Abstract
Personal Best (PB) goals are defined as specific, challenging, and competitively self-referenced goals involving a level of performance or effort that meets or exceeds an individual’s previous best. Much of the available research underpinning arguments for PB goal-setting is self-report-based; thus, the causal effect of PB goals on learning outcomes remains in question. The present experiment examined the impact of PB goal-setting (against a no-goal condition) on 68 Year 5 and 6 schoolchildren’s problem-solving during an arithmetic fluency-building activity, SuperSpeed Math. Equivalence of the two conditions was established across a range of prior ability and self-report motivational variables, including prior mathematical ability; Personal Best, Mastery, and Performance goal orientations at the individual and classroom level; mathematics self-concept; and valuing of and interest in mathematics. Controlling for initial problem-solving performance, students who set PB goals in subsequent rounds showed a small but reliable advantage over students in the control condition. These results suggest PB goals may provide a way for students to experience both challenge and success in a range of classroom activities. Suggestions for future research based on these initial findings are made.
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Notes
Reliability coefficients are not provided as these were single-item constructs.
References
Alschuler, A. S. (1969). The effects of classroom structure on achievement motivation and academic performance. Educational Technology, IX, 19–24.
Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261–271.
Anderman, E. M., Gimbert, B., O’Connell, A. A., & Riegel, L. (2015). Approaches to academic growth assessment. British Journal of Educational Psychology, 85, 138–153. https://doi.org/10.1111/bjep.12053.
Beady, C. H., Slavin, R. E., & Fennessey, G. M. (1981). Alternative student evaluation structures and a focused schedule of instruction in an innercity junior high school. Journal of Educational Psychology, 73, 518–523.
Biffle, C. (2007a). SuperSpeed math. Yucaipa: Crafton Hills College.
Biffle, C. (2007b). SuperSpeed letters and phonics. Yucaipa: Crafton Hills College.
Boomsma, A., & Herzog, W. (2013). R function swain: Correcting structural equation model t-statistics and indexes under small-sample and/or large-model conditions. Retrieved March 28, 2017, from http://www.ppsw.rug.nl/~boomsma/swain.pdf.
Bratina, T. A., & Krudwig, K. M. (2003). Get it right and get it fast! Building automaticity to strengthen mathematical proficiency. Focus on Learning Problems in Mathematics, 25, 47–63.
Breaugh, J. A. (2003). Effect size estimation: Factors to consider and mistakes to avoid. Journal of Management, 29, 79–97.
Dweck, C. S. (2012). Mindsets and human nature: Promoting change in the Middle East, the schoolyard, the racial divide, and willpower. American Psychologist, 67, 614–622. https://doi.org/10.1037/a0029783.
Edgington, E., & Onghena, P. (2007). Randomization tests. Boca Raton, FL: CRC Press.
Elliot, A. J. (2005). A conceptual history of the achievement goal construct. In A. J. Elliot & C. Dweck (Eds.), Handbook of competence and motivation (pp. 52–72). New York, NY: Guilford Press.
Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality and Social Psychology, 80, 501–519.
Elliot, A. J., Murayama, K., & Pekrun, R. (2011). A 3 × 2 achievement goal model. Journal of Educational Psychology, 103, 632–648. https://doi.org/10.1037/a0023952.
Graham, J. W., & Hoffer, S. M. (2000). Multiple imputation in multivariate research. In T. D. Little, K. U. Schnable, & J. Baumert (Eds.), Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples (pp. 201–218). Mahwah, NJ: Erlbaum.
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. New York: Routledge.
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). New York: Guilford Publications.
Herzog, W., & Boomsma, A. (2009). Small-sample robust estimators of noncentrality-based and incremental model fit. Structural Equation Modeling, 16, 1–27. https://doi.org/10.1080/10705510802561279.
Huitema, B. (2011). The analysis of covariance and alternatives: Statistical methods for experiments, quasi-experiments, and single-case studies (2nd ed.). Hoboken, NJ: Wiley.
