. Sci Educ 91:988–1009 Frege G (1904) Grundgesetze der Arithmentik. In: Geach PT, Black M (eds) Selections from the philosophical writings of Gotlob Frege. Blackwell, Oxford Ganter B, Wille R (1999) Formal concept analysis: mathematical foundations. Springer, Berlin Hassanien AE (2003) Intelligent data analysis of breast cancer based on rough set theory. Int J Artif Intell Tools 12:465–479 Hsu T (2005) Research methods and data analysis procedures used by educational researchers. Int J Res Method Educ 28:109–133 Jiashang J, Congxin W, Degang C (2005) The product structure of fuzzy rough sets on a group and the rough T—fuzzy group. Inf Sci 175(1–2):97–107 Kattmann U (2001) Aquatics, flyers, creepers and terrestrials-students’ conceptions of animal classifications. J Biol Educ 35:141–147 Kellert SR (1985) American attitudes toward and knowledge of animals: an update. In: Fox M, Mickley L (eds) Advances in animal welfare science. Humane Society of the United States, Washington, DC, pp 177–213 Kellert SR (1991) Japanese perceptions of wildlife. Conserv Biol 5:297–308 Kellert SR (1993a) The biological basis for human values of nature. In: Kellert SR, Wilson EO (eds) The biophilia hypothesis. Island Press, Washington, DC, pp 42–69 Kellert SR (1993b) Attitudes, knowledge, and behavior toward wildlife among the industrial superpowers: United States, Japan, and Germany. J Soc Issues 49:53–69 Kellert SR (1996) The value of life: biological diversity and human society. Island Press, Washington, DC Kellert SR, Berry JK (1980) Knowledge, affection and basic attitudes toward animals in American society. US Government Printing Office, Washington, DC (2040-101-00-625-1) Kent RE (1994) Rough concept analysis, rough sets, fuzzy sets knowledge discovery. In: Ziarko WP, Alta B (eds) Proceeding of the international workshop on rough sets, knowledge, discovery. Springer, Canada, pp 248–255 Kumar R (1993) Fuzzy algebra I. Publ. Division, University of Delhi Kuroki N (1997) Rough ideals in semigroups. Inform Sci 100:139–163 Lin TY, Cercone N (1997) Rough sets and data mining. Kluwer, Netherlands Loslever P, Lepoutre FX (2004) Analysis of objective and subjective data using fuzzy coding and multiple correspondence analysis: principle and example in a sitting posture study. Theor Issues Ergon Sci 5:425–443 Munakata Y (1998) Fundamentals of the new artificial intelligence: beyond traditional paradigms. Springer, New York, USA Narli S (in press) An alternative evaluation method for Likert type attitude scales: rough set data analysis. Sci Res Essays 5 Narli S, Ozcelik A (2008) On generalizing rough set theory via using a fitler. Int J Comput Math Sci 2–3:149–152 Nings S, Ziarko WP, Hamilton J, Cercone N (1995) Using rough sets as tools for knowledge discovery. In: Fayyad UM, Uthurusamy R (eds) KDD’95 Proceedings first international conference on knowledge discovery data mining. AAAI, Montreal, Canada, pp 263–268 Novotny J, Novotny M (1992) Notes on the algebraic approach to dependence in information systems. Fundamenta Informaticae 16:263–273 Pawlak Z (1982) Rough sets. Int J Comput Inf Sci 11:341–356 Pawlak Z (1991) Rough sets-theoretical aspect of reasoning about data. Kluwer, Dordrecht, Netherlands Pawlak Z (1995) Vagueness and uncertainty: a rough set perspective. Comput Intell 11:277–282 Pawlak Z (1997) Sets, fuzzy sets and rough sets. http://grammars.grlmc.com/GRLMC/reports/rep29.doc. Accessed 15 February 2010 Pawlak Z (1998) Rough set theory and its applications to data analysis. Cybern Syst Int J 29:661–688 Pawlak Z, Grzymala-Busse J, Slowinski R, Ziarko W (1995) Rough sets. Commun ACM 38:89–95 Polkowski L, Skowron A (1998a) Rough sets in knowledge discovery (vols. 1–2). In: Kacprzyk J (ed) Studies in fuzziness and soft computing series. Physica-Verlag/Springer-Verlag, Heidelberg Polkowski L, Skowron A (1998b) Rough sets and current trends in computing. In: Goebel R, Siekmann J, Wahlster W (eds) Lecture notes in artificial intelligence series. Springer, Heidelberg Pomykala J, Pomykala JA (1988) The stone algebra of rough sets, Bull. Polish Acad Sci Math 36:495–508 Shepardson DP (2005) Student ideas: what is an environment? J Environ Educ 36:49–58 Stefanutti L (2008) A characterization of the concept of independence in knowledge structures. J Math Psychol 52:207–217 Tarski A (1930) Fundamentale begriffe der methodologie der deduktiven wissenschaften. Monatshefte fur Mathematik und Physik 37:361–404 Tunnicliffe SD, Reiss MJ (1999) Building a model: how do children see animals? J Biol Educ 33:142–148 Tunnicliffe SD, Reiss MJ (2000) Building a model: how do children see plants? J Biol Educ 34:172–177 Weiten W (1997) Psychology: themes and variations. Brooks/Cole Publishing, CA Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I (ed) Ordered sets. Reidel, Dordrecht, pp 445–470 Yorek N, Narli S (2009) Modeling of cognitive structure of uncertain scientific concepts using fuzzy-rough set and intuitionistic fuzzy sets: example of the life concept. Int J Uncertain Fuzziness Knowl Based Syst 17(5):371–380 Yorek N, Sahin M, Aydin H (2009) Are animals ‘more alive’ than plants? animistic-anthropocentric construction of life concept. Eurasia J Math Sci Technol Educ 5(4):369–378 Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353 Zhong N, Skowron A (2000) Rough sets in KDD: tutorial notes. Bull Int Rough Set Soc 4(1/2)