Abstract
Between 2015 and 2018, a university in the Mountain West region of the United States piloted a mathematics intervention supported by the U.S. Department of Education’s Strengthening Institutions Program (SIP). Designed to improve outcomes of undergraduates taking Algebra and Pre-Calculus courses, the intervention applied pedagogical and delivery practices founded in self-efficacy theory and mathematics mindset utilizing peer tutors in the classroom. Using hierarchical linear modelling, we compared outcomes of SIP (n = 325) and non-SIP (n = 2727) students while controlling for teaching and classroom characteristics and student background characteristics. Students enrolled in College Algebra were three times as likely to pass if they were enrolled in the SIP intervention section (Odds Ratio = 3.1). Pre-Calculus students enrolled in the intervention had approximately the same likelihood of passing as students in traditional instruction, but final examination scores were significantly higher for SIP students. Our research suggests that the SIP intervention played a role in improving student performance in both courses. Program successes and challenges for implementation are also presented.
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References
ACT Statement on ACT-SAT Concordance (2016). May 13, 2016. Retrieved from: https://leadershipblog.act.org/2016/05/act-statement-on-act-sat-concordance.html
Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. Office of Vocational and Adult Education, U.S. Department of Education. Retrieved from: http://eric.ed.gov/PDFS/ED490195.pdf
Allensworth, E. M., & Clark, K. (2020). High school GPAs and ACT scores as predictors of college completion: Examining assumptions about consistency across high schools. Educational Researcher. https://doi.org/10.3102/0013189X20902110
Alt, D. (2015). Assessing the contribution of a constructivist learning environment to academic self-efficacy in higher education. Learning Environments Research, 18(1), 47–67. https://doi.org/10.1007/s10984-015-9174-5. https://doi-org.libproxy.uccs.edu/
Bandalos, D. L., Yales, K., & Thorndike-Christ, T. (1995). Effects of math self-concept perceived self-efficacy and attributions for failure and success on test anxiety. Journal of Educational Psychology, 87(4), 611–623
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215
Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117–148
Barroso, C., Ganley, C. M., McGraw, A. L., Geer, E. A., Hart, S. A., & Daucourt, M. C. (2021). A meta-analysis of the relation between math anxiety and math achievement. Psychological Bulletin, 147(2), 134–168. https://doi.org/10.1037/bul0000307
Bliese, P. D. (1998). Group size, ICC values, and group-level correlations: A simulation. Organizational Research Methods, 1(4), 355–373
Boaler, J. (2016). Mathematical mindsets: Unleashing students’ potential through creative math, inspiring messages, and innovative teaching. San Francisco: Jossey-Bass
Boden, M. T., Bonn-Miller, M. O., Kashdan, T. B., Alvarez, J., & Gross, J. J. (2012). The interactive effects of emotional clarity and cognitive reappraisal in posttraumatic stress disorder. Journal of Anxiety Disorders, 26, 233–238. https://doi.org/10.1016/j.jandis.2011.11.007
Boud, D., Cohen, R., & Sampson, J. (2001). Peer learning in higher education: Learning from and with each other. London, UK: Kogan Page
Browne, W., & Rasbash, J. (2004). Multilevel modelling. In M. Hardy, & A. Bryman (Eds.), Handbook of data analysis (pp. 459–479). SAGE Publications, Ltd. https://doi.org/10.4135/9781848608184.n20
Bryant, R. T. (2015). College preparation for African American students: Gaps in the high school education experience. Washington DC: Center for Law and Social Policy (CLASP)
Bryer, J. (2012). Peer tutoring program for academic success of returning nursing students. Journal of the New York State Nurses Association, 43(1), 20–22
Buckley, J., Letukas, L., & Wildavsky, B. (2018). Measuring success. Testing, grades, and the future of college admissions. Baltimore, MD: Johns Hopkins University Press
Campbell, C. M., Smith, M., Dugan, J. P., & Komives, S. R. (2012). Mentors and college student leadership outcomes: The importance of position and process. The Review of Higher Education, 35(4), 595–625
Carmody, G., & Wood, L. (2009). Peer tutoring in mathematics for university students. Mathematics and Computer Education, 43(1), 18–28
