Keeping in School Shape (KiSS): A Program for Rehearsing Math Skills Over Breaks from School

Carla C. van de Sande (Arizona State University)

Article ID: 1383



If you don’t use it, you lose it. School breaks, during which students do not regularly participate in instruction, can therefore have negative consequences on learning. This is especially true for mathematics learning since skills build progressively on earlier materials. How can we bridge these gaps in formal instruction? The Keeping in School Shape (KiSS) program is a mobile, engaging, innovative, and cost-effective way of using technology to help students who have time off between related math courses stay fresh on prerequisite knowledge and skills. Founded on learning theory and designed on a model of behavioral change, the KiSS program embodies retrieval practice and nudges by sending students a daily multiple-choice review problem via text messaging over school break. After rating their confidence in solving the daily problem students receive feedback and a solution. This study explores measures of participation, accuracy, and confidence in an implementation of the KiSS program over winter break between two sequential introductory engineering courses at a large state university in the Southwest United States. Results indicate that careful attention should be paid to the construction of the first few days of the program, and that encouragement, additional resources for review and practice, and an increased breadth of problem difficulty may improve participation.


Retrieval practice, Summer gap, Nudges, Mathematics education, Text messages

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[1] Cooper, H., Nye, B., Charlton, K., Lindsay, J., & Greathouse, S. (1996). The effects of summer vacation on achievement test scores: A narrative and meta-analytic review. Review of Educational Research, 66(3), 227–268.

[2] van de Sande, C. & Reiser, M. (2018). The effect of summer break on engineering student success in calculus. International Journal of Research in Education and Science (IJRES), 4(2), 349–357.

[3] Bangert-Drowns, R.L., Kulik, C.C., Kulik, J.A., & Morgan, M. (1991). The instructional effects of feedback in test-like events. Review of Educational Research, 61(2), 213–238.

[4] U.S. Department of Education, Office of Educational Technology. (2017). Reimagining the Role of Technology in Higher Education: A Supplement to the National Education Technology Plan, Washington, D.C.

[5] Jiang, J. “Millennials stand out for their technology use, but older generations also embrace digital life.” Pew Research Center, Washington, D.C. (May 2, 2018)

[6] Anderson, M. “Mobile Technology and Home Broadband 2019.” Pew Research Center, Washington, D.C. (June 13, 2019).

[7] Dabbagh, N., Bass, R., Bishop, M., Costelloe, S., Cummings, K., Freeman, B., Frye, M., Picciano,A. G., Porowki, A., Sparrow, J., & Wilson, S. J. (2019). Using technology to support postsecondary student learning: A practice guide for college and university administrators, advisors, and faculty. Washington, DC: Institute of Education Sciences, What Works Clearinghouse. (WWC 20090001) Washington DC: National Center for Education Evaluation and Regional Assistance (NCEE), Institute of Education Sciences, U.S. Department of Education.

[8] Farrell, E. F. (2006). Taking anxiety out of the equation. Chronicle of Higher Education, 52(19), 41–42.

[9] The Millennial Impact Report. (2015). Top 100 Findings from the Millennial Impact Project. Achieve and The Case Foundation. Retrieved from

[10] The Cassandra Report. (2017). The Gen Z Effect. New York: NY. Retrieved from

[11] Butler, A. C., Marsh, E. J., Slavinsky, J. P., & Baraniuk, R. G. (2014). Integrating cognitive science and technology improves learning in a STEM classroom. Educational Psychology Review, 26, 331–340.

[12] McDaniel, M. A., Anderson, J. L., Derbish, M. H., & Morrisette, N. (2007). Testing the testing effect in the classroom, European Journal of Cognitive Psychology, 19(4/5), 494–513.

[13] Agarwal, P., Roediger, H. L., McDaniel, M. A. & McDermont, K. B. (2013). How to use retrieval practice to improve learning. Washington University in St. Louis: Institute of Education Sciences. Retrieved from

[14] Roediger, H. L., III & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Science, 15(1), 20–27.

[15] Roediger, H.L., III, & Karpicke, J. D. (2006). The power of testing memory: basic research and implications for educational practice. Perspectives on Psychological Science, 1, 181–210.

[16] Butler, A.C. (2010). Repeated testing produces superior transfer of learning relative to repeated studying. Journal of Experimental Psychology: Learning, Memory, & Cogntition, 36, 1118–1133.

[17] Johnson, C.I., & Mayer, R.E. (2009). A testing effect with multimedia learning. Journal of Educational Psychology, 101, 621–629.

[18] Rohrer, D., Taylor, K., & Sholar, B. (2010). Tests enhance the transfer of learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 233–239.

[19] Carpenter, S.K. (2009). Cue strength as a moderator of the testing effect: the benefits of elaborative retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 1563–1569.

