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Cognitive regulation outdoes behavior regulation in predicting state standardized test scores over time

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Abstract

Individual differences in self-regulation have been a topic of increased empirical research. However, few investigations have been conducted on how sub-components of self-regulation differentially predict education outcomes over time. We examined cognitive and behavior regulation as predictors of middle-school students’ (n = 127) long-term academic achievement. It has been previously reported that behavior regulation, not cognitive regulation, predicts state standardized test scores in the first year (Modrek et al. 2019). However, here we show that after two years, this pattern flips in that cognitive regulation, not behavior regulation, predicts state standardized test scores for both math and English. We analyzed the mediating role of learning using structural equation modeling, suggesting the differing roles of self-regulation in education where certain facets may or may not affect students’ long-term outcomes.

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References

  • Bailey, D., Duncan, G. J., Odgers, C. L., & Yu, W. (2017). Persistence and fadeout in the impacts of child and adolescent interventions. Journal of Research on Educational Effectiveness, 10(1), 7–39.

    Article  Google Scholar 

  • Bandura, A., Caprara, G. V., Barbaranelli, C., Pastorelli, C., & Regalia, C. (2001). Sociocognitive self-regulatory mechanisms governing transgressive behavior. Journal of Personality and Social Psychology, 80, 125–135. https://doi.org/10.1037/0022-3514.80.1.125.

    Article  Google Scholar 

  • Barriga, A. Q., Doran, J. W., Newell, S. B., Morrison, E. M., Barbetti, V., & Dean Robbins, B. (2002). Relationships between problem behaviors and academic achievement in adolescents: The unique role of attention problems. Journal of Emotional and Behavioral Disorders, 10(4), 233–240.

    Article  Google Scholar 

  • Baumeister, R. F., Heatherton, T. F., & Tice, D. M. (1994). Losing control: How and why people fail at self-regulation. Academic Press.

  • Ben-Eliyahu, A. (2019). Academic emotional learning: A critical component of self-regulated learning in the emotional learning cycle. Educational Psychologist, 54(2), 84–105.

    Article  Google Scholar 

  • Ben-Eliyahu, A., & Linnenbrink-Garcia, L. (2015). Integrating the regulation of affect, behavior, and cognition into self-regulated learning paradigms among secondary and post-secondary students. Metacognition & Learning, 10, 15–42.

    Article  Google Scholar 

  • Blair, C., & Diamond, A. (2008). Biological processes in prevention and intervention: The promotion of self-regulation as a means of preventing school failure. Development and Psychopathology, 20(3), 899–911.

    Article  Google Scholar 

  • Blair, C., & Raver, C. C. (2014). Closing the achievement gap through modification of neurocognitive and neuroendocrine function: Results from a cluster randomized controlled trial of an innovative approach to the education of children in kindergarten. PLoS One, 9(11), e112393.

    Article  Google Scholar 

  • Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78(2), 647–663.

    Article  Google Scholar 

  • Blair, C., Ursache, A., Greenberg, M., & Vernon-Feagans, L. (2015). Multiple aspects of self-regulation uniquely predict mathematics but not letter–word knowledge in the early elementary grades. Developmental Psychology, 51(4), 459–472.

    Article  Google Scholar 

  • Bodovski, K., & Farkas, G. (2007). Mathematics growth in early elementary school: The roles of beginning knowledge, student engagement, and instruction. The Elementary School Journal, 108(2), 115-130.

  • Braga, M., Paccagnella, M., & Pellizzari, M. (2014). Evaluating students’ evaluations of professors. Economics of Education Review, 41, 71–88. https://doi.org/10.1016/j.econedurev.2014.04.002.

    Article  Google Scholar 

  • Brock, L. L., Rimm-Kaufman, S. E., Nathanson, L., & Grimm, K. J. (2009). The contributions of ‘hot' and ‘cool' executive function to children's academic achievement, learning-related behaviors, and engagement in kindergarten. Early Childhood Research Quarterly, 24(3), 337–349.

    Article  Google Scholar 

  • Brown, B. B. (2004). Adolescents' relationship with peers. In R. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (2nd ed., pp. 363–394). New York: Wiley.

