Paraphrasing and prediction with self-explanation as generative strategies for learning science principles in a simulation

Educational Technology Research and Development

Volumn 63, Issue 6, 2015, Pages 861-882

  Morrison, Jennifer R ^a   Bol, Linda ^b   Ross, Steven M ^a   Watson, Ginger S ^b  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b OLD DOMINION UNIVERSITY   (United States)

Author keywords

Calibration; Cognitive load; Guided discovery; Instructional simulations; Mental effort; Principle learning; Self regulation

Indexed keywords

EID: 84947494783     PISSN: 10421629     EISSN: 15566501     Source Type: Journal    
DOI: 10.1007/s11423-015-9397-2     Document Type: Article

References (73)

1. Afflerbach, P. (1990). The influence of prior knowledge and text genre on readers’ prediction strategies. Journal of Literacy Research,22(2), 131–148.
2. Afflerbach, P., & Walker, B. (1990). Prediction instruction in basal readers. Reading Research and Instruction,29(4), 26–45. doi:10.1080/19388079009558022.
3. Alessi, S., & Trollip, S. R. (2001). Multimedia for learning: Methods and development (3rd ed.). Boston, MA: Allyn & Bacon.
4. Alfieri, L., Brooks, P. J., Aldrich, N. J., & Tenenbaum, H. R. (2011). Does discovery-based instruction enhance learning? Journal of Educational Psychology,103(1), 1–18. doi:10.1037/a0021017.
5. Anderson, R. C., & Pearson, P. D. (1984). A schema-theoretic view of basic processes in reading comprehension. In P. D. Pearson, R. Barr, M. L. Kamil, & P. Modenthal (Eds.), Handbook of reading research (Vol. 1, pp. 255–291). White Plains, NY: Longman.
6. Bangert-Drowns, R. L., Kulik, J., & Kulik, C. (1985). Effectiveness of computer-based education in secondary schools. Journal of Computer-Based Instruction,12, 59–68.
7. Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology,64, 417–444.
8. Bol, L., & Garner, J. (2011). The challenges of supporting self-regulation in distance education environments. Journal of Computing in Higher Education, 23(2–3), 104–123.
9. Bol, L., & Hacker, D. J. (2001). A comparison of the effects of practice tests and traditional review on performance and calibration. The Journal of Experimental Education, 69(2), 133–151. doi:10.1080/00220970109600653.
10. Bol, L., Hacker, D. J., O’Shea, P., & Allen, D. (2005). The influence of overt practice, achievement level, and explanatory style on calibration accuracy and performance. The Journal of Experimental Education, 73(4), 269–290.
11. Bol, L., Hacker, D. J., Walck, C. C., & Nunnery, J. A. (2012). The effects of individual or group guidelines on the calibration accuracy and achievement of high school biology students. Contemporary Educational Psychology, 37(4), 280–287. doi:10.1016/j.cedpsych.2012.02.004.
12. Bretzing, B. H., & Kulhavy, R. W. (1979). Notetaking and depth of processing. Contemporary Educational Psychology,4(2), 145–153. doi:10.1016/0361-476X(79)90069-9.
13. Byrne, M. D., Catrambone, R., & Stasko, J. T. (1999). Evaluating animations as student aids in learning computer algorithms. Computers & Education,33(4), 253–278. doi:10.1016/S0360-1315(99)00023-8.
14. Chi, M. T. H. (2009). Active-constructive-interactive: A conceptual framework for differentiating learning activities. Topics in Cognitive Science,1, 73–105. doi:10.1111/j.1756-8765.2008.01005.x.
15. Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science,13(2), 145–182. doi:10.1016/0364-0213(89)90002-5.
16. Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science,18(3), 439–477. doi:10.1016/0364-0213(94)90016-7.
17. Chi, M. T. H., & VanLehn, K. A. (1991). The content of physics self-explanations. The Journal of the Learning Sciences,1(1), 69–105.
18. Clark, D., & Linn, M. C. (2003). Designing for knowledge integration: The impact of instructional time. The Journal of the Learning Sciences,12(4), 451–493.
19. Collins, A., Brown, J. S., & Larkin, K. M. (1980). Inferences in text understanding. In R. J. Spiro, B. C. Bruce, & W. F. Brewer (Eds.), Theoretical issues in reading comprehension (pp. 385–407). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
20. Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior,11(6), 671–684.
21. Davey, B., & McBride, S. (1986). Effects of question-generation training on reading comprehension. Journal of Educational Psychology,78(4), 256–262. doi:10.1037/0022-0663.78.4.256.
