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Student Buy-In Toward Formative Assessments: The Influence of Student Factors and Importance for Course Success

    Authors: Kathleen R. Brazeal1, Brian A. Couch1,*
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    Affiliations: 1: School of Biological Sciences, University of Nebraska, Lincoln, NE 68588
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Received 05 September 2016 Accepted 25 January 2017 Published 21 April 2017
    • ©2017 Author(s). Published by the American Society for Microbiology.
    • [open-access] This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-NoDerivatives 4.0 International license (https://creativecommons.org/licenses/by-nc-nd/4.0/ and https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode), which grants the public the nonexclusive right to copy, distribute, or display the published work.

    • Supplemental materials available at http://asmscience.org/jmbe
    • *Corresponding author. Mailing address: School of Biological Sciences, University of Nebraska, 204 Manter, Lincoln, NE 68588-0118. Phone: 402-472-8130. Fax: 402-472-2083. E-mail: bcouch2@unl.edu.
    Source: J. Microbiol. Biol. Educ. April 2017 vol. 18 no. 1 doi:10.1128/jmbe.v18i1.1235
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    Abstract:

    Formative assessment (FA) techniques, such as pre-class assignments, in-class activities, and post-class homework, have been shown to improve student learning. While many students find these techniques beneficial, some students may not understand how they support learning or may resist their implementation. Improving our understanding of FA buy-in has important implications, since buy-in can potentially affect whether students fully engage with and learn from FAs. We investigated FAs in 12 undergraduate biology courses to understand which student characteristics influenced buy-in toward FAs and whether FA buy-in predicted course success. We administered a mid-semester survey that probed student perceptions toward several different FA types, including activities occurring before, during, and after class. The survey included closed-ended questions aligned with a theoretical framework outlining key FA objectives. We used factor analysis to calculate an overall buy-in score for each student and general linear models to determine whether certain characteristics were associated with buy-in and whether buy-in predicted exam scores and course grades. We found that unfixed student qualities, such as perceptions, behaviors, and beliefs, consistently predicted FA buy-in, while fixed characteristics, including demographics, previous experiences, and incoming performance metrics, had more limited effects. Importantly, we found that higher buy-in toward most FA types predicted higher exam scores and course grades, even when controlling for demographic characteristics and previous academic performance. We further discuss steps that instructors can take to maximize student buy-in toward FAs.

