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Instructional Scaffolding: Foundations and Evolving Definition

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Belland, Brian R.·2017·Instructional Scaffolding in STEM Education
DOI 10.1007/978-3-319-02565-0_2
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Abstract

This chapter covers the definition of instructional scaffolding, as well as its theoretical bases, and how those bases are reflected in computer-based scaffolding. Computer-based scaffolding is defined as a computer-based tool that extends and enhances student capabilities as students engage with authentic and ill-structured tasks. Despite its original atheoretical nature, scaffolding was linked to many theoretical frameworks, including activity theory, Adaptive Character of Thought-Rational (ACT-R), and knowledge integration. This variation in theoretical frameworks has led to differing scaffolding strategies (e.g., fading, adding, and fading/adding strategies) and overall scaffolding approaches. These are described in depth in this chapter.

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  • Scaffolding-the breaking down of a complex concept or task into smaller parts that can be structured with guidance for students-is a common instructional strategy that can improve students' self-regulation of learning and student learning outcomes in STEM.

    “Scaffolding—the breaking down of a complex concept or task into smaller parts that can be structured with guidance for students—is a common instructional strategy that can improve students’ self-regulation of learning and student learning outcomes in STEM (Belland, 2016; Offerdahl et al., 2017; Sabel et al., 2017; Ewell et al., 2022).”

    From Reading Primary Scientific Literature: Approaches for Teaching Students in the Undergraduate STEM Classroom (2023) · cites this paper as Belland, 2016

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  1. Abd-El-Khalick, F., BouJaoude, S., Duschl, R., Lederman, N. G., Mamlok-Naaman, R., Hofstein, A., Niaz, M., Treagust, D., & Tuan, H. (2004). Inquiry in science education: International per- spectives. Science Education, 88(3), 397-419. http://doi.org/10.1002/sce.10118. References · DOI
  2. Ainsworth, S., Grimshaw, S., & Underwood, J. (1999). Teachers implementing pedagogy through redeem. Computers & Education, 33(2-3), 171-187. http://doi.org/10.1016/S0360- 1315(99)00031-7. · DOI
  3. Akhras, F. N., & Self, J. A. (2002). Beyond intelligent tutoring systems: Situations, interac- tions, processes and affordances. Instructional Science, 30(1), 1-30. http://doi.org/10.1023 /A:1013544300305. · DOI
  4. Albanese, M. A. (2004). Treading tactfully on tutor turf: does PBL tutor content expertise make a dif- ference? Medical Education, 38, 918-920. http://doi.org/10.1111/j.1365-2929.2004.01964.x. · DOI
  5. Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA, USA: Harvard University Press.
  6. Anderson, J. R. (1987). Methodologies for studying human knowledge. Behavioral and Brain Sci- ences, 10(03), 467-477. http://doi.org/10.1017/S0140525X00023554. · DOI
  7. Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365. http://doi.org/10.1037/0003-066X.51.4.355. · DOI
  8. Anderson, J. R., Matessa, M., & Lebiere, C. (1997). ACT-R: A theory of higher level cognition and its relation to visual attention. Human-Computer Interaction, 12(4), 439-462. http://doi. org/10.1207/s15327051hci1204_5. · DOI
  9. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrat- ed theory of the mind. Psychological Review, 111(4), 1036-1060. http://doi.org/10.1037/0033- 295X.111.4.1036. · DOI
  10. Angelova, M., Gunawardena, D., & Volk, D. (2006). Peer teaching and learning: Co-constructing language in a dual language first grade. Language and Education, 20(3), 173-190. http://doi. org/10.1080/09500780608668722. · DOI
  11. Aufschnaiter, C., von Erduran, S., Osborne, J., & Simon, S. (2008). Arguing to learn and learning to argue: Case studies of how students' argumentation relates to their scientific knowledge. Journal of Research in Science Teaching, 45(1), 101-131. http://doi.org/10.1002/tea.20213. · DOI
  12. Ausubel, D. P. (1980). Schemata, cognitive structure, and advance organizers: A reply to Ander- son, Spiro, and Anderson. American Educational Research Journal, 17(3), 400-404. http://doi. org/10.3102/00028312017003400. · DOI
  13. Baker, R. S. J. D., Corbett, A. T., & Koedinger, K. R. (2007). The difficulty factors approach to the design of lessons in intelligent tutor curricula. International Journal of Artificial Intelligence in Education, 17(4), 341-369.
