El rol de la metacognición en el efecto de la memoria de trabajo sobre la capacidad mental del estudiante para resolver problemas matemáticos
El rol de la metacognición en el efecto de la memoria de trabajo sobre la capacidad mental del estudiante para resolver problemas matemáticos
Contenido principal del artículo
Resumen
El principal objetivo de este estudio era investigar los efectos de la capacidad de memoria en el Trabajo (CMT) en los estudiantes, y la forma de resolver los ejercicios matemáticos planteados, mientras se consideraban diferentes factores psicológicos. En una muestra de 256 estudiantes mujeres entre los desde Teherán 17 y 18 años fueron evaluadas en a) Inventario conciencia meta cognitiva (ICM), (b) Prueba de atención Matemáticas (PAM), (c) Escala de ansiedad ante mas matemáticas (EAAM), (d) Prueba “Digit Span Backward”, y (e) un examen de Matemáticas. Los datos del presente estudio se analizaron mediante estadística descriptiva e inferencial de T-test y correlación de Spearman con el Paquete Estadístico para las Ciencias Sociales (SPSS). Los resultados indicaron que la meta cognición tiene distintivos y distintas variables desafiantes que otros factores usados en el WMC en la resolución de problemas matemáticos. En otras palabras, la superioridad correlación entre WMC y el rendimiento matemático se encontró en el grupo de alta metacognición. Además, en cada grupo de baja/ alta metacognición, atención alta/ baja de matemáticas, y bajo altos niveles de ansiedad/ matemáticas, los estudiantes con alta WMC mostraron mejor rendimiento matemático de los bajos de WMC. Los resultados del estudio son adecuados para los investigadores que estén interesados en los diferentes factores que influyen en los problemas matemáticos que los estudiantes resuelven.
Citas
Adams, J.W. & Hitch, G.J. (1998). Children’s mental arithmetic and working memory. In C. Donlan (Ed.), The development of mathematical skills. Hove: Psychology Press.
Airasian, W. & Miranda, H. (2002). The role of assessment in The Revised Taxonomy. Theory into practice, 41(4), 249-254. ERIC EJ667161.
Alamolhodaei, H. (2009). A Working Memory Model Applied to Mathematical word Problem Solving. Asia Pac. Educ. Rev., 10(1),183-192.
Alamolhodaei, H. (2002). Students’ cognitive style and mathematical problem solving. Journal of the Korea Society of Mathematical Education Series D: Research in Mathematical Education, 6(1), 171-182.
Alamolhodaei, H. & Farsad, N. (2009). A Psychological Model Applied to Mathematical Problem Solving. Journal of the Korea Society of Mathematical Education Series D: Research in Mathematical Education, 13(3), 181-195.
Alamolhodaei, H., Farsad, N. & Radmehr, F. (2011). On the capacity of mathematics Attention: It's role on metacognition, math attitude, Field-dependency and mathematical problem solving. Educational Psychology. Under review.
Alloway, T.P., Gathercole, S.E., Holmes, J., Place, M. & Elliott, J. (2009). The diagnostic utility of behavioral checklists in identifying children with ADHD and children with working memory deficits. Child Psychiatry & Human Development, 40, 353-366.
Amani, A., Alamolhodaei, A. & Radmehr, F. (2011). A gender study on predictive factors of mathematical performance of University students. Educational Research, 2(6), 11791192.
Amer, A. (2006). Reflections on Bloom’s Revised Taxonomy. Electronic Journal of Research in Educational Psychology, 4(1), 213-230. ERIC EJ804068.
Anderson, L., Krathwohl, R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., Raths, J. & Wittrock, M. (2001). Taxonomy for learning, Teaching, and Assessing: A Revision of
Bloom’s Taxonomy. New York, NY: Longman.
Ashcraft, M.H. & Kirk, E.P. (2001).The relationships among working memory, math anxiety and performance. Journal of Experimental Psychology: General, 130(2), 224-237.
Bloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H. & Krathwohl, D.R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook 1: Cognitive domain. New York: David McKay.
Baddeley, A.D. (1986). Working memory. Oxford: Oxford University Press.
Baddeley, A.D. (1990). Human memory: Theory and practice. Hove, UK: Lawrence Erlbaum Associates Ltd.
Balo?lu, M. & Koçak, R. (2006).A multivariate investigation of the differences in mathematics anxiety. Personality and Individual Differences, 40(7), 1325-1335.
