Erratum to: Using Avida-ED for teaching and learning about evolution in undergraduate introductory biology courses (Evolution: Education and Outreach (2009) 2:3 DOI: 10.1007/s12052-009-0154-z);Using Avida-ED for Teaching and Learning about Evolution in Undergraduate Introductory Biology Courses

Evolution: Education and Outreach

Volumn 2, Issue 3, 2008, Pages 415-428

  Bray Speth, Elena ^a   Long, Tammy M ^a   Pennock, Robert T ^a   Ebert May, Diane ^a  

^a MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Assessment; Avida ED; Complex systems thinking; Digital evolution; Evolution education; Instructional design

Indexed keywords

EID: 85067105321     PISSN: 19366426     EISSN: 19366434     Source Type: Journal    
DOI: 10.1007/s12052-009-0169-5     Document Type: Erratum

References (52)

1. Ainsworth S. The functions of multiple representations. Comput Educ. 1999;33:131-52.
2. Alters BJ, Nelson CE. Perspective: teaching evolution in higher education. Evolution. 2002;56:1891-901.
3. Anderson LW, Krathwohl DR, Bloom BS. A taxonomy for learning, teaching, and assessing: a revision of Bloom's taxonomy of educational objectives. New York: Longman; 2001.
4. Anderson DL, Fisher KM, Norman GJ. Development and evaluation of the conceptual inventory of natural selection. J Res Sci Teach. 2002;39:952-78.
5. Bar-Yam Y. Dynamics of complex systems. Boulder: Westview; 2003.
6. Bishop BA, Anderson CW. Student conceptions of natural selection and its role in evolution. J Res Sci Teach. 1990;27:415-27.
7. Bloom BS. Taxonomy of educational objectives; the classification of educational goals. New York: D. McKay; 1956.
8. Bodemer D, Ploetzner R, Bruchmuller K, Hacker S. Supporting learning with interactive multimedia through active integration of representations. Instr Sci. 2005;33:73-95.
9. Chi MTH, Feltovich PJ, Glaser R. Categorization and representation of physics problems by experts and novices. Cogn Sci. 1981;5:121-52.
10. Dagher ZR, BouJaoude S. Students' perceptions of the nature of evolutionary theory. Sci Educ. 2005;89:378-91.
11. Dobzhansky T. Nothing in biology makes sense except in the light of evolution. Am Biol Teach. 1973;35:125-9.
12. Ebert-May D, Hodder J. Pathways to scientific teaching. Sunderland: Sinauer Associates; 2008.
13. Evagorou M, Korfiatis K, Nicolaou C, Constantinou C. An investigation of the potential of interactive simulations for developing system thinking skills in elementary school: a case study with fifth-graders and sixth-graders. Int J Sci Educ. 2009;31:655-74.
14. Fields S, Johnston M. Cell biology: whither model organism research? Science. 2005;307:1885-6.
15. Goldstone RL, Wilensky U. Promoting transfer by grounding complex systems principles. J Learn Sci. 2008;17:465-516.
16. Handelsman J, Ebert-May D, Beichner R, Bruns P, Chang A, DeHaan R, et al. Scientific teaching. Science. 2004;304:521-2.
17. Handelsman J, Miller S, Pfund C. Scientific teaching. New York: W.H. Freeman; 2006.
18. Hang DH, Torng E, Ofria C, Schmidt TM. The effect of natural selection on the performance of maximum parsimony. BMC Evol Biol. 2007;7:94.
19. Hmelo-Silver CE, Azevedo R. Understanding complex systems: some core challenges. J Learn Sci. 2006;15:53-61.
20. Hokayem H, BouJaoude S. College students' perceptions of the theory of evolution. J Res Sci Teach. 2008;45:395-419.
21. Jacobson MJ, Wilensky U. Complex systems in education: scientific and educational importance and implications for the learning sciences. J Learn Sci. 2006;15:11-34.
22. Jensen MS, Finley FN. Changes in students' understanding of evolution resulting from different curricular and instructional strategies. J Res Sci Teach. 1996;33:879-900.
23. Kozma RB, Russell J. Multimedia and understanding: expert and novice responses to different representations of chemical phenomena. J Res Sci Teach. 1997;34:949-68.
24. Larkin J, McDermott J, Simon DP, Simon HA. Expert and novice performance in solving physics problems. Science. 1980;208:1335-42.
