1887

Increasing Student Metacognition and Learning through Classroom-Based Learning Communities and Self-Assessment

    Author: Amy Siegesmund1
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    Affiliations: 1: Department of Biology, Pacific Lutheran University, Tacoma, WA 98447
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Published 04 May 2016
    • ©2016 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/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: Department of Biology, Pacific Lutheran University, Tacoma, WA 98447. Phone: 253-535-8310. Fax: 253-536-5055. E-mail: siegesam@plu.edu.
    Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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    Abstract:

    Student overconfidence challenges success in introductory biology. This study examined the impact of classroom learning communities and self-assessment on student metacognition and subsequent impact on student epistemological beliefs, behaviors, and learning. Students wrote weekly self-assessments reflecting on the process of learning and received individual feedback. Students completed a learning strategies inventory focused on metacognition and study behaviors at the beginning and end of the semester and a Student Assessment of their Learning Gains (SALG) at the end of the semester. Results indicated significant changes in both metacognition and study behaviors over the course of the semester, with a positive impact on learning as determined by broad and singular measures. Self-assessments and SALG data demonstrated a change in student beliefs and behaviors. Taken together, these findings argue that classroom learning communities and self-assessment can increase student metacognition and change student epistemological beliefs and behaviors.

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References & Citations

1. Ambrose SA, Kirst MW, Lovett MC, Norman MK2010How learning works: seven research-based principles for smart teachingJossey-BassSan Francisco, CA
2. Andrade MS2007Learning communities: examining positive outcomesJ Coll Stud Retent912010.2190/E132-5X73-681Q-K188 http://dx.doi.org/10.2190/E132-5X73-681Q-K188
3. Angelo TA, Cross KP1993Diagnostic learning logs311315Classroom assessment techniques: a handbook for college teachersJossey-BassSan Francisco, CA
4. Arum R, Roksa J, Cho E2011Improving undergraduate learning: findings and policy recommendations from the SSRC-CLA longitudinal projectSocial Science Research CouncilNew York, NY
5. Billett S2009Personal epistemologies, work and learningEduc Res Rev421021910.1016/j.edurev.2009.06.001 http://dx.doi.org/10.1016/j.edurev.2009.06.001
6. Black P, William D1998Assessment and classroom learningAssess Educ577410.1080/0969595980050102 http://dx.doi.org/10.1080/0969595980050102
7. Black P, William D2009Developing the theory of formative assessmentEduc Assess Eval Account2153110.1007/s11092-008-9068-5 http://dx.doi.org/10.1007/s11092-008-9068-5
8. Blackwell LS, Tresniewski KH, Dweck CS2007Implicit theories of intelligence predict achievement across an adolescent transition: a longitudinal study and an interventionChild Dev7824626310.1111/j.1467-8624.2007.00995.x17328703 http://dx.doi.org/10.1111/j.1467-8624.2007.00995.x
9. Bose J, Rengel Z2009A model formative assessment strategy to promote student-centered self-regulated learning in higher educationUS-China Educ Rev62935
10. Buch K, Spaulding S2008Using program assessment to “prove and improve” a discipline-based learning communityJ Learn Communit Res33546