Kanfer, R., & Ackerman, P. L. (1989). Motivation and cognitive abilities: An integrative/aptitude-treatment interaction approach to skill acquisition. Journal of Applied Psychology, 74, 657–690.
Keselman, H. J., Othman, A.R., & Wilcox, R.R. (2013). Preliminary testing for normality: Is this a good practice? Journal of Modern Applied Statistical Methods, 12(2), 2. Retrieved from http://digitalcommons.wayne.edu/jmasm/vol12/iss2/2
Klein, H. J., Wesson, M. J., Hollenbeck, J. R., Wright, P. M., & DeShon, R. P. (2001). The assessment of goal commitment: A measurement model meta-analysis. Organizational Behavior and Human Decision Processes, 85, 32–55. https://doi.org/10.1006/obhd.2000.2931.
Kratochwill, T. R., & Levin, J. R. (Eds.). (2014). Single-case intervention research: Methodological and statistical advances. Washington, DC: American Psychological Association.
Latham, E. A., & Locke, G. P. (2013). Goal setting theory, 1990. In E. A. Locke & G. P. Latham (Eds.), New developments in goal setting and task performance (pp. 3–15). New York: Routledge.
Liem, G. A. D., Ginns, P., Martin, A. J., Stone, B., & Herett, M. (2012). Personal best goals and academic and social functioning: A longitudinal perspective. Learning and Instruction, 22, 222–230. https://doi.org/10.1016/j.learninstruc.2011.11.003.
Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57, 705–717.
Marsh, H. W. (1990). Self description questionnaire—I (SDQ I). Manual. Macarthur, NSW. Australia: University of Western Sydney.
Marsh, H. W., Balla, J. R., & Hau, K. T. (1996). An evaluation of incremental fit indices: A clarification of mathematical and empirical processes. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling techniques (pp. 315–353). Hillsdale, NJ: Erlbaum.
Marsh, H. W., Hau, K. T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling, 11, 320–341. https://doi.org/10.1207/s15328007sem1103_2.
Martin, A. J. (2006). Personal bests (PBs): A proposed multidimensional model and empirical analysis. British Journal of Educational Psychology, 76, 803–825. https://doi.org/10.1348/000709905X55389.
Martin, A. J. (2011a). Personal Best (PB) approaches to academic development: Implications for motivation and assessment. Educational Theory and Practice, 33, 93–99.
Martin, A. J. (2011b). The Motivation and Engagement Scale. Sydney, Australia: Lifelong Achievement Group.
Martin, A. J. (2015). Implicit theories about intelligence and growth (personal best) goals: Exploring reciprocal relationships. British Journal of Educational Psychology, 85, 207–223. https://doi.org/10.1111/bjep.12038.
Martin, A. J., Anderson, J., Bobis, J., Way, J., & Vellar, R. (2012). Switching on and switching off in mathematics: An ecological study of future intent and disengagement among middle school students. Journal of Educational Psychology, 104, 1–18. https://doi.org/10.1037/a0025988.
Martin, A. J., Durksen, T. L., Williamson, D., Kiss, J., & Ginns, P. (2014). Personal Best (PB) goal setting and students’ motivation in science: A study of science valuing and aspirations. The Australian Educational and Developmental Psychologist, 31, 85–96. https://doi.org/10.1017/edp.2014.19.
Martin, A. J., & Elliot, A. J. (2016a). The role of personal best (PB) and dichotomous achievement goals in students’ academic motivation and engagement: A longitudinal investigation. Educational Psychology, 36, 1285–1302. https://doi.org/10.1080/01443410.2015.1093606.
Martin, A. J., & Elliot, A. J. (2016b). The role of personal best (PB) goal setting in students’ academic achievement gains. Learning and Individual Differences, 45, 222–227. https://doi.org/10.1016/j.lindif.2015.12.014.