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References & Citations

1. American Association for the Advancement of Science2011Vision and Change in Undergraduate Biology Education: A Call to Action: a summary of recommendations made at a national conference organized by the American Association for the Advancement of Science, July 15–17, 2009Washington, DC
2. National Research Council (NRC)2003Evaluating and improving undergraduate teaching in science, technology, engineering, and mathematicsThe National Academies Press, Center for Education, Division of Behavioral and Social Sciences and EducationWashington, DC
3. Eddy SL, Hogan KA2014Getting under the hood: how and for whom does increasing course structure work?CBE Life Sci Educ1345346810.1187/cbe.14-03-0050251852294152207 http://dx.doi.org/10.1187/cbe.14-03-0050
4. Reimer LC, Schenke K, Nguyen T, O’Dowd DK, Domina T, Warschauer M2016Evaluating promising practices in undergraduate STEM lecture coursesRSF Russell Sage Found J Soc Sci2212233
5. Freeman S, Haak D, Wenderoth MP2011Increased course structure improves performance in introductory biologyCBE Life Sci Educ1017518610.1187/cbe.10-08-0105216330663105924 http://dx.doi.org/10.1187/cbe.10-08-0105
6. Black P, Wiliam D2009Developing the theory of formative assessmentEduc Assess Eval Account Former J Pers Eval Educ2153110.1007/s11092-008-9068-5 http://dx.doi.org/10.1007/s11092-008-9068-5
7. Kay RH, LeSage A2009Examining the benefits and challenges of using audience response systems: a review of the literatureComput Educ5381982710.1016/j.compedu.2009.05.001 http://dx.doi.org/10.1016/j.compedu.2009.05.001
8. Keough SM2012Clickers in the classroom: a review and a replicationJ Manag Educ3682284710.1177/1052562912454808 http://dx.doi.org/10.1177/1052562912454808
9. Vickrey T, Rosploch K, Rahmanian R, Pilarz M, Stains M2015Research-based implementation of peer instruction: a literature reviewCBE Life Sci Educ14es310.1187/cbe.14-11-0198257130954353089 http://dx.doi.org/10.1187/cbe.14-11-0198
10. Brazeal KR, Brown TL, Couch BA2016Characterizing student perceptions of and buy-in toward common formative assessment techniquesCBE Life Sci Educ15ar7310.1187/cbe.16-03-0133279090235132370 http://dx.doi.org/10.1187/cbe.16-03-0133
11. Seidel SB, Tanner KD2013“What if students revolt?”— Considering student resistance: origins, options, and opportunities for investigationCBE Life Sci Educ1258659510.1187/cbe-13-09-0190242972863846509 http://dx.doi.org/10.1187/cbe-13-09-0190
12. Prosser M, Trigwell K2014Qualitative variation in approaches to university teaching and learning in large first-year classesHigh Educ6778379510.1007/s10734-013-9690-0 http://dx.doi.org/10.1007/s10734-013-9690-0
13. Welsh AJ2012Exploring undergraduates’ perceptions of the use of active learning techniques in science lecturesJ Coll Sci Teach428087
14. Wolter BH, Lundeberg MA, Kang H, Herreid CF2011Students’ perceptions of using personal response systems (“clickers”) with cases in scienceJ Coll Sci Teach401419
15. Birenbaum M, Feldman RA1998Relationships between learning patterns and attitudes towards two assessment formatsEduc Res40909810.1080/0013188980400109 http://dx.doi.org/10.1080/0013188980400109
16. Gok T2011An evaluation of student response systems from the viewpoint of instructors and studentsTurk Online J Educ Technol1046783
17. Hoekstra A2008Vibrant student voices: exploring effects of the use of clickers in large college coursesLearn Media Technol3332934110.1080/17439880802497081 http://dx.doi.org/10.1080/17439880802497081
18. Kay RH2009Examining gender differences in attitudes toward interactive classroom communications systems (ICCS)Comput Educ5273074010.1016/j.compedu.2008.11.015 http://dx.doi.org/10.1016/j.compedu.2008.11.015
19. Hillyard C, Gillespie D, Littig P2010University students’ attitudes about learning in small groups after frequent participationAct Learn High Educ1192010.1177/1469787409355867 http://dx.doi.org/10.1177/1469787409355867