[20] Bjork, R.A. (1975). Retrieval as a memory modifier: an interpretation of negative recency and related phenomena. In Information Processing and Cognition (Solso, R.L., ed.), pp. 123–144, Wiley.

[21] McDaniel, M.A. & Masson, M.E.J. (1985). Altering memory representations through retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11, 371–385.

[22] Pyc, M.A. & Rawson, K.A. (2009). Testing the retrieval effort hypothesis: does greater difficulty correctly recalling information lead to higher levels of memory? Journal of Memory and Language, 60, 437–447.

[23] Gardiner, J.M. et al. (1973) Retrieval difficulty and subsequent recall. Memory and Cognition, 1, 213–216.

[24] Thaler, R. H. & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. 2nd ed., New Haven, CT: Yale University Press.

[25] Woolford, S. J., Clark, S. J., Strecher, V. J. & Resnicow, K. (2010). Tailored mobile phone text messages as an adjunct to obesity treatment for adolescents. Journal of Telemedicine and Telecare, 16(8), 458–461.

[26] Castleman, B. L. & Meyer, K. (April, 2016). Can text message nudges improve academic outcomes in college? Evidence from a West Virginia Initiative, EdPolicy Works Working Paper Series, No. 43.

[27] Karlan, D., McConnell, M., Mullainathan, S., & Zinman, J. (2010). Getting to the top of mind: How reminders increase saving (No. w16205). National Bureau of Economic Research.

[28] Obermayer, J. L., Riley, W. T., Asif, O., & Jean-Mary, J. (2004). College smoking cessation using cell phone text messaging, Journal of American College Health, 53(2), 71–78.

[29] Castleman, B. L. & Page, L. C. (June, 2014). Freshman year financial aid nudges: An experiment to increase FAFSA renewal and college persistence. EdPolicy Works Working Paper Series, No. 29.

[30] Castleman, B. L. & Page, L. C. (2015). Summer nudging: Can personalized text messages and peer mentor outreach increase college going among low-income high school graduates? Journal of Economic Behavior & Organization, 115, 144–160.

[31] Kraft, M. A., & Dougherty, S. M. (2013). The effect of teacher–family communication on student engagement: Evidence from a randomized field experiment. Journal of Research on Educational Effectiveness, 6(3), 199–222.

[32] Kraft, M.A., & Monti-Nussbaum, M. (2017). Can schools enable parents to prevent summer learning loss? A text messaging field experiment to promote literacy skills. The ANNALS of the American Academy of Political and Social Science, 674(1), 85– 112.

[33] Astin, A. (1993). What Matters in College: Four Critical Years Revisited, San Francisco: Jossey Bass.

[34] Ewell, P., & Jones, D. (1996). Indicators of “good practice” in undergraduate education: A handbook for development and implementation, Boulder, CO: National Center for Higher Education Management Systems.

[35] Pascarella, E. T., & Terenzini, P. (1991). How College Affects Students: Findings and Insights from Twenty Years of Research, San Francisco: Jossey-Bass.

[36] Tinto, V. (1993). Rethinking the Causes and Cures of Student Attrition (2nd ed.). Chicago: University of Chicago Press.

[37] Tinto, V. (2000). Linking learning and leaving: Exploring the role of the college classroom in student departure. In J. M. Braxton (ed.), Reworking the Student Departure Puzzle (pp. 81–94), Nashville: Vanderbilt University Press.

[38] Pascarella, E.T.&Terenzini,P.T. (1977). Patterns of student-faculty informal interaction beyond the classroom and voluntary freshman attrition. Journal of Higher Education, 48(5), 540–552.

[39] Ho, A.D, Reich, J, Nesterko, S, Seaton, D.T, Mullaney, T, Waldo, J, & Chuang, I. (2014). The first year of open online courses HarvardX and MITx (Working Paper No. 1).

[40] Reich, J. (2014). MOOC Completion and Retention in the Context of Student Intent. Educause Review. Retrieved from:

[41] Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Eductional Psychologist, 28(2), 117–148.

[42] Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., Tipton, E., Schneider, B., Hulleman, C. S., Cintia P., Paunesku, D., Romero, C., Flint, K., Roberts, A., Trott, J., Iachan, R., Buontempo, J., Yang, S. M., Carvalho, C. M., Hahn, P. R., Gopalan, M., Mhatre, P., Ferguson, R., Duckworth, A. L. & Dweck, C. S. (2019). A national experiment reveals where a growth mindset improves achievement. Nature. Retrieved from

[43] Mitrovic, A, Martin B. (2004). Evaluating adaptive problem selection. In De bra, P, Nejdl, W (eds.) Third International Conference on Adaptive Hypermedia and Adaptive Web‐Based Systems (Ah'2004) (pp. 185–194). Berlin: Springer‐Verlag, Eindhoven.


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