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    政大機構典藏 > 理學院 > 心理學系 > 學位論文 >  Item 140.119/128862
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/128862


    Title: 以功能性磁振造影探討算術應用題解題之大腦機制
    An fMRI investigation of brain mechanisms underlying arithmetic word problem solving
    Authors: 伍贊達
    Ng, Chan-Tat
    Contributors: 張葶葶
    Chang, Ting-Ting
    伍贊達
    Ng, Chan-Tat
    Keywords: 應用題
    功能性磁振造影
    數學認知
    閱讀理解
    數學學習
    認知控制
    額頂網絡
    一致效應
    Word problems
    fMRI
    Mathematical cognition
    Text comprehension
    Mathematical learning
    Cognitive control
    Fronto-parietal network
    Consistency effect
    Date: 2020
    Issue Date: 2020-03-02 11:13:58 (UTC+8)
    Abstract: The practice of arithmetic word problems serves to generalize mathematical concepts into real-world settings, but the word problem performances of both children and adults are far from satisfactory. Despite the extensive research on behavioral and cognitive components of arithmetic word problem solving, the underlying neural mechanisms are poorly understood. This current thesis aims to tackle the issue by investigating brain responses towards word problem solving using fMRI. In Study 1, we compared arithmetic word problems and nonarithmetic narrative problems with no numerical manipulation so that we should be allowed to study the specific role of numerical processing embedded within a narrative structure. Results showed that the processing of word problems should be distinct from text comprehension, as the former involved more in the frontal-insular-parietal areas whereas the latter was more strongly engaged in the canonical language system. In Study 2, to investigate how linguistic factors modulate numerical processing during word problem solving, we examined solutions of compare word problems, and each problem includes a relational term comparing the values of two parameters (e.g. dumpling costs 2 dollars more than wonton). Results revealed a consistency by operation interaction in the fronto-insular-parietal network. Specifically, mathematical models requiring subtraction engaged stronger activations than addition during consistent problem solving (in which the relational term was consistent with the required arithmetic operation, e.g., “more than” - addition), whereas the neural activation pattern of the operation effect for inconsistent problems was opposite to that for consistent problems. These findings further indicated that relations between the linguistic and numerical factors were interactive in word problems. In Study 3, we conducted the experiment of Study 2 on children from Grade 3 to Grade 6 to investigate developmental changes in word problem solving. Results suggested greater involvement of the network of inhibitory control in children for inconsistent than consistent problems. Furthermore, the interaction between consistency and operation was observed only in adults but not children, emphasizing that the interaction observed between linguistic and numerical factors could be a learned effect. To sum up, the current thesis examines the underlying brain mechanisms of word problem solving. We demonstrate that word problem solving is more dependent on the cognitive control system than semantic processing, probably due to the need for deriving mathematical problem models from the text. Also, we stress the important roles of interactive effects between different factors in word problems rather than separate components alone, as numerical processing is possibly altered by the problem description. More importantly, we have demonstrated age-group differences in these effects, revealing critical developmental changes in word problem solving. By uncovering brain mechanisms of this school curriculum practice, we potentially provide foundations for deficit remediation and pedagogical improvement.
    Reference: Abedi, J., Lord, C., & Plummer, J. (1997). Final Report of Language Background as a Variable in NAEP Mathematics Performance. Retrieved from https://cresst.org/wp-content/uploads/TECH429.pdf
    Academia Sinica. (2010). Academia Sinica Balanced Corpus of Modern Chinese. Retrieved from http://asbc.iis.sinica.edu.tw/
    Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press.
    Amalric, M., & Dehaene, S. (2018). Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain`s semantic networks. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1740), 20160515. doi:10.1098/rstb.2016.0515
    Amalric, M., & Dehaene, S. (2019). A distinct cortical network for mathematical knowledge in the human brain. Neuroimage, 189, 19-31. doi:10.1016/j.neuroimage.2019.01.001
    Ansari, D., Dhital, B., & Siong, S. C. (2006). Parametric effects of numerical distance on the intraparietal sulcus during passive viewing of rapid numerosity changes. Brain Research, 1067(1), 181-188. doi:10.1016/j.brainres.2005.10.083
    Arsalidou, M., Pawliw-Levac, M., Sadeghi, M., & Pascual-Leone, J. (2018). Brain areas associated with numbers and calculations in children: Meta-analyses of fMRI studies. Developmental Cognitive Neuroscience, 30, 239-250. doi:10.1016/j.dcn.2017.08.002
    Ashcraft, M. H. (1982). The development of mental arithmetic: A chronometric approach. Developmental Review, 2(3), 213-236. doi:10.1016/0273-2297(82)90012-0
    Ashcraft, M. H. (1995). Cognitive psychology and simple arithmetic: A review and summary of new directions. Mathematical Cognition, 1, 3-34.
    Austin, J. D., & Lee, M. A. B. (1982). Readability and mathematics text item difficulty. School Science and Mathematics, 82, 284-290.