    Google Scholar 

  • Brown, B. B., & Larson, J. (2009). Peer relationships in adolescence. In R. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (Vol. 2, 3rd ed., pp. 74–103). New York: Wiley.

    Google Scholar 

  • Bull, R., & Scerif, G. (2001). Executive functioning as a predictor of children's mathematics ability: Inhibition, switching, and working memory. Developmental Neuropsychology, 19(3), 273–293.

    Article  Google Scholar 

  • Burrage, M. S., Ponitz, C. C., McCready, E. A., Shah, P., Sims, B. C., Jewkes, A. M., & Morrison, F. J. (2008). Age-and schooling-related effects on executive functions in young children: A natural experiment. Child Neuropsychology, 14(6), 510–524.

    Article  Google Scholar 

  • Carrell, S. E., & West, J. E. (2010). Does professor quality matter? Evidence from random assignment of students to professors. Journal of Political Economy, 118(3), 409–432.

    Article  Google Scholar 

  • Carver, C. S., & Scheier, M. F. (2004). Self-regulation of action and affect. Handbook of self-regulation: Research, theory, and applications (pp.13-39).

  • Chafouleas, S. M., Briesch, A. M., Riley-Tillman, T. C., Christ, T. J., Black, A. C., & Kilgus, S. P. (2010). An investigation of the generalizability and dependability of direct behavior rating single item scales (DBR-SIS) to measure academic engagement and disruptive behavior of middle school students. Journal of School Psychology, 48(3), 219–246.

    Article  Google Scholar 

  • Chevalier, N., Huber, K. L., Wiebe, S. A., & Espy, K. A. (2013). Qualitative change in executive control during childhood and adulthood. Cognition, 128(1), 1–12.

    Article  Google Scholar 

  • Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically authentic inquiry in schools: A theoretical framework for evaluating inquiry tasks. Science Education, 86(2), 175–218.

    Article  Google Scholar 

  • Cisler, J. M., Olatunji, B. O., Feldner, M. T., & Forsyth, J. P. (2010). Emotion regulation and the anxiety disorders: An integrative review. Journal of Psychopathol Behav Assess, 32(1), 68–82. https://doi.org/10.1007/s10862-009-9161-1.

    Article  Google Scholar 

  • Claessens, A., Duncan, G. J., & Engel, M. (2009). Kindergarten skills and fifth-grade achievement: Evidence from the ECLS-K. Economics of Education Review, 28, 415–427.

    Article  Google Scholar 

  • Conway, A., Miller, A. L., & Modrek, A. (2017). Testing reciprocal links between trouble getting to sleep and internalizing behavior problems, and bedtime resistance and externalizing behavior problems in toddlers. Child Psychiatry & Human Development, 48(4), 678–689.

    Article  Google Scholar 

  • Corno, L., & Mandinach, E. B. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18(2), 88–108.

    Article  Google Scholar 

  • Corno, L., & Rohrkemper, M. (1985). The intrinsic motivation to learn in classrooms. Research on motivation in education, 2, 53–90.

    Google Scholar 

  • De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179–201.

    Article  Google Scholar 

  • Dean Jr., D., & Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91(3), 384–397.

    Article  Google Scholar 

  • Diamond, A. (2012). Activities and programs that improve children’s executive functions. Current Directions in Psychological Science, 21(5), 335–341.

    Article  Google Scholar 

  • Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Preschool program improves cognitive control. Science, 318(5855), 1387–1388.

    Article  Google Scholar 

  • D'Mello, S., Dieterle, E., & Duckworth, A. (2017). Advanced, analytic, automated (AAA) measurement of engagement during learning. Educational Psychologist, 52(2), 104–123.

    Article  Google Scholar 

  • Doremus-Fitzwater, T. L., Varlinskaya, E. I., & Spear, L. P. (2010). Motivational systems in adolescence: Possible implications for age differences in substance abuse and other risk-taking behaviors. Brain and Cognition, 72, 114–123. https://doi.org/10.1016/j.bandc.2009.08.008.

    Article  Google Scholar 

  • Duckworth, A. L., & Kern, M. L. (2011). A meta-analysis of the convergent validity of self-control measures. Journal of Research in Personality, 45(3), 259–268.

    Article  Google Scholar 

  • Duckworth, A. L., & Seligman, M. E. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological Science, 16(12), 939–944.

