2010 3 1001-4918 2010 03-0267-273 G442 A * 510006 215 1 2 3 4 1 retrieval structure Ackerman Beier & Boyle 2002 Hambrick & Engle 2002 2008 Chen Fan & Macredie 2006 Lawless & Kulikowich 2006 Shapiro 2004 Alexander 2006 2008 Gagne 1985 Anderson 1986 Moos & Azevedo 2008 Winne 1996 domain knowledge declarative procedural conditional Mayer 1992 Alexander Kulikowich & Jetton * BBA080049. E - mail guxycai@ tom. com 1995 Alexander Schallert & Hare 1991 Alexander & Murphy 1998 267
2010 3 F 2 212 = 21. 96 P < 0. 01 1 18 18 24 17 77 19 12 20 24 75 18 16 15 14 63 55 46 59 55 215 2. 2 2. 2. 1 2 Hutchinson 1993 2. 1 4 t = 1. 51 p > 0. 05 4 227 110 117 215 94. 71% 75 25 1 1 2. 2. 2 2 3 268
2 3 3 5 45 2007 2. 3 2. 3. 1 0. 82 0. 81 P 0. 01 Ausubel 2005 Ausubel 1994 0. 65 0. 97 0. 66 P 0. 01 2. 3. 3 7 2 1 Gagne 1985 Gagne & Glaser 1987 r = 0. 974 P 0. 01 0. 66 0. 60 0. 74 0. 85 P 0. 01 2. 3. 2 269
2010 3 0. 84 0. 79 0. 76 0. 80 P 0. 01 2 0. 69 0. 69 0. 82 0. 74 M SD M SD M SD 0. 94 P 0. 01 3 64. 28 23. 01 85. 36 19. 10 149. 64 36. 10 52. 58 22. 73 79. 85 20. 13 132. 42 37. 01 t 2. 97 1. 63 2. 74 3. 1 3 2 3 M SD M SD M SD M SD M SD 62. 61 26. 33 42. 75 41. 37 60. 14 40. 89 74. 56 24. 90 240. 27 85. 96 52. 27 28. 97 31. 82 34. 68 44. 39 42. 18 62. 87 28. 34 191. 64 85. 95 t 2. 17 * 1. 66 2. 20 * 2. 58 * 3. 29 3. 2 5 B t R 2 Δ R 2 0. 03 0. 68 * 0. 08 0. 08 0. 02 1. 39 * 0. 24 0. 16 4 3. 3 5 4 6 7 B t R 2 Δ R 2 0. 95 587. 73 0. 56 0. 56 0. 19 56. 64 0. 63 0. 07 0. 12 21. 46 0. 67 0. 04 6 M SD F M SD F M SD F 54. 61 25. 81 76. 54 22. 04 131. 15 43. 31 57. 64 23. 40 1. 13 82. 92 21. 36 4. 12 * 140. 57 38. 64 3. 08 * 63. 26 21. 24 87. 91 13. 24 151. 16 26. 94 270
7 M SD M SD M SD M SD M SD 54. 36 29. 72 30. 77 35. 57 48. 72 42. 19 61. 46 27. 71 195. 38 100. 13 53. 96 30. 28 40. 57 38. 05 41. 89 42. 16 69. 57 27. 19 205. 98 84. 98 64. 88 22. 19 39. 53 41. 63 68. 84 37. 68 74. 44 25. 81 248. 60 75. 36 F 2. 92 0. 22 5. 90 0. 62 3. 38 * 4 4. 1 2 3 2 t = 1. 82 p > 0. 05 t = 0. 43 p > 0. 05 t = 0. 31 p > 0. 05 Anderson Reder & Simon 1996 Bonder 1986 4 3 4. 2 4 Alexander 1997 knowledge knowledge use 271
2010 3 4. 4 5 1 4. 3 6 7 2 Gagne Gagne 5 Gagne 1985 Gagne & Glaser 1987 1 2 Anderson 1982 3 4 2006 Ackerman P. L. Beier M. E. & Boyle M. O. 2002. Individual Differences in Working Memory Within a Nomological Network of Cognitive and Perceptual Speed Abilities. Journal of Experimental Psychol- ogy 131 4 567-589. Alexander P. A. Kulikowich J. M. & Jetton T. L. 1995. Interrelationship of Knowledge Interest and Recall Assessing a Model of Domain Learning. Journal of Educational Psychology 87 4 559-575. 272 Alexander P. A. Murphy P. K. Woods B. S. Duhon K. E. & Parker D. 1997. College Instruction and Concomitant Changes in Students' Knowledge Interest and Strategy Use A Study of Domain Learning. Contemporary Educational Psychology 22 2 125-146. Alexander P. A. Schallert D. L. & Hare V. C. 1991. Coming
to terms How researchers in learning and literacy talk about knowledge. Review of Educational Research 61 3 315-343. Alexander P. A. & Murphy P. K. 1998. Profiling the Differences in Students' Knowledge Interest and Strateic Processing. Journal of Educational Psychology 90 3 435-447. Anderson J. R. 1982. Acquisition of cognitive skill. Psychological Review 89 4 369-406. Anderson J. R. 1986. Knowledge compilation The general learningmechanism. In R. Michalski J. Carbonell & T. Mitchell Eds. Machine Learning Volume 2. Los Altos CA Morgan Kaufmann. Anderson J. R. Reder L. M. & Simon H. A. 1996. situated learning and