  14. Barthes, R. (1994). The semiotic challenge. (R. Howard, Trans.). Berkeley, CA, USA: University of California Press.
  15. Belland, B. R. (2010). Portraits of middle school students constructing evidence-based arguments during problem-based learning: The impact of computer-based scaffolds. Educational Technol- ogy Research and Development, 58(3), 285-309. http://doi.org/10.1007/s11423-009-9139-4. · DOI
  16. Belland, B. R. (2012). Habitus, scaffolding, and problem-based learning: Why teachers' experi- ences as students matter. In S. B. Fee & B. R. Belland (Eds.), The role of criticism in under- standing problem solving: Honoring the work of John C. Belland (pp. 87-100). New York: Springer.
  17. Belland, B. R. (2014). Scaffolding: Definition, current debates, and future directions. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th edn., pp. 505-518). New York: Springer.
  18. Belland, B. R., & Drake, J. (2013). Toward a framework on how affordances and motives can drive different uses of computer-based scaffolds: Theory, evidence, and design implications. Edu- cational Technology Research & Development, 61, 903-925. http://doi.org/10.1007/s11423- 013-9313-6. · DOI
  19. Belland, B. R., Glazewski, K. D., & Richardson, J. C. (2008). A scaffolding framework to sup- port the construction of evidence-based arguments among middle school students. Educational Technology Research and Development, 56(4), 401-422. http://doi.org/10.1007/s11423-007- 9074-1. · DOI
  20. Belland, B. R., French, B. F., & Ertmer, P. A. (2009). Validity and problem-based learning re- search: A review of instruments used to assess intended learning outcomes. Interdisciplinary Journal of Problem-Based Learning, 3(1), 59-89. http://doi.org/10.7771/1541-5015.1059. · DOI
  21. Belland, B. R., Glazewski, K. D., & Richardson, J. C. (2011). Problem-based learning and ar- gumentation: Testing a scaffolding framework to support middle school students' creation of evidence-based arguments. Instructional Science, 39(5), 667-694. http://doi.org/10.1007/ s11251-010-9148-z. · DOI
  22. Belland, B. R., Kim, C., & Hannafin, M. (2013). A framework for designing scaffolds that improve motivation and cognition. Educational Psychologist, 48(4), 243-270. http://doi.org/10.1080/0 0461520.2013.838920. · DOI · Paper page
  23. Belland, B. R., Gu, J., Armbrust, S., & Cook, B. (2013). Using generic and context-specific scaf- folding to support authentic science inquiry. In Proceedings of the IADIS International Confer- ence on Cognition and Exploratory Learning in Digital Age (CELDA 2013) (pp. 185-192).
  24. Belland, B. R., Walker, A., Olsen, M. W., & Leary, H. (2015). A pilot meta-analysis of computer- based scaffolding in STEM education. Educational Technology and Society, 18(1), 183-197.
  25. Belland, B. R., Burdo, R., & Gu, J. (2015). A blended professional development program to help a teacher learn to provide one-to-one scaffolding. Journal of Science Teacher Education, 26(3), 263-289. http://doi.org/10.1007/s10972-015-9419-2. · DOI
  26. Belland, B. R., Gu, J., Armbrust, S., & Cook, B. (2015). Scaffolding argumentation about water quality: A mixed method study in a rural middle school. Educational Technology Research & Development, 63(3), 325-353. http://doi.org/10.1007/s11423-015-9373-x. · DOI
  27. Bierman, P., Massey, C., & Manduca, C. (2006). Reconsidering the textbook. Eos, Transactions American Geophysical Union, 87(31), 306-306. http://doi.org/10.1029/2006EO310004. · DOI
  28. Bottge, B. A., Rueda, E., Kwon, J. M., Grant, T., & LaRoque, P. (2007). Assessing and tracking stu- dents' problem solving performances in anchored learning environments. Educational Technol- ogy Research and Development, 57(4), 529-552. http://doi.org/10.1007/s11423-007-9069-y. · DOI
  29. Bransford, J., Plants, B., & Vye, N. (2003). Three AMIGO3s: Using "anchored modular inquiry" to help prepare future teachers. Educational Technology Research & Development, 51(1), 105- 123. http://doi.org/10.1007/BF02504521. · DOI
  30. Brown, A. L., & Campione, J. C. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice. Cam- bridge, MA, USA: The MIT Press.