    Barbey, A. K., Koenigs, M., & Grafman, J. (2013). Dorsolateral prefrontal contributions to human working memory. Cortex, 49(5), 1195-1205. doi:10.1016/j.cortex.2012.05.022
    Barrouillet, P., Mignon, M., & Thevenot, C. (2008). Strategies in subtraction problem solving in children. Journal of Experimental Child Psychology, 99(4), 233-251. doi:10.1016/j.jecp.2007.12.001
    Barrouillet, P., & Thevenot, C. (2013). On the problem-size effect in small additions: Can we really discard any counting-based account? Cognition, 128(1), 35-44. doi:10.1016/j.cognition.2013.02.018
    Bassok, M., Chase, V. M., & Martin, S. A. (1998). Adding Apples and Oranges: Alignment of Semantic and Formal Knowledge. Cognitive Psychology, 35(2), 99-134. doi:10.1006/cogp.1998.0675
    Bernardo, A. B. I. (1999). Overcoming Obstacles to Understanding and Solving Word Problems in Mathematics. Educational Psychology, 19(2), 149-163. doi:10.1080/0144341990190203
    Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 2767-2796. doi:10.1093/cercor/bhp055
    Björn, P. M., Aunola, K., & Nurmi, J.-E. (2016). Primary school text comprehension predicts mathematical word problem-solving skills in secondary school. Educational Psychology, 36(2), 362-377. doi:10.1080/01443410.2014.992392
    Boonen, A. J. H., de Koning, B. B., Jolles, J., & van der Schoot, M. (2016). Word Problem Solving in Contemporary Math Education: A Plea for Reading Comprehension Skills Training. Frontiers in Psychology, 7(191). doi:10.3389/fpsyg.2016.00191
    Bressler, S. L., & Menon, V. (2010). Large-scale brain networks in cognition: emerging methods and principles. Trends in Cognitive Sciences, 14(6), 277-290. doi:10.1016/j.tics.2010.04.004
    Cai, W., Chen, T., Ryali, S., Kochalka, J., Li, C. S., & Menon, V. (2016). Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation. Cerebral Cortex, 26(5), 2140-2153. doi:10.1093/cercor/bhv046
    Campbell, J. I. D. (2008). Subtraction by addition. Memory & Cognition, 36(6), 1094-1102. doi:10.3758/mc.36.6.1094
    Campbell, J. I. D., & Timm, J. C. (2000). Adults’ strategy choices for simple addition: Effects of retrieval interference. Psychonomic Bulletin & Review, 7(4), 692-699. doi:10.3758/BF03213008
    Cantlon, J. F., Brannon, E. M., Carter, E. J., & Pelphrey, K. A. (2006). Functional imaging of numerical processing in adults and 4-y-old children. PLoS Biology, 4(5), e125. doi:10.1371/journal.pbio.0040125
    Carpentier, A., Pugh, K. R., Westerveld, M., Studholme, C., Skrinjar, O., Thompson, J. L., . . . Constable, R. T. (2001). Functional MRI of Language Processing: Dependence on Input Modality and Temporal Lobe Epilepsy. Epilepsia, 42(10), 1241-1254. doi:10.1046/j.1528-1157.2001.35500.x
    Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: cytoarchitectonic parcellation and interindividual variability. Neuroimage, 33(2), 430-448. doi:10.1016/j.neuroimage.2006.06.054
    Chai, W. J., Abd Hamid, A. I., & Abdullah, J. M. (2018). Working Memory From the Psychological and Neurosciences Perspectives: A Review. Frontiers in Psychology, 9, 401-401. doi:10.3389/fpsyg.2018.00401
    Chang, T.-T., Lee, P.-H., & Metcalfe, A. W. S. (2018). Intrinsic insula network engagement underlying children`s reading and arithmetic skills. Neuroimage, 167, 162-177. doi:10.1016/j.neuroimage.2017.11.027
    Chang, T.-T., Metcalfe, A. W. S., Padmanabhan, A., Chen, T., & Menon, V. (2016). Heterogeneous and nonlinear development of human posterior parietal cortex function. Neuroimage, 126, 184-195. doi:10.1016/j.neuroimage.2015.11.053
    Chang, T.-T., Rosenberg-Lee, M., Metcalfe, A. W. S., Chen, T., & Menon, V. (2015). Development of common neural representations for distinct numerical problems. Neuropsychologia, 75, 481-495. doi:10.1016/j.neuropsychologia.2015.07.005
    Choi, H. J., Zilles, K., Mohlberg, H., Schleicher, A., Fink, G. R., Armstrong, E., & Amunts, K. (2006). Cytoarchitectonic identification and probabilistic mapping of two distinct areas within the anterior ventral bank of the human intraparietal sulcus. The Journal of Comparative Neurology, 495(1), 53-69. doi:10.1002/cne.20849
    Clark, H. H. (1969). Linguistic processes in deductive reasoning. Psychological Review, 76(4), 387-404. doi:10.1037/h0027578
    Cox, R. W. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29(3), 162-173.