Branca, N. (1980). Problem solving as a goal, process and basic skill. In S. Krulik & R. Reys (Eds.), Problem solving in school mathematics 1980 yearbook (pp. 3-8). Reston, VA: NCTM.
Buxton, L. (1981). Do you panic about maths? London: Heinemann.
Cakan, M. (2000). Interaction between cognitive styles and assessment approaches. Unpublished doctoral dissertation, Louisiana State University, USA. Baton Rouge.
Collings, J.N. (1985). Scientific thinking through the development of formal operations: Training in the cognitive restructuring aspect of field-independence. Research in Science & Technological Education, 3, 145-152. doi:10.1080/0263514850030107.
DeBellis, V.A. & Goldin, G.A. (2006). Affect and meta-affect in mathematical problem solving: A representational perspective. Educ. Stud. Math., 63(2), 131-147.
Di Martino, P. & Zan, R. (2011). Attitude towards mathematics: a bridge between beliefs and emotions. ZDM Mathematics Education, 43, 471-482. DOI 10.1007/s11858-011-0309-6.
Ellis, H. & Hunt, R. (1993) Fundamentals of Cognitive Psychology, Fifth Edition. Brown & Benchmark, Dubuque, USA.
Fardin, D., Alamolhodaei, H. & Radmehr, F. (2011). A Meta -Analyze On Mathematical Beliefs and Mathematical Performance of Iranian Students. Educ. Res., 2(4), 1051-1058.
Gierl, M.J. & Bisanz, J. (1994). Anxieties and attitudes related to mathematics in grade 3 and 6. Journal of Experimental Education, 63(2), 139-158.
Grootenboer, P.J. (2003). The affective views of primary school children. In N.A. Pateman, B.J. Dougherty & J. Zilliox (Eds.), Navigating between theory and practice (Proceedings of the 27th conference of the International Group for the Psychology of Mathematics Education, Vol. 3, pp. 1-8). Honolulu, HI: PME.
Hassi, M.L. & Laursen, S. (2009). Studying undergraduate mathematics: exploring students’ beliefs, experiences and gains. Proceedings of the Thirty First Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, 5, 113-121.
Hembree, R. (1990). The nature, effects and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21(1), 33-46.
Holmes, G. & Adams, J.W. (2006). Working memory and Children’s Mathematical skills: Implications for mathematical development and mathematics Curricula. Educ. Psychol., 26(3), 339-366.
Javris, H.L. & Gathercole, S.E. (2003). Verbal and nonverbal working memory and achievements on national curriculum tests at 7 and 14 years of age. Educ. Child Psychol., 20, 123-140.
Johnstone, A.H. (1984). New stars for the teacher steer by. Journal of Chemical Education, 61(10), 847-849.
Johnstone, A.H. & Al-Naeme, F.F. (1991). Room for scientific thought. International Journal of Science Education, 13(2), 187-192. doi:10.1080/0950069910130205.
Johnstone, A.H. & Al-Naeme, F.F. (1995). Filling a curriculum gap in chemistry. International Journal of Science Education, 17(2), 219-232.
Kirkley, J. (2003). Principles for Teaching Problem Solving. Bloomington, MN: Plato Learning.
www.plato.com/media/Technical-White%20Papers/2/Principles%20for%20Teaching%20Problem%20Solving.pdf
Kramarski, B., Weisse, I. & Kololshi-Minsker, I. (2010). How can self-regulated learning support the problem solving of third-grade students with mathematics anxiety? ZDM Mathematics Education, 42,179-193.
Krathwohl, D. (2002). A Revision of Bloom’s Taxonomy: An Overview. Theory into Practice, 41(4), 212-218. ERIC EJ667155.
Kreitzer, A. & Madaus, G. (1994). Empirical Investigations of the Hierarchical Structure of the Taxonomy. In L. Anderson and L. Sosniak (Eds.), Bloom’s Taxonomy: A Forty year Retrospective (pp. 64-81). Chicago, IL: National Society for the Study of Education.
Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30(5), 520-540.
Ma, X. & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal for Research in Mathematics Education, 28(1), 26-47.
Maloney, E.A., Risko, E.F., Ansari, D & Fugelsang, J. (2010). Mathematics anxiety affects counting but not subitizing during visual enumeration. Cognition 114, 293-297.
Malmivuori, M.L. (2001). The dynamics of affect, cognition, and social environment in the regulation of personal learning processes: The case of mathematics. Research Report 172, University of Helsinki.
McLeod, D.B. (1992). Research on affect in mathematics education: A reconceptualization. In D.G. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). New York: McMillan Library Reference.