  31. Cafri, G., Kromrey, J. D., & Brannick, M. T. (2010). A meta-meta-analysis: Empirical review of statistical power, type I error rates, effect sizes, and model selection of meta-analyses published in psychology. Multivariate Behavioral Research, 45(2), 239-270. http://doi. org/10.1080/00273171003680187. References · DOI · Paper page
  32. Cavalli-Sforza, V., Weiner, A. W., & Lesgold, A. M. (1994). Software support for students engag- ing in scientific activity and scientific controversy. Science Education, 78(6), 577-599. http:// doi.org/10.1002/sce.3730780604. · DOI
  33. Chang, H.-Y., & Linn, M. C. (2013). Scaffolding learning from molecular visualizations. Journal of Research in Science Teaching, 50(7), 858-886. http://doi.org/10.1002/tea.21089. · DOI
  34. Cheung, A. C. K., & Slavin, R. E. (2012). How features of educational technology applications af- fect student reading outcomes: A meta-analysis. Educational Research Review, 7(3), 198-215. http://doi.org/10.1016/j.edurev.2012.05.002. · DOI · Paper page
  35. Cheung, A. C. K., & Slavin, R. E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review, 9, 88-113. http://doi.org/10.1016/j.edurev.2013.01.001. · DOI · Paper page
  36. Chi, M. T. H. (1996). Constructing self-explanations and scaffolded explanations in tutor- ing. Applied Cognitive Psychology, 10(7), 33-49. http://doi.org/10.1002/(SICI)1099- 0720(199611)10:7<33::AID-ACP436>3.0.CO;2-E. Cho, K., & Jonassen, D. H. (2002). The effects of argumentation scaffolds on argumentation and problem-solving. Educational Technology Research and Development, 50(3), 5-22. http://doi. org/10.1007/BF02505022. · DOI
  37. Clancey, W. J. (2008). Scientific antecedents of situated cognition. In P. Robbins & M. Aydede (Eds.), The Cambridge handbook of situated cognition. Cambridge, UK: Cambridge Univer- sity Press.
  38. Clark, D. B., & Linn, M. C. (2013). The knowledge integration perspective: Connections across research and education. In S. Vosniadou (Ed.), International handbook of research on concep- tual change (pp. 520-538). New York: Routledge.
  39. Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York: Academic Press.
  40. Cohen, P. A., Kulik, J. A., & Kulik, C.-L. C. (1982). Educational outcomes of tutoring: A me- ta-analysis of findings. American Educational Research Journal, 19(2), 237-248. http://doi. org/10.3102/00028312019002237. · DOI · Paper page
  41. D'Andrade, R. G. (1981). The cultural part of cognition. Cognitive Science, 5(3), 179-195. http:// doi.org/10.1207/s15516709cog0503_1. · DOI
  42. Davin, K. J., & Donato, R. (2013). Student collaboration and teacher-directed classroom dynam- ic assessment: A complementary pairing. Foreign Language Annals, 46(1), 5-22. http://doi. org/10.1111/flan.12012. · DOI
  43. Davis, E. A., & Linn, M. C. (2000). Scaffolding students' knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22, 819-837. http://doi. org/10.1080/095006900412293. · DOI
  44. Dimitrova, V., & Dicheva, D. (1998). "Who is who": The roles in an intelligent system for foreign language terminology learning. British Journal of Educational Technology, 29, 47-57. http:// doi.org/10.1111/1467-8535.00045. · DOI
  45. diSessa, A. (1988). Knowledge in pieces. In G. Forman & P. Pufall (Eds.), Constructivism in the computer age (pp. 49-70). Mahwah, NJ, USA: Lawrence Erlbaum Associates.
  46. Diziol, D., Walker, E., Rummel, N., & Koedinger, K. R. (2010). Using intelligent tutor technol- ogy to implement adaptive support for student collaboration. Educational Psychology Review, 22(1), 89-102. http://doi.org/10.1007/s10648-009-9116-9. · DOI
  47. Dolmans, D. H. J. M., Gijselaers, W. H., Moust, J. H. C., de Grave, W. S., Wolfhagen, I. H. A. P., & van der Vleuten, C. P. M. (2002). Trends in research on the tutor in problem-based learning: Conclusions and implications for educational practice and research. Medical Teacher, 24(2), 173-180. http://doi.org/10.1080/01421590220125277. · DOI
  48. Duschl, R. (2008). Science education in three-part harmony: Balancing conceptual, epistemic, and social learning goals. Review of Research in Education, 32(1), 268-291. http://doi.org/10.310 2/0091732X07309371. · DOI
  49. Engeström, Y. (2009). The future of activity theory: A rough draft. In A. Sannino, H. Daniels, & K. D. Gutiérrez (Eds.), Learning and expanding with activity theory (pp. 303-328). Cambridge, UK: Cambridge University Press.
