How Much Mightier Is the Pen than the Keyboard for Note-Taking? A Replication and Extension of Mueller and Oppenheimer (2014)

Abstract

Many students use laptops to take notes in classes, but does using them impact later test performance? In a high-profile investigation comparing note-taking writing on paper versus typing on a laptop keyboard, Mueller and Oppenheimer (Psychological Science, 25, 1159–1168, 2014) concluded that taking notes by longhand is superior. We conducted a direct replication of Mueller and Oppenheimer (2014) and extended their work by including groups who took notes using eWriters and who did not take notes. Some trends suggested longhand superiority; however, performance did not consistently differ between any groups (experiments 1 and 2), including a group who did not take notes (experiment 2). Group differences were further decreased after students studied their notes (experiment 2). A meta-analysis (combining direct replications) of test performance revealed small (nonsignificant) effects favoring longhand. Based on the present outcomes and other available evidence, concluding which method is superior for improving the functions of note-taking seems premature.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Notes

  1. 1.

    Although Mueller and Oppenheimer (2014) used a delayed test in experiment 3, the delayed test results from the present experiment do not constitute a direct replication of their experiment 3 because they used different materials.

  2. 2.

    As stated in the Method section, we added questions to those used by Mueller and Oppenheimer (2014). To ensure that any different outcomes were not due to the new questions, we also conducted the planned comparisons based on performance for only test questions that were used in the original report. Conclusions were the same whether analyses were conducted on the entire question set (reported in the text) or the original questions (analyses available from the first author).

  3. 3.

    Given that our initial aim was to replicate Mueller and Oppenheimer (2014), who did not include a no-notes group, we also did not include this group in experiment 1. We included it in experiment 2 because it could potentially offer insight into the overall encoding benefits of note-taking.

  4. 4.

    Mueller and Oppenheimer (2014, experiment 3) allowed students 10 min to study their notes. Most participants in the present study took only one or two pages of notes; thus, we expected that 7 min would be plenty of time for study, and no participants reported needing more time.

References

  1. Barrett, M. E., Swan, A. B., Mamikonian, A., Ghajoyan, I., Kramarova, O., & Youmans, R. J. (2014). Technology in note taking and assessment: the effects of congruence on student performance. International Journal of Instruction, 7, 49–58.

    Google Scholar 

  2. Blasiman, R., Dunlosky, J., & Rawson, K. A. (2017). The what, how much, and when of study strategies: comparing intended versus actual study behavior. Memory, 25, 784–792. https://doi.org/10.1080/09658211.2016.1221974.

    Article  Google Scholar 

  3. Braver, S. L., Thoemmes, F. J., & Rosenthal, R. (2014). Continuously cumulating meta-analysis and replicability. Perspectives on Psychological Science, 9, 333–342. https://doi.org/10.1177/1745691614529796.

    Article  Google Scholar 

  4. Bui, D. C., Myerson, J., & Hale, S. (2013). Note-taking with computers: Exploring alternative strategies for improved recall. Journal of Educational Psychology, 105, 299–309. https://doi.org/10.1037/a0030367.

    Article  Google Scholar 

  5. Carter, J. F., & Van Matre, N. H. (1975). Note taking versus note having. Journal of Educational Psychology, 67, 900–904. https://doi.org/10.1037/0022-0663.67.6.900.

    Article  Google Scholar 

  6. Carter, S. P., Greenberg, K., & Walker, M. S. (2017). The impact of computer usage on academic performance: evidence from a randomized trial at the United States Military Academy. Economics of Education Review, 56, 118–132. https://doi.org/10.1016/j.econedurev.2016.12.005.

    Article  Google Scholar 

  7. Di Vesta, F. J., & Gray, G. S. (1972). Listening and note taking. Journal of Educational Psychology, 63, 8–14. https://doi.org/10.1037/h0032243.

    Article  Google Scholar 

  8. Fiorella, L., & Mayer, R. E. (2017). Spontaneous spatial strategy use in learning from scientific text. Contemporary Educational Psychology, 49, 66–79. https://doi.org/10.1016/j.cedpsych.2017.01.002.

    Article  Google Scholar 

  9. Francis, G. (2012). Publication bias and the failure of replication in experimental psychology. Psychonomic Bulletin & Review, 19, 975–991. https://doi.org/10.3758/s13423-012-0322-y.

    Article  Google Scholar 

  10. Glass, A. L., & Kang, M. (2018). Dividing attention in the classroom reduces exam performance. Educational Psychology. 1–14. On-line first publication. https://doi.org/10.1080/01443410.2018.1489046.

