Problem-Centered Supplemental Instruction in Biology: Influence on Content Recall, Content Understanding, and Problem Solving Ability

Abstract

To address the need for effective, efficient ways to apply active learning in undergraduate biology courses, in this paper, we propose a problem-centered approach that utilizes supplemental web-based instructional materials based on principles of active learning. We compared two supplementary web-based modules using active learning strategies: the first used Merrill’s First Principles of Instruction as a framework for organizing multiple active learning strategies; the second used a traditional web-based approach. Results indicated that (a) the First Principles group gained significantly from pretest to posttest at the Remember level (t(40) = −1.432, p = 0.08, ES = 0.4) and at the Problem Solving level (U = 142.5, N1 = 21, N2 = 21, p = .02, ES = 0.7) and (b) the Traditional group gained significantly from pretest to posttest at the Remember level (t(36) = 1.762, p = 0.043, ES = 0.6). Those in the First Principles group were significantly more likely than the traditional group to be confident in their ability to solve problems in the future (χ2 (2, N = 40) = 3.585, p = 0.09).

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

References

  1. Allen D, Tanner K (2003) Approaches to cell biology teaching: learning content in context—problem-based learning. Life Sci Educ 2(2):73–81

  2. American Association for the Advancement of Science. (2009). Vision and change in undergraduate biology: a view for the twenty-first century. Retrieved from http://www.visionandchange.org

  3. Anderson LW, Krathwohl DR, Airasian PW, Samuel B (2001) A taxonomy for learning, teaching, and assessing: a revision of Bloom’s taxonomy of educational objectives. Longman, New York, NY

    Google Scholar 

  4. Armbruster P, Patel M, Johnson E, Weiss M (2009) Active learning and student-centered pedagogy imrove student attitudes and performance in introductory biology. CBE-Life Sciences Education 8(3):203–213. doi:10.1187/cbe.09-03-0025

    Article  Google Scholar 

  5. Barclay MW, Gur B, Wu X (2004) The impact of media on the family: assessing the availability and quality of instruction on the world wide web for enhancing the marriage relationship. Presented at the United Nations international year of the family conference. Asia Pacific Dialogue, Kuala Lumpur

    Google Scholar 

  6. Belland B, Glazewski K, Ertmer P (2009) Inclusion and problem-based learning: roles of students in a mixed-ability group. RMLE Online 32(9):1–19

  7. Bland M, Saunders G, Frisch JK (2007) In defense of the lecture. J Coll Sci Teach 37(2):10–13

    Google Scholar 

  8. Brewer C (2004) Near real-time assessment of student learning and understanding in biology courses. BioScience 54(11):1034

  9. Chinn CA, Malhotra BA (2002) Epistemologically authentic inquiry in schools: a theoretical framework for evaluating inquiry tasks. Sci Educ 86(2):175–218. doi:10.1002/sce.10001

    Article  Google Scholar 

  10. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. N. p.: Lawrence Erlbaum

  11. Collins JW, O’Brien NP (2003) The Greenwood dictionary of education. Greenwood, Westport, CT

    Google Scholar 

  12. Davis EA, Hodgson Y, Macaulay JO (2012) Engagement of students with lectures in biochemistry and pharmacology. Biochem Mol Biol Educ 40(5):300–309

    Article  Google Scholar 

  13. DiCarlo SE (2006) Cell biology should be taught as science is practiced. Nat Rev Mol Cell Biol 7(4):290–295

    Article  Google Scholar 

  14. Dochy F, Segers M, Van den Bossche P, Gijbels D (2003) Effects of problem-based learning: a meta-analysis. Learn Instr 13(5):533–568

    Article  Google Scholar 

  15. Dori YJ, Belcher J (2005) How does technology-enabled active learning affect undergraduate students’ understanding of electromagnetism concepts? Journal of the Learning Sciences 14(2):243–279. doi:10.1207/s15327809jls1402_3

    Article  Google Scholar 

  16. Ebert-May D, Brewer C, Allred S (1997) Innovation in large lectures: teaching for active learning. Bioscience 47:601–607

  17. Eick CJ, King DT Jr (2012) Nonscience majors’ perceptions on the use of YouTube video to support learning in an integrated science lecture. J Coll Sci Teach 42(1):26–30

    Google Scholar 

  18. Fagen AP, Crouch CH, Mazur E (2002) Peer instruction: results from a range of classrooms. Phys Teach 40(4):206. doi:10.1119/1.1474140