20. Terrion JL, Aceti V2012Perceptions of the effects of clicker technology on student learning and engagement: A study of freshmen chemistry studentsRes Learn Technol20216150doi:http://dx.doi.org/10.3402/rlt.v20i0.1615010.3402/rlt.v20i0.16150 http://dx.doi.org/10.3402/rlt.v20i0.16150
21. Zeidner M1987Essay versus multiple-choice type classroom exams: the student’s perspectiveJ Educ Res8035235810.1080/00220671.1987.10885782 http://dx.doi.org/10.1080/00220671.1987.10885782
22. Preszler RW, Dawe A, Shuster CB, Shuster M2007Assessment of the effects of student response systems on student learning and attitudes over a broad range of biology coursesCBE Life Sci Educ6294110.1187/cbe.06-09-0190173393921854854 http://dx.doi.org/10.1187/cbe.06-09-0190
23. Trees AR, Jackson MH2007The learning environment in clicker classrooms: student processes of learning and involvement in large university-level courses using student response systemsLearn Media Technol32214010.1080/17439880601141179 http://dx.doi.org/10.1080/17439880601141179
24. Crossgrove K, Curran KL2008Using clickers in nonmajors-and majors-level biology courses: student opinion, learning, and long-term retention of course materialCBE Life Sci Educ714615410.1187/cbe.07-08-0060183168172262112 http://dx.doi.org/10.1187/cbe.07-08-0060
25. Akerlind GS, Trevitt AC1999Enhancing self-directed learning through educational technology: when students resist the changeInnov Educ Train Int369610510.1080/1355800990360202 http://dx.doi.org/10.1080/1355800990360202
26. Taylor M1986Learning for self-direction in the classroom: the pattern of a transition processStud High Educ11557210.1080/03075078612331378461 http://dx.doi.org/10.1080/03075078612331378461
27. Birenbaum M1997Assessment preferences and their relationship to learning strategies and orientationsHigh Educ33718410.1023/A:1002985613176 http://dx.doi.org/10.1023/A:1002985613176
28. Jones A, Kember D1994Approaches to learning and student acceptance of self-study packagesProgram Learn Educ Technol319397
29. Felder RM, Brent R1996Navigating the bumpy road to student-centered instructionColl Teach44434710.1080/87567555.1996.9933425 http://dx.doi.org/10.1080/87567555.1996.9933425
30. Keeley SM, Shemberg KM, Cowell BS, Zinnbauer BJ1995Coping with student resistance to critical thinking: what the psychotherapy literature can tell usColl Teach4314014510.1080/87567555.1995.9925537 http://dx.doi.org/10.1080/87567555.1995.9925537
31. Fabrigar LR, Wegener DT, MacCallum RC, Strahan EJ1999Evaluating the use of exploratory factor analysis in psychological researchPsychol Methods427210.1037/1082-989X.4.3.272 http://dx.doi.org/10.1037/1082-989X.4.3.272
32. Osborne JW, Costello AB2009Best practices in exploratory factor analysis: four recommendations for getting the most from your analysisPan-Pac Manag Rev12131146
33. Theobald R, Freeman S2014Is it the intervention or the students? Using linear regression to control for student characteristics in undergraduate STEM education researchCBE Life Sci Educ13414810.1187/cbe-13-07-0136245915023940461 http://dx.doi.org/10.1187/cbe-13-07-0136
34. Terenzini PT, Springer L, Yaeger PM, Pascarella ET, Nora A1996First-generation college students: characteristics, experiences, and cognitive developmentRes High Educ3712210.1007/BF01680039 http://dx.doi.org/10.1007/BF01680039
35. Warburton EC, Bugarin R, Nunez AM2001Bridging the gap: academic preparation and postsecondary success of first-generation students (NCES 2001-153)National Center for Education Statistics, US Government Printing OfficeWashington, DC
36. Stephens NM, Fryberg SA, Markus HR, Johnson CS, Covarrubias R2012Unseen disadvantage: how American universities’ focus on independence undermines the academic performance of first-generation college studentsJ Pers Soc Psychol102117810.1037/a002714322390227 http://dx.doi.org/10.1037/a0027143
37. Collier PJ, Morgan DL2008“Is that paper really due today?”: Differences in first-generation and traditional college students’ understandings of faculty expectationsHigh Educ5542544610.1007/s10734-007-9065-5 http://dx.doi.org/10.1007/s10734-007-9065-5