  50. Eylon, B.-S., & Linn, M. C. (1988). Learning and instruction: An examination of four research perspectives in science education. Review of Educational Research, 58(3), 251-301. http://doi. org/10.3102/00346543058003251. · DOI
  51. Fair, C., Vandermaas-Peeler, M., Beaudry, R., & Dew, J. (2005). "I learned how little kids think": Third-graders' scaffolding of craft activities with preschoolers. Early Child Development and Care, 175(3), 229-241. http://doi.org/10.1080/0300443042000230438. · DOI
  52. Ford, M. J. (2012). A dialogic account of sense-making in scientific argumentation and reasoning. Cognition and Instruction, 30(3), 207-245. http://doi.org/10.1080/07370008.2012.689383. · DOI
  53. Friesen, N. (2012). Critical theory and the mythology of learning with technology. In S. B. Fee & B. R. Belland (Eds.), The role of criticism in understanding problem solving: Honoring the work of John C. Belland (pp. 69-86). New York: Springer.
  54. Ge, X., & Land, S. M. (2004). A conceptual framework for scaffolding ill-structured problem-solv- ing processes using question prompts and peer interactions. Educational Technology Research and Development, 52(2), 5-22. http://doi.org/10.1007/BF02504836. · DOI
  55. Gentner, D., & Stevens, A. L. (Eds.). (2014). Mental models. New York: Psychology Press.
  56. Gerard, L. F., Varma, K., Corliss, S. B., & Linn, M. C. (2011). Professional development for technology-enhanced inquiry science. Review of Educational Research, 81(3), 408-448. http:// doi.org/10.3102/0034654311415121. · DOI
  57. Gillies, R. M., & Boyle, M. (2006). Ten Australian elementary teachers' discourse and reported pedagogical practices during cooperative learning. The Elementary School Journal, 106(5), 429-452. http://doi.org/10.1086/esj.2006.106.issue-5. · DOI
  58. Graesser, A. C., Bowers, C., Hacker, D. J., & Person, N. (1997). An anatomy of naturalistic tutor- ing. In K. Hogan & M. Pressley (Eds.), Scaffolding student learning: Instructional approaches and issues (pp. 145-184). Cambridge, MA, USA: Brookline Books.
  59. Greeno, J. G., & van de Sande, C. (2007). Perspectival understanding of conceptions and conceptual growth in interaction. Educational Psychologist, 42(1), 9-23. http://doi. org/10.1080/00461520709336915. · DOI
  60. Hakkarainen, K. (2004). Pursuit of explanation within a computer-supported classroom. Internation- al Journal of Science Education, 26(8), 979-996. http://doi.org/10.1080/1468181032000354. · DOI
  61. Hannafin, M., Land, S., & Oliver, K. (1999). Open-ended learning environments: Foundations, methods, and models. In C. M. Reigeluth (Ed.), Instructional design theories and models: Vol- ume II: A new paradigm of instructional theory (pp. 115-140).
  62. Hawkins, J., & Pea, R. D. (1987). Tools for bridging the cultures of everyday and scientific thinking. Journal of Research in Science Teaching, 24(4), 291-307. http://doi.org/10.1002/ tea.3660240404. · DOI · Paper page
  63. Helle, L., Tynjälä, P., Olkinuora, E., & Lonka, K. (2007). "Ain"t nothin' like the real thing'. Mo- tivation and study processes on a work-based project course in information systems design. British Journal of Educational Psychology, 77(2), 397-411. http://doi.org/10.1348/0007099 06X105986. · DOI
  64. Herrington, J., & Oliver, R. (2000). An instructional design framework for authentic learning environments. Educational Technology Research & Development, 48(3), 23-48. http://doi. org/10.1007/BF02319856. References · DOI · Paper page
  65. Hlynka, D. (2012). Postmodernism: A twenty-first century primer to problem-based learning. In S. B. Fee & B. R. Belland (Eds.), The role of criticism in understanding problem solving: Honor- ing the work of John C. Belland (pp. 35-42). New York: Springer.
  66. Hogan, K., & Maglienti, M. (2001). Comparing the epistemological underpinnings of students' and scientists' reasoning about conclusions. Journal of Research in Science Teaching, 38(6), 663-687. http://doi.org/10.1002/tea.1025. · DOI
  67. Ifenthaler, D., & Seel, N. M. (2013). Model-based reasoning. Computers & Education, 64, 131- 142. http://doi.org/10.1016/j.compedu.2012.11.014. · DOI
  68. Jadallah, M., Anderson, R. C., Nguyen-Jahiel, K., Miller, B. W., Kim, I.-H., Kuo, L.-J., Miller, B. W., Dong, T., & Wu, X. (2010). Influence of a teacher's scaffolding moves during child-led small-group discussions. American Educational Research Journal, 48(1), 194-230. http://doi. org/10.3102/0002831210371498. · DOI
  69. Jeong, A., & Joung, S. (2007). Scaffolding collaborative argumentation in asynchronous discus- sions with message constraints and message labels. Computers & Education, 48(3), 427-445. http://doi.org/10.1016/j.compedu.2005.02.002. · DOI
  70. Johnson-Laird, P. N. (2001). Mental models and deduction. Trends in Cognitive Sciences, 5(10), 434-442. http://dx.doi.org/10.1016/S1364-6613(00)01751-4. · DOI
  71. Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Re- search and Development, 48(4), 63-85. http://doi.org/10.1007/BF02300500. · DOI · Paper page
  72. Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.