22. de Bruin, A. B. H., Rikers, R. M. J. P., & Schmidt, H. G. (2007). The effect of self-explanation and prediction on the development of principled understanding of chess in novices. Contemporary Educational Psychology,32(2), 188–205. doi:10.1016/j.cedpsych.2006.01.001.
23. de Jong, T. (2006). Scaffolds for scientific discovery learning. In J. Elen & R. E. Clark (Eds.), Handling complexity in learning environments: Theory and research (pp. 107–128). London: Elsevier.
24. de Jong, T., & van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research,68(2), 179–201. doi:10.3102/00346543068002179.
25. Freeman, R. H. (1982). Improving the comprehension of stories using predictive strategies. Paper presented at the Annual Meeting of the International Reading Association, Chicago, IL.
26. Gerjets, P., Scheiter, K., & Catrambone, R. (2006). Can learning from molar and modular worked examples be enhanced by providing instructional explanations and prompting self-explanations? Learning and Instruction,16(2), 104–121. doi:10.1016/j.learninstruc.2006.02.007.
27. Glover, J. A., Plake, B. S., Roberts, B., Zimmer, J. W., & Palmere, M. (1981). Distinctiveness of encoding: The effects of paraphrasing and drawing inferences on memory from prose. Journal of Educational Psychology,73(5), 736–744. doi:10.1037/0022-0663.73.5.736.
28. Glover, J. A., Timme, V., Deyloff, D., Rogers, M., & Dinell, D. (1987). Oral directions: Remembering what to do when. Journal of Educational Research,81(1), 33–40.
29. Grimes, P. W. (2002). The overconfident principles of economics students: An examination of a metacognitive skill. The Journal of Economic Education,33, 15–30.
30. Hacker, D. J., Bol, L., & Bahbahani, K. (2008). Explaining calibration accuracy in classroom contexts: The effects of incentives, reflection, and explanatory style. Metacognition and Learning, 3(2), 101–121. doi:10.1007/s11409-008-9021-5.
31. Hacker, D. J., Bol, L., Horgan, D. D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160–170. doi:10.1037/0022-0663.92.1.160.
32. Hansen, J. (1981). The effects of inference training and practice on young children’s reading comprehension. Reading Research Quarterly,16(3), 391–417.
33. Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of experimental and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139–183). Amsterdam: North Holland.
34. Hegarty, M., Kriz, S., & Cate, C. (2003). The roles of mental animations and external animations in understanding mechanical systems. Cognition and Instruction,2(4), 325–360.
35. Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: A response to Kirschner, Sweller, and Clark (2006). Educational Psychologist,42(2), 99–107. doi:10.1080/00461520701263368.
36. Jonassen, D. H. (1988). Integrating learning strategies into courseware to facilitate deeper processing. In D. Jonassen (Ed.), Instructional designs for microcomputer courseware (pp. 151–181). Hillsdale, NJ: Lawrence Erlbaum Associates.
37. Jonassen, D. H., & Ionas, I. G. (2008). Designing effective supports for causal reasoning. Educational Technology Research and Development,56, 287–308. doi:10.1007/s11423-006-9021-6.
38. Kasmer, L., & Kim, O.-K. (2011). Using prediction to promote mathematical understanding and reasoning. School Science and Mathematics,111(1), 20–33.
39. Keren, G. (1991). Calibration and probability judgements: Conceptual and methodological issues. Acta Psychologica,77(3), 217–273. doi:10.1016/0001-6918(91)90036-Y.
40. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist,41(2), 75–86. doi:10.1207/s15326985ep4102_1.
41. Kulik, C.-L. C., & Kulik, J. A. (1991). Effectiveness of computer-based instruction: An updated analysis. Computers in Human Behavior,7(1–2), 75–94. doi:10.1016/0747-5632(91)90030-5.
42. Linn, M. C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah, NJ: Lawrence Erlbaum Associates Inc.
43. Maki, R. H., Foley, J. M., Kajer, W. K., Thompson, R. C., & Willert, M. G. (1990). Increased processing enhances calibration of comprehension. Journal of Experimental Psychology. Learning, Memory, and Cognition,16(4), 609–616. doi:10.1037/0278-7393.16.4.609.
44. Markle, S. M. (1969). Good frames and bad: A grammar of frame writing. New York: Wiley.
45. Mayer, R. E. (2004). Should there be a three strikes rule against pure discovery learning? The case for guided methods of instruction. American Psychologist,59, 14–19.