38. Pascarella ET, Pierson CT, Wolniak GC, Terenzini PT2004First-generation college students: additional evidence on college experiences and outcomesJ High Educ24928410.1353/jhe.2004.0016 http://dx.doi.org/10.1353/jhe.2004.0016
39. Pike GR, Kuh GD2005First-and second-generation college students: a comparison of their engagement and intellectual developmentJ High Educ27630010.1353/jhe.2005.0021 http://dx.doi.org/10.1353/jhe.2005.0021
40. Stebleton M, Soria K2013Breaking down barriers: academic obstacles of first-generation students at research universities
41. Lundberg CA, Schreiner LA, Hovaguimian K, Slavin Miller S2007First-generation status and student race/ethnicity as distinct predictors of student involvement and learningNASPA J44578310.2202/0027-6014.1755 http://dx.doi.org/10.2202/0027-6014.1755
42. Soria KM, Stebleton MJ2012First-generation students’ academic engagement and retentionTeach High Educ1767368510.1080/13562517.2012.666735 http://dx.doi.org/10.1080/13562517.2012.666735
43. Luo W2008Just-in-Time Teaching (JiTT) improves students’ performance in classes—adaptation of JiTT in four geography coursesJ Geosci Educ5616617110.5408/1089-9995-56.2.166 http://dx.doi.org/10.5408/1089-9995-56.2.166
44. Marrs KA, Novak G2004Just-in-Time Teaching in biology: creating an active learner classroom using the internetCell Biol Educ3496110.1187/cbe.03-11-0022220393453203712 http://dx.doi.org/10.1187/cbe.03-11-0022
45. Simkins S, Maier M2004Using Just-in-Time Teaching techniques in the principles of economics courseSoc Sci Comput Rev2244445610.1177/0894439304268643 http://dx.doi.org/10.1177/0894439304268643
46. Cavanagh AJ, Aragón OR, Chen X, Couch B, Durham M, Bobrownicki A, Hanauer DI, Graham MJ2016Student buy-in to active learning in a college science courseCBE Life Sci Educ15ar7610.1187/cbe.16-07-0212279090265132373 http://dx.doi.org/10.1187/cbe.16-07-0212
47. Lizzio A, Wilson K, Simons R2002University students’ perceptions of the learning environment and academic outcomes: implications for theory and practiceStud High Educ27275210.1080/03075070120099359 http://dx.doi.org/10.1080/03075070120099359
48. Struyven K, Dochy F, Janssens S2005Students’ perceptions about evaluation and assessment in higher education: a reviewAssess Eval High Educ3032534110.1080/02602930500099102 http://dx.doi.org/10.1080/02602930500099102
49. Trigwell K, Prosser M1991Improving the quality of student learning: the influence of learning context and student approaches to learning on learning outcomesHigh Educ2225126610.1007/BF00132290 http://dx.doi.org/10.1007/BF00132290
50. Davidson RA2003Relationship of study approach and exam performanceJ Account Educ20294410.1016/S0748-5751(01)00025-2 http://dx.doi.org/10.1016/S0748-5751(01)00025-2
51. Elias RZ2005Students’ approaches to study in introductory accounting coursesJ Educ Bus8019419910.3200/JOEB.80.4.194-199 http://dx.doi.org/10.3200/JOEB.80.4.194-199
52. Holschuh JP2000Do as I say, not as I do: high, average, and low-performing students’ strategy use in biologyJ Coll Read Learn319410810.1080/10790195.2000.10850105 http://dx.doi.org/10.1080/10790195.2000.10850105
53. Silverthorn DU2006Teaching and learning in the interactive classroomAdv Physiol Educ3013514010.1152/advan.00087.200617108239 http://dx.doi.org/10.1152/advan.00087.2006
54. Biggs J1996Enhancing teaching through constructive alignmentHigh Educ3234736410.1007/BF00138871 http://dx.doi.org/10.1007/BF00138871
55. Blumberg P2009Maximizing learning through course alignment and experience with different types of knowledgeInnov High Educ349310310.1007/s10755-009-9095-2 http://dx.doi.org/10.1007/s10755-009-9095-2
56. Allen D, Tanner K2007Putting the horse back in front of the cart: using visions and decisions about high-quality learning experiences to drive course designCBE Life Sci Educ6858910.1187/cbe.07-03-0017175488701885907 http://dx.doi.org/10.1187/cbe.07-03-0017
57. Wiggins G, McTighe J2005Understanding by designAssociation for Supervision and Curriculum DevelopmentAlexandria, VA
58. Allen D, Tanner K2002Approaches to cell biology teaching: questions about questionsCell Biol Educ1636710.1187/cbe.02-07-002112459794128545 http://dx.doi.org/10.1187/cbe.02-07-0021