  73. Jonassen, D. H., & Rohrer-Murphy, L. (1999). Activity theory as a framework for designing con- structivist learning environments. Educational Technology Research and Development, 47(1), 61-79. http://doi.org/10.1007/BF02299477. · DOI
  74. Kali, Y., & Linn, M. C. (2008). Technology-enhanced support strategies for inquiry learning. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd edn., pp. 145-161). New York: Lawrence Erlbaum Associates.
  75. Kali, Y., Orion, N., & Eylon, B.-S. (2003). Effect of knowledge integration activities on students' perception of the earth's crust as a cyclic system. Journal of Research in Science Teaching, 40(6), 545-565. http://doi.org/10.1002/tea.10096. · DOI
  76. Koedinger, K. R., & Aleven, V. (2007). Exploring the assistance dilemma in experiments with cog- nitive tutors. Educational Psychology Review, 19(3), 239-264. http://doi.org/10.1007/s10648- 007-9049-0. · DOI · Paper page
  77. Koedinger, K. R., & Corbett, A. (2006). Cognitive tutors: Technology bringing learning sciences to the classroom. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 61- 78). Cambridge, UK: Cambridge University Press.
  78. Kolodner, J. L. (1993). Case-based reasoning. San Mateo, CA, USA: Morgan Kaufmann.
  79. Kozulin, A. (1986). The concept of activity in Soviet psychology: Vygotsky, his disciples and critics. American Psychologist, 41(3), 264-274. http://doi.org/10.1037/0003-066X.41.3.264. · DOI
  80. Kozulin, A., & Garb, E. (2002). Dynamic assessment of EFL text comprehension. School Psychol- ogy International, 23(1), 112-127. http://doi.org/10.1177/0143034302023001733. · DOI
  81. Kuhn, D. (2010). Teaching and learning science as argument. Science Education, 94(5), 810-824. http://doi.org/10.1002/sce.20395. · DOI
  82. Laird, J. E. (2008). Extending the SOAR cognitive architecture. In P. Wang, B. Goertzel, & S. Franklin (Eds.), Artificial General Intelligence 2008: Proceedings of the first AGI conference. Amsterdam: IOS Press.
  83. Leary, H., Walker, A., Shelton, B., & Fitt, M. (2013). Exploring the relationships between tutor background, tutor training, and student learning: A problem-based learning meta-analysis. In- terdisciplinary Journal of Problem-Based Learning, 7(1), 40-66. http://doi.org/10.7771/1541- 5015.1331. · DOI
  84. Leont'ev, A. N. (1974). The problem of activity in psychology. Soviet Psychology, 13(2), 4-33. http://doi.org/10.2753/RPO1061-040513024. · DOI
  85. Lepper, M. R., Drake, M. F., & O'Donnell-Johnson, T. (1997). Scaffolding techniques of expert human tutors. In K. Hogan & M. Pressley (Eds.), Scaffolding student learning: Instructional approaches & issues (pp. 108-144). Cambridge, MA, USA: Brookline.
  86. Levpušček, M. P., Zupančič, M., & Sočan, G. (2013). Predicting achievement in mathematics in adolescent students: The role of individual and social factors. The Journal of Early Adoles- cence, 33(4), 523-551. http://doi.org/10.1177/0272431612450949. · DOI
  87. Lidz, C. S. (1995). Dynamic assessment and the legacy of L.S. Vygotsky. School Psychology In- ternational, 16(2), 143-153. http://doi.org/10.1177/0143034395162005. · DOI
  88. Lin, T.-J., Jadallah, M., Anderson, R. C., Baker, A. R., Nguyen-Jahiel, K., Kim, I. H., Kuo, L. J., Miller, B. W., Dong, T., & Wu, X. (2014). Less is more: Teachers' influence during peer collaboration. Journal of Educational Psychology, 107, 609. http://doi.org/10.1037/a0037758. · DOI
  89. Linn, M. C. (2000). Designing the knowledge integration environment. International Journal of Science Education, 22(8), 781-796. http://doi.org/10.1080/095006900412275. · DOI
  90. Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87(4), 517-538. http://doi.org/10.1002/sce.10086. · DOI
  91. Locke, E. A., & Latham, G. P. (2006). New directions in goal-setting theory. Current Directions in Psychological Science, 15(5), 265-268. http://doi.org/10.1111/j.1467-8721.2006.00449.x. · DOI · Paper page
  92. Luria, A. R. (1976). Cognitive development: Its cultural and social foundations. (M. Cole, Ed., M. Lopez-Morillas & L. Solotaroff, Trans.). Cambridge, MA, USA: Harvard University Press.
