Journal of Science Education and Technology

, Volume 24, Issue 6, pp 803–817 | Cite as

The Effectiveness of an Online Curriculum on High School Students’ Understanding of Biological Evolution



An online curriculum about biological evolution was designed to promote increased student content knowledge and evidentiary reasoning. A feasibility study was conducted with 77 rural high school biology students who learned with the online biological evolution unit. Data sources included the Biological Evolution Assessment Measure (BEAM), an analysis of discussion forum posts, and a post-implementation perceptions and attitudes questionnaire. BEAM posttest scores were significantly higher than the pretest scores. However, the findings revealed that the students required additional support to develop evidentiary reasoning. Many students perceived that the Web-based curriculum would have been enhanced by increased immediate interaction and feedback. Students required greater scaffolding to support complex, process-oriented tasks. Implications for designing Web-based science instruction with curriculum materials to support students’ acquisition of content knowledge and science process skills in a Web-based setting are discussed.


Online curriculum Evidentiary reasoning Biology Biological evolution Curriculum implementation 


  1. Baker C (2010) The impact of instructor immediacy and presence for online student affective learning, cognition, and motivation. J Educ Online 7(1):1–30Google Scholar
  2. Bandura A (1977) Social learning theory. Prentice Hall, Englewood CliffsGoogle Scholar
  3. Bandura A (2001) Social cognitive theory: an agentic perspective. Annu Rev Psychol 52(1):1–26CrossRefGoogle Scholar
  4. Barbour MK, Hill J (2011) What are they doing and how are they doing it? Rural student experiences in virtual schooling. J Distance Educ 25(1):1–14CrossRefGoogle Scholar
  5. Baumgartner E, Duncan K (2009) Evolution of students’ ideas about natural selection through a constructivist framework. Am Biol Teach 71(4):218–227CrossRefGoogle Scholar
  6. Biggers M, Forbes CT, Zangori L (2013) Elementary teachers’ curriculum design and pedagogical reasoning for supporting students’ comparison and evaluation of evidence-based explanation. Elem Sch J 114(1):48–72CrossRefGoogle Scholar
  7. Brecht HD, Ogilby SM (2008) Enabling a comprehensive teaching strategy: video lectures. J Inform Technol Educ 7:IIP71–IIP86Google Scholar
  8. Brown NJ, Furtak EM, Timms M, Nagashima SO, Wilson M (2010) The evidence-based reasoning framework: assessing scientific reasoning. Educ Assess 15(3–4):123–141CrossRefGoogle Scholar
  9. Burton SR, Dobson C (2009) Spork & beans: addressing evolutionary misconceptions. Am Biol Teach 71(2):89–91CrossRefGoogle Scholar
  10. Cetin G, Nisanci SH (2010) The effectiveness of the new 9th grade biology curriculum on students’ environmental awareness. Asia-Pac Forum Sci Learn Teach 11(2):1–25Google Scholar
  11. Clark RC, Mayer RE (2003) E-learning and the science of instruction: proven guidelines for consumers and designers of multimedia learning. Wiley, San FranciscoGoogle Scholar
  12. Cohen J (1977) Statistical power analysis for behavioral sciences (revised ed.). Academic Press, New YorkGoogle Scholar
  13. Coll C, Rochera MJ, de Gispert I (2014) Supporting online collaborative learning in small groups: teacher feedback on learning content, academic task and social participation. Comput Educ. doi: 10.1016/j.compedu.2014.01.015 Google Scholar
  14. Croxton RA (2014) The role of interactivity in student satisfaction and persistence in online learning. J Online Learn Teach 10(2):314–324Google Scholar
  15. Dobzhansky T (1973) Nothing in biology makes sense except in the light of evolution. Am Biol Teach 35(3):125–129CrossRefGoogle Scholar
  16. Dougherty M (2011) Six million years ago, what set our ancestors on the path from ape to human? Am Biol Teach 73(2):66–66. doi: 10.1525/abt.2011.73.2.2 CrossRefGoogle Scholar