59. Crowe A, Dirks C, Wenderoth MP2008Biology in bloom: implementing Bloom’s taxonomy to enhance student learning in biologyCBE Life Sci Educ736838110.1187/cbe.08-05-0024190474242592046 http://dx.doi.org/10.1187/cbe.08-05-0024
60. Krathwohl DR2002A revision of Bloom’s taxonomy: an overviewTheory Pract4121221810.1207/s15430421tip4104_2 http://dx.doi.org/10.1207/s15430421tip4104_2
61. Tanner K, Allen D2005Understanding the wrong answers— teaching toward conceptual changeCell Biol Educ411211710.1187/cbe.05-02-0068159178681103711 http://dx.doi.org/10.1187/cbe.05-02-0068
62. Miri B, David B-C, Uri Z2007Purposely teaching for the promotion of higher-order thinking skills: a case of critical thinkingRes Sci Educ3735336910.1007/s11165-006-9029-2 http://dx.doi.org/10.1007/s11165-006-9029-2
63. Smith MK, Wood WB, Adams WK, Wieman C, Knight JK, Guild N, Su TT2009Why peer discussion improves student performance on in-class concept questionsScience32312212410.1126/science.116591919119232 http://dx.doi.org/10.1126/science.1165919
64. Benford R, Gess-Newsome J2006Factors affecting student academic success in gateway courses at Northern Arizona UniversityCent Sci Teach Learn North Ariz Univ ERIC Document No ED495693
65. Graham CR, Tripp TR, Seawright L, Joeckel G2007Empowering or compelling reluctant participators using audience response systemsAct Learn High Educ823325810.1177/1469787407081885 http://dx.doi.org/10.1177/1469787407081885
66. Oakley B, Felder RM, Brent R, Elhajj I2004Turning student groups into effective teamsJ Stud Centered Learn2934
67. Tanner KD2009Talking to learn: why biology students should be talking in classrooms and how to make it happenCBE Life Sci Educ8899410.1187/cbe.09-03-0021194874942689152 http://dx.doi.org/10.1187/cbe.09-03-0021
68. Knight JK, Wise SB, Southard KM2013Understanding clicker discussions: student reasoning and the impact of instructional cuesCBE Life Sci Educ1264565410.1187/cbe.13-05-0090242972913846515 http://dx.doi.org/10.1187/cbe.13-05-0090
69. Novak GM2011Just-in-Time TeachingNew Dir Teach Learn2011637310.1002/tl.469 http://dx.doi.org/10.1002/tl.469
70. Benfield G2002Designing and managing effective online discussions Oxford Centre for Staff and Learning DevelopmentOxford Brookes UniversityOxford, UK
71. Fishman EJ2014With great control comes great responsibility: the relationship between perceived academic control, student responsibility, and self-regulationBr J Educ Psychol8468570210.1111/bjep.1205725251935 http://dx.doi.org/10.1111/bjep.12057
72. Vermunt JD, Vermetten YJ2004Patterns in student learning: relationships between learning strategies, conceptions of learning, and learning orientationsEduc Psychol Rev1635938410.1007/s10648-004-0005-y http://dx.doi.org/10.1007/s10648-004-0005-y
73. Trigwell K, Prosser M, Waterhouse F1999Relations between teachers’ approaches to teaching and students’ approaches to learningHigh Educ37577010.1023/A:1003548313194 http://dx.doi.org/10.1023/A:1003548313194
74. Vermunt J, Verschaffel L2000Process-oriented teaching209225 Simons RL, van der Linden J, Duffy TNew learningKluwer Academic PublishersNetherlands10.1007/0-306-47614-2_11 http://dx.doi.org/10.1007/0-306-47614-2_11
75. Vermunt JD, Verloop N1999Congruence and friction between learning and teachingLearn Instr925728010.1016/S0959-4752(98)00028-0 http://dx.doi.org/10.1016/S0959-4752(98)00028-0
76. Tanner KD2012Promoting student metacognitionCBE Life Sci Educ1111312010.1187/cbe.12-03-0033226655843366894 http://dx.doi.org/10.1187/cbe.12-03-0033
77. Ertmer PA, Newby TJ1996The expert learner: strategic, self-regulated, and reflectiveInstr Sci2412410.1007/BF00156001 http://dx.doi.org/10.1007/BF00156001
78. Schraw G, Crippen KJ, Hartley K2006Promoting self-regulation in science education: metacognition as part of a broader perspective on learningRes Sci Educ3611113910.1007/s11165-005-3917-8 http://dx.doi.org/10.1007/s11165-005-3917-8
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/content/journal/jmbe/10.1128/jmbe.v18i1.1235
2017-04-21
2017-09-19