    Cragg, L., & Gilmore, C. (2014). Skills underlying mathematics: The role of executive function in the development of mathematics proficiency. Trends in Neuroscience and Education, 3(2), 63-68. doi:10.1016/j.tine.2013.12.001
    Cummins, D. D. (1991). Children`s Interpretations of Arithmetic Word Problems. Cognition and Instruction, 8(3), 261-289. doi:10.1207/s1532690xci0803_2
    Cummins, D. D., Kintsch, W., Reusser, K., & Weimer, R. (1988). The role of understanding in solving word problems. Cognitive Psychology, 20(4), 405-438. doi:10.1016/0010-0285(88)90011-4
    Daroczy, G., Wolska, M., Meurers, W. D., & Nuerk, H.-C. (2015). Word problems: a review of linguistic and numerical factors contributing to their difficulty. Frontiers in Psychology, 6, 348. doi:10.3389/fpsyg.2015.00348
    Daselaar, S. M., Prince, S. E., & Cabeza, R. (2004). When less means more: deactivations during encoding that predict subsequent memory. Neuroimage, 23(3), 921-927. doi:10.1016/j.neuroimage.2004.07.031
    Davis, N., Cannistraci, C. J., Rogers, B. P., Gatenby, J. C., Fuchs, L. S., Anderson, A. W., & Gore, J. C. (2009). The neural correlates of calculation ability in children: an fMRI study. Magnetic Resonance Imaging, 27(9), 1187-1197. doi:10.1016/j.mri.2009.05.010
    De Corte, E., & Verschaffel, L. (1986). Eye-movement data as access to solution processes of elementary addition and subtraction problems. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco.
    De Corte, E., & Verschaffel, L. (1987). The Effect of Semantic Structure on First Graders` Strategies for Solving Addition and Subtraction Word Problems. Journal for Research in Mathematics Education, 18(5), 363-381. doi:10.2307/749085
    De Corte, E., Verschaffel, L., & Pauwels, A. (1990). Influence of the semantic structure of word problems on second graders` eye movements. Journal of Educational Psychology, 82(2), 359-365. doi:10.1037/0022-0663.82.2.359
    De Corte, E., Verschaffel, L., & Van Coillie, V. (1988). Influence of number size, problem structure, and response mode on children`s solutions of multiplication word problems. The Journal of Mathematical Behavior, 7, 197-216. Retrieved from https://files.eric.ed.gov/fulltext/ED295783.pdf
    De Smedt, B., Holloway, I. D., & Ansari, D. (2011). Effects of problem size and arithmetic operation on brain activation during calculation in children with varying levels of arithmetical fluency. Neuroimage, 57, 771-781. doi:10.1016/j.neuroimage.2010.12.037
    De Smedt, B., Torbeyns, J., Stassens, N., Ghesquière, P., & Verschaffel, L. (2010). Frequency, efficiency and flexibility of indirect addition in two learning environments. Learning and Instruction, 20(3), 205-215. doi:10.1016/j.learninstruc.2009.02.020
    Dee-Lucas, D., & Larkin, J. H. (1988). Novice rules for assessing importance in scientific texts. Journal of Memory and Language, 27(3), 288-308. doi:10.1016/0749-596X(88)90056-3
    Dee-Lucas, D., & Larkin, J. H. (1991). Equations in Scientific Proofs: Effects on Comprehension. American Educational Research Journal, 28(3), 661-682. doi:10.3102/00028312028003661
    Dehaene, S., Piazza, M., Pinel, P., & Cohen, L. (2003). Three parietal circuits for number processing. Cognitive Neuropsychology, 20, 487. doi:10.1080/02643290244000239
    Deschuyteneer, M., De Rammelaere, S., & Fias, W. (2005). The addition of two-digit numbers: Exploring carry versus no-carry problems. Psychology Science, 47(1), 74-83.
    DeStefano, D., & LeFevre, J. A. (2004). The role of working memory in mental arithmetic. European Journal of Cognitive Psychology, 16(3), 353-386. doi:10.1080/09541440244000328
    Devlin, J. T., Matthews, P. M., & Rushworth, M. F. S. (2003). Semantic Processing in the Left Inferior Prefrontal Cortex: A Combined Functional Magnetic Resonance Imaging and Transcranial Magnetic Stimulation Study. Journal of Cognitive Neuroscience, 15(1), 71-84. doi:10.1162/089892903321107837
    Diamond, A. (2013). Executive Functions. Annual Review of Psychology, 64(1), 135-168. doi:10.1146/annurev-psych-113011-143750
    Durston, S., Thomas, K. M., Yang, Y., Uluğ, A. M., Zimmerman, R. D., & Casey, B. J. (2002). A neural basis for the development of inhibitory control. Developmental Science, 5(4), F9-F16. doi:10.1111/1467-7687.00235
    Edin, F., Klingberg, T., Johansson, P., McNab, F., Tegnér, J., & Compte, A. (2009). Mechanism for top-down control of working memory capacity. Proceedings of the National Academy of Sciences, 106(16), 6802-6807. doi:10.1073/pnas.0901894106
    Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage, 25(4), 1325-1335. doi:10.1016/j.neuroimage.2004.12.034
    Emerson, R. W., & Cantlon, J. F. (2012). Early math achievement and functional connectivity in the fronto-parietal network. Developmental Cognitive Neuroscience, 2, S139-S151. doi:10.1016/j.dcn.2011.11.003