McLeod, D.B. (1993). Research on affect in mathematics education: A reconceptualisation. In D.A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). London: Macmillan.
Meelissen, M. & Luyten, H. (2008).The Dutch gender gap in mathematics: Small for achievement, substantial for beliefs and attitudes. Studies in Educational Evaluation, 34, 82-93.
Miyake, A. & Shah, P. (1999). Models of working memory: Mechanisms of active maintenance and executive control. Cambridge, UK: Cambridge University Press.
Mousavi, S., Radmehr, F. & Alamolhodaei, H. (2012). The role of mathematical homework and prior knowledge on the relationship between students’ mathematical performance, cognitive style and working memory capacity. Electronic Journal of Research in Educational Psychology, 10(3), 1223-1248.
Murphy, H.J., Casey, B., Day, D.A. & Young, J.D. (1997). Scores on the Group Embedded Figures Test by undergraduates in information management. Perceptual and Motor Skills, 84, 1135-1138.
National Council of Teachers of Mathematics (NCTM) (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics (NCTM) (1991). Professional Standards for Teaching Mathematics.National Council of Teachers of Mathematics, Reston, VA. ME 1991e.00332 ERIC ED344779.
National Council of Teachers of Mathematics (NCTM) (2000). Principles and Standards for School Mathematics. Reston, VA: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics (2003). Problem solving [online]. Retrieve d June 20, 2003, from http://standards.nctm.org/document/ chapter3/prob.htm.
Niaz, M. & Logie, R.H. (1993).Working memory, mental capacity, and science education: Towards an understanding of the working memory overloud hypothesis. Oxford Review of Education, 19, 511-525. doi:10.1080/0305498930190407.
Niaz, M. (1996). Reasoning strategies of student in solving chemistry problems as a function of development level, functional M-capacity and disembedding ability. International Journal of Science Education, 18(5), 525-541. doi:10.1080/0950069960180503.
Pezeshki, P., Alamolhodaei, H. & Radmehr, F. (2011). A predictive model for mathematical performance of blind and seeing students. Educ.Res., 2(2), 864-873.
Pintrich, P.R. (2002). The Role of Metacognitive Knowledge in Learning, Teaching, and Assessing. Theory into Practice, 41(4), 219-225.
Polya, G. (1949). On solving mathematical problems in high school. In S. Krulik & R.E. Reys (Eds.), Problem solving in school mathematics 1980 yearbook (pp. 1-2). Reston, VA: National Council of Teachers of Mathematics.
Radmehr, F. & Alamolhodaei, H. (2010). A Study on the Performance of Students’ Mathematical Problem Solving Based On Cognitive Process of Revised Bloom Taxonomy. Journal of the Korea Society of Mathematical Education Series D: Research In Mathematical Education, 14(4), 381-403.
Radmehr, F. & Alamolhodaei, H. (2012). Revised Bloom Taxonomy and its application for mathematics teaching, learning and curriculum development. Journal of Curriculum Studies, 6(24), 183-202.
Raghubar, K.P., Barnes, M.A. & Hecht, S.A. (2010).Working memory and mathematics: A review of developmental, individual difference, and cognitive approaches. Learning and Individual Differences, 20, 110-122.
Ribaupierre, A. & Hitch, G.J. (1994). The development of working memory. Hove: Lawrence Erlbaum Associates.
Richardson, F.C. & Suinn, R.M. (1972). The Mathematics Anxiety Rating Scale. Journal of Counseling Psychology, 19(6), 551-554.
Saha, S. (2007). A study of Gender Attitude to Mathematics, Cognitive style and Achievement in mathematics. Experiments in Education, 35, 61-67.
Saracho, O.N. (1998). Editor’s introduction cognitive style research and its relationship to various disciplines. International Journal of Educational Research, 29, 169-172. doi:10.1016/S08830355(98)00022-6.
Schweizer, K. & Moosbrugger, H. (2004). Attention and Working Memory as Predictors of Intelligence. Intelligence, 32, 329-347.
Sherman, B.F. & Wither, D.P. (2003). Mathematics anxiety and mathematics achievement. Mathematics Education Research Journal, 15(2), 138-150.
Smith, G., Wood, L., Coupland, M. & Stephen, B. (1996). Constructing mathematical examination to assess a range of knowledge and skills. Int. J. Math. Educ. Sci. Technol., 21(1), 65-77.
Stodolsky, S.S. (1985). Telling math: Origins of math aversion and anxiety. Educational Psychologist, 20(2), 125-133.