  93. Luria, A. R. (1979). The making of mind: a personal account of Soviet psychology. (M. Cole & S. Cole (Eds.)). Cambridge, MA, USA: Harvard University Press.
  94. Mahardale, J. W., & Lee, C. B. (2013). Understanding how social and epistemic scripts perpetuate intersubjectivity through patterns of interactions. Interactive Learning Environments, 21(1), 68-88. http://doi.org/10.1080/10494820.2010.547204. · DOI
  95. Matthews, M. R. (2004). Reappraising positivism and education: The arguments of Philipp Frank and Herbert Feigl. Science & Education, 13(1-2), 7-39. http://doi.org/10.1023/B:SCED.0000 018544.34295.8b. · DOI
  96. McNeill, K. L., & Krajcik, J. (2009). Synergy between teacher practices and curricular scaffolds to support students in using domain-specific and domain-general knowledge in writing argu- ments to explain phenomena. Journal of the Learning Sciences, 18(3), 416-460. http://doi. org/10.1080/10508400903013488. · DOI
  97. McNeill, K. L., Lizotte, D. J., Krajcik, J., & Marx, R. W. (2006). Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. Journal of the Learning Sciences, 15(2), 153-191. http://doi.org/10.1207/s15327809jls1502_1. · DOI · Paper page
  98. Means, B., & Gott, S. P. (1988). Cognitive task analysis as a basis for tutor development: Articu- lating abstract knowledge representations. In J. Psotka, L. D. Massey, & S. A. Mutter (Eds.), Intelligent tutoring systems: Lessons learned (pp. 35-58). Hillsdale, NJ, USA: Lawrence Erl- baum Associates.
  99. Metcalf, S. J. (1999). The design of guided learner-adaptable scaffolding in interactive learning en- vironments (PhD Dissertation). Ann Arbor, MI, USA University of Michigan, USA. Retrieved from ProQuest Dissertations & Theses Full Text. (Publication Number 9959821).
  100. Middleton, M. J., & Midgley, C. (2002). Beyond motivation: Middle school students' perceptions of press for understanding in math. Contemporary Educational Psychology, 27(3), 373-391. http://doi.org/10.1006/ceps.2001.1101. References · DOI
  101. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capac- ity for processing information. Psychological Review, 63(2), 81-97. http://doi.org/10.1037/ h0043158. · DOI · Paper page
  102. Mortimer, E. F., & Wertsch, J. V. (2003). The architecture and dynamics of intersubjectivity in science classrooms. Mind, Culture, and Activity, 10(3), 230-244. http://doi.org/10.1207/ s15327884mca1003_5. · DOI
  103. Murray, T. (1999). Authoring intelligent tutoring systems: An analysis of the state of the art. Inter- national Journal of Artificial Intelligence in Education (IJAIED), 10, 98-129.
  104. Muukkonen, H., Lakkala, M., & Hakkarainen, K. (2005). Technology-mediation and tutoring: How do they shape progressive inquiry discourse? Journal of the Learning Sciences, 14(4), 527-565. http://doi.org/10.1207/s15327809jls1404_3. · DOI