Carnevale, A. P., Smith, N., & Melton, M. (2011). STEM: Science, Technology, Engineering, Mathematics. Washington, DC: Georgetown University Center on Education and the Workforce. Accessed Nov 2, 2020 from: https://cew.georgetown.edu/cew-reports/stem/
Colver, M., & Fry, T. (2016). Evidence to support peer tutoring programs at the undergraduate level. Journal of College Reading and Learning, 46(1), 16–41. https://doi.org/10.1080/10790195.2015.1075446
Cooper, E. (2010). Tutoring center effectiveness: The effect of drop-in tutoring. Journal of College Reading and Learning, 40(2), 21–34. https://doi.org/10.1080/10790195.2010.10850328
Dinther, M. V., Dochy, F., & Segers, M. S. (2011). Factors affecting students’ self-efficacy in higher education. Educational Research Review, 6, 95–108
Dunning, T. (2008). Improving causal inference: strengths and limitations of natural experiments. Political Research Quarterly, 61(2), 282–293. https://www.jstor.org/stable/20299732
Elliot, A., & McGregor, H. (2001). A 2 x 2 achievement goal framework. Journal of Personality and Social Psychology, 80(3), 501–519. https://doi.org/10.1037//0022-3514.80.3.501
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111
Ganter, S., & Haver, W. (Eds, 2011). Partner discipline recommendations for introductory college mathematics and the implications for college algebra. Washington, DC: Mathematical Association of America
Green, A., & Sanderson, D. (2018). The roots of STEM achievement: An analysis of persistence and attainment in STEM majors. The American Economist, 63(1), 79–93
Halcrow, C., & Iiams, M. (2011). You can build it, but will they come? PRIMUS: Problems Resources and Issues in Mathematics Undergraduate Studies, 21(4), 323–337. https://doi.org/10.1080/10511970903164148
Hall, J. M., & Ponton, M. K. (2005). Mathematics self-efficacy of college freshman. Journal of Developmental Education, 28(3), 26–32
Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94(3), 638–645. https://doi.org/10.1037//0022-0663.94.3.638
Hembree, R. (1990). The nature, effects, and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21, 33–46. https://doi.org/10.5951/jresematheduc.21.1.0033. https://doi-org.libproxy.uccs.edu/
Holliday, T. (2012). Evaluating the effectiveness of tutoring: An easier way. Learning Assistance Review (TLAR), 17(2), 21–32
Khan, B. R. (2020). Metacognitive skills of students in a mathematics class with supplemental instruction and online homework. Journal of Mathematics Education at Teachers College, 11(1), 33–41. https://doi.org/10.7916/jmetc.v11i1.6707
Characteristics of well-propagated teaching innovations in undergraduate STEM.International Journal of STEM Education, 4(2),1–10
Kolluri, S. (2018). Advanced Placement: The dual challenge of equal access and effectiveness. Review of Educational Research, 88(5), 671–711. https://doi.org/10.3102/0034654318787268
Komarraju, M., Musulkin, S., & Bhattacharya, G. (2010). Role of student-faculty interactions in developing college students’ academic self-concept, motivation, and achievement. Journal of College Student Development, 51(3), 332–342
Lahcen, R. A., & Mohapatra, R. (2020). Promoting proactive behavior through motivation: Required math lab hours case. International Journal of Research in Education and Science, 6(1), 110–119
Larson, L. M., Pesch, K. M., Surapaneni, S., Bonitz, V. S., Wu, T. F., & Werbel, J. D. (2014). Predicting graduation: the role of mathematics/science self-efficacy. Journal of Career Assessment, 23(3), 399–409
Lee, Y. G., & Ferrare, J. J. (2019). Finding one’s place or losing the race? The consequences of stem departure for college dropout and degree completion. The Review of Higher Education, 43(1), 221–261. https://doi.org/10.1353/rhe.2019.0095
Lepore, S. J., Greenberg, M. A., Bruno, M., & Smyth, J. M. (2002). Expressive writing and health: Self-regulation of emotion-related experience, physiology, and behavior. In S. J. Lepore, & J. M. Smyth (Eds.), The writing cure: How expressive writing promotes health and emotional well-being (pp. 99–117). Washington, DC: American Psychological Association. https://doi.org/10.1037/10451-005
Lewis, M., & Powell, J. A. (2016). Modeling zombie outbreaks: A problem-based approach to improving mathematics one brain at a time. PRIMUS, 26(7), 705–726. https://doi.org/10.1080/10511970.2016.1162236