25. Lederman NG. Students' and teachers' conceptions of the nature of science: a review of the research. J Res Sci Teach. 1992;29:331-59.
26. Lenski RE, Ofria C, Pennock RT, Adami C. The evolutionary origin of complex features. Nature. 2003;423:139-44.
27. National Academy of Science. Teaching about evolution and the nature of science. Washington: National Academies; 1998.
28. National Research Council. How people learn: brain, mind, experience, and school. Washington: National Academies; 2000.
29. National Research Council. Knowing what students know: the science and design of educational assessment. Washington: National Academies; 2001.
30. National Research Council. Bio 2010: transforming undergraduate education for future research biologists. Washington: National Academies; 2003.
31. National Research Council. How students learn: science in the classroom. Washington: National Academies; 2005.
32. National Research Council. The role of theory in advancing 21st-century biology: catalyzing transformative research. Washington: National Academies; 2008.
33. Nehm RH, Reilly L. Biology majors' knowledge and misconceptions of natural selection. Bioscience. 2007;57:263-72.
34. Nehm RH, Schonfeld IS. Measuring knowledge of natural selection: a comparison of the CINS, an open-response instrument, and an oral interview. J Res Sci Teach. 2008;45:1131-60.
35. Nelson CE. Teaching evolution (and all of biology) more effectively: strategies for engagement, critical reasoning, and confronting misconceptions. Integr Comp Biol. 2008;48:213-25.
36. Nunez F, Banet E. Students' conceptual patterns of human nutrition. Int J Sci Educ. 1997;19:509-26.
37. Ofria C, Wilke CO. Avida: a software platform for research in computational evolutionary biology. Artif Life. 2004;10:191-229.
38. Ofria C, Huang W, Torng E. On the gradual evolution of complexity and the sudden emergence of complex features. Artif Life. 2008;14:255-63.
39. Pennock RT. On teaching evolution and the nature of science. In: Cracraft J, Bybee R, editors. Evolutionary science and society: educating a new generation. Colorado Springs: Biological Sciences Curriculum Study; 2005. p. 1-12.
40. Pennock RT. Learning evolution and the nature of science using evolutionary computing and artificial life. McGill J Educ. 2007a;42:211-24.
41. Pennock RT. Models, simulations, instantiations, and evidence: the case of digital evolution. J Exp Theor Artif Intell. 2007b;19:29-42.
42. Smith KA, Sheppard SD, Johnson DW, Johnson RT. Pedagogies of engagement: classroom-based practices. J Eng Educ. 2005;94:87-101.
43. Songer CJ, Mintzes JJ. Understanding cellular respiration - an analysis of conceptual change in college biology. J Res Sci Teach. 1994;31:621-37.
44. Stewart J, Rudolph JL. Considering the nature of scientific problems when designing science curricula. Sci Educ. 2001;85:207-22.
45. Timmerman BE, Strickland DC, Carstensen SM. Curricular reform and inquiry teaching in biology: where are our efforts most fruitfully invested? Integr Comp Biol. 2008;48:226-40.
46. Verhoeff RP, Waarlo AJ, Boersma KT. Systems modelling and the development of coherent understanding of cell biology. Int J Sci Educ. 2008;30:543-68.
47. West CK, Farmer JA, Wolff PM. Instructional design: implications from cognitive science. Englewood Cliffs: Prentice Hall; 1991.
48. Wiggins GP, McTighe J. Understanding by design. Alexandria: Association for Supervision and Curriculum Development; 1998.
49. Wilensky U, Resnick M. Thinking in levels: a dynamic systems approach to making sense of the world. J Sci Educ Technol. 1999;8:3-19.
50. Wilke CO, Adami C. The biology of digital organisms. Trends Ecol Evol. 2002;17:528-32.
51. Wyckoff S. Changing the culture of undergraduate science teaching. J Coll Sci Teach. 2001;30:306-12.
52. Yedid G, Ofria CA, Lenski RE. Historical and contingent factors affect re-evolution of a complex feature lost during mass extinction in communities of digital organisms. J Evol Biol. 2008;21:1335-57.