    Article  Google Scholar 

  19. Francom G, Gardner J (2014) What is task-centered learning? TechTrends. doi:10.1007/s11528-014- 0784-z

    Google Scholar 

  20. Francom G, Bybee D, Wolfersberger M, Mendenhall A, Merrill M (2009) A task-centered approach to freshman-level general biology. Bioscience 35:66–73

  21. Freeman S, O’Connor E, Parks JW, Cunningham M, Hurley D, Haak D et al (2007) Prescribed active learning increases performance in introductory biology. CBE-Life Sciences Education 6(2):132–139. doi:10.1187/cbe.06-09-0194

    Article  Google Scholar 

  22. Frick, T., Chadha, R., Watson, C., Wang, Y., & Green, P. (2007). Theory-based course evaluation: Nine Scales for measuring teaching and learning quality. Retrieved from http://www.indiana.edu/~tedfrick/TALQ.pdf

  23. Gall MD, Gall JP, Borg WR (2007) Educational research: an introduction, 7th edn. Pearson, Boston

  24. Garamszegi LZ (2006) Comparing effect sizes across variables: generalization without the need for Bonferroni correction. Behav Ecol 17(4):682–687. doi:10.1093/beheco/ark005

    Article  Google Scholar 

  25. Gardner J, Belland B (2012) A conceptual framework for organizing active learning experiences in biology instruction. J Sci Educ Technol 21(4):465–475

  26. Gijbels D, Dochy F, Van den Bossche P, Segers M (2005) Effects of problem-based learning: a meta-analysis from the angle of assessment. Rev Educ Res 75(1):27–61

    Article  Google Scholar 

  27. Heitz JG, Cheetham JA, Capes EM, Jeanne R (2010) Interactive evolution modules promote conceptual change. Evolution: Education and Outreach 3(3):436–442. doi:10.1007/s12052-010-0208-2

    Google Scholar 

  28. Jonassen DH (2000) Toward a design theory of problem solving. Educ Technol Res Dev 48(4):63–85. doi:10.1007/BF02300500

    Article  Google Scholar 

  29. Kiboss JK, Ndirangu M, Wekesa EW (2004) Effectiveness of a computer-mediated simulations program in school biology on pupils’ learning outcomes in cell theory. J Sci Educ Technol 13:207–213

    Article  Google Scholar 

  30. Kolstø SD (2001) Scientific literacy for citizenship: tools for dealing with the science dimension of controversial socioscientific issues. Sci Educ 85(3):291–310. doi:10.1002/sce.1011

    Article  Google Scholar 

  31. Krathwohl DR (2002) A revision of Bloom’s taxonomy: an overview. Theory Pract 41:212–218

    Article  Google Scholar 

  32. Kuhn D (2010) Teaching and learning science as argument. Sci Educ 94(5):810–824. doi:10.1002/sce.20395

    Article  Google Scholar 

  33. Lennon RT (1956) Assumptions underlying the use of content validity. Educ Psychol Meas 16(3):294–304. doi:10.1177/001316445601600303

    Article  Google Scholar 

  34. Lord T (2008) We know how to improve science understanding in students, so why aren’t college professors embracing it? J Coll Sci Teach 38(1):66–70

    Google Scholar 

  35. McDermott LC (2001) Oersted medal lecture 2001: “physics education research: the key to student learning.”. Am J Phys 69(11):1127–1137

  36. Merrill MD (2002) First principles of instruction. Educ Technol Res Dev 50(3):43–59

    Article  Google Scholar 

  37. Merrill MD (2006a) First principles of instruction: a synthesis. In: Reiser R, Dempsey JV (eds) Trends and issues in instructional design and technology, 2nd edn. Prentice Hall, Upper Saddle River, NJ, pp 2–71

    Google Scholar 

  38. Merrill MD (2006b) Levels of instructional strategy. Educ Technol 46(4):5–10

    Google Scholar 

  39. Michael J (2006) Where’s the evidence that active learning works? AJP: Advances in Physiology Education 30(4):159–167. doi:10.1152/advan.00053.2006

    Google Scholar 

  40. MIT Office of Educational Innovation and Technology. (2011, December 7. TEAL—Technology Enabled Active Learning. iCampus. Retrieved Jan. 2, 2014, from http://icampus.mit.edu/projects/teal/

  41. Nehm RH, Rector M, Ha M (2010) “Force talk” in evolutionary explanation: metaphors and misconceptions. Evolution Education and Outreach 3:605–613

    Article  Google Scholar 

  42. Nelson CE (2008) Teaching evolution (and all of biology) more effectively: strategies for engagement, critical reasoning, and confronting misconceptions. Integr Comp Biol 48(2):213–225