  105. Nersessian, N. J. (2008). Creating scientific concepts. Cambridge, MA, USA: MIT Press.
  106. Oh, S., & Jonassen, D. H. (2007). Scaffolding online argumentation during problem solv- ing. Journal of Computer Assisted Learning, 23(2), 95-110. http://doi.org/10.1111/j.1365- 2729.2006.00206.x. · DOI
  107. Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1(2), 117-175. http://doi. org/10.1207/s1532690xci0102_1. · DOI · Paper page
  108. Pata, K., Lehtinen, E., & Sarapuu, T. (2006). Inter-relations of tutors' and peers' scaffolding and decision-making discourse acts. Instructional Science, 34(4), 313-341. http://doi.org/10.1007/ s11251-005-3406-5. · DOI
  109. Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13(3), 423-451. http://doi.org/10.1207/s15327809jls1303_6. · DOI · Paper page
  110. Pifarre, M., & Cobos, R. (2010). Promoting metacognitive skills through peer scaffolding in a CSCL environment. International Journal of Computer-Supported Collaborative Learning, 5(2), 237-253. http://doi.org/10.1007/s11412-010-9084-6. · DOI
  111. Pressley, M., Gaskins, I. W., Solic, K., & Collins, S. (2006). A portrait of Benchmark School: How a school produces high achievement in students who previously failed. Journal of Educational Psychology, 98(2), 282-306. http://doi.org/10.1037/0022-0663.98.2.282. · DOI
  112. Pritchard, D. E., Barrantes, A., & Belland, B. R. (2009). What else (besides the syllabus) should students learn in introductory physics? In M. Sabella, C. Henderson, & C. Singh (Eds.), Pro- ceedings of the annual conference of the American Institute of Physics (pp. 43-46). Ann Arbor, MI, USA: American Institute of Physics. http://doi.org/10.1063/1.3266749. · DOI
  113. Puntambekar, S., & Hübscher, R. (2005). Tools for scaffolding students in a complex learning environment: What have we gained and what have we missed? Educational Psychologist, 40, 1-12. http://doi.org/10.1207/s15326985ep4001_1. · DOI · Paper page
  114. Puntambekar, S., & Kolodner, J. L. (2005). Toward implementing distributed scaffolding: Helping students learn science from design. Journal of Research in Science Teaching, 42(2), 185-217. http://doi.org/10.1002/tea.20048. · DOI
  115. Quintana, C., Krajcik, J., & Soloway, E. (2003). Issues and approaches for developing learner- centered technology. Advances in Computers, 57, 271-321. http://doi.org/10.1016/S0065- 2458(03)57006-1. · DOI
  116. Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., Kyza, E., Edelson, D., & Soloway, E. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13(3), 337-386. http://doi.org/10.1207/s15327809jls1303_4. · DOI
  117. Raes, A., Schellens, T., De Wever, B., & Vanderhoven, E. (2012). Scaffolding information problem solving in web-based collaborative inquiry learning. Computers & Education, 59(1), 82-94. http://doi.org/10.1016/j.compedu.2011.11.010. · DOI
  118. Raphael, L. M., Pressley, M., & Mohan, L. (2008). Engaging instruction in middle school class- rooms: An observational study of nine teachers. The Elementary School Journal, 109(1), 61- 81. http://doi.org/10.1086/592367. · DOI
  119. Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problema- tizing student work. Journal of the Learning Sciences, 13(3), 273-304. http://doi.org/10.1207/ s15327809jls1303_2. · DOI · Paper page
  120. Rodgers, E. M. (2004). Interactions that scaffold reading performance. Journal of Literacy Re- search, 36(4), 501-532. http://doi.org/10.1207/s15548430jlr3604_4. · DOI
  121. Rogoff, B., & Toma, C. (1997). Shared thinking: Community and institutional variations. Dis- course Processes, 23(3), 471-497. http://doi.org/10.1080/01638539709545000. · DOI
  122. Roth, W. (2012). Science of learning is learning of science: Why we need a dialectical approach to science education research. Cultural Studies of Science Education, 7(2), 255-277. http://doi. org/10.1007/s11422-012-9390-6. · DOI
  123. Roth, W., & Lee, Y. (2007). "Vygotsky's neglected legacy": Cultural-historical activity theory. Review of Educational Research, 77(2), 186-232. http://doi.org/10.3102/0034654306298273. · DOI
  124. Sabet, M. K., Tahriri, A., & Pasand, P. G. (2013). The impact of peer scaffolding through process approach on EFL learners' academic writing fluency. Theory & Practice in Language Studies, 3(10), 1893-1901. http://doi.org/10.4304/tpls.3.10.1893-1901. · DOI
  125. Saffi, S. (2005). Discussion de l'arbitraire du signe: Quand le hasard occulte la relation entre le physique et le mental [Discussion of the arbitrariness of the sign: When chance hides the re- lationship between the physical and the mental]. Italies. Littérature-Civilisation-Société, 9, 345-394. http://doi.org/10.4000/italies.487. · DOI
  126. Saye, J. W., & Brush, T. (2002). Scaffolding critical reasoning about history and social issues in multimedia-supported learning environments. Educational Technology Research and Develop- ment, 50(3), 77-96. http://doi.org/10.1007/BF02505026. · DOI · Paper page
  127. Seethaler, P. M., Fuchs, L. S., Fuchs, D., & Compton, D. L. (2012). Predicting first graders' de- velopment of calculation versus word-problem performance: The role of dynamic assessment. Journal of Educational Psychology, 104(1), 224-234. http://doi.org/10.1037/a0024968. · DOI
  128. Self, J. (1998). The defining characteristics of intelligent tutoring systems research: ITSs care, precisely. International Journal of Artificial Intelligence in Education (IJAIED), 10, 350-364.