Tannock, R. (2008). Paying attention to inattention. Paper presented at the Harvard Learning Differences Conference.
Thomas, J. (2006). The effects on student’s achievements and attitudes using integrated learning systems with co-operative pairs. Journal Educational Technology Research and Development, 45, 51-64.
Witkin, H.A., Moore, C.A., Goodenough, D.R. & Cox, P.W. (1977). Field-dependent and fieldindependent cognitive styles and their educational implications. Review of Educational Research, 47(1), 1-64.
Witkin, H.A. & Goodenough, D.R. (1981). Cognitive styles: Essence and origins, NY: International University Press.
Wilkins, J.L.M. & Ma, X. (2003). Modeling change in student attitude toward and beliefs about mathematics. The Journal of Educational Research, 97(1), 52-63.
Witkin, H.A., Oltman, P., Raskin, E. & Karp, S. (1971). A manual for the embedded figures test. Palo Alto, CA: Consulting Psychologists Press.
Airasian, W. & Miranda, H. (2002). The role of assessment in The Revised Taxonomy. Theory into practice, 41(4), 249-254. ERIC EJ667161.
Alamolhodaei, H. (2009). A Working Memory Model Applied to Mathematical word Problem Solving. Asia Pac. Educ. Rev., 10(1),183-192.
Alamolhodaei, H. (2002). Students’ cognitive style and mathematical problem solving. Journal of the Korea Society of Mathematical Education Series D: Research in Mathematical Education, 6(1), 171-182.
Alamolhodaei, H. & Farsad, N. (2009). A Psychological Model Applied to Mathematical Problem Solving. Journal of the Korea Society of Mathematical Education Series D: Research in Mathematical Education, 13(3), 181-195.
Alamolhodaei, H., Farsad, N. & Radmehr, F. (2011). On the capacity of mathematics Attention: It's role on metacognition, math attitude, Field-dependency and mathematical problem solving. Educational Psychology. Under review.
Alloway, T.P., Gathercole, S.E., Holmes, J., Place, M. & Elliott, J. (2009). The diagnostic utility of behavioral checklists in identifying children with ADHD and children with working memory deficits. Child Psychiatry & Human Development, 40, 353-366.
Amani, A., Alamolhodaei, A. & Radmehr, F. (2011). A gender study on predictive factors of mathematical performance of University students. Educational Research, 2(6), 11791192.
Amer, A. (2006). Reflections on Bloom’s Revised Taxonomy. Electronic Journal of Research in Educational Psychology, 4(1), 213-230. ERIC EJ804068.
Anderson, L., Krathwohl, R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., Raths, J. & Wittrock, M. (2001). Taxonomy for learning, Teaching, and Assessing: A Revision of
Bloom’s Taxonomy. New York, NY: Longman.
Ashcraft, M.H. & Kirk, E.P. (2001).The relationships among working memory, math anxiety and performance. Journal of Experimental Psychology: General, 130(2), 224-237.
Bloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H. & Krathwohl, D.R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook 1: Cognitive domain. New York: David McKay.
Baddeley, A.D. (1986). Working memory. Oxford: Oxford University Press.
Baddeley, A.D. (1990). Human memory: Theory and practice. Hove, UK: Lawrence Erlbaum Associates Ltd.
Balo?lu, M. & Koçak, R. (2006).A multivariate investigation of the differences in mathematics anxiety. Personality and Individual Differences, 40(7), 1325-1335.
Branca, N. (1980). Problem solving as a goal, process and basic skill. In S. Krulik & R. Reys (Eds.), Problem solving in school mathematics 1980 yearbook (pp. 3-8). Reston, VA: NCTM.
Buxton, L. (1981). Do you panic about maths? London: Heinemann.
Cakan, M. (2000). Interaction between cognitive styles and assessment approaches. Unpublished doctoral dissertation, Louisiana State University, USA. Baton Rouge.
Collings, J.N. (1985). Scientific thinking through the development of formal operations: Training in the cognitive restructuring aspect of field-independence. Research in Science & Technological Education, 3, 145-152. doi:10.1080/0263514850030107.
DeBellis, V.A. & Goldin, G.A. (2006). Affect and meta-affect in mathematical problem solving: A representational perspective. Educ. Stud. Math., 63(2), 131-147.
Di Martino, P. & Zan, R. (2011). Attitude towards mathematics: a bridge between beliefs and emotions. ZDM Mathematics Education, 43, 471-482. DOI 10.1007/s11858-011-0309-6.