    Article  Google Scholar 

  • Duckworth, A. L., Tsukayama, E., & Geier, A. (2010). Self-controlled children stay leaner in the transition to adolescence. Appetite, 54, 304–308. https://doi.org/10.1016/j.appet.2009.11.016.

    Article  Google Scholar 

  • Duckworth, A. L., Quinn, P. D., & Tsukayama, E. (2012). What no child left behind leaves behind: The roles of IQ and self-control in predicting standardized achievement test scores and report card grades. Journal of Educational Psychology, 104(2), 439–451.

    Article  Google Scholar 

  • Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., Feinstein, L., Engel, M., Brooks-Gunn, J., & Sexton, H. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428–1446.

    Article  Google Scholar 

  • Eccles, J. S., Wigfield, A., Midgley, C., Reuman, D., Iver, D. M., & Feldlaufer, H. (1993). Negative effects of traditional middle schools on students' motivation. The Elementary School Journal, 93(5), 553–574.

    Article  Google Scholar 

  • Espy, K. A. (1997). The shape school: Assessing executive function in preschool children. Developmental Neuropsychology, 13(4), 495–499.

    Article  Google Scholar 

  • Espy, K. A., Kaufmann, P. M., McDiarmid, M. D., & Glisky, M. L. (1999). Executive functioning in preschool children: Performance on A-not-B and other delayed response format tasks. Brain and Cognition, 41(2), 178–199.

    Article  Google Scholar 

  • Espy, K. A., McDiarmid, M. M., Cwik, M. F., Stalets, M. M., Hamby, A., & Senn, T. E. (2004). The contribution of executive functions to emergent mathematic skills in preschool children. Developmental neuropsychology, 26(1), 465-486.

  • Espy, K. A., Bull, R., Martin, J., & Stroup, W. (2006). Measuring the development of executive control with the shape school. Psychological Assessment, 18(4), 373–381.

    Article  Google Scholar 

  • Feldlaufer, H., Midgley, C., & Eccles, J. S. (1988). Student, teacher, and observer perceptions of the classroom environment before and after the transition to junior high school. The Journal of Early Adolescence, 8(2), 133–156.

    Article  Google Scholar 

  • Fischler, H., & Lichtfeld, M. (1992). Modern physics and students' conceptions. International Journal of Science Education, 14, 181–190.

    Article  Google Scholar 

  • Frick, M. A., Bohlin, G., Hedqvist, M., & Brocki, K. C. (2019). Temperament and cognitive regulation during the first 3 years of life as predictors of inattention and hyperactivity/impulsivity at 6 years. Journal of Attention Disorders, 23(11), 1291–1302.

    Article  Google Scholar 

  • Fried, C. B. (2008). In-class laptop use and its effects on student learning. Computers & Education, 50(3), 906–914. https://doi.org/10.1016/j.compedu.2006.09.006.

    Article  Google Scholar 

  • Ganesalingam, K., Yeates, K. O., Taylor, H. G., Walz, N. C., Stancin, T., & Wade, S. (2011). Executive functions and social competence in young children 6 months following traumatic brain injury. Neuropsychology, 25(4), 466–476.

    Article  Google Scholar 

  • Geldhof, G. J., Little, T. D., and Colombo, J. (2010). Self-regulation across the lifespan, in The Handbook of Life-Span Development, Vol. 2. Social and Emotional Development, eds M. E. Lamb, and A. Freund (Vol. eds R. M. Lerner) (Hoboken, NJ: Wiley), 116–157.

  • Graham, S., & Taylor, A. Z. (2014). An attributional approach to emotional life in the classroom. In R. Pekrun & L. Linnenbrink-Garcia (Eds.), International handbook of emotions in education (pp. 96–119). New York, NY: Routledge.

    Google Scholar 

  • Greiff, S., Fischer, A., Wüstenberg, S., Sonnleitner, P., Brunner, M., & Martin, R. (2013). A multitrait–multimethod study of assessment instruments for complex problem solving. Intelligence, 41(5), 579–596.

    Article  Google Scholar 

  • Gross, J. J. (1998). Antecedent-and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74(1), 224–237.