  11. Gurung, R. A. (2005). How do students really study (and does it matter)? Education, 39, 323–340.

    Google Scholar 

  12. James, K. H. (2017). The importance of handwriting experience on the development of the literate brain. Current Directions in Psychological Science, 26, 502–508. https://doi.org/10.1177/0963721417709821.

    Article  Google Scholar 

  13. James, K. H., & Engelhardt, L. (2012). The effects of handwriting experience on functional brain development in pre-literate children. Trends in Neuroscience and Education, 1, 32–42. https://doi.org/10.1016/j.tine.2012.08.001.

    Article  Google Scholar 

  14. James, K. H., & Gauthier, I. (2006). Letter processing automatically recruits a sensory-motor brain network. Neuropsychologia, 44, 2937–2949. https://doi.org/10.1016/j.neuropsychologia.2006.06.026.

    Article  Google Scholar 

  15. Johnson, C. I., & Mayer, R. E. (2009). A testing effect with multimedia learning. Journal of Educational Psychology, 101, 621–629. https://doi.org/10.1037/a0015183.

    Article  Google Scholar 

  16. Karpicke, J. D., Butler, A. C., & Roediger, H. L. (2009). Metacognitive strategies in student learning: do students practice retrieval when they study on their own? Memory, 17, 471–479. https://doi.org/10.1080/09658210802647009.

    Article  Google Scholar 

  17. Kiewra, K. A. (1985). Students’ note-taking behaviors and the efficacy of providing the instructor’s notes for review. Contemporary Educational Psychology, 10, 378–386. https://doi.org/10.1016/0361-476X(85)90034-7.

    Article  Google Scholar 

  18. Kiewra, K. A. (1989). A review of note-taking: the encoding-storage paradigm and beyond. Educational Psychology Review, 1, 147–172. https://doi.org/10.1007/BF01326640.

    Article  Google Scholar 

  19. Kobayashi, K. (2005). What limits the encoding effect of note-taking? A meta-analytic examination. Contemporary Educational Psychology, 30, 242–262. https://doi.org/10.1016/j.cedpsych.2004.10.001.

    Article  Google Scholar 

  20. Kobayashi, K. (2006). Combined effects of note-taking/reviewing on learning and the enhancement through interventions: a meta-analytic review. Educational Psychology, 26, 459–477. https://doi.org/10.1080/01443410500342070.

    Article  Google Scholar 

  21. Kornell, N., Bjork, R. A., & Garcia, M. A. (2011). Why tests appear to prevent forgetting: a distribution-based bifurcation model. Journal of Memory and Language, 65, 85–97. https://doi.org/10.1016/j.jml.2011.04.002.

    Article  Google Scholar 

  22. Luo, L., Kiewra, K. A., Flanigan, A. E., & Peteranetz, M. S. (2018). Laptop versus longhand note taking: effects on lecture notes and achievement. Instructional Science, 46, 1–25. https://doi.org/10.1007/s11251-018-9458-0.

    Article  Google Scholar 

  23. Morehead, K., Dunlosky, J., Rawson, K. A., Blasiman, R., & Hollis, R. B. (2019). Note-taking habits of 21st century college students: implications for student learning, memory, and achievement. Memory. https://doi.org/10.1080/09658211.2019.156969.

  24. Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: advantages of longhand over laptop note taking. Psychological Science, 25, 1159–1168. https://doi.org/10.1177/0956797614524581.

    Article  Google Scholar 

  25. Nandagopal, K., & Ericsson, K. A. (2012). An expert performance approach to the study of individual differences in self-regulated learning activities in upper-level college students. Learning and Individual Differences, 22, 597–609. https://doi.org/10.1016/j.lindif.2011.11.018.

    Article  Google Scholar 

  26. Palmatier, R. A., & Bennett, J. M. (1974). Notetaking habits of college students. Journal of Reading, 18, 215–218. http://www.jstor.org/stable/40009958. Accessed 12 April 2016.

  27. Patterson, R. W., & Patterson, R. M. (2017). Computers and productivity: evidence from laptop use in the college classroom. Economics of Education Review, 57, 66–79. https://doi.org/10.1016/j.econedurev.2017.02.004.

    Article  Google Scholar 

  28. Peverly, S. T., & Sumowski, J. F. (2012). What variables predict quality of text notes and are text notes related to performance on different types of tests? Applied Cognitive Psychology, 26, 104–117. https://doi.org/10.1002/acp.1802.

    Article  Google Scholar 

  29. Peverly, S. T., & Wolf, A. D. (2019). Note-taking. To appear in J. Dunlosky & K. A. Rawson (Eds.), Cambridge handbook of cognition and education (pp. 320–355). New York, NY: Cambridge University Press.