Ellis, H. & Hunt, R. (1993) Fundamentals of Cognitive Psychology, Fifth Edition. Brown & Benchmark, Dubuque, USA.
Fardin, D., Alamolhodaei, H. & Radmehr, F. (2011). A Meta -Analyze On Mathematical Beliefs and Mathematical Performance of Iranian Students. Educ. Res., 2(4), 1051-1058.
Gierl, M.J. & Bisanz, J. (1994). Anxieties and attitudes related to mathematics in grade 3 and 6. Journal of Experimental Education, 63(2), 139-158.
Grootenboer, P.J. (2003). The affective views of primary school children. In N.A. Pateman, B.J. Dougherty & J. Zilliox (Eds.), Navigating between theory and practice (Proceedings of the 27th conference of the International Group for the Psychology of Mathematics Education, Vol. 3, pp. 1-8). Honolulu, HI: PME.
Hassi, M.L. & Laursen, S. (2009). Studying undergraduate mathematics: exploring students’ beliefs, experiences and gains. Proceedings of the Thirty First Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, 5, 113-121.
Hembree, R. (1990). The nature, effects and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21(1), 33-46.
Holmes, G. & Adams, J.W. (2006). Working memory and Children’s Mathematical skills: Implications for mathematical development and mathematics Curricula. Educ. Psychol., 26(3), 339-366.
Javris, H.L. & Gathercole, S.E. (2003). Verbal and nonverbal working memory and achievements on national curriculum tests at 7 and 14 years of age. Educ. Child Psychol., 20, 123-140.
Johnstone, A.H. (1984). New stars for the teacher steer by. Journal of Chemical Education, 61(10), 847-849.
Johnstone, A.H. & Al-Naeme, F.F. (1991). Room for scientific thought. International Journal of Science Education, 13(2), 187-192. doi:10.1080/0950069910130205.
Johnstone, A.H. & Al-Naeme, F.F. (1995). Filling a curriculum gap in chemistry. International Journal of Science Education, 17(2), 219-232.
Kirkley, J. (2003). Principles for Teaching Problem Solving. Bloomington, MN: Plato Learning.
www.plato.com/media/Technical-White%20Papers/2/Principles%20for%20Teaching%20Problem%20Solving.pdf
Kramarski, B., Weisse, I. & Kololshi-Minsker, I. (2010). How can self-regulated learning support the problem solving of third-grade students with mathematics anxiety? ZDM Mathematics Education, 42,179-193.
Krathwohl, D. (2002). A Revision of Bloom’s Taxonomy: An Overview. Theory into Practice, 41(4), 212-218. ERIC EJ667155.
Kreitzer, A. & Madaus, G. (1994). Empirical Investigations of the Hierarchical Structure of the Taxonomy. In L. Anderson and L. Sosniak (Eds.), Bloom’s Taxonomy: A Forty year Retrospective (pp. 64-81). Chicago, IL: National Society for the Study of Education.
Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30(5), 520-540.
Ma, X. & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal for Research in Mathematics Education, 28(1), 26-47.
Maloney, E.A., Risko, E.F., Ansari, D & Fugelsang, J. (2010). Mathematics anxiety affects counting but not subitizing during visual enumeration. Cognition 114, 293-297.
Malmivuori, M.L. (2001). The dynamics of affect, cognition, and social environment in the regulation of personal learning processes: The case of mathematics. Research Report 172, University of Helsinki.
McLeod, D.B. (1992). Research on affect in mathematics education: A reconceptualization. In D.G. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). New York: McMillan Library Reference.
McLeod, D.B. (1993). Research on affect in mathematics education: A reconceptualisation. In D.A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). London: Macmillan.
Meelissen, M. & Luyten, H. (2008).The Dutch gender gap in mathematics: Small for achievement, substantial for beliefs and attitudes. Studies in Educational Evaluation, 34, 82-93.
Miyake, A. & Shah, P. (1999). Models of working memory: Mechanisms of active maintenance and executive control. Cambridge, UK: Cambridge University Press.
Mousavi, S., Radmehr, F. & Alamolhodaei, H. (2012). The role of mathematical homework and prior knowledge on the relationship between students’ mathematical performance, cognitive style and working memory capacity. Electronic Journal of Research in Educational Psychology, 10(3), 1223-1248.
Murphy, H.J., Casey, B., Day, D.A. & Young, J.D. (1997). Scores on the Group Embedded Figures Test by undergraduates in information management. Perceptual and Motor Skills, 84, 1135-1138.
