Instructors and students are on a continuing quest to identify predictors of learning.
Objective:
This study examines the associations between self-reported exam score and study techniques among students in two courses, Introductory Psychology and Computer Science.
Method:
We used an online survey to measure the extent students (N = 249) used 10 techniques studied in cognitive science. We also measured students’ perseverance, metacognitive skill, distractions, and procrastination.
Results:
Student use of specific study techniques varied between the two courses and a high utility technique, practice testing, was well used. Students reported low levels of spaced practice. Perseverance and metacognitive skills both correlated significantly with many of the study techniques. While no study techniques predicted exam scores in Introductory Psychology beyond variance predicted by GPA, the use of spaced practice predicted a significant portion of variance in students in Computer Science.
Conclusions:
Students’ use of study techniques varies between their courses and while related to GPA and exam scores, are not unique predictors of variance in learning. Additional moderators and mediators of learning need to be identified.
Teaching Implications:
We discuss ways instructors can help prepare students in Introductory Psychology and key needs for future research on studying.
AgarwalP. K. (2018). Retrieval practice and Bloom’s taxonomy: Do students need fact knowledge before higher order learning?Journal of Educational Psychology, 111(2), 189–209. https://doi.org/10.1037/edu000028
2.
BartoszewskiB. L.GurungR. A. R. (2015). Comparing the relationship of learning techniques and exam score. Scholarship of Teaching and Learning in Psychology, 1(3), 219–228. https://doi.org/10.1037/stl0000036
3.
BlasimanR. N.DunloskyJ.RawsonK. A. (2016). The what, how much, and when of study strategies: Comparing intended versus actual study behavior. Memory, 25(6), 784–792. https://doi.org/10.1080/09658211.2016.1221974
4.
ButlerA. C.MarshE. J.SlavinskyJ. P.BaraniukR. G. (2014). Integrating cognitive science and technology improves learning in a STEM Classroom. Educational Psychology Review, 26(2), 331–340. https://doi.org/10.1007/s10648-014-9256-4
5.
CohenJ. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
6.
CredéM. (2018). What shall we do about grit? A critical review of what we know and what we don’t know. Educational Researcher, 47(9), 606–611. https://doi.org/10.3102/0013189X18801322
7.
CredéM.PhillipsL. A. (2011). A meta-analytic review of the motivated strategies for learning questionnaire. Learning and Individual Differences, 21(4), 337–346. https://doi.org/10.1016/j.lindif.2011.03.002
8.
CredéM.TynanM. C.HarmsP. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492–511. https://doi.org/10.1037/pspp0000102
9.
DavidP.KimJ. H.BrickmanJ. S.RanW.CurtisC. M. (2015). Mobile phone distraction while studying. New Media & Society, 17(10), 1661–1679. https://doi.org/10.1177/1461444814531692
10.
DuckworthA. LGrossJ. J. (2014). Self-control and grit: Related but separable determinants of success. Current Directions in Psychological Science, 23(5), 319–325. https://doi.org/10.1177/0963721414541462
11.
DuckworthA. L.QuinnP. D. (2009). Development and validation of the short Grit Scale (Grit–S). Journal of Personality Assessment, 91(2), 166–174. https://doi.org/10.1080/00223890802634290
12.
DunloskyJ.RawsonK. A. (2015). Do students use testing and feedback while learning? A focus on key concept definitions and learning to criterion. Learning and Instruction, 39, 32–44. https://doi.org/10.1016/j.learninstruc.2015.05.003
DunloskyJ.RawsonK. A.MarshE. J.NathanM. J.WillinghamD. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58. https://doi.org/10.1177/1529100612453266
15.
FernerJ. D. (1980). Successful time management. Wiley.
16.
GurungR. A. RBurnsK. (2019). Putting evidence-based claims to the test: A multi-site classroom study of retrieval practice and spaced practice. Applied Cognitive Psychology, 33(5), 732–743. https://doi.org/10.1002/acp.3507
17.