    Article  Google Scholar 

  43. O’Hara S, Shandas V, Wright E (2000) The costs of technology intensive education: a preliminary analysis of studio physics. The Journal of Computers in Mathematics and Science Teaching 19(4):379–396

    Google Scholar 

  44. Osborne J (2010) Arguing to learn in science: the role of collaborative, critical discourse. Science 328(5977):463–466. doi:10.1126/science.1183944

    Article  Google Scholar 

  45. Polit DF, Beck CT (2006) The content validity index: are you sure you know what’s being reported? Critique and recommendations. Research in Nursing & Health 29(5):489–497. doi:10.1002/nur.20147

    Article  Google Scholar 

  46. Prince M (2004) Does active learning work? A review of the research. J Eng Educ 93:223–232

    Article  Google Scholar 

  47. Reuter JG, Perrin NA (1999) Using a simulation to teach food web dynamics. Am Biol Teach 61:116–123

    Article  Google Scholar 

  48. Rifell S, Sibley D (2005) Using web-based instruction to improve large undergraduate biology courses: an evaluation of a hybrid course format. Computers and Education 44:217–235

    Article  Google Scholar 

  49. Sanger MJ, Brecheisen DM, Hynek BM (2001) Can computer animations affect college biology students’ conceptions about diffusion and osmosis? Am Biol Teach 63(2):104–109

    Article  Google Scholar 

  50. Schmidt HG, van der Molen HT, Te Winkel WWR, Wijnen WHFW (2009) Constructivist, problem-based learning does work: a meta-analysis of curricular comparisons involving a single medical school. Educ Psychol 44(4):227–249. doi:10.1080/00461520903213592

    Article  Google Scholar 

  51. Sheskin DJ (2011) Handbook of parametric and nonparametric statistical procedures, 5th edn. CRC Press, Boca Raton

    Google Scholar 

  52. Shute VJ (2008) Focus on formative feedback. Rev Educ Res 78(1):153–189. doi:10.3102/0034654307313795

    Article  Google Scholar 

  53. Smith AC, Stewart R, Shields P, Hayes-Klosteridis J, Robinson P, Yuan R (2005) Introductory biology courses: a framework to support active learning in large enrollment introductory science courses. Life Sciences Education 4(2):143–156

    Article  Google Scholar 

  54. Sugrue B (1995) A theory-based framework for assessing domain-specific problem-solving ability. Educational Measurement: Issues and Practice 14(3):29–35. doi:10.1111/j.1745-3992.1995.tb00865.x

    Article  Google Scholar 

  55. Thomson. (2002). Thomson job impact study: the next generation of learning. Retrieved from http://www.delmarlearning.com/resources/ job_impact_study_whitepaper.pdf

  56. Vialatte F-B, Cichocki A (2008) Split-test Bonferroni correction for QEEG statistical maps. Biol Cybern 98(4):295–303. doi:10.1007/s00422-008-0210-8

    Article  Google Scholar 

  57. Villasenor MR, Etkina E (2007) Reformed physics instruction through the eyes of students. Physics Education Research Conference 2006 Vol. 883:105–108. doi:10.1063/1.2508702

    Article  Google Scholar 

  58. Walker A, Leary H (2009) A problem based learning meta analysis: differences across problem types, implementation types, disciplines, and assessment levels. Interdisciplinary Journal of Problem-Based Learning 3(1). doi:10.7771/1541-5015.1061

  59. Watkins J, Mazur E (2013) Retaining students in science, technology, engineering, and mathematics (STEM) majors. J Coll Sci Teach 42(5):36–41

    Google Scholar 

  60. Yamanoi, T., Iwasaki, W. (2015). Origami bird simulator: a teaching resource linking natural selection and speciation. Evolution: Education and Outreach. Accessed online at http://evolution-outreach.springeropen.com/articles/10.1186/s12052-015-0043-6.

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Joel Gardner.

Electronic supplementary material

ESM 1

(DOCX 16 kb).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gardner, J., Belland, B.R. Problem-Centered Supplemental Instruction in Biology: Influence on Content Recall, Content Understanding, and Problem Solving Ability. J Sci Educ Technol 26, 383–393 (2017). https://doi.org/10.1007/s10956-017-9686-0

Download citation

Keywords

  • Biology
  • Evolution
  • Teaching
  • Instructional design
  • First principles of instruction
  • Introductory biology course
  • Multimedia
  • Active learning
  • Problem solving
  • Recall
  • Understanding