    Article  Google Scholar 

  • Gross, J. J. (2008). Emotion regulation. Handbook of emotions, 3(3), 497–513.

    Google Scholar 

  • Hasher, L., Zacks, R. T., & May, C. P. (1999). Inhibitory control, circadian arousal, and age. In D. Gopher & A. Koriat (Eds.), Attention and performance XVII (pp. 653–675). MIT Press.

  • Heaton, R. K., Chelune, G. J., Talley, J. L., Kay, G. G., & Curtiss, G. (1993). Wisconsin Card Sorting Test (WCST) manual: Revised and expanded. Psychological assessment resources (PAR).

  • Herman, J. L. (1992). What research tells us about good assessment. Educational Leadership, 49(8), 74–78.

    Google Scholar 

  • Hinshaw, S. P. (1992). Academic underachievement, attention deficits, and aggression: Comorbidity and implications for intervention. Journal of Consulting and Clinical Psychology, 60(6), 893–903.

    Article  Google Scholar 

  • Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174–180.

    Article  Google Scholar 

  • Holland, J. H., Holyoak, K. J., Nisbett, R. E., & Thagard, P. R. (1989). Induction: Processes of inference, learning, and discovery. MIT press.

  • Holyoak, K. J., & Cheng, P. W. (2011). Causal learning and inference as a rational process: The new synthesis. Annual Review of Psychology, 62, 135–163.

    Article  Google Scholar 

  • Hooper, C. J., Luciana, M., Conklin, H. M., & Yarger, R. S. (2004). Adolescents' performance on the Iowa gambling task: Implications for the development of decision making and ventromedial prefrontal cortex. Developmental Psychology, 40(6), 1148–1158.

    Article  Google Scholar 

  • Inzlicht, M., & Schmeichel, B. J. (2016). Beyond limited resources: Self-control failure as the product of shifting priorities. Handbook of self-regulation, 165-181.

  • Jones, L. B., Rothbart, M. K., & Posner, M. I. (2003). Development of executive attention in preschool children. Developmental Science, 6(5), 498–504.

    Article  Google Scholar 

  • Junco, R. (2012). In-class multitasking and academic performance. Computers in Human Behavior, 28(6), 2236–2243.

    Article  Google Scholar 

  • Kaplan, A., Middleton, M. J., Urdan, T., & Midgley, C. (2002). Achievement goals and goal structures. In C. Midgley (Ed.), Goals, goal structures, and patterns of adaptive learning (pp. 21–55). Erlbaum.

  • Kim, S., Nordling, J. K., Yoon, J. E., Boldt, L. J., & Kochanska, G. (2013). Effortful control in “hot” and “cool” tasks differentially predicts children’s behavior problems and academic performance. Journal of Abnormal Child Psychology, 41(1), 43–56.

    Article  Google Scholar 

  • Kim, Y. E., Brady, A. C., & Wolters, C. A. (2020). College students' regulation of cognition, motivation, behavior, and context: Distinct or overlapping processes? Learning and Individual Differences, 101872.

  • Klahr, D., & Dunbar, K. (2013). Developmental differences in scientific discovery processes. In Complex information processing (pp. 129-164). Psychology press.

  • Konold, T. R., & Pianta, R. C. (2005). Empirically-derived, person-oriented patterns of school readiness in typically-developing children: Description and prediction to first-grade achievement. Applied Developmental Science, 9(4), 174–187.

    Article  Google Scholar 

  • Kornell, N., & Hausman, H. (2016). Do the best teachers get the best ratings? Frontiers in Psychology, 7, 570.

    Article  Google Scholar 

  • Kuhn, D., & Pease, M. (2008). What needs to develop in the development of inquiry skills? Cognition and Instruction, 26(4), 512–559.

    Article  Google Scholar 

  • Kuhn, D., & Pease, M. (2009). The dual components of developing strategy use: Production and inhibition. In H. S. Waters & W. Schneider (Eds.), Metacognition, strategy use, and instruction. New York: Guilford Press.

    Google Scholar 

  • Kuhn, D., Ramsey, S., & Arvidsson, T. S. (2015). Developing multivariable thinkers. Cognitive Development, 35, 92–110.