    Fayol, M., Abdi, H., & Gombert, J.-E. (1987). Arithmetic Problems Formulation and Working Memory Load. Cognition and Instruction, 4(3), 187-202. doi:10.1207/s1532690xci0403_3
    Fuchs, L. S., Compton, D. L., Fuchs, D., Powell, S. R., Schumacher, R. F., Hamlett, C. L., . . . Vukovic, R. K. (2012). Contributions of domain-general cognitive resources and different forms of arithmetic development to pre-algebraic knowledge. Developmental Psychology, 48(5), 1315-1326. doi:10.1037/a0027475
    Fuchs, L. S., Fuchs, D., Compton, D. L., Hamlett, C. L., & Wang, A. Y. (2015). Is Word-Problem Solving a Form of Text Comprehension? Scientific Studies of Reading, 19(3), 204-223. doi:10.1080/10888438.2015.1005745
    Fuchs, L. S., Powell, S. R., Cirino, P. T., Schumacher, R. F., Marrin, S., Hamlett, C. L., . . . Changas, P. C. (2014). Does Calculation or Word-Problem Instruction Provide A Stronger Route to Pre-Algebraic Knowledge? Journal of Educational Psychology, 106(4), 990-1006. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25541565
    Fung, W., & Swanson, H. L. (2017). Working memory components that predict word problem solving: Is it merely a function of reading, calculation, and fluid intelligence? Memory & Cognition, 45(5), 804-823. doi:10.3758/s13421-017-0697-0
    García, A. I., Jiménez, J. E., & Hess, S. (2006). Solving Arithmetic Word Problems: An Analysis of Classification as a Function of Difficulty in Children With and Without Arithmetic LD. Journal of Learning Disabilities, 39(3), 270-281. doi:10.1177/00222194060390030601
    Gilmore, C., Keeble, S., Richardson, S., & Cragg, L. (2015). The role of cognitive inhibition in different components of arithmetic. ZDM, 47(5), 771-782. doi:10.1007/s11858-014-0659-y
    Goodrich, J. M., & Namkung, J. M. (2019). Correlates of reading comprehension and word-problem solving skills of Spanish-speaking dual language learners. Early Childhood Research Quarterly, 48, 256-266. doi:10.1016/j.ecresq.2019.04.006
    Grabner, R. H., Ansari, D., Koschutnig, K., Reishofer, G., Ebner, F., & Neuper, C. (2009). To retrieve or to calculate? Left angular gyrus mediates the retrieval of arithmetic facts during problem solving. Neuropsychologia, 47(2), 604-608. doi:10.1016/j.neuropsychologia.2008.10.013
    Griffis, J. C., Nenert, R., Allendorfer, J. B., Vannest, J., Holland, S., Dietz, A., & Szaflarski, J. P. (2017). The canonical semantic network supports residual language function in chronic post-stroke aphasia. Human Brain Mapping, 38(3), 1636-1658. doi:10.1002/hbm.23476
    Haghverdi, M. (2012). Recognition of students` difficulties in solving mathematical word problems from the viewpoint of teachers. Journal of Basic and Applied Scientific Research, 2(3), 2923-2928.
    Haghverdi, M., Semnani, A. S., & Seifi, M. (2012). The relationship between different kinds of students` errors and the knowledge required to solve mathematics word problems. Bolema: Boletim de Educação Matemática, 26, 649-666. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-636X2012000200012&nrm=iso
    Hegarty, M., Mayer, R. E., & Green, C. E. (1992). Comprehension of arithmetic word problems: Evidence from students` eye fixations. Journal of Educational Psychology, 84(1), 76-84. doi:10.1037/0022-0663.84.1.76
    Hegarty, M., Mayer, R. E., & Monk, C. A. (1995). Comprehension of arithmetic word problems: A comparison of successful and unsuccessful problem solvers. Journal of Educational Psychology, 87(1), 18-32. doi:10.1037/0022-0663.87.1.18
    Hudson, T. (1983). Correspondences and Numerical Differences between Disjoint Sets. Child Development, 54(1), 84-90. doi:10.2307/1129864
    Huebner, M. G., & LeFevre, J.-A. (2018). Selection of procedures in mental subtraction: Use of eye movements as a window on arithmetic processing. Canadian Journal of Experimental Psychology, 72(3), 171-182. doi:10.1037/cep0000127
    Imbo, I., & Vandierendonck, A. (2008). Effects of problem size, operation, and working-memory span on simple-arithmetic strategies: differences between children and adults? Psychological Research, 72(3), 331-346. doi:10.1007/s00426-007-0112-8
    Jahanshahi, M., Obeso, I., Rothwell, J. C., & Obeso, J. A. (2015). A fronto–striato–subthalamic–pallidal network for goal-directed and habitual inhibition. Nature Reviews Neuroscience, 16(12), 719-732. doi:10.1038/nrn4038
    Jerman, M. (1974). Problem length as a structural variable in verbal arithmetic problems. Educational Studies in Mathematics, 5(1), 109-123. doi:10.1007/BF00684692
    Kaput, J. J. (1979). Mathematics andlearning: Roots of epistemological status. In J. Clement & J. Lochhead (Eds.), Cognitive Process Instruction (pp. 289-303). Philadephia, PA: Franklin Institute Press.
