The triarchic theory of intelligence and computer-based inquiry learning

Educational Technology Research and Development

Volumn 49, Issue 4, 2001, Pages 49-69

  Howard, Bruce C ^a   McGee, Steven ^a   Shin, Namsoo ^a   Shia, Regina ^a  

^a WHEELING JESUIT UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0035648384     PISSN: 10421629     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02504947     Document Type: Article

References (56)

1. American Association for the Advancement of Science. (1993). Benchmarks for science literacy: Project 2061. New York: Oxford University Press.
2. Baxter, G.P., Glaser R., & Raghavan, K. (1993). Analysis of cognitive demand in selected alternative science assessments. Pittsburgh, PA: CRESST/Learning Research and Development Center. (ERIC Document Reproduction Service No. ED 368 776)
3. Bell, P., Davis, E.A., & Linn, M.C. (1995). The knowledge integration environment: Theory and design. University of California, Berkeley.
4. Brown, A.L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The Journal of the Learning Sciences, 2(2), 141-178.
5. Brown, J.S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42.
6. Collins, A. (1992). Toward a design science of education. In E. Scanlon & T. O'Shea (Eds.), New directions in educational technology. New York: Springer-Verlag.
7. Cognition and Technology Group at Vanderbilt (CTGV). (1993). Integrated media: Toward a theoretical framework for utilizing their potential. Journal of Special Education Technology, 12(2), 76-89.
8. Cronbach, L.J., & Snow, R.E. (1977). Aptitudes and instructional methods. New York: Irvington.
9. Fraser, B.J. (1978). Development of a test of science-related attitudes. Science Education, 62, 509-515.
10. Gall, M.D., Borg, W.R., & Gall, J.P. (1996) Educational research: An introduction (6th ed.). New York: Longman Publisher.
11. Gardner, H., Krechevsky, M., Sternberg, R.J., & Okagaki, L. (1994). Intelligence in context: Enhancing students' practical intelligence for school. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 105-127). Cambridge, MA: Bradford Books.
12. Grabinger, R.S. (1996). Rich environments for active learning. In D.H. Jonassen (Ed.), Handbook of research for educational communications and technology: A project of the Association for Educational Communication and Technology (pp. 665-692). New York: Simon and Schuster MacMillan.
13. Gredler, M.E. (1996). Educational games and simulations: A technology in search of a (research) paradigm. In D.H. Jonassen (Ed.), Educational communications and technology. New York: Simon & Schuster Macmillan.
14. Haladyna, T., & Shaughnessy. J., (1982). Attitudes towards science: A quantitative synthesis. Science Education, 66, 547-563.
15. Hong, N. (1998). The relationship between well-structured and ill-structured problem solving in multimedia simulation. Unpublished doctoral dissertation. The Pennsylvania State University, State College.
16. Hong, N.S., Jonassen, D.H., & McGee, S. (in press). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching.
17. Jonassen, D.H. (1997). Instruction design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65-94.
18. Jonassen, D.H., & Reeves, T.C. (1996). Learning with technology: Using computers as cognitive tools. In D.H. Jonassen (Ed.), Handbook of research for educational communications and technology. New York: Simon and Schuster Macmillan.
19. Julyan, C. (1991). Getting connected to science. Hands On! 14(1), 4-7.
20. Klopfer, L.E. (1971). Evaluation of learning in science. In B.S. Bloom, J.T. Hastings, & G.F. Madaus (Eds.), Handbook on summative and formative evaluation of student learning. New York: McGraw-Hill.
21. Lane, S. (1993). The conceptual framework for the development of a mathematics performance assessment instrument. Educational Measurement: Issues and Practice, 12(2), 6-13.
22. Linn, M.C. (1995). Designing computer learning environments for engineering and computer science: The scaffolded knowledge integration framework. Journal of Science Education and Technology, 4(2), 103-126.
23. Linn, M.C. (1996). Key to the information highway. Communications of the AMC, 39, 34-35.
24. Linn, M.C., & Songer, N.B. (1991). Teaching thermodynamics to middle school students: What are appropriate cognitive demands? Journal of Research in Science Teaching, 28, 885-918.
25. Maor, D., & Fraser, B.F. (1996). Use of classroom environment perceptions in evaluating inquiry-based computer assisted learning. International Journal of Science Education, 18(4), 401-421.
26. ™. [On-line]. Retrieved December 15, 2000: http://www.cet.edu/research/papers.
27. McGee, S., & Howard, B.C. (1999, June). Using design experiments as a means of guiding software development. Paper presented at the annual ED-MEDIA conference, sponsored by the Association for the Advancement of Computing in Education. Seattle, WA.