    Article  Google Scholar 

  • Kuhn, D., Modrek, A. S., Sandoval, W. A. (2020). Teaching and Learning by Questioning. In L. Butler, S. Ronfard, & K. Corriveau (Eds.) The Questioning Child: Insights from Psychology and Education (pp. 232–251). Cambridge, UK: Cambridge University Press.

  • Laird, T., Shoup, R., & Kuh, G. D. (2005). Measuring deep approaches to learning using the National Survey of student engagement. In Annual meeting of the Association for Institutional Research.

    Google Scholar 

  • Latzman, R. D., Elkovitch, N., Young, J., & Clark, L. A. (2010). The contribution of executive functioning to academic achievement among male adolescents. Journal of Clinical and Experimental Neuropsychology, 32(5), 455–462.

    Article  Google Scholar 

  • Laursen, B., & Collins, W. A. (2009). Parent-child relationships during adolescence. In R. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (3rd ed.). Wiley.

  • Li, J., Pang, B., Zhang, B., & Du, H. (2011). Self-regulation: From basic theories to applications. J. Beijing Norm. Univ., 2011, 5–13. https://doi.org/10.1190/1.3659042.

    Article  Google Scholar 

  • Lindquist, S. I., & McLean, J. P. (2011). Daydreaming and its correlates in an educational environment. Learning and Individual Differences, 21, 158–167.

    Article  Google Scholar 

  • Linnenbrink, E. A., & Pintrich, P. R. (2000). Multiple pathways to learning and achievement: The role of goal orientation in fostering adaptive motivation, affect, and cognition. In C. Sansone & J. M. Harackiewicz (Eds.), Intrinsic and extrinsic motivation: The search for optimal motivation and performance (p. 195–227). Academic Press.

  • Mazzocco, M. M., & Kover, S. T. (2007). A longitudinal assessment of executive function skills and their association with math performance. Child neuropsychology, 13(1), 18–45.

  • McClelland, M. M., Morrison, F. J., & Holmes, D. L. (2000). Children at risk for early academic problems: The role of learning-related social skills. Early Childhood Research Quarterly, 15(3), 307–329.

    Article  Google Scholar 

  • McGlamery, M. E., Ball, S. E., Henley, T. B., & Besozzi, M. (2007). Theory of mind, attention, and executive function in kindergarten boys. Emotional and Behavioural Difficulties, 12(1), 29-47.

  • McClelland, M., Geldhof, J., Morrison, F., Gestsdóttir, S., Cameron, C., Bowers, E., Duckworth, A., Little, T., & Grammer, J. (2018). Self-Regulation. In Self-regulation, In Handbook of life course health development (pp. 275–298). Cham: Springer.

  • McNeil, N. M., & Alibali, M. W. (2005). Why won't you change your mind? Knowledge of operational patterns hinders learning and performance on equations. Child Development, 76(4), 883–899.

    Article  Google Scholar 

  • Meindl, P., Yu, A., Galla, B. M., Quirk, A., Haeck, C., Goyer, J. P., Lejuez, C. W., D’Mello, S. K., & Duckworth, A. L. (2019). A brief behavioral measure of frustration tolerance predicts academic achievement immediately and two years later. Emotion, 19(6), 1081–1092.

    Article  Google Scholar 

  • Milyavskaya, M., Berkman, E. T., & De Ridder, D. T. (2019). The many faces of self-control: Tacit assumptions and recommendations to deal with them. Motivation Science, 5(1), 79–85.

    Article  Google Scholar 

  • Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science, 21(1), 8–14.

    Article  Google Scholar 

  • Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100.

    Article  Google Scholar 

  • Modrek, A.S. (2020) Accounting for cognitive costs: Can scientists be creative? Philosophical Psychology. (in press)

  • Modrek, A., & Kuhn, D. (2017). A cognitive cost of the need to achieve? Cognitive Development, 44, 12–20.

  • Modrek, A. S., Kuhn, D., Conway, A., Arvidsson, T. (2019) Cognitive regulation, not behavior regulation, predicts learning. Learning and Instruction, 60(C), 237–244.

  • Modrek, A. S., & Sandoval, W. A. (2020) Can autonomy play a role in causal reasoning? Cognitive Development, 54(C), 1–9.

  • Moffett, L., & Morrison, F. J. (2020). Off-task behavior in kindergarten: Relations to executive function and academic achievement. Journal of Educational Psychology, 112(5), 938–955.