    Kawashima, R., Taira, M., Okita, K., Inoue, K., Tajima, N., Yoshida, H., . . . Fukuda, H. (2004). A functional MRI study of simple arithmetic–a comparison between children and adults. Brain Research. Cognitive Brain Research, 18(3), 227-233. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/14741309
    Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008). Competition between functional brain networks mediates behavioral variability. Neuroimage, 39(1), 527-537. doi:10.1016/j.neuroimage.2007.08.008
    Kim, C., Kroger, J. K., Calhoun, V. D., & Clark, V. P. (2015). The role of the frontopolar cortex in manipulation of integrated information in working memory. Neuroscience Letters, 595, 25-29. doi:10.1016/j.neulet.2015.03.044
    Kingsdorf, S., & Krawec, J. (2014). Error Analysis of Mathematical Word Problem Solving Across Students with and without Learning Disabilities. Learning Disabilities Research & Practice, 29(2), 66-74. doi:10.1111/ldrp.12029
    Kintsch, W., & Greeno, J. G. (1985). Understanding and solving word arithmetic problems. Psychological Review, 92(1), 109-129. doi:10.1037/0033-295X.92.1.109
    Ko, C.-H., Yen, J.-Y., Yen, C.-F., Chen, C.-S., Lin, W.-C., Wang, P.-W., & Liu, G.-C. (2013). Brain activation deficit in increased-load working memory tasks among adults with ADHD using fMRI. European Archives of Psychiatry and Clinical Neuroscience, 263(7), 561-573. doi:10.1007/s00406-013-0407-2
    Koedinger, K. R., & Nathan, M. J. (2004). The Real Story Behind Story Problems: Effects of Representations on Quantitative Reasoning. Journal of the Learning Sciences, 13(2), 129-164. doi:10.1207/s15327809jls1302_1
    Lean, G. A., Clements, M. A., & Del Campo, G. (1990). Linguistic and pedagogical factors affecting children`s understanding of arithmetic word problems: A comparative study. Educational Studies in Mathematics, 21(2), 165-191. doi:10.1007/BF00304900
    Lee, K., Lim, Z. Y., Yeong, S. H., Ng, S. F., Venkatraman, V., & Chee, M. W. (2007). Strategic differences in algebraic problem solving: neuroanatomical correlates. Brain Research, 1155, 163-171. doi:10.1016/j.brainres.2007.04.040
    LeFevre, J.-A., & Morris, J. (1999). More on the relation between division and multiplication in simple arithmetic: Evidence for mediation of division solutions via multiplication. Memory & Cognition, 27(5), 803-812. doi:10.3758/BF03198533
    LeFevre, J.-A., Sadesky, G. S., & Bisanz, J. (1996). Selection of procedures in mental addition: Reassessing the problem size effect in adults. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(1), 216-230. doi:10.1037/0278-7393.22.1.216
    Lemaire, P., & Lecacheur, M. (2011). Age-related changes in children`s executive functions and strategy selection: A study in computational estimation. Cognitive Development, 26(3), 282-294. doi:10.1016/j.cogdev.2011.01.002
    Lepik, M. (1990). Algebraic word problems: Role of linguistic and structural variables. Educational Studies in Mathematics, 21(1), 83-90. doi:10.1007/BF00311017
    Lewis, A. B., & Mayer, R. E. (1987). Students` miscomprehension of relational statements in arithmetic word problems. Journal of Educational Psychology, 79(4), 363-371. doi:10.1037/0022-0663.79.4.363
    Lubin, A., Vidal, J., Lanoë, C., Houdé, O., & Borst, G. (2013). Inhibitory control is needed for the resolution of arithmetic word problems: A developmental negative priming study. Journal of Educational Psychology, 105(3), 701-708. doi:10.1037/a0032625
    Martiniello, M. (2008). Language and the performance of English-language learners in math word problems. Harvard Educational Review, 78, 333-368.
    Mastrothanasis, K., Geladari, A., Zervoudakis, K., & Strakalis, P. (2018). Primary school pupils` strategies for mental addition and subtraction computations. International Journal of Education and Research, 6(8), 43-56. Retrieved from http://www.ijern.com/journal/2018/August-2018/04.pdf
    Mayer, R. E. (1985). Implications of cognitive psychology for instruction in mathematical problem solving. In E. A. Silver (Ed.), Teaching and Learning Mathematical Problem Solving: Multiple Research Perspectives (pp. 123-138). Hillsdale, NJ: Lawrence Erlbaum Associates.
    Menon, V. (2014). Arithmetic in the child and adult brain. In R. C. Kadosh & A. Dowker (Eds.), The Oxford Handbook of Mathematical Cognition: Oxford University Press.
    Menon, V. (2016). Memory and cognitive control circuits in mathematical cognition and learning. In M. Cappelletti & W. Fias (Eds.), Progress in Brain Research (Vol. 227, pp. 159-186): Elsevier.
    Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain Structure and Function, 214(5-6), 655-667. doi:10.1007/s00429-010-0262-0
    Metcalfe, A. W. S., Ashkenazi, S., Rosenberg-Lee, M., & Menon, V. (2013). Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children. Developmental Cognitive Neuroscience, 6, 162-175. doi:10.1016/j.dcn.2013.10.001
    Miller, E. K., & Cohen, J. D. (2001). An Integrative Theory of Prefrontal Cortex Function. Annual Review of Neuroscience, 24(1), 167-202. doi:10.1146/annurev.neuro.24.1.167
    Mock, J., Huber, S., Bloechle, J., Dietrich, J. F., Bahnmueller, J., Rennig, J., . . . Moeller, K. (2018). Magnitude processing of symbolic and non-symbolic proportions: an fMRI study. Behavioral and Brain Functions, 14(1), 9. doi:10.1186/s12993-018-0141-z
    Mädamürk, K., Kikas, E., & Palu, A. (2018). Calculation and word problem-solving skill profiles: relationship to previous skills and interest. Educational Psychology, 38(10), 1239-1254. doi:10.1080/01443410.2018.1495830
    Molko, N., Cachia, A., Rivière, D., Mangin, J.-F., Bruandet, M., Le Bihan, D., . . . Dehaene, S. (2003). Functional and Structural Alterations of the Intraparietal Sulcus in a Developmental Dyscalculia of Genetic Origin. Neuron, 40(4), 847-858. doi:10.1016/S0896-6273(03)00670-6
    Monti, M. M., Parsons, L. M., & Osherson, D. N. (2012). Thought beyond language: neural dissociation of algebra and natural language. Psychological Science, 23(8), 914-922. doi:10.1177/0956797612437427
    Muth, K. D. (1992). Extraneous information and extra steps in arithmetic word problems. Contemporary Educational Psychology, 17(3), 278-285. doi:10.1016/0361-476X(92)90066-8
    National Mathematics Advisory Panel. (2008). Foundations for Success: The Final Report of the National Mathematics Advisory Panel. Washington, DC: U.S. Department of Education.
    Nesher, P. (1976). Three determinants of difficulty in verbal arithmetic problems. Educational Studies in Mathematics, 7(4), 369-388. doi:10.1007/BF00452220
    Nesher, P., & Teubal, E. (1975). Verbal cues as an interfering factor in verbal problem solving. Educational Studies in Mathematics, 6(1), 41-51. doi:10.1007/bf00590023
    Newman, S. D., Just, M. A., Keller, T. A., Roth, J., & Carpenter, P. A. (2003). Differential effects of syntactic and semantic processing on the subregions of Broca’s area. Cognitive Brain Research, 16(2), 297-307. doi:10.1016/S0926-6410(02)00285-9
    Newman, S. D., Pruce, B., Rusia, A., & Burns Jr., T. (2010). The effect of strategy on problem solving: an fMRI study. The Journal of Problem Solving, 3(1). doi:10.7771/1932-6246.1076
    Newman, S. D., Willoughby, G., & Pruce, B. (2011). The effect of problem structure on problem-solving: an fMRI study of word versus number problems. Brain Research, 1410, 77-88. doi:10.1016/j.brainres.2011.06.053
    Ni, W., Constable, R. T., Mencl, W. E., Pugh, K. R., Fulbright, R. K., Shaywitz, S. E., . . . Shankweiler, D. (2000). An Event-related Neuroimaging Study Distinguishing Form and Content in Sentence Processing. Journal of Cognitive Neuroscience, 12(1), 120-133. doi:10.1162/08989290051137648
    Nieder, A., & Dehaene, S. (2009). Representation of number in the brain. Annual Review of Neuroscience, 32, 185-208. doi:10.1146/annurev.neuro.051508.135550
    Nuerk, H.-C., Moeller, K., & Willoughby, G. (2015). Multi-digit number processing: overview, conceptual clarifications, and language influences. In R. C. Kadosh & A. Dowker (Eds.), The Oxford Handbook of Numerical Cognition. Oxford: Oxford University Press.
    OECD. (2014). PISA 2012 Results: What Students Know and Can Do – Student Performance in Mathematics, Reading and Science (Revised ed. Vol. I): OECD.