  129. Simons, K. D., & Ertmer, P. A. (2006). Scaffolding disciplined inquiry in problem-based learning environments. International Journal of Learning, 12(6), 297-305.
  130. Skinner, B. F. (1984). The phylogeny and ontogeny of behavior. Behavioral and Brain Sciences, 7(4), 669-711. http://doi.org/10.1017/S0140525X00027990. · DOI
  131. Smagorinsky, P. (1995). The social construction of data: Methodological problems of investigat- ing learning in the zone of proximal development. Review of Educational Research, 65(3), 191-212. http://doi.org/10.3102/00346543065003191. · DOI
  132. Solomon, D. L. (2000). Toward a post-modern agenda in instructional technology. Educational Technology Research and Development, 48(4), 5-20. http://doi.org/10.1007/BF02300497. · DOI
  133. Songer, N. B., & Linn, M. C. (1991). How do students' views of science influence knowledge integration? Journal of Research in Science Teaching, 28(9), 761-784. http://doi.org/10.1002/ tea.3660280905. · DOI
  134. Spada, H. (1994). Conceptual change or multiple representations? Learning and Instruction, 4(1), 113-116. http://doi.org/10.1016/0959-4752(94)90021-3. · DOI
  135. Tabak, I. (2004). Synergy: A complement to emerging patterns of distributed scaffolding. Journal of the Learning Sciences, 13(3), 305-335. http://doi.org/10.1207/s15327809jls1303_3. · DOI
  136. Taber, K. S. (2008). Conceptual resources for learning science: Issues of transience and grain- size in cognition and cognitive structure. International Journal of Science Education, 30(8), 1027-1053. http://doi.org/10.1080/09500690701485082. The Cognition and Technology Group at Vanderbilt. (1990). Anchored instruction and its relation- ship to situated cognition. Educational Researcher, 19(6), 2-10. http://doi.org/10.3102/00131 89x019006002. · DOI
  137. Tzuriel, D. (2000). Dynamic assessment of young children: Educational and intervention perspectives. Educational Psychology Review, 12(4), 385-435. http://doi.org/10.1023 /A:1009032414088. · DOI
  138. Van de Pol, J., Volman, M., & Beishuizen, J. (2011). Patterns of contingent teaching in teacher- student interaction. Learning and Instruction, 21(1), 46-57. http://doi.org/10.1016/j.learnin- struc.2009.10.004. · DOI
  139. Van de Pol, J., Volman, M., & Beishuizen, J. (2012). Promoting teacher scaffolding in small-group work: A contingency perspective. Teaching and Teacher Education, 28(2), 193-205. http://doi. org/10.1016/j.tate.2011.09.009. · DOI
  140. Vosniadou, S., Ioannides, C., Dimitrakopoulou, A., & Papademetriou, E. (2001). Designing learn- ing environments to promote conceptual change in science. Learning and Instruction, 11(4-5), 381-419. http://doi.org/10.1016/S0959-4752(00)00038-4. · DOI
  141. Vygotsky, L. S. (1962). Thought and language. Cambridge, MA, USA: MIT Press.
  142. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cam- bridge, MA, USA: Harvard University Press.
  143. Wertsch, J. V. (1984). The zone of proximal development: Some conceptual issues. New Di- rections for Child and Adolescent Development, 1984(23), 7-18. http://doi.org/10.1002/ cd.23219842303. · DOI
  144. Wertsch, J. V. (1991). Voices of the mind: A sociocultural approach to mediated action. Cam- bridge, MA, USA: Harvard University Press.
  145. Wood, D. (2003). The why? What? When? and How? of tutoring: The development of helping and tutoring skills in children. Literacy Teaching and Learning, 7(1), 1-30.
  146. Wood, D., & Wood, H. (1996). Vygotsky, tutoring and learning. Oxford Review of Education, 22(1), 5-16. http://doi.org/10.1080/0305498960220101. · DOI

Cited by

Sorted by citations

Authors
Belland, B. R.
Affiliations
Utah State University (US)
Corresponding author
Belland, Brian R.
ORCID
Belland, Brian R.
Venue
Instructional Scaffolding in STEM Education
Publisher
Springer International Publishing
Published
2016-10-04
Pages
17-53
DOI
10.1007/978-3-319-02565-0_2
OpenAlex
W2528641039
Cited by
40
References
17
Citations by year
2026: 4 · 2025: 5 · 2024: 9 · 2023: 3 · 2022: 6 · 2021: 4 · 2020: 4 · 2019: 2 · 2018: 3
FWCI
4.45
Type
book chapter
Language
en
Open access
Licence
Locations
Springer eBooks (publishedVersion, cc-by-nc)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
instructional scaffolding, fading, activity theory, ACT-R, knowledge integration

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