11. Butler DL, Winne PH1999Feedback and self-regulated learning: a theoretical synthesisRev Educ Res6524528110.3102/00346543065003245 http://dx.doi.org/10.3102/00346543065003245
12. Chew SL2008Study more! Study harder! Students’ and teachers’ faulty beliefs about how people learn2225 Meyers S, Stowell JEssays from E-Xcellence in teaching Society for the Teaching of Psychology[Online] http://teachpsych.org/ebooks/eit2008/index.php
13. Chew SL2014Helping students to get the most out of studyingApplying science of learning in education: infusing psychological science into the curriculum, society for the teaching of psychology[Online.] http://teachpsych.org/ebooks/asle2014/index.phpaccessed 15 January 2015
14. Coutinho SA2007The relationship between goals, metacognition, and academic successEducate73947
15. 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
16. Dewey J1933How we thinkD. C. Heath & Co.Boston, MA
17. Dunning D, Heath C, Suls JM2004Flawed self-assessmentPsychol Sci Public Interest56910610.1111/j.1529-1006.2004.00018.x26158995 http://dx.doi.org/10.1111/j.1529-1006.2004.00018.x
18. Dunning D, Johnson K, Ehrlinger J, Kruger J2003Why people fail to recognize their own incompetenceCurr Dir Psychol Sci12838710.1111/1467-8721.01235 http://dx.doi.org/10.1111/1467-8721.01235
19. Elwood J, Klenowski V2002Creating communities of shared practice: the challenges of assessment use in learning and teachingAssess Eval High Educ2724325610.1080/02602930220138606 http://dx.doi.org/10.1080/02602930220138606
20. Flavell JH1979Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiryAm Psychol3490610.1037/0003-066X.34.10.906 http://dx.doi.org/10.1037/0003-066X.34.10.906
21. Goodsell Love A2012The growth and current state of learning communities in higher educationNew Dir Teach Learn201251810.1002/tl.20032 http://dx.doi.org/10.1002/tl.20032
22. Hake RR1998Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics coursesAm J Phys66647410.1119/1.18809 http://dx.doi.org/10.1119/1.18809
23. Handelsman J, Miller S, Pfund C2007Scientific TeachingW. H. Freeman and CompanyNew York, NY
24. Hill KM, Brözel VS, Heiberger GA2014Examining the delivery modes of metacognitive awareness and active reading lessons in a college nonmajors introductory biology courseJ Microbiol Biol Educ1551210.1128/jmbe.v15i1.629248395094004747 http://dx.doi.org/10.1128/jmbe.v15i1.629
25. Kienhues D, Bromme R, Stahl E2008Changing epistemological beliefs: the unexpected impact of a short-term interventionBr J Educ Psychol7854556510.1348/000709907X26858918166142 http://dx.doi.org/10.1348/000709907X268589
26. Kruger J, Dunning D1999Unskilled and unaware of it: how difficulties in recognizing one’s own incompetence lead to inflated self-assessmentsJ Pers Soc Psychol771121113410.1037/0022-3514.77.6.1121 http://dx.doi.org/10.1037/0022-3514.77.6.1121
27. Lenning O, Ebbers L1999The powerful potential of learning communities: improving education for the future (No. 6), ASHE-ERIC Higher Education ReportGraduate School of Education and Human Development, George Washington UniversityWashington, DC
28. Mair C2012Using technology for enhancing reflective writing, metacognition and learningJ Furth High Educ3614716710.1080/0309877X.2011.590583 http://dx.doi.org/10.1080/0309877X.2011.590583
29. Markulis PM, Murff E, Strang DR2011Should college instructors change their teaching styles to meet the millennial student?Dev Bus Simul Exp Learn38189200
30. McMillan JH, Hearn J2008Student self-assessment: the key to stronger student motivation and higher achievementEduc Horiz874049
31. Mieklejohn A1932The experimental collegeHarper CollinsNew York, NY