    Orrantia, J., & Múñez, D. (2013). Arithmetic word problem solving: evidence for a magnitude-based mental representation. Memory & Cognition, 41(1), 98-108. doi:10.3758/s13421-012-0241-1
    Orrantia, J., Rodríguez, L., & Vicente, S. (2010). Automatic activation of addition facts in arithmetic word problems. The Quarterly Journal of Experimental Psychology, 63(2), 310-319. doi:10.1080/17470210902903020
    Ostad, S. A. (1998). Developmental Differences in Solving Simple Arithmetic Word Problems and Simple Number-fact Problems: A Comparison of Mathematically Normal and Mathematically Disabled Children. Mathematical Cognition, 4(1), 1-19. doi:10.1080/135467998387389
    Pape, S. J. (2003). Compare word problems: Consistency hypothesis revisited. Contemporary Educational Psychology, 28(3), 396-421. doi:10.1016/S0361-476X(02)00046-2
    Passolunghi, M. C., & Siegel, L. S. (2001). Short-Term Memory, Working Memory, and Inhibitory Control in Children with Difficulties in Arithmetic Problem Solving. Journal of Experimental Child Psychology, 80(1), 44-57. doi:10.1006/jecp.2000.2626
    Peters, G., De Smedt, B., Torbeyns, J., Ghesquière, P., & Verschaffel, L. (2013). Children`s use of addition to solve two-digit subtraction problems. British Journal of Psychology, 104(4), 495-511. doi:10.1111/bjop.12003
    Peters, L., & De Smedt, B. (2018). Arithmetic in the developing brain: A review of brain imaging studies. Developmental Cognitive Neuroscience, 30, 265-279. doi:10.1016/j.dcn.2017.05.002
    Piazza, M., Izard, V., Pinel, P., Le Bihan, D., & Dehaene, S. (2004). Tuning curves for approximate numerosity in the human intraparietal sulcus. Neuron, 44(3), 547-555. doi:10.1016/j.neuron.2004.10.014
    Pinel, P., Dehaene, S., Riviere, D., & LeBihan, D. (2001). Modulation of parietal activation by semantic distance in a number comparison task. Neuroimage, 14(5), 1013-1026. doi:10.1006/nimg.2001.0913
    Powell, S. R., & Fuchs, L. S. (2014). Does Early Algebraic Reasoning Differ as a Function of Students` Difficulty with Calculations versus Word Problems? Learning Disabilities Research and Practice, 29(3), 106-116. doi:10.1111/ldrp.12037
    Powell, S. R., Fuchs, L. S., Cirino, P. T., Fuchs, D., Compton, D. L., & Changas, P. C. (2015). Effects of a Multitier Support System on Calculation, Word Problem, and Prealgebraic Performance Among At-Risk Learners. Exceptional Children, 81(4), 443-470. doi:10.1177/0014402914563702
    Prabhakaran, V., Rypma, B., & Gabrieli, J. D. (2001). Neural substrates of mathematical reasoning: a functional magnetic resonance imaging study of neocortical activation during performance of the necessary arithmetic operations test. Neuropsychology, 15(1), 115-127. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/11216882
    Raduan, I. H. (2010). Error analysis and the corresponding cognitive activities committed by year five primary students in solving mathematical word problems. Procedia - Social and Behavioral Sciences, 2(2), 3836-3838. doi:10.1016/j.sbspro.2010.03.600
    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(2), 110-122. doi:10.1016/j.lindif.2009.10.005
    Riley, M. S., & Greeno, J. G. (1988). Developmental analysis of understanding language about quantities and of solving problems. Cognition and Instruction, 5(1), 49-101. doi:10.1207/s1532690xci0501_2
    Riley, M. S., Greeno, J. G., & Heller, J. I. (1983). Development of children`s problem solving ability in arithmetic. In H. P. Ginsburg (Ed.), The Development of Mathematical Thinking (pp. 153-196). New York: Academic Press.
    Rosenberg-Lee, M., Chang, T. T., Young, C. B., Wu, S., & Menon, V. (2011). Functional dissociations between four basic arithmetic operations in the human posterior parietal cortex: A cytoarchitectonic mapping study. Neuropsychologia, 49(9), 2592-2608. doi:10.1016/j.neuropsychologia.2011.04.035
    Scheperjans, F., Eickhoff, S. B., Homke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic maps, morphometry, and variability of cytoarchitectonic areas in the human superior parietal cortex. Cerebral Cortex, 18(9), 2141-2157. doi:10.1093/cercor/bhm241
    Schumacher, R. F., & Fuchs, L. S. (2012). Does understanding relational terminology mediate effects of intervention on compare word problems? Journal of Experimental Child Psychology, 111(4), 607-628. doi:10.1016/j.jecp.2011.12.001
    Searle, B. W., Lorton, P., & Suppes, P. (1974). Structural variables affecting CAI performance on arithmetic word problems of disadvantaged and deaf students. Educational Studies in Mathematics, 5(1), 371-384. doi:10.1007/BF00684708
    Shaftel, J., Belton-Kocher, E., Glasnapp, D., & Poggio, J. (2006). The Impact of Language Characteristics in Mathematics Test Items on the Performance of English Language Learners and Students With Disabilities. Educational Assessment, 11(2), 105-126. doi:10.1207/s15326977ea1102_2
    Shenhav, A., Cohen, J. D., & Botvinick, M. M. (2016). Dorsal anterior cingulate cortex and the value of control. Nature Neuroscience, 19, 1286. doi:10.1038/nn.4384
    Stanescu-Cosson, R., Pinel, P., van de Moortele, P.-F., Le Bihan, D., Cohen, L., & Dehaene, S. (2000). Understanding dissociations in dyscalculia: A brain imaging study of the impact of number size on the cerebral networks for exact and approximate calculation. Brain, 123(11), 2240-2255. doi:10.1093/brain/123.11.2240