Long, M. C., Iatarola, P., & Conger, D. (2009). Explaining gaps in readiness for college-level math: The role of high school courses. Education Finance and Policy, 4(1), 1–33
Maher, P. A., Bailey, J. M., Etheridge, D. A., & Warby, D. B. (2013). Preservice teachers’ beliefs and confidence after working with STEM faculty mentors: An exploratory study. Teacher Education and Practice, 26(2), 266. https://link.gale.com/apps/doc/A514683034/PPNU?u=colosprings&sid=bookmark-PPNU&xid=51bf4d15
Martin, D. C., & Arendale, D. R. (1994). Supplemental instruction: Increasing achievement and retention. Jossey-Bass
McMinn, M., Aldridge, J., & Henderson, D. (2021). Learning environment, self-efficacy for teaching mathematics, and beliefs about mathematics. Learning Environments Research, 24, 355–369. https://doi.org/10.1007/s10984-020-09326-x
Micari, M., & Pazos, P. (2021). Beyond grades: Improving college students’ social-cognitive outcomes in STEM through a collaborative learning environment. Learning Environments Research, 24, 123–136. https://doi.org/10.1007/s10984-020-09325-y. https://doi-org.libproxy.uccs.edu/
Mickelson, R. A., & Everett, B. J. (2008). Neotracking in North Carolina: How high school courses of study reproduce race and class-based stratification. Teachers College Record, 110, 535–570
Middleton, J., Tallman, M., Hatfield, N., & Davis, O. (2015). Taking the severe out of perseverance: Strategies for building mathematical determination. In N. Alpert, & C. Kurose (Eds.), Mathematical instruction for perseverance. Spencer Foundation
Mitra, S., & Goldstein, Z. (2018). Impact of supplemental instruction on business courses: A statistical study. Transactions on Education, 18(2), 89–101. https://doi.org/10.1287/ited.2017.0178
National Mathematics Advisory Panel (2008). Foundations for success: The final report of the National Mathematics Advisory Panel. Washington DC., U.S. Department of Education
National Research Council. (2013). The mathematical sciences in 2025. Washington, DC: The National Academies Press. https://doi.org/10.17226/15269
Nunez-Pena, M. I., Suarez-Pellicioni, M., & Bono, R. (2013). Effects of math anxiety on student success in higher education. International Journal of Educational Research, 58, 36–43
Ng, B., Shi, J., Chen, S. H. A., & Chen, W. W. N. (2020). A Preliminary study on the impact of a brief online growth mindset intervention on university students. In S. Tan & S. H. Chen (Eds.), Transforming teaching and learning in higher education (pp. 73–90). Springer. https://doi-org.libproxy.uccshttps://doi.org/10.1007/978-981-15-4980-9_4
Park, D., Ramirez, G., & Beilock, S. L. (2014). The role of expressive writing in math anxiety. Journal of Experimental Psychology: Applied, 20(2), 103. https://doi.org/10.1037/xap0000013
Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S., & Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 34(1), 29–48
Peacock, M. L. (2008). A program evaluation of supplemental instruction for developmental mathematics at a community college in Virginia (Publication No.304411833). Doctoral dissertation, Old Dominion University. ProQuest Dissertations & Theses Global
Reinholz, D. L. (2017). Co-calculus: Integrating the academic and the social. International Journal of Research in Education and Science, 521–521. https://doi.org/10.21890/ijres.327911
Rice, L., Barth, J. M., Guadagno, R. E., Smith, G. P. A., & McCallum, D. M. (2012). The role of social support in students’ perceived abilities and attitudes toward math and science. Journal of Youth Adolescence, 42, 1028–1040
Rutschow, E. Z., Diamond, J., & Serna-Wallender, E. (2017). Math in the real world: Early findings from a study of the Dana Center Mathematics Pathways (Research Brief). Center for the Analysis of Postsecondary Readiness. https://eric.ed.gov/?id=ED583571
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Saxe, K., & Braddy, L. (2015). A common vision for undergraduate mathematical sciences programs in 2025. The Mathematical Association of America, Inc. ISBN 978-0-88385-840-0
Stewart, J., Henderson, R., Michaluk, L., Deshler, J., Fuller, E., & Rambo-Hernandez, K. (2020). Using the social cognitive theory framework to chart gender differences in the developmental trajectory of STEM self-efficacy in science and engineering students. Journal of Science Education and Technology, 29(6), 758–773. https://doi.org/10.1007/s10956-020-09853-5