32. Nicol DJ, Macfarlane-Dick D2006Formative assessment and self-regulated learning: a model and seven principles of good feedback practiceStud High Educ3119921810.1080/03075070600572090 http://dx.doi.org/10.1080/03075070600572090
33. Psycharis S2013Examining the effect of the computational models on learning performance, scientific reasoning, epistemic beliefs and argumentation: an implication for the STEM agendaComput Educ6825326510.1016/j.compedu.2013.05.015 http://dx.doi.org/10.1016/j.compedu.2013.05.015
34. Ridley DS, Schutz PA, Glanz RS, Weinstein CE1992Self-regulated learning: the interactive influence of metacognitive awareness and goal-settingJ Exp Educ6029330610.1080/00220973.1992.9943867 http://dx.doi.org/10.1080/00220973.1992.9943867
35. Rocconi LM2011The impact of learning communities on first year students’ growth and development in collegeRes High Educ5217819310.1007/s11162-010-9190-3 http://dx.doi.org/10.1007/s11162-010-9190-3
36. Sanbonmatsu DM, Strayer DL, Medeiros-Ward N, Watson JM2013Who multi-tasks and why? Multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seekingPLoS ONE8e5440210.1371/journal.pone.0054402233727203553130 http://dx.doi.org/10.1371/journal.pone.0054402
37. Saville BK, Lawrence NK, Jakobsen KV2012Creating learning communities in the classroomNew Dir Teach Learn2012576910.1002/tl.20036 http://dx.doi.org/10.1002/tl.20036
38. Schommer-Aikins M, Easter M2006Ways of knowing and epistemological beliefs: combined effect on academic performanceEduc Psychol2641142310.1080/01443410500341304 http://dx.doi.org/10.1080/01443410500341304
39. Schraw G, Dennison RS1994Assessing metacognitive awarenessEduc Psychol19460475
40. Shepard LA2000The role of assessment in a learning cultureEduc Res2941410.3102/0013189X029007004 http://dx.doi.org/10.3102/0013189X029007004
41. Sperling R, Howard BC, Staley R, DuBois N2004Metacognition and self-regulated learning constructsEduc Res Eval1011713910.1076/edre.10.2.117.27905 http://dx.doi.org/10.1076/edre.10.2.117.27905
42. Sweeney R2006Millennial behaviors and demographicsNewark NJ Institute of Technology[Online.] http://unbtls.ca/teachingtips/pdfs/sew/Millennial-Behaviors.pdfaccessed on 24 November 2014
43. Tan C1992An evaluation of the use of continuous assessment in the teaching of physiologyHigher Educ2325527210.1007/BF00145016 http://dx.doi.org/10.1007/BF00145016
44. Tanner KD2012Promoting student metacognitionCBE Life Sci Educ1111312010.1187/cbe.12-03-0033226655843366894 http://dx.doi.org/10.1187/cbe.12-03-0033
45. Taraban R, Rynearson K, Kerr MS2000Metacognition and freshman academic performanceJ Dev Educ241214161820
46. Taylor K, Moore WS, MacGregor J, Lindblad J2003Learning community research and assessment: what we know nowNational Learning Communities Project Monograph SeriesThe Evergreen State CollegeOlympia, WA
47. Tinto V2003Learning better together: the impact of learning communities on student success (No. 8)Higher Education Monograph SeriesSyracuse University, Higher Education Program, School of EducationSyracuse, NY
48. Tomanek D, Montplaisir L2004Students’ studying and approaches to learning in introductory biologyCBE Life Sci Educ325326210.1187/cbe.04-06-0041 http://dx.doi.org/10.1187/cbe.04-06-0041
49. Young A, Fry J2012Metacognitive awareness and academic achievement in college studentsJ Scholar Teach Learn8110
50. Zhao N, Wardeska JG, McGuire SY, Cook E2014Metacognition: an effective tool to promote success in college science learningJ Coll Sci Teach43485410.2505/4/jcst14_043_04_48 http://dx.doi.org/10.2505/4/jcst14_043_04_48
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2016-05-04
2017-09-23