    Supekar, K., & Menon, V. (2012). Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model. PLoS Computational Biology, 8(2), e1002374. doi:10.1371/journal.pcbi.1002374
    Swanson, H. L., Cooney, J. B., & Brock, S. (1993). The Influence of Working Memory and Classification Ability on Children′s Word Problem Solution. Journal of Experimental Child Psychology, 55(3), 374-395. doi:10.1006/jecp.1993.1021
    Swanson, H. L., Jerman, O., & Zheng, X. (2008). Growth in working memory and mathematical problem solving in children at risk and not at risk for serious math difficulties. Journal of Educational Psychology, 100(2), 343-379. doi:10.1037/0022-0663.100.2.343
    Thevenot, C., Devidal, M., Barrouillet, P., & Fayol, M. (2007). Why does placing the question before an arithmetic word problem improve performance? A situation model account. The Quarterly Journal of Experimental Psychology, 60(1), 43-56. doi:10.1080/17470210600587927
    Thevenot, C., & Oakhill, J. (2005). The strategic use of alternative representations in arithmetic word problem solving. The Quarterly Journal of Experimental Psychology Section A, 58(7), 1311-1323. doi:10.1080/02724980443000593
    Torbeyns, J., De Smedt, B., Ghesquière, P., & Verschaffel, L. (2009). Acquisition and Use of Shortcut Strategies by Traditionally Schooled Children. Educational Studies in Mathematics, 71(1), 1-17. Retrieved from www.jstor.org/stable/40284582
    Uddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011). Dynamic reconfiguration of structural and functional connectivity across core neurocognitive brain networks with development. Journal of Neuroscience, 31(50), 18578-18589. doi:10.1523/JNEUROSCI.4465-11.2011
    Van Beek, L., Ghesquièr, P., De Smedt, B., & Lagae, L. (2014). The arithmetic problem size effect in children: an event-related potential study. Frontiers in Human Neuroscience, 8(756). doi:10.3389/fnhum.2014.00756
    Vandierendonck, A. (2017). A comparison of methods to combine speed and accuracy measures of performance: A rejoinder on the binning procedure. Behavior Research Methods, 49(2), 653-673. doi:10.3758/s13428-016-0721-5
    Verschaffel, L., De Corte, E., & Pauwels, A. (1992). Solving compare problems: An eye movement test of Lewis and Mayer`s consistency hypothesis. Journal of Educational Psychology, 84(1), 85-94. doi:10.1037/0022-0663.84.1.85
    Vicente, S., Orrantia, J., & Verschaffel, L. (2007). Influence of situational and conceptual rewording on word problem solving. British Journal of Educational Psychology, 77(4), 829-848. doi:10.1348/000709907x178200
    Vilenius-Tuohimaa, P. M., Aunola, K., & Nurmi, J.-E. (2008). The association between mathematical word problems and reading comprehension. Educational Psychology, 28(4), 409-426. doi:10.1080/01443410701708228
    Wang, A. Y., Fuchs, L. S., & Fuchs, D. (2016). Cognitive and Linguistic Predictors of Mathematical Word Problems With and Without Irrelevant Information. Learning and Individual Differences, 52, 79-87. doi:10.1016/j.lindif.2016.10.015
    Weiss, Y., Cweigenberg, H. G., & Booth, J. R. (2018). Neural specialization of phonological and semantic processing in young children. Human Brain Mapping, 39(11), 4334-4348. doi:10.1002/hbm.24274
    Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The neural bases of momentary lapses in attention. Nature Neuroscience, 9(7), 971-978. doi:10.1038/nn1727
    Wilcox, S., & Palermo, D. (1997). In, on under; more, less; some artifactrs revealed. Paper presented at the Eastern Psychologyical Association meetings, Boston.
    Woltz, D. J., & Was, C. A. (2006). Availability of related long-term memory during and after attention focus in working memory. Memory & Cognition, 34(3), 668-684. doi:10.3758/bf03193587
    Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nature Methods, 8(8), 665-670. doi:10.1038/nmeth.1635
    Yearp, B. H., & Kaur, B. (2001). Semantic characteristics that make arithmetic word problems difficult. Paper presented at the Numeracy and Beyond: Proceedings of the 24th Annual Conference of the Mathematics Education Research Group of Australasia Incorporated, Australia.
    Zamarian, L., Ischebeck, A., & Delazer, M. (2009). Neuroscience of learning arithmetic—Evidence from brain imaging studies. Neuroscience & Biobehavioral Reviews, 33(6), 909-925. doi:10.1016/j.neubiorev.2009.03.005
    Zarnhofer, S., Braunstein, V., Ebner, F., Koschutnig, K., Neuper, C., Ninaus, M., . . . Ischebeck, A. (2013). Individual differences in solving arithmetic word problems. Behavioral and Brain Function, 9(1), 28. doi:10.1186/1744-9081-9-28
    Zbrodoff, N. J., & Logan, G. D. (2005). What everyone finds: The problem-size effect. In Handbook of Mathematical Cognition. (pp. 331-345). New York, NY, US: Psychology Press.
    Zhang, S., & Li, C.-s. R. (2012). Functional networks for cognitive control in a stop signal task: Independent component analysis. Human Brain Mapping, 33(1), 89-104. doi:10.1002/hbm.21197
    Zhou, X., Li, M., Li, L., Zhang, Y., Cui, J., Liu, J., & Chen, C. (2018). The semantic system is involved in mathematical problem solving. Neuroimage, 166, 360-370. doi:10.1016/j.neuroimage.2017.11.017
    Description: 碩士
    國立政治大學
    心理學系
    106752027
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106752027
    Data Type: thesis
    DOI: 10.6814/NCCU202000130
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