  30. Peverly, S. T., Sumowski, J. F., & Garner, J. (2007). Skill in lecture note-taking: what predicts? Journal of Educational Psychology, 99, 167–180. https://doi.org/10.1037/0022-0663.99.1.167.

    Article  Google Scholar 

  31. Peverly, S. T., Vekaria, P. C., Reddington, L. A., Sumowski, J. F., Johnson, K. R., & Ramsay, C. M. (2013). The relationship of handwriting speed, working memory, language comprehension and outlines to lecture note-taking and test-taking among college students. Applied Cognitive Psychology, 27, 115–126. https://doi.org/10.1002/acp.2881.

    Article  Google Scholar 

  32. Peverly, S. T., Garner, J. K., & Vekaria, P. C. (2014). Both handwriting speed and selective attention are important to lecture note-taking. Reading and Writing: An Interdisciplinary Journal, 27, 1–30. https://doi.org/10.1007/s11145-013-9431-x.

    Article  Google Scholar 

  33. Ragan, E. D., Jennings, S. R., Massey, J. D., & Doolittle, P. E. (2014). Unregulated use of laptops over time in large lecture classes. Computers & Education, 78, 78–86. https://doi.org/10.1016/j.compedu.2014.05.002.

    Article  Google Scholar 

  34. Reddington, L. A., Peverly, S. T., & Block, C. J. (2015). An examination of some of the cognitive and motivation variables related to gender differences in lecture note-taking. Reading and Writing: An Interdisciplinary Journal, 28, 1155–1185. https://doi.org/10.1007/s11145-015-9566-z.

    Article  Google Scholar 

  35. Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: taking memory tests improves long-term retention. Psychological Science, 17, 249–255. https://doi.org/10.1111/j.1467-9280.2006.01693.x.

    Article  Google Scholar 

  36. Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24–31. https://doi.org/10.1016/j.compedu.2012.10.003.

    Article  Google Scholar 

  37. Sibley, C. G. (2008). Utilities for examining simple meta-analytic avergages [computer software]. Auckland: University of Auckland.

    Google Scholar 

  38. Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22, 1359–1366. https://doi.org/10.1177/0956797611417632.

    Article  Google Scholar 

  39. Simons, D. J. (2014). The value of direct replications. Perspectives on Psychological Sciences, 9, 76–80. https://doi.org/10.1177/1745691613514755.

    Article  Google Scholar 

  40. Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on generality (COG): a proposed addition to all empirical papers. Perspectives on Psychological Science, 12, 1123–1128. https://doi.org/10.1177/1745691617708630.

    Article  Google Scholar 

  41. Toppino, T. C., & Cohen, M. S. (2009). The testing effect and the retention interval. Experimental Psychology, 56, 252–257. https://doi.org/10.1027/1618-3169.56.4.252.

    Article  Google Scholar 

  42. Vinci-Booher, S., James, T. W., & James, K. H. (2016). Visual-motor functional connectivity in preschool children emerges after handwriting experience. Trends in Neuroscience and Education, 5, 107–120. https://doi.org/10.1016/j.tine.2016.07.006.

    Article  Google Scholar 

Download references

Acknowledgments

Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF. The authors have no financial or non-financial interest in the materials discussed in this manuscript. Many thanks to Asad Khan, Annette Kratcoski, Duane Marhefka, Erica Montbach, and Todd Packer for support and encouragement with this project.

Funding

This research was supported by a National Science Foundation (NSF) grant, STTR Phase II: Digital e-Writer for the Classroom, Grant Number 413328.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Kayla Morehead.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1. Correlation Tables Within Note-Taking Method Group for Experiment 1

Table 7 Longhand group correlations between test performance and secondary outcome measures for experiment 1
Table 8 Laptop group correlations between test performance and secondary outcome measures for experiment 1
Table 9 eWriter group correlations between test performance and secondary outcome measures for experiment 1

Appendix 2. Correlation Tables Within Note-Taking Method Group for Experiment 2

Table 10 Longhand group correlations between test performance and secondary outcome measures for experiment 2
Table 11 Laptop group correlations between test performance and secondary outcome measures for experiment 2
Table 12 eWriter correlations between test performance and secondary outcome measures for experiment 2

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Morehead, K., Dunlosky, J. & Rawson, K.A. How Much Mightier Is the Pen than the Keyboard for Note-Taking? A Replication and Extension of Mueller and Oppenheimer (2014). Educ Psychol Rev 31, 753–780 (2019). https://doi.org/10.1007/s10648-019-09468-2

Download citation

Keywords

  • Note-taking
  • Laptop
  • Longhand
  • eWriter
  • Encoding
  • Storage