Abstract:

Student overconfidence challenges success in introductory biology. This study examined the impact of classroom learning communities and self-assessment on student metacognition and subsequent impact on student epistemological beliefs, behaviors, and learning. Students wrote weekly self-assessments reflecting on the process of learning and received individual feedback. Students completed a learning strategies inventory focused on metacognition and study behaviors at the beginning and end of the semester and a Student Assessment of their Learning Gains (SALG) at the end of the semester. Results indicated significant changes in both metacognition and study behaviors over the course of the semester, with a positive impact on learning as determined by broad and singular measures. Self-assessments and SALG data demonstrated a change in student beliefs and behaviors. Taken together, these findings argue that classroom learning communities and self-assessment can increase student metacognition and change student epistemological beliefs and behaviors.

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Figures

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FIGURE 1

Student predictions versus actual grade distribution in BIOL 225. During the 1 week of the semester, students ( 145) anonymously predicted the grade they would receive in the course (dark bars). The actual end-of-the-semester grade distribution for BIOL 225-1 is shown for comparison (light bars); a similar distribution of final grades was observed in BIOL 225-2. A = 100–90%; B = 89–80%; C = 79–65%; D = 64–56%; E = 55–0%.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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FIGURE 2

Student-predicted exam scores vs. actual exam scores. Students were asked to predict their score on the 1 exam. This was the final question on the exam; students had therefore completed the exam before making prediction. Predicted data are plotted against the actual score for each student who made a prediction. Data shown are for a single exam in BIOL 225-1 ( = 0.6); the same trend was observed in BIOL 225-2. Boxes highlight two students who had large discrepancies in predicted and actual exam scores.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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Image of FIGURE 3

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FIGURE 3

Impact of classroom community on student learning. At the end of the semester, students completed the Student Assessment of Learning Gains (SALG) online survey. Data shown are selected responses reporting gains in understanding class content and skills and how the class activities impacted learning and attitudes. Questions were scored on a 5-point scale ranging from 1 (no gain) to 5 (great gain). Data shown are the combined percentages of BIOL 225-1 and BIOL 225-2 students ( 73).

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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FIGURE 4

Metacognitive awareness (MA) scores pre- and post-ELP. Students completed electronic learning portfolio (ELP) entries from week 5 through the end of the semester. Metacognitive awareness was assessed as part of the learning strategies inventory (items 1–52) given at the beginning (pre-ELP) and end (post-ELP) of the semester. There were significant increases in MA scores in both BIOL 225-1 (dark bars, 0.01) and BIOL 225-2 (light bars, 0.02). Error bars depict the standard error of the mean.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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FIGURE 5

Study skills (SS) scores pre- and post-ELP. Students completed electronic learning portfolio (ELP) entries from week 5 through the end of the semester. Study skills were assessed as part of the learning strategies inventory (items 53–68) given at the beginning (pre-ELP) and end (post-ELP) of the semester. In both BIOL 225-1 (dark bars) and BIOL 225-2 (light bars), there was a significant ( 0.0001) decrease in SS scores. Error bars depict the standard error of the mean.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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FIGURE 6

Impact of ELP on student behaviors. At the end of the semester, students completed the Student Assessment of Learning Gains (SALG; www.salgsite.org) online survey. Data shown are selected responses related to changes in student behaviors targeted in the ELP including the class impact on attitudes; how class activities helped learning; and gains made in particular skills. Students were asked how much an activity helped their learning (e.g. writing in my ELP and reading the feedback) and what gains they made in particular skills (all other behaviors). Questions were scored on a five-point scale ranging from 1 (no gain) to 5 (great gain). Data shown are the combined percentages of BIOL 225-1 and BIOL 225-2 students ( 73).

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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FIGURE 7

DFW and DE rates pre- and post-ELP. BIOL 225-1 and BIOL 225-2 students ( 92) completed electronic learning portfolio (ELP) entries from week 5 through the end of the semester. DFW rates represent students who dropped, failed, or withdrew from the course. DE rate represents students who received a failing grade (D or E) in the course. No ELP refers to a cohort of BIOL 225 taught by the same instructor in which the ELP was not employed.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
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Image of FIGURE 8

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FIGURE 8

Metacognitive gains (MG) and exam scores in BIOL 225-1 and BIOL 225-2. Metacognitive gains (MG) were calculated as described in Methods. Exam 1 was taken pre-ELP and exams 2, 3, and 4 were taken post-ELP. A) Positive impact of MG on exam performance. Exam scores are shown for three representative students with increased MG and exam scores over the course of the semester. One student (MG = 0.35) had an exam score above 100% due to an extra credit question. B) Lower MG and relatively unchanged exam performance. Exam scores are shown for three representative students with little change in MG and exam scores over the course of the semester.

Source: J. Microbiol. Biol. Educ. May 2016 vol. 17 no. 2 204-214. doi:10.1128/jmbe.v17i2.954
Download as Powerpoint

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