    Article  Google Scholar 

  • Ocumpaugh, J. (2012). Baker-Rodrigo observation method protocol (BROMP) 1.0. Training manual version 1.0. Baker-Rodrigo Observation Method Protocol (BROMP) 1.0. Training Manual version 1.0, Tech. Rep.

  • Ocumpaugh, J., Baker, R. S., & Rodrigo, M. M. T. (2012). Baker-Rodrigo observation method protocol (BROMP) 1.0, Training manual version 1.0. Teachers College: Columbia University.

  • Ocumpaugh, J., Baker, R., Gowda, S., Heffernan, N., & Heffernan, C. (2014). Population validity for educational data mining: A case study in affect detection. British Journal of Educational Psychology, 45, 487–501.

    Google Scholar 

  • Ocumpaugh, J., Baker, R. S., & Rodrigo, M. M. T. (2015). Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) 2.0 Technical and Training Manual. New York, NY and Manila, Philippines: Teachers College, Columbia University and Ateneo Laboratory for the Learning Sciences.

  • Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049–1079.

    Article  Google Scholar 

  • Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications. Prentice Hall.

    Google Scholar 

  • Ponitz, C. E. C., McClelland, M. M., Jewkes, A. M., Connor, C. M., Farris, C. L., & Morrison, F. J. (2008). Touch your toes! Developing a direct measure of behavioral regulation in early childhood. Early Childhood Research Quarterly, 23(2), 141–158.

    Article  Google Scholar 

  • Prencipe, A., Kesek, A., Cohen, J., Lamm, C., Lewis, M. D., & Zelazo, P. D. (2011). Development of hot and cool executive function during the transition to adolescence. Journal of Experimental Child Psychology, 108(3), 621–637.

    Article  Google Scholar 

  • Rigas, G., Carling, E., & Brehmer, B. (2002). Reliability and validity of performance measures in microworlds. Intelligence, 30(5), 463-480.

  • Risko, E. F., Anderson, N., Sarwal, A., Engelhardt, M., & Kingstone, A. (2012). Everyday attention: Variation in mind wandering and memory in a lecture. Applied Cognitive Psychology, 26(2), 234–242.

    Article  Google Scholar 

  • Sacks, P. (2000). Predictable losers in testing schemes. School Administrator, 57(11), 6–9.

    Google Scholar 

  • Sameroff, A. (2010). A unified theory of development: A dialectic integration of nature and nurture. Child Development, 81(1), 6–22.

    Article  Google Scholar 

  • Schauble, L. (1990). Belief revision in children: The role of prior knowledge and strategies for generating evidence. Journal of Experimental Child Psychology, 49(1), 31–57.

    Article  Google Scholar 

  • Schunk, D. H. (2005). Commentary on self-regulation in school contexts. Learning and Instruction, 15(2), 173–177.

    Article  Google Scholar 

  • Shepard, L. (2000). The role of assessment in a learning culture. Educational Researcher, 29(7), 4–14.

    Article  Google Scholar 

  • Shepard, L. A., & Smith, M. L. (1990). Synthesis of research on grade retention. Educational Leadership, 47(8), 84–88.

    Google Scholar 

  • Shoda, Y., Mischel, W., & Peake, P. K. (1990). Predicting adolescent cognitive and self-regulatory competencies from preschool delay of gratification: Identifying diagnostic conditions. Developmental Psychology, 26(6), 978–986.

    Article  Google Scholar 

  • Sinatra, G. M., Heddy, B. C., & Lombardi, D. (2015). The challenges of defining and measuring student engagement in science. Educational Psychologist, 50(1), 1–13.

    Article  Google Scholar 

  • Smith, M. L., & Fey, P. (2000). Validity and accountability of high-stakes testing. Journal of Teacher Education, 51(5), 334–344.

    Article  Google Scholar 

  • Smith, E. N., Romero, C., Donovan, B., Herter, R., Paunesku, D., Cohen, G. L., Dweck, C. S., & Gross, J. J. (2018). Emotion theories and adolescent well-being: Results of an online intervention. Emotion, 18(6), 781–788.

