References
- Athanases, S. Z., Wahleithner, J. M., & Bennett, L. H. (2012). Learning to attend to culturally and linguistically diverse learners through teacher inquiry in teacher education. Teachers College Record, 114(7), 1–50. https://doi.org/https://doi.org/10.1080/1547688x.2013.841506
- Berg, J., Osher, D., Same, M. R., Nolan, E., Benson, D., & Jacobs, N. (2017). Identifying, defining, and measuring social and emotional competencies. American Institutes for Research.
- Berkowitz, R., Moore, H., Astor, R. A., & Benbenishty, R. (2017). A research synthesis of the associations between socioeconomic background, inequality, school climate, and academic achievement. Review of Educational Research, 87(2), 425–469. https://doi.org/https://doi.org/10.3102/0034654316669821
- Blazar, D., & Kraft, M. A. (2017). Teacher and teaching effects on Students’ Attitudes and Behaviors. Educational Evaluation and Policy Analysis, 39(1), 146–170. https://doi.org/https://doi.org/10.3102/0162373716670260
- Borghans, L., Duckworth, A. L., Heckman, J. J., & Ter Weel, B. (2008). The economics and psychology of personality traits. Journal of Human Resources, 43(4), 972–1059. https://doi.org/https://doi.org/10.1353/jhr.2008.0017
- Brookhart, S. M., Guskey, T. R., Bowers, A. J., McMillan, J. H., Smith, J. K., Smith, L. F., Stevens, M. T., & Welsh, M. E. (2016). A century of grading research: Meaning and value in the most common educational measure. Review of Educational Research, 86(4), 803–848. https://doi.org/https://doi.org/10.3102/0034654316672069
- Burton, N. W., & Ramist, L. (2001). Predicting success in college: SAT® studies of classes graduating since 1980. College Entrance Examination Board.
- Caprara, G. V., Barbaranelli, C., Pastorelli, C., Bandura, A., & Zimbardo, P. G. (2000). Prosocial foundations of children’s academic achievement. Psychological Science, 11(4), 302–306. https://doi.org/https://doi.org/10.1111/1467-9280.00260
- Caspi, A., Roberts, B. W., & Shiner, R. L. (2005). Personality development: Stability and change. Annual Review of Psychology, 56(1), 453–484. https://doi.org/https://doi.org/10.1146/annurev.psych.55.090902.141913
- Collaborative for Academic, Social and Emotional Learning. (2018). What is SEL?
- Cowie, B., & Cooper, B. (2017). Exploring the challenge of developing student teacher data literacy. Assessment in Education: Principles, Policy & Practice, 24(2), 147–163. https://doi.org/https://doi.org/10.1080/0969594x.2016.1225668
- Credé, M. (2018). What shall we do about grit? A critical review of what we know and what we don’t know. Educational Researcher, 47(9), 606–611. https://doi.org/https://doi.org/10.3102/0013189X18801322
- Crone, D. A., Carlson, S. E., Haack, M. K., Kennedy, P. C., Baker, S. K., & Fien, H. (2016). Data-based decision-making teams in middle school: Observations and implications from the middle school intervention project. Assessment for Effective Intervention, 41(2), 79–93. https://doi.org/https://doi.org/10.1177/1534508415610322
- Datnow, A., & Hubbard, L. (2015). Teachers’ use of assessment data to inform instruction: Lessons from the past and prospects for the future. Teachers College Record, 117(4), 1–26.