education. Educational Researcher 25 4 5-11. Bonder G. M. 1986. Constructivism A theory of knowledge. Journal of Chemical Education 63 873-878. Chen S. Y. Fan J. & Macredie R. D. 2006. navigation in hypermedia learning systems experts vs. novices. Computers in Human Behavior 22 251-266. Gagne E. D. 1985. The cognitive psychology of school learning. Boston Little Brown. Hutchinson N. L. 1993. effects of cognitive strategy insturuction on algebra problems solving of adolesecents with learning disabilities. Learning Disability Quarterly 16 34-63. Hambrick D. Z. & Engle R. W. 2002. Effects of Domain Knowledge Working Memory Capacity and Age on Cognitive Performance An Investigation of the Knowledge - Is - Power Hypothesis. Cognitive Psychology 44 4 339-387. Lawless K. A. & Kulikowich J. M. 2006. Domain knowledge and individual interest The effects of academic level and specialization in statistics and psychology. Contemporary Educational Psychology 31 1 30-43. Gagn e R. M. & Glaser R. 1987. Foundations in learning research. In R. M. Gagn e Ed. Instructional Technology Foundations. Hillsdale NJ Lawrence Erlbaum Associates. Mayer R. E. 1992. Cognition and instrction Their historic meeting within educational psychology. Journal of Educational Psychology 84 4 405-412. Moos D. C. & Azevedo R. 2008. Monitoring planning and self - efficacy during learning with hypermedia the impact of conceptual scaffolds. Computers in Human Behavior 24 1686-1706. Shapiro A. M. 2004. How Including Prior Knowledge As a Subject Variable May Change Outcomes of Learning Research. American Educational Research journal 41 1 159-189. Winne P. H. 1996. A metacognitive view of individual differences in self-regulated learning. Learning and Individual Difference 8 327-353.. 2008.. 4 306-310.. 2006.. 1 43-46.. 2005.... 2006.... 2007.. 32 1 154-157.. 2008.. 6 55-58. Ausubel. 1994... The Research on the Knowledge Representation of Disciplinary Domain Knowledge and Mathematics Learning LI Chang-hong CAI Xiao-yue HE Bo-feng Educational college of Guangzhou university Guangzhou Guangdong 510006 Abstract Teaching experiments can be carried out with units of the disciplinary domain knowledge which are adapted and reorganized from the disciplinary knowledge in mathematics on the basis of structural characteristics of domain knowledge. Some questionnaires and in-depth interviews which contained 215 students at second year at middle school were used to investigate the effect which is caused by disciplinary domain knowledge in knowledge representation and also did some research on the relationship between knowledge representation and mathematical a- chievements. The results are as follows 1 disciplinary domain knowledge can significantly improve the comprehensive and overall level of declarative knowledge representation 2 disciplinary domain knowledge can significantly improve students procedural knowledge representation in comprehensive automation organization and o- verall level 3 the three elements of cognitive structure declarative knowledge representation and procedural knowledge representation are significantly correlated with students mathematics achievements 4 excellent students are significantly better than average students and poor students with respect to the accuracy and overall level of declarative representation and the organization and overall level of procedural knowledge representation. Key words disciplinary domain knowledge domain knowledge teaching mathematics learning knowledge representation cognitive structure 273