    Article  Google Scholar 

  • Sobel, D. M., & Munro, S. E. (2009). Domain generality and specificity in children's causal inference about ambiguous data. Developmental Psychology, 45(2), 511–524.

    Article  Google Scholar 

  • Soderstrom, N. C., & Bjork, R. A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10(2), 176–199.

    Article  Google Scholar 

  • Stroebe, W. (2016). Are most published social psychological findings false? Journal of Experimental Social Psychology, 66, 134–144.

    Article  Google Scholar 

  • Sturman, D. A., & Moghaddam, B. (2011). The neurobiology of adolescence: Changes in brain architecture, functional dynamics, and behavioral tendencies. Neuroscience and Biobehavioral Reviews, 35, 1704–1712. https://doi.org/10.1016/j.neubiorev.2011.04.003.

    Article  Google Scholar 

  • Thorndike, E. L. (1904). Introduction to the theory of mental measurement. New York, NY: Columbia University.

  • Trzesniewski, K. H., Moffitt, T. E., Caspi, A., Taylor, A., & Maughan, B. (2006). Revisiting the association between reading achievement and antisocial behavior: New evidence of an environmental explanation from a twin study. Child Development, 77(1), 72–88.

    Article  Google Scholar 

  • Unsworth, N., McMillan, B. D., Brewer, G. A., & Spillers, G. J. (2012). Everyday attention failures: An individual differences investigation. Journal of Experimental Psychology: Learning, Memory and Cognition, 38(6), 1765–1772.

    Google Scholar 

  • Watts, T. W., Duncan, G. J., Siegler, R. S., & Davis-Kean, P. E. (2014). What’s past is prologue: Relations between early mathematics knowledge and high school achievement. Education Research, 43(7), 352–360.

    Article  Google Scholar 

  • Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–573.

    Article  Google Scholar 

  • Willoughby, M., Kupersmidt, J., Voegler-Lee, M., & Bryant, D. (2011). Contributions of hot and cool self-regulation to preschool disruptive behavior and academic achievement. Developmental Neuropsychology, 36(2), 162–180.

    Article  Google Scholar 

  • Wilson, T. D., & Buttrick, N. R. (2016). New directions in social psychological interventions to improve academic achievement. Journal of Educational Psychology, 108(3), 392–396.

    Article  Google Scholar 

  • Wilson, C. D., Taylor, J. A., Kowalski, S. M., & Carlson, J. (2010). The relative effects and equity of inquiry-based and commonplace science teaching on students' knowledge, reasoning, and argumentation. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 47(3), 276–301.

    Google Scholar 

  • Wood, E., Zivcakova, L., Gentile, P., Archer, K., De Pasquale, D., & Nosko, A. (2012). Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Computers & Education, 58(1), 365–374.

    Article  Google Scholar 

  • Xu, F., Han, Y., Sabbagh, M. A., Wang, T., Ren, X., & Li, C. (2013). Developmental differences in the structure of executive function in middle childhood and adolescence. PLoS One, 8(10), e77770.

    Article  Google Scholar 

  • Yunker, P. J., & Yunker, J. A. (2003). Are student evaluations of teaching valid? Evidence from an analytical business core course. The Journal of Education for Business, 78, 313–317. https://doi.org/10.1080/08832320309598619.

    Article  Google Scholar 

  • Zhou, Q., Chen, S. H., & Main, A. (2012). Commonalities and differences in the research on children’s effortful control and executive function: A call for an integrated model of self-regulation. Child Development Perspectives, 6(2), 112–121.

    Article  Google Scholar 

  • Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45, 166–183. https://doi.org/10.3102/0002831207312909.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Psychology, Thomas Jefferson University, Downs Hall, Office 24, 4201 Henry Avenue, Philadelphia, PA, 19144, USA

    Anahid S. Modrek

  2. Department of Educational Psychology, Ball State University, Muncie, IN, 47306, USA

    Gerardo Ramirez

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  1. Anahid S. Modrek
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  2. Gerardo Ramirez
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Correspondence to Anahid S. Modrek.

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Modrek, A.S., Ramirez, G. Cognitive regulation outdoes behavior regulation in predicting state standardized test scores over time. Metacognition Learning 16, 113–134 (2021). https://doi.org/10.1007/s11409-020-09242-8

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