- DiPerna, J. C., Lei, P., Cheng, W., Hart, S. C., & Bellinger, J. (2018). A cluster randomized trial of the Social Skills Improvement System-Classwide Intervention Program (SSIS-CIP) in first grade. Journal of Educational Psychology, 110(1), 1–16. https://doi.org/https://doi.org/10.1037/edu0000191
- Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher (Washington, D.C. : 1972)), 44(4), 237–251. https://doi.org/https://doi.org/10.3102/0013189x15584327
- 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. https://doi.org/https://doi.org/10.1037/a0026280
- Dunlap, K., Piro, J. S., & Wang, S. (2016). Diving into data: Developing the capacity for data literacy in teacher education. Cogent Education, 3(1), 1132526. https://doi.org/https://doi.org/10.1080/2331186X.2015.1132526
- Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions . Child Development, 82(1), 405–432. https://doi.org/https://doi.org/10.1111/j.1467-8624.2010.01564.x
- Ebbeler, J., Poortman, C. L., Schildkamp, K., & Pieters, J. M. (2016). Effects of a data use intervention on educators’ use of knowledge and skills. Studies in Educational Evaluation, 48, 19–31. https://doi.org/https://doi.org/10.1016/j.stueduc.2015.11.002
- Faria, A. M., Greenberg, A., Meakin, J., Bichay, K., & Heppen, J. (2013, March 7–9). Replicating the relationship between teachers’ data use and student achievement: The urban data study and the data dashboard usage study [Paper Presentation]. Society for Research on Educational Effectiveness.
- Farrell, C. C., & Marsh, J. A. (2016). Contributing conditions: A qualitative comparative analysis of teachers’ instructional responses to data. Teaching and Teacher Education, 60, 398–412. https://doi.org/https://doi.org/10.1016/j.tate.2016.07.010
- Flannery, K. B., Fenning, P., Kato, M. M., & McIntosh, K. (2014). Effects of school-wide positive behavioral interventions and supports and fidelity of implementation on problem behavior in high schools. School Psychology Quarterly : The Official Journal of the Division of School Psychology, American Psychological Association, 29(2), 111–124. https://doi.org/https://doi.org/10.1037/spq0000039
- Gallagher, L., Means, B., & Padilla, C. (2008). Teachers’ use of student data systems to improve instruction: 2005 to 2007. U.S. Department of Education, Office of Planning, Evaluation and Policy Development.
- Gelderblom, G., Schildkamp, K., Pieters, J., & Ehren, M. (2016). Data-based decision making for instructional improvement in primary education. International Journal of Educational Research, 80, 1–14. https://doi.org/https://doi.org/10.1016/j.ijer.2016.07.004
- Guss, S. S., Morris, A. S., Bosler, C., Castle, S. L., Hays-Grudo, J., Horm, D. M., & Treat, A. (2020). Parents’ adverse childhood experiences and current relationships with their young children: The role of executive function. Early Child Development and Care, 190(7), 1042–1052. https://doi.org/https://doi.org/10.1080/03004430.2018.1513921
- Hamilton, L. S., Schwartz, H. L., Stecher, B. M., & Steele, J. L. (2013). Improving accountability through expanded measures of performance. Journal of Educational Administration, 51(4), 453–475. https://doi.org/https://doi.org/10.1108/09578231311325659
- Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance.
- Hiebert, J., Morris, A. K., Berk, D., & Jansen, A. (2007). Preparing teachers to learn from teaching. Journal of Teacher Education, 58(1), 47–61. https://doi.org/https://doi.org/10.1177/0022487106295726
- Hoover, N. R., & Abrams, L. M. (2013). Teachers’ instructional use of summative student assessment data. Applied Measurement in Education, 26(3), 219–231. https://doi.org/https://doi.org/10.1080/08957347.2013.793187
- Illinois State Board of Education. (n.d.). Social/emotional learning standards. https://www.isbe.net/pages/social-emotional-learning-standards.aspx
- Ingram, D., Louis, K. S., & Schroeder, R. G. (2004). Accountability policies and teacher decision making: Barriers to the use of data to improve practice. Teachers College Record, 106(6), 1258–1287. https://doi.org/https://doi.org/10.1111/j.1467-9620.2004.00379.x
- Jones, S. M., & Kahn, J. (2017). The evidence base for how we learn: Supporting students’ social, emotional, and academic development. The WERA Educational Journal, 10(1), 5–20.
- Kennedy, P. W., Sheckley, B. G., & Kehrhahn, M. T. (2000, May). The dynamic nature of student persistence: Influence of interactions between student attachment, academic adaptation, and social adaptation [Paper Presentation]. Annual Meeting of the Association for Institutional Research.
- Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(4), 496–520. https://doi.org/https://doi.org/10.1086/505057
- Kyllonen, P. C., Walters, A. M., & Kaufman, J. C. (2005). Noncognitive constructs and their assessment in graduate education: A review. Educational Assessment, 10(3), 153–184. https://doi.org/https://doi.org/10.1207/s15326977ea1003_2
- LaRocca, B., & Bartolino Krachman, S. (2018). A data-informed approach to social-emotional learning: Policy recommendations for state and local leaders. A policy brief. Transforming Education. https://www.transformingeducation.org/wp-content/uploads/2018/05/TE-April-2018-Paper-April-2018-FINAL-v3.pdf
- Le, H., Casillas, A., Robbins, S. B., & Langley, R. (2005). Motivational and skills, social, and self-management predictors of college outcomes: Constructing the student readiness inventory. Educational and Psychological Measurement, 65(3), 482–508. https://doi.org/https://doi.org/10.1177/0013164404272493
- Lee, J., & Shute, V. J. (2009). The influence of noncognitive domains on academic achievement in K-12. Educational Testing Service. https://doi.org/https://doi.org/10.1002/j.2333-8504.2009.tb02191.x
- Little, J. W. (2012). Understanding data use practice among teachers: The contribution of micro-process studies. American Journal of Education, 118(2), 143–166. https://doi.org/https://doi.org/10.1086/663271
- Little, R. J. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. https://doi.org/https://doi.org/10.1080/01621459.1988.10478722
- Little, R. J., & Rubin, D. B. (1987). Statistical analysis with missing data. Wiley. https://doi.org/https://doi.org/10.1002/9781119013563.ch7
- Lotkowski, V. A., Robbins, S. B., & Noeth, R. J. (2004). The role of academic and non-academic factors in improving college retention. American College Testing. https://doi.org/https://doi.org/10.1037/e420492008-001
- Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366–376. https://doi.org/https://doi.org/10.1016/j.tate.2016.07.011
- Mandinach, E. B., & Jimerson, J. B. (2016). Teachers learning how to use data: A synthesis of the issues and what is known. Teaching and Teacher Education, 60, 452–457. https://doi.org/https://doi.org/10.1016/j.tate.2016.07.009
- Mandinach, E., Friedman, J. M., & Gummer, E. (2015). How can schools of education help to build educators’ capacity to use data? A systemic view of the issue. Teachers College Record, 117(4), 1–50.
- Maras, M. A., Thompson, A. M., Lewis, C., Thornburg, K., & Hawks, J. (2015). Developing a tiered response model for social-emotional learning through interdisciplinary collaboration. Journal of Educational and Psychological Consultation, 25(2–3), 198–223. https://doi.org/https://doi.org/10.1080/10474412.2014.929954
- Marsh, J. A. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1–48.
- Marsh, J. A., Bush-Mecenas, S., & Hough, H. (2017). Learning from early adopters in the new accountability era: Insights from California’s CORE waiver districts. Educational Administration Quarterly, 53(3), 327–364. https://doi.org/https://doi.org/10.1177/0013161X16688064
- Marsh, J. A., Sloan McCombs, J., & Martorell, F. (2010). How instructional coaches support data-driven decision making. Educational Policy, 24(6), 872–907. https://doi.org/https://doi.org/10.1177/0895904809341467
- Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers’ ability to use data to inform instruction: Challenges and supports. U.S. Department of Education, Office of Planning, Evaluation and Policy Development.
- Means, B., Gallagher, L., & Padilla, C. (2007). Teachers’ use of student data management systems to improve instruction. U.S. Department of Education, Office of Planning, Evaluation and Policy Development.