  17. Dupuis J, Coutu J, Laneuville O (2013) Application of linear mixed-effect models for the analysis of exam scores: online video associated with higher scores for undergraduate students with lower grades. Comput Educ 66:64–73. doi: 10.1016/j.compedu.2013.02.011 CrossRefGoogle Scholar
  18. Falk A, Brodsky L (2014) Scientific explanations and arguments: supporting students with explicit reasoning in argumentation. Sci Scope 38(2):10–21CrossRefGoogle Scholar
  19. Geri N (2012) The resonance factor: probing the impact of video on student retention in distance learning. Interdiscip J E-Learn Learn Objects 8:1–13Google Scholar
  20. Hallyburton CL, Lunsford E (2013) Challenges and opportunities for learning biology in distance-based settings. Bioscene 39(1):27–33Google Scholar
  21. Heddy BC, Sinatra GM (2013) Transforming misconceptions: using transformative experience to promote positive affect and conceptual change in students’ learning about biological evolution. Sci Educ 97(5):723–744CrossRefGoogle Scholar
  22. Hermann RS (2013) High school biology teachers’ views on teaching evolution: implications for science teacher educators. J Sci Teach Educ 24:597–616. doi: 10.1007/s10972-012-9328-6 CrossRefGoogle Scholar
  23. Herreid CF, Schiller NA, Herreid KF, Wright CB (2014a) A chat with the survey monkey: case studies and the flipped classroom. J Coll Sci Teach 44(1):75–80Google Scholar
  24. Herreid CF, Terry DR, Lemons P, Armstrong N, Brickman P, Ribbens E (2014b) Emotion, engagement, and case studies. J Coll Sci Teach 44(1):86–95Google Scholar
  25. Isaak M (2005) Five major misconceptions about evolution. Calif J Sci Educ 5(2):133–142Google Scholar
  26. Kampourakis K, Zogza V (2009) Preliminary evolutionary explanations: a basic framework for conceptual change and explanatory coherence in evolution. Sci Educ 18(10):1313–1340. doi: 10.1007/s11191-008-9171-5 CrossRefGoogle Scholar
  27. Latham LG II, Scully EP (2008) CRITTERS! A realistic simulation for teaching evolutionary biology. Am Biol Teach (Natl Assoc Biol Teach) 70(1):30–33CrossRefGoogle Scholar
  28. Lave J, Wenger E (1991) Situated learning: legitimate peripheral participation. Cambridge University Press, New YorkCrossRefGoogle Scholar
  29. Lee H-S, Liu OL, Linn MC (2007) TELS report: validating inquiry science assessments at the design, construct, and instruction levels. University of California, BerkeleyGoogle Scholar
  30. Lee H-S, Linn MC, Varna K, Liu OL (2010) How do technology-enhanced inquiry science units impact classroom learning? J Res Sci Teach 47(1):71–90CrossRefGoogle Scholar
  31. Lee HS, Liu OL, Linn MC (2011) Validating measurement of knowledge integration is science using multiple-choice and explanation items. Appl Meas Educ 24(2):115–136. doi: 10.1080/08957347.2011.554604 CrossRefGoogle Scholar
  32. Lents NH, Cifuentes OE (2009) Web-based learning enhancements: video lectures through voice-over PowerPoint in a majors-level biology course. J Coll Sci Teach 39(2):38–46Google Scholar
  33. Liu OL, Lee HS, Hofstetter C, Linn MC (2008) Assessing knowledge integration in science: construct, measures, and evidence. Educ Assess 13(1):33–55. doi: 10.1080/10627190801968224 CrossRefGoogle Scholar
  34. Llewellyn D (2013) Inquire within: implementing inquiry- and argument-based science standards in grades 3–8, 3rd edn. Corwin Press, Thousand OaksGoogle Scholar
  35. Lynn LE Jr (1999) Teaching and learning with cases: a guidebook. Seven Bridges Press, ChappaquaCrossRefGoogle Scholar
  36. Marshall C, Rossman G (1989) Designing qualitative research. Sage Publications, Newbury ParkGoogle Scholar
  37. Mathieson K, Leafman JS (2014) Comparison of student and instructor perceptions of social presence. J Educ Online 11(2):1–27Google Scholar
  38. Mayer RE, Moreno R (2002) Aids to computer-based multimedia learning. Learn Instr 12(1):107–119CrossRefGoogle Scholar
  39. Meyer KA (2007) Student perceptions of face-to-face and online discussions: the advantage goes to…. J Asynchron Learn Netw 11(4):53–69Google Scholar
  40. National Research Council (2012) A framework for K-12 science education: practices, crosscutting concepts, and core ideas. National Research Council, WashingtonGoogle Scholar