46. McNamara, D. S., & Magliano, J. P. (2009). Self-explanation and metacognition: The dynamics of reading. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 60–82). New York: Routledge.
47. Morrison, G. R., & Anglin, G. J. (2005). Research on cognitive load theory: Application to e-learning. Educational Technology Research and Development,53(3), 94–104.
48. Okada, T., & Simon, H. A. (1997). Collaborative discovery in a scientific domain. Cognitive Science,21(2), 109–146. doi:10.1207/s15516709cog2102_1.
49. Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and monitoring activities. Cognition & Instruction,1, 117–175.
50. Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education,66, 211–227.
51. Pressley, M., & Ghatala, E. S. (1990). Self-regulated learning: Monitoring learning from text. Educational Psychologist,25, 19–33.
52. Reigeluth, C. M., & Schwartz, E. (1989). An instructional theory for the design of computer-based simulations. Journal of Computer-Based Instruction,16(1), 1–10.
53. Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science,21(1), 1–29. doi:10.1207/s15516709cog2101_1.
54. Renkl, A. (2002). Worked-out examples: instructional explanations support learning by self-explanations. Learning and Instruction,12(5), 529–556.
55. Rummelhart, D. E., & Ortony, A. (1977). The representation of knowledge in memory. In R. C. Anderson, R. J. Spiro, & W. E. Montague (Eds.), Schooling and the acquisition of knowledge. Mahwah, NJ: Lawrence Erlbaum Associates.
56. Salomon, G. (1981). Communication and education: Social and psychological interactions. Beverly Hills, CA: Sage Publications.
57. Schommer, M., & Surber, J. R. (1986). Comprehension-monitoring failure in skilled adult readers. Journal of Educational Psychology,78(5), 353–357. doi:10.1037/0022-0663.78.5.353.
58. Schraw, G. (2009). Measuring metacognitive judgments. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 415–429). New York: Routledge.
59. Sweller, J. (1999). Instructional design in technical areas. Camberwell, VIC: The Australian Council for Educational Research Ltd.
60. Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review,22(2), 123–138. doi:10.1007/s10648-010-9128-5.
61. Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer.
62. Thiede, K. W., & Anderson, M. C. M. (2003). Summarizing can improve metacomprehension accuracy. Contemporary Educational Psychology,28(2), 129–160. doi:10.1016/S0361-476X(02)00011-5.
63. Tuovinen, J. E., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Educational Psychology,91(2), 334–341. doi:10.1037/0022-0663.91.2.334.
64. Van Loon, M. H., de Bruin, A. B. H., van Gog, T., & van Merrienboer, J. J. G. (2013). Activation of inaccurate prior knowledge affects primary-school students’ metacognitive judgments and calibration. Learning and Instruction,24, 15–25.
65. Van Loon, M. H., de Bruin, A. B. H., van Gog, T., van Merrienboer, J. J. G., & Dunlosky, J. (2014). Can students evaluate their understanding of cause-and-effect relations? The effects of diagram completion on monitoring accuracy. Acta Psychologica,151, 143–154.
66. Winne, P. H. (2004). Students’ calibration of knowledge and learning processes: Implications for designing powerful software learning environments. International Journal of Educational Research,41, 466–488.
67. Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In J. Dunlosky & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah, NJ: Lawrence Erlbaum Associates.
68. Wittrock, M. C. (1974). Learning as a generative process. Educational Psychologist,19(2), 87–95. doi:10.1080/00461520903433554.
69. Wittrock, M. C. (1979). The cognitive movement in instruction. Educational Researcher,8(2), 5–11. doi:10.3102/0013189X008002005.
70. Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist,24, 345–376. doi:10.1207/s15326985ep2404_2.
71. Wittrock, M. C., & Alesandrini, K. (1990). Generation of summaries and analogies and analytic and holistic abilities. American Educational Research Journal,27(3), 489–502.
72. Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology,11(4), 307–313. doi:10.1016/0361-476X(86)90027-5.
73. Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts & P. R. Pintrich (Eds.), Handbook of self-regulation (pp. 13–39). New York: Academic Press.