Strada Education Network and Gallup, Inc (2019). 2018 Strada-Gallup Alumni Survey: Mentoring College Students to Success., Indianapolis, IN: Author. https://go.stradaeducation.org/strada-gallup-alumni-survey
Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., Chambwe, N., Cintrón, D. L., Cooper, J. D., Dunster, G., Grummer, J. A., Hennessey, K., Hsiao, J., Iranon, N., Jones, L., Jordt, H., Keller, M., Lacey, M. E., Littlefield, C. E., & Freeman, S. (2020). Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proceedings of the National Academy of Sciences, 117(12), 6476–6483. https://doi.org/10.1073/pnas.1916903117
Topping, K. (2005). Trends in peer learning. Educational Psychology, 25(6), 631–645
Topping, K. J., & Ehly, S. W. (2001). Peer assisted learning: A framework for consultation. Journal of Educational and Psychological Consultation, 12(2), 113–132. https://doi.org/10.1207/S1532768XJEPC1202_03
Urdan, T., & Kaplan, A. (2020). The origins, evolution, and future directions of achievement goal theory. Contemporary Educational Psychology, 61, https://doi.org/10.1016/j.cedpsych.2020.101862. Article 101862https://doi-org.libproxy.uccs.edu/
Westrick, P. (2014). Average ACT mathematics scores for quantitative science majors. ACT
Information Brief 2014-20). Iowa City, IA:ACT
Westrick, P. A., Le, H., Robbins, S. B., Radunzel, J. M. R., & Schmidt, F. L. (2015). College performance and retention: A meta-analysis of the predictive validities of ACT® scores, high school grades, and SES. Educational Assessment, 20(1), 23–45. https://doi.org/10.1080/10627197.2015.997614
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Appendix
Appendix
SIP Math Intervention Theory to Practice Model
Theoretical framework | Components | Instructional interventions | Supporting literature |
---|---|---|---|
Math self-efficacy | Mastery experience | Supplemental instructional hour with peer group work and individual attention from Math Helpers | Khan (2020); Micari & Pazos (2021); Mitra & Goldstein (2018) |
Active learning and gamification (e.g. factoring bingo, station learning, and sharing exercises) | |||
Test Corrections built into exam grades/assessment | Boaler (2015); McDaniel et al. (2012) | ||
Problem based learning and educational games. | Lewis & Powell (2016) | ||
Low-stakes assessments with re-take options throughout the curriculum | Middleton et al., (2015); Walck-Shannon et al. (2019); McDaniel et al. (2012) | ||
Assignments designed to connect and relate problems to real world applications. | Boaler (2015) | ||
Vicarious experiences | Active learning through group work on problems in class | Freeman et al., (2014); Reinholz (2017); Theobald et al., (2020) | |
Math Helpers embedded in classes will share their experiences and encouragement | |||
Faculty mentoring through sharing in their adversity as students | DeFreitas & Bravo, (2012); Komarraju et al., (2010); Campbell et al., (2012) | ||
Social persuasion | Math Helpers are assigned a maximum of 15 students to support through follow-up emails, encouragement, and advising. | ||
Math Helpers offer additional office hours for coaching on study strategies and support for problem solving | Topping (2005) | ||
Faculty encourage students by rewarding effort and trying progressively difficult math problems | Campbell et al., (2012); Komarraju et al., (2010); Maher et al., (2013) | ||
Physiological/emotional states | Multiple expressive writing exercises are required and focus on math anxiety, problem solving strategies, and learning processes | Barroso et al., (2021); Deieso & Fraser (2019); Hall & Ponton (2005) | |
Goal-setting exercise early in the course to help students connect coursework to their long-term goals. | Middleton et al., (2015); Ryan & Deci (2020); Larson et al. (2014) | ||
Foster Math Mindset by incorporating praise for effort, rather than for individuals or accomplishments | Boaler (2015); Ng et al. (2020) |
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Morris, P., Agbonlahor, O., Winters, R. et al. Self-efficacy curriculum and peer leader support in gateway college mathematics. Learning Environ Res 26, 219–240 (2023). https://doi.org/10.1007/s10984-022-09424-y
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DOI: https://doi.org/10.1007/s10984-022-09424-y