GurungR. A. R.HackathornJ. (2018). Ramp it up: A call for more research in introductory psychology. Teaching of Psychology, 45(4), 302–311. https://doi.org/10.1177/0098628318796413
18.
HackerD. J.BolL. (2019). Calibration and self-regulated learning: Making the connections. In DunloskyJ.RawsonK. A. (Eds.), Cambridge handbook of cognition and education (pp. 647–677). Cambridge University Press.
19.
HattieJ. (2015). The applicability of visible learning to higher education. Scholarship of Teaching and Learning in Psychology, 1(1), 79–91. https://doi.org/10.1037/stl0000021
20.
JeongS. H.HwangY. (2012). Does multitasking increase or decrease persuasion? Effects of multitasking on comprehension and counterarguing. Journal of Communication, 62(4), 571–587. https://doi.org/10.1111/j.1460-2466.2012.01659.x
21.
KarpickeJ. D.BauernschmidtA. (2011). Spaced retrieval: Absolute spacing enhances learning regardless of relative spacing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(5), 1250. https://doi.org/10.1037/a0023436
22.
KeeleyJ.SmithD.BuskistW. (2006). The Teacher Behaviors Checklist: Factor analysis of its utility for evaluating teaching. Teaching of Psychology, 33(2), 84–91. https://doi.org/10.1207/s15328023top3302_1
23.
KomarrajuM.NadlerD. (2013). Self-efficacy and academic achievement: Why do implicit beliefs, goals, and effort regulation matter?Learning and Individual Differences, 25, 67–272. https://doi.org/10.1016/j.lindif.2013.01.005
24.
LyleK. B.BegoC. R.HopkinsR. F.HiebJ. L.RalstonP. A. S. (2020). How the amount and spacing of retrieval practice affect the short- and long-term retention of mathematics knowledge. Educational Psychology Review, 32, 277–295. https://doi.org/10.1007/s10648-019-09489-x
PanS. C.RickardT. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710–756. https://dx.doi.org/10.1037/bul0000151
27.
PérezJ. F.MatíasS. B. (2019). Cognitive neuroscience and how students learn: Hype or hope. International Journal of Psychological Research, 12(1), 6–8. https://dx.doi.org/10.21500/20112084.4047
28.
PintrichP. R.SmithD. A. F.GarciaT.McKeachieW. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ) (Technical report no. 91-B004). The Regents of the University of Michigan.
29.
RodriguezF.RivasM. J.MatsumuraL. H.WarschauerM.SatoB. K. (2018). How do students study in STEM courses? Findings from a light-touch intervention and its relevance for underrepresented students. PLOS ONE, 13(7). https://doi.org/10.1371/journal.pone.0200767
30.
RohrerD.TaylorK.SholarB. (2010). Tests enhance the transfer of learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(1), 233. https://doi.org/10.1037/a0017678
31.
RosenL. D.CarrierL. M.CheeverN. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948–958. https://doi.org/10.1016/j.chb.2012.12.001
32.
UrryH. L.CrittleC. S.FloerkeV. A.LeonardM. Z.PerryC. S.IIIAkdilekN.AlbertE. R.BlockA. J.Ackerley BollingerC.BowersE. M.BrodyR. S.BurkK. C.BurnsteinA.ChanA. K.ChanP. C.ChangL. J.ChenE.ChiarawongseC. P.ChinG.ChinK. (in press). Don’t ditch the laptop just yet: A direct replication of Mueller and Oppenheimer’s (2014) study 1 plus mini-meta-analyses across similar studies. Psychological Science.
33.
WardA. F.DukeK.GneezyA.BosM. W. (2017). Brain drain: The mere presence of one’s own smartphone reduces available cognitive capacity. Journal of the Association for Consumer Research, 2(2), 140–154. https://doi.org/10.1086/691462
34.
WoltersC. A.HussainM. (2015). Investigating grit and its relations with college students’ self-regulated learning and academic achievement. Metacognition Learning10, 293–311. https://doi.org/10.1007/s11409-014-9128-9