- Nocera, E. J., Whitbread, K. M., & Nocera, G. P. (2014). Impact of school-wide positive behavior supports on student behavior in the middle grades. Rmle Online, 37(8), 1–14. https://doi.org/https://doi.org/10.1080/19404476.2014.11462111
- Penuel, W. R., & Shepard, L. A. (2016). Assessment and teaching. In D. H. Gitomer & C. A. Bell (Eds.), Handbook of research on teaching (pp. 787–850). American Educational Research Association. https://doi.org/https://doi.org/10.3102/978-0-935302-48-6_12
- Phelps-Gregory, C., & Spitzer, S. (2018). Assessing prospective teachers’ analysis of teaching: How well can they link teaching and learning?Mathematics Teacher Educator, 7(1), 34–49. https://doi.org/https://doi.org/10.5951/mathteaceduc.7.1.0034
- Pierce, R., Chick, H., Watson, J., Les, M., & Dalton, M. (2014). A statistical literacy hierarchy for interpreting educational system data. Australian Journal of Education, 58(2), 195–217. https://doi.org/https://doi.org/10.1177/0004944114530067
- Rangel, V. S., Monroy, C., & Bell, E. (2016). Science teachers’ data use practices: A descriptive analysis. Education Policy Analysis Archives, 24, 86. https://doi.org/https://doi.org/10.14507/epaa.24.2348
- Reeves, T. D., Summers, K. H., Grove, E., & Boylan, M. (2016). Examining the landscape of teacher learning for data use: The case of Illinois. Cogent Education, 3(1), 1211476. https://doi.org/https://doi.org/10.1080/2331186X.2016.1211476
- Schildkamp, K., Karbautzki, L., & Vanhoof, J. (2014). Exploring data use practices around Europe: Identifying enablers and barriers. Studies in Educational Evaluation, 42, 15–24. https://doi.org/https://doi.org/10.1016/j.stueduc.2013.10.007
- Sommerfeld, A. (2011). Recasting non-cognitive factors in college readiness as what they truly are: Non-academic factors. Journal of College Admission, 213, 18–22.
- Sun, J., Przybylski, R., & Johnson, B. J. (2016). A review of research on teachers’ use of student data: From the perspective of school leadership. Educational Assessment, Evaluation and Accountability, 28(1), 5–33. https://doi.org/https://doi.org/10.1007/s11092-016-9238-9
- Supovitz, J. (2012). Getting at student understanding–The key to teachers’ use of test data. Teachers College Record, 114(11), 1–29.
- Supovitz, J. A., Foley, E., & Mishook, J. (2012). In search of leading indicators in education. Education Policy Analysis Archives, 20, 19. https://doi.org/https://doi.org/10.14507/epaa.v20n19.2012
- Tough, P. (2012). How children succeed: Grit, curiosity, and the hidden power of character. Houghton Mifflin Harcourt.
- Wayman, J. C., Jimerson, J. B., & Cho, V. (2012). Organizational considerations in establishing the data-informed district. School Effectiveness and School Improvement, 23(2), 159–178. https://doi.org/https://doi.org/10.1080/09243453.2011.652124
- West, M. R., Kraft, M. A., Finn, A. S., Martin, R. E., Duckworth, A. L., Gabrieli, C. F., & Gabrieli, J. D. (2016). Promise and paradox: Measuring students’ non-cognitive skills and the impact of schooling. Educational Evaluation and Policy Analysis, 38(1), 148–170. https://doi.org/https://doi.org/10.3102/0162373715597298
- Xu, Y., & Brown, G. T. (2016). Teacher assessment literacy in practice: A reconceptualization. Teaching and Teacher Education, 58, 149–162. https://doi.org/https://doi.org/10.1016/j.tate.2016.05.010
- Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302–314. https://doi.org/https://doi.org/10.1080/00461520.2012.722805
- Yeh, C., & Santagata, R. (2015). Preservice teachers’ learning to generate evidence-based hypotheses about the impact of mathematics teaching on learning. Journal of Teacher Education, 66(1), 21–34. https://doi.org/https://doi.org/10.1177/0022487114549470
- Young, V. M. (2006). Teachers’ use of data: Loose coupling, agenda setting, and team norms. American Journal of Education, 112(4), 521–548. https://doi.org/https://doi.org/10.1086/505058
- Young, V. M., & Kim, D. H. (2010). Using assessments for instructional improvement: A literature review. Education Policy Analysis Archives, 18(19), 19. https://doi.org/https://doi.org/10.14507/epaa.v18n19.2010