Abstract:

Formative assessment (FA) techniques, such as pre-class assignments, in-class activities, and post-class homework, have been shown to improve student learning. While many students find these techniques beneficial, some students may not understand how they support learning or may resist their implementation. Improving our understanding of FA buy-in has important implications, since buy-in can potentially affect whether students fully engage with and learn from FAs. We investigated FAs in 12 undergraduate biology courses to understand which student characteristics influenced buy-in toward FAs and whether FA buy-in predicted course success. We administered a mid-semester survey that probed student perceptions toward several different FA types, including activities occurring before, during, and after class. The survey included closed-ended questions aligned with a theoretical framework outlining key FA objectives. We used factor analysis to calculate an overall buy-in score for each student and general linear models to determine whether certain characteristics were associated with buy-in and whether buy-in predicted exam scores and course grades. We found that unfixed student qualities, such as perceptions, behaviors, and beliefs, consistently predicted FA buy-in, while fixed characteristics, including demographics, previous experiences, and incoming performance metrics, had more limited effects. Importantly, we found that higher buy-in toward most FA types predicted higher exam scores and course grades, even when controlling for demographic characteristics and previous academic performance. We further discuss steps that instructors can take to maximize student buy-in toward FAs.

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Figures

Image of FIGURE 1

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FIGURE 1

Distributions of FA buy-in scores for each FA type. Central bars represent medians, boxes represent inner quartiles, and whiskers represent the 5 and 95 percentiles. FA = formative assessment; JiTT = Just-in-Time Teaching; OTP-pre = online textbook program pre-class assignments; CQ = clicker questions; ICA = in-class activities; OTP-post = online textbook program post-class assignments; HW/Q = homework assignments/quizzes.

Source: J. Microbiol. Biol. Educ. April 2017 vol. 18 no. 1 doi:10.1128/jmbe.v18i1.1235
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Image of FIGURE 2

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FIGURE 2

Model-predicted exam grade z-scores (A) and course grades (B) of students with differing FA buy-in. Bars represent point estimate predictions from the general linear models for grades of three hypothetical students with very high, medium, and very low buy-in (i.e., resistant), at the 95, 50, and 5 percentile buy-in scores, respectively, for each FA type. Asterisks indicate FAs for which buy-in significantly influenced grades ( < 0.05; Table 5 ), while controlling for demographic variables, incoming GPA, and course section. FA = formative assessment; JiTT = Just-in-Time Teaching; OTP-pre = online textbook program pre-class assignments; CQ = clicker questions; ICA = in-class activities; OTP-post = online textbook program post-class assignments; HW/Q = homework assignments/quizzes.

Source: J. Microbiol. Biol. Educ. April 2017 vol. 18 no. 1 doi:10.1128/jmbe.v18i1.1235
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