National Council of Teachers of Mathematics (NCTM) (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics (NCTM) (1991). Professional Standards for Teaching Mathematics.National Council of Teachers of Mathematics, Reston, VA. ME 1991e.00332 ERIC ED344779.
National Council of Teachers of Mathematics (NCTM) (2000). Principles and Standards for School Mathematics. Reston, VA: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics (2003). Problem solving [online]. Retrieve d June 20, 2003, from http://standards.nctm.org/document/ chapter3/prob.htm.
Niaz, M. & Logie, R.H. (1993).Working memory, mental capacity, and science education: Towards an understanding of the working memory overloud hypothesis. Oxford Review of Education, 19, 511-525. doi:10.1080/0305498930190407.
Niaz, M. (1996). Reasoning strategies of student in solving chemistry problems as a function of development level, functional M-capacity and disembedding ability. International Journal of Science Education, 18(5), 525-541. doi:10.1080/0950069960180503.
Pezeshki, P., Alamolhodaei, H. & Radmehr, F. (2011). A predictive model for mathematical performance of blind and seeing students. Educ.Res., 2(2), 864-873.
Pintrich, P.R. (2002). The Role of Metacognitive Knowledge in Learning, Teaching, and Assessing. Theory into Practice, 41(4), 219-225.
Polya, G. (1949). On solving mathematical problems in high school. In S. Krulik & R.E. Reys (Eds.), Problem solving in school mathematics 1980 yearbook (pp. 1-2). Reston, VA: National Council of Teachers of Mathematics.
Radmehr, F. & Alamolhodaei, H. (2010). A Study on the Performance of Students’ Mathematical Problem Solving Based On Cognitive Process of Revised Bloom Taxonomy. Journal of the Korea Society of Mathematical Education Series D: Research In Mathematical Education, 14(4), 381-403.
Radmehr, F. & Alamolhodaei, H. (2012). Revised Bloom Taxonomy and its application for mathematics teaching, learning and curriculum development. Journal of Curriculum Studies, 6(24), 183-202.
Raghubar, K.P., Barnes, M.A. & Hecht, S.A. (2010).Working memory and mathematics: A review of developmental, individual difference, and cognitive approaches. Learning and Individual Differences, 20, 110-122.
Ribaupierre, A. & Hitch, G.J. (1994). The development of working memory. Hove: Lawrence Erlbaum Associates.
Richardson, F.C. & Suinn, R.M. (1972). The Mathematics Anxiety Rating Scale. Journal of Counseling Psychology, 19(6), 551-554.
Saha, S. (2007). A study of Gender Attitude to Mathematics, Cognitive style and Achievement in mathematics. Experiments in Education, 35, 61-67.
Saracho, O.N. (1998). Editor’s introduction cognitive style research and its relationship to various disciplines. International Journal of Educational Research, 29, 169-172. doi:10.1016/S08830355(98)00022-6.
Schweizer, K. & Moosbrugger, H. (2004). Attention and Working Memory as Predictors of Intelligence. Intelligence, 32, 329-347.
Sherman, B.F. & Wither, D.P. (2003). Mathematics anxiety and mathematics achievement. Mathematics Education Research Journal, 15(2), 138-150.
Smith, G., Wood, L., Coupland, M. & Stephen, B. (1996). Constructing mathematical examination to assess a range of knowledge and skills. Int. J. Math. Educ. Sci. Technol., 21(1), 65-77.
Stodolsky, S.S. (1985). Telling math: Origins of math aversion and anxiety. Educational Psychologist, 20(2), 125-133.
Tannock, R. (2008). Paying attention to inattention. Paper presented at the Harvard Learning Differences Conference.
Thomas, J. (2006). The effects on student’s achievements and attitudes using integrated learning systems with co-operative pairs. Journal Educational Technology Research and Development, 45, 51-64.
Witkin, H.A., Moore, C.A., Goodenough, D.R. & Cox, P.W. (1977). Field-dependent and fieldindependent cognitive styles and their educational implications. Review of Educational Research, 47(1), 1-64.
Witkin, H.A. & Goodenough, D.R. (1981). Cognitive styles: Essence and origins, NY: International University Press.
Wilkins, J.L.M. & Ma, X. (2003). Modeling change in student attitude toward and beliefs about mathematics. The Journal of Educational Research, 97(1), 52-63.
Witkin, H.A., Oltman, P., Raskin, E. & Karp, S. (1971). A manual for the embedded figures test. Palo Alto, CA: Consulting Psychologists Press.