28. McGee, S., & Howard, B.C. (2000). Testing educational theory through educational practice: A framework for the design of inquiry-based multimedia learning environments [Unpublished manuscript, on-line]. Retrieved December 15, 2000: http://www.cet.edu/research/papers.
29. Means, B., & Olson, K., (1997). Technology and education reform: Studies of education reform. Office of Educational Research and Improvement, U.S. Department of Education.
30. Moore, R., & Foy, R.L.H. (1996). The scientific attitude inventory: A revision (SAI II). Journal of Science Teaching, 34(4), 327-336.
31. Newman, D. (1990). Opportunities for research on the organizational impact of school computers. Educational Researcher, 19(3), 8-13.
32. Newman, D. (1992). Technology as support for school structure and school restructuring. Phi Delta Kappan, 308-315.
33. Norusis, M. (1994). SPSS advanced statistics 6.1. Chicago: SPSS Inc.
34. Pompea, S.M., & Blurton, C. (1995, Jan/Feb). A walk through the Astronomy Village. Mercury, 32-33.
35. Robitaille, D.F., Schmidt, W.H., Raizen, S., McKnight, C., Britton, E., & Nicol, C. (1993). Curriculum frameworks for mathematics and science. Vancouver, Canada: Pacific Educational Press.
36. Scardamalia, M., & Bereiter, C. (1993). Technologies for knowledge-building discourse. Communications of the AMC, 36(5), 37-41.
37. Simon, H.S. (1981). The psychology of scientific problem solving. In R.D. Tweney, M.E. Doherty, & C.R. Mynalt (Eds.), On scientific thinking (pp. 41-54). New York: Columbia University Press.
38. Simonson, M., & Maushak, N. (1996). Instructional technology and attitude change. In D.H. Jonassen (Ed.), Handbook of research for educational communications and technology: A project of the Association for Educational Communication and Technology (pp. 984-1016). New York: Simon and Schuster Macmillan.
39. Smist, J.M., Archambault, F.X., & Owen, S.V. (1994, April). Gender differences in attitude toward science. Paper presented at the meeting of National Council on Measurement in Education, New Orleans, LA.
40. Sternberg, R.J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press.
41. Sternberg, R.J. (1991). Theory-based testing of intellectual abilities: Rationale for the triarchic abilities test. In H. Rowe (Ed.), Intelligence: Reconceptualization and measurement (pp. 183-202). Hillsdale, NJ: Lawrence Erlbaum.
42. Sternberg, R.J. (1992). Sternberg triarchic abilities test. Unpublished test.
43. Sternberg, R.J. (1996). Successful intelligence: How practical and creative intelligence determine success in life. New York: Plume.
44. Sternberg, R.J. (1997, March). What does it mean to be smart? Educational Leadership, 20-24.
45. Sternberg, R.J. (1998a). Applying the triarchic theory of human intelligence in the classroom. In R.J. Sternberg and W.M. Williams (Eds.), Intelligence, instruction, and assessment. Mahwah, New Jersey: Lawrence Erlbaum Associates.
46. Sternberg, R.J. (1998b). Principles of teaching for successful intelligence. Educational Psychologist, 33(2/3), 65-72.
47. Sternberg, R.J., & Clinkenbeard, P. (1995). The triarchic model applied to identifying, teaching, and assessing gifted children. Roeper Review, 17(4), 255-260.
48. Sternberg, R.J., Ferrari, M., Clinkenbeard, P., & Grigorenko, E.L. (1996). Identification, instruction, and assessment of gifted children: A construct validation of a triarchic model. Gifted Children Quarterly, 40, 129-137.
49. Sternberg, R.J., Grigorenko, E.L., Ferrari, M., & Clinkenbeard, P. (1999). A triarchic analysis of an aptitude-treatment interaction. European Journal of Psychological Assessment, 15(1), 1-11.
50. Sternberg, R.J., & Spear-Swerling, L. (1996). Teaching for thinking. Washington, DC: American Psychological Association.
51. Sternberg, R.J., Torff, B., & Grigorenko, E.L. (1998). Teaching triarchically improves school achievement. Journal of Educational Psychology, 90(3), 374-384.
52. Sternberg, R.J., Wagner, R.K., Williams, W.M., & Horvath, J.A. (1995). Testing common sense. American Psychologist, 50, 912-927.
53. Sternberg, R.J., & Williams, W.M (1997). Does the graduate record examination predict meaningful success in the graduate training of psychologists? American Psychologist, 634-641.
54. White, B.Y., & Frederiksen, J.R. (1995). The ThinkerTools inquiry project: Making scientific inquiry accessible to si udents and teachers (Causal Models Research Group Report CM-95-02). University of California at Berkeley, School of Education.
55. White, B.Y., & Frederiksen, J.R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16, 3-118.
56. Yager, R.E. (1995). Constructivism and the learning of science. In S.M. Glynn & R. Duit (Eds.), Learning science in the schools: Research reforming practice (pp. 35-57). Mahwah, NJ: Lawrence Erlbaum.