Martin, A. J., & Liem, G. A. D. (2010). Academic personal bests (PBs), engagement, and achievement: A cross-lagged panel analysis. Learning and Individual Differences, 20(3), 265–270. https://doi.org/10.1016/j.lindif.2010.01.001.
McDonald, R. P., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness-of-fit. Psychological Bulletin, 107, 247–255.
Muthén, L.K. & Muthén, B.O. (1998–2010). Mplus user’s guide. Los Angeles: Muthén & Muthén.
Nordstokke, D. W., & Zumbo, B. D. (2010). A new nonparametric test for equal variances. Psicologica, 31, 401–430.
Nordstokke, D. W., Zumbo, B. D., Cairns, S .L., & Saklofske, D. H. (2011). The operating characteristics of the nonparametric Levene test for equal variances with assessment and evaluation data. Practical Assessment, Research & Evaluation, 16. 84. Retrieved from http://pareonline.net/getvn.asp?v=16&n=5.
Prentice, D. A., & Miller, D. T. (1992). When small effects are impressive. Psychological Bulletin, 112, 160–164.
Schmidt, F. L. (2013). The economic value of goal setting to employers. In E. A. Locke & G. P. Latham (Eds.), New developments in goal setting and task performance (pp. 16–20). New York: Routledge.
Schunk, D. H. (1985). Participation in goal setting: Effects on self-efficacy and skills of learning-disabled children. The Journal of Special Education, 19, 307–317.
Schunk, D. H., & Rice, J. M. (1989). Learning goals and children’s reading comprehension. Journal of Reading Behavior, 21, 279–293.
Seijts, G. H., Latham, G. P., & Woodwark, M. (2013). Learning goals: A qualitative and quantitative review. In E. A. Locke & G. P. Latham (Eds.), New developments in goal setting and task performance (pp. 195–212). New York: Routledge.
Slavin, R. E. (1980). Effects of individual learning expectations on student achievement. Journal of Educational Psychology, 72, 520–524.
Steiner, E. T., & Ashcraft, M. H. (2012). Three brief assessments of math achievement. Behavior Research Methods, 44, 1101–1107. https://doi.org/10.3758/s13428-011-0185-6.
Swain, A.J. (1975). Analysis of parametric structures for variance matrices. Unpublished doctoral dissertation, Department of Statistics, University of Adelaide, Australia.
Tallmadge, G. A. (1977). The joint dissemination review panel ideabook. Washington, DC: National Institute of Education & US Office of Education.
Weinberg, R. S. (2002). Goal setting in sport and exercise: Research to practice. In J. L. Van Raalte & B. W. Brewer (Eds.), Exploring sport and exercise psychology (pp. 25–48). Washington, DC: American Psychological Association.
Whisman, M. A., & McClelland, G. H. (2005). Designing, testing, and interpreting interactions and moderator effects in family research. Journal of Family Psychology, 19, 111–120. https://doi.org/10.1037/0893-3200.19.1.111.
Williams, K. J. (2013). Goal setting in sports. In E. A. Locke & G. P. Latham (Eds.), New developments in goal setting and task performance (pp. 375–396). New York: Routledge.
Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81, 267–301. https://doi.org/10.3102/0034654311405999.
Yu, K., & Martin, A. J. (2014). Personal best (PB) and ‘classic’ achievement goals in the Chinese context: their role in predicting academic motivation, engagement and buoyancy. Educational Psychology, 34, 635–658. https://doi.org/10.1080/01443410.2014.895297.
Yuan, K. H. (2005). Fit indices versus test statistics. Multivariate Behavioral Research, 40, 115–148. https://doi.org/10.1207/s15327906mbr4001_5.
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The present study was supported by Discovery Research Project Grant DP140104294.
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Ginns, P., Martin, A.J., Durksen, T.L. et al. Personal Best (PB) goal-setting enhances arithmetical problem-solving. Aust. Educ. Res. 45, 533–551 (2018). https://doi.org/10.1007/s13384-018-0268-9
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DOI: https://doi.org/10.1007/s13384-018-0268-9