  41. Neal J (2009) The power of performance based assessment at the post-secondary level. Int J Learn 16(9):87–101Google Scholar
  42. NGSS Lead States (2013) Next generation science standards: for states, by states. National Academies Press, WashingtonGoogle Scholar
  43. Patton M (1990) Qualitative evaluation methods. Sage Publications, Newbury ParkGoogle Scholar
  44. Pellegrino JW, Wilson MR, Koenig JA, Beatty AS (2014) Developing assessments for the next generation science standards. National Academies Press, WashingtonGoogle Scholar
  45. Pereira JA, Pleguezuelos E, Merí A, Molina-Ros A, Molina-Tomás MC, Masdeu C (2007) Effectiveness of using blended learning strategies for teaching and learning human anatomy. Med Educ 41(2):189–195. doi: 10.1111/j.1365-2929.2006.02672.x CrossRefGoogle Scholar
  46. Pobiner BL (2012) Use human examples to teach evolution. AM Biol Teach 74(2):71–72. doi: 10.1525/abt.2012.74.2.2 CrossRefGoogle Scholar
  47. Quattrone L (2013) From framework to next generation science standards. In: Banko W, Grant ML, Jabot ME, McCormack AJ, O’Brien T (eds) Science for the next generation. NSTA Press, Arlington, p 37Google Scholar
  48. Ramsey K, Baethe B (2013) The keys to future STEM careers: basic skills, critical thinking, and ethics. Delta Kappa Gamma Bull 80(1):26–33Google Scholar
  49. Rovai AP, Baker JS, Ponton MK (2013) Social science research design and statistics: a practitioner’s guide to research methods and SPSS analysis. Watertree Press, ChesepeakeGoogle Scholar
  50. Ruiz-Primo MA, Shavelson RJ, Hamilton L, Klein S (2002) On the evaluation of systemic science education reform: searching for instructional sensitivity. J Res Sci Teach 39(5):369–393CrossRefGoogle Scholar
  51. Russo-Gleicher RJ (2013) Qualitative insights into faculty use of student support services with online students at risk: implications for student retention. J Educ Online 10(1):58–90Google Scholar
  52. Schalk H, Schee J, Boersma K (2013) The development of understanding of evidence in pre-university biology education in the Netherlands. Res Sci Educ 43(2):551–578. doi: 10.1007/s11165-011-9276-8 CrossRefGoogle Scholar
  53. Sickel AJ, Friedrichsen PJ (2012) Using the FAR guide to teach simulations: an example with natural selection. Am Biol Teach 74(1):47–51CrossRefGoogle Scholar
  54. Slavin RE (2008) Perspectives on evidence-based research in education-what works? Issues in synthesizing educational program evaluations. Educ Res 37(1):5–14CrossRefGoogle Scholar
  55. The Design-Based Research Collective (2003) Design-based research: an emerging paradigm for educational inquiry. Educ Res 32(1):5–8CrossRefGoogle Scholar
  56. Tisue S, Wilensky U (2004) Netlogo: a simple environment for modeling complexity. Paper presented at the International Conference on Complex Systems (ICCS 2004), BostonGoogle Scholar
  57. Van Dijk EM, Reydon TA (2010) A conceptual analysis of evolutionary theory for teacher education. Sci Educ 19(6–8):655–677. doi: 10.1007/s11191-009-9190-x CrossRefGoogle Scholar
  58. Walker JP, Sampson V, Zimmerman CO, Grooms JA (2011) A performance-based assessment for limiting reactants. J Chem Educ 88(9):1243–1246. doi: 10.1021/ed1006629 CrossRefGoogle Scholar
  59. Watson J, Murin A, Vashaw L, Gemin B, Rapp C (2012) Keeping pace with K—online and blended learning: an annual review of policy and practice. Evergreen Education Group.
  60. Wekesa E, Kiboss J, Ndirangu M (2006) Improving students’ understanding and perception of cell theory in school biology using a computer-based instruction simulation program. J Educ Multimed Hypermed 15(4):397–410Google Scholar
  61. Wiggins G, McTighe J (2005) Understanding by design. ASCD, AlexandriaGoogle Scholar
  62. Wilensky U, Reisman K (2006) Thinking like a wolf, a sheep, or a firefly: learning biology through constructing and testing computational theories—an embodied modeling approach. Cogn Instr 24(2):171–209CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Education and Human ServicesLehigh UniversityBethlehemUSA

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