Longitudinal tracking of academic progress during teacher preparation

British Journal of Educational Psychology

Volumn 87, Issue 4, 2017, Pages 664-682

  Corcoran, Roisin P ^a,b   O'Flaherty, Joanne ^c  

^a IRINSTITUTES   (United States)

^b UNIVERSITY COLLEGE DUBLIN   (Ireland)

^c UNIVERSITY OF LIMERICK   (Ireland)

Author keywords

academic achievement; latent growth curve analysis; pre service student teachers

Indexed keywords

ACADEMIC ACHIEVEMENT; ADULT; FEMALE; HUMAN; LONGITUDINAL STUDY; MALE; SCHOOL TEACHER; STATISTICS AND NUMERICAL DATA; TEACHER TRAINING; YOUNG ADULT;

ACADEMIC PERFORMANCE; ADULT; FEMALE; HUMANS; LONGITUDINAL STUDIES; MALE; SCHOOL TEACHERS; TEACHER TRAINING; YOUNG ADULT;

EID: 85028438481     PISSN: 00070998     EISSN: 20448279     Source Type: Journal    
DOI: 10.1111/bjep.12171     Document Type: Article

References (93)

1. ACT (2007). The ACT technical manual. Iowa City, IA: Author.
2. Alexander, K. L., Entwisle, D. R., & Kabbani, N. (2001). The dropout process in life course perspective: Early risk factors at home and school. Teachers College Record, 103, 760–822. https://doi.org/10.1111/0161-4681.00134
3. Allen, J., Robbins, S., Casillas, A., & Oh, I. (2008). Third-year college retention and transfer: Effects of academic performance, motivation, and social connectedness. Research in Higher Education, 49, 647–664. https://doi.org/10.1007/s11162-008-9098-3
4. Anderman, E. R., 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
5. Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155–173. https://doi.org/10.1007/bf02294170
6. Astin, A. W., & Antonio, A. L. (2012). Assessment for excellence: The philosophy and practice of assessment and evaluation in higher education (2nd ed.). New York, NY: Rowman & Littlefield/American Council on Education.
7. Astin, A. W., Tsui, L., & Avalos, J. (1996). Degree attainment rates at American colleges and universities: Effects of race, gender, and institutional type. Los Angeles, CA: Higher Education Research Institute, Graduate School of Education, University of California.
8. Bagg, D. G. (1970). A-levels and university performance. Nature, 225, 1105–1108. https://doi.org/10.1038/2251105a0
9. Banta, T. W., Jones, E. A., & Black, K. E. (2009). Designing effective assessment: Principles and profiles of good practice. San Francisco, CA: Jossey-Bass.
10. Berdie, R. F., Layton, W. L., Swanson, E. O., & Hagenah, T. (1963). Testing in guidance and counseling. New York, NY: McGraw-Hill.
11. Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246–263. https://doi.org/10.1111/j.1467-624.2007.00995.x
12. Brabeck, M. M., Dwyer, C. A., Geisinger, K. R., Marx, R. W., Noell, G. H., Pianta, R. C., … Worrell, F. C. (2016). Assessing the assessments of teacher preparation. Theory Into Practice, 55(2), 160–167. https://doi.org/10.1080/00405841.2015.1036667
13. Bridgeman, B., Pollack, J., & Burton, N. (2008). Predicting grades in different types of college courses (College Board Research Report No. 2008-1, ETS RR-08-06). New York, NY: The College Board.
14. Cabrera, A., Nora, A., Terenzini, P., Pascarella, E., & Hagedorn, L. (1999). Campus racial climate and the adjustment of students to college: A comparison between white students and African-American students. The Journal of Higher Education, 70(2), 134–160. https://doi.org/10.2307/2649125
15. Camara, W. J., & Echternacht, G. (2000). The SAT I and high school grades: Utility in predicting success in college. Research Notes RN-10, The College Board, Office of Research and Development.
16. Cole, D. A. (1987). Utility of confirmatory factor analysis in test validation research. Journal of Consulting and Clinical Psychology, 55, 584–594. https://doi.org/10.1037/0022-006X.55.4.584
17. Coolahan, J. (2003). Attracting, developing and retaining effective teachers: Country background report for Ireland. Dublin, Ireland: Department of Education and Science.
18. Corcoran, R. P. (2017a). Preparing teachers' to raise students' mathematics learning. International Journal of Science and Mathematics Education, https://doi.org/10.1007/s10763-017-9819-1
19. Corcoran, R. P. (2017b). Preparing principals to improve student achievement. Child & Youth Care Forum, https://doi.org/10.1007/s10566-017-9399-9
20. Corcoran, R. P., & O'Flaherty, J. (2016a). Personality development during teacher preparation. Frontiers in Psychology, 7, 1677. https://doi.org/10.3389/fpsyg.2016.01677
21. Corcoran, R. P., & O'Flaherty, J. (2016b). Moral reasoning development among college students: A growth curve analysis. Journal of Moral Education, 45(4), 433–448. https://doi.org/10.1080/03057240.2016.1230051
22. Corcoran, R. P., & O'Flaherty, J. (2017). Executive function during teacher preparation. Teaching and Teacher Education, 63, 168–175. https://doi.org/10.1016/j.tate.2016.12.023
23. Corcoran, R. P., & Tormey, R. (2012). How emotionally intelligent are pre-service teachers? Teaching and Teacher Education, 28, 750–759. https://doi.org/10.1016/j.tate.2012.02.007
24. Corno, L., & Mandinach, E. B. (2004). What we have learned about student engagement in the past twenty years. In D. M. McInerney & S. Van Etten (Eds.), Big theories revisited (pp. 299–328). Greenwich, CT: Information Age.
25. Davis-Kean, P. E., & Jager, J. (2014). Trajectories of achievement within race/ethnicity: “Catching up” in achievement across time. The Journal of Educational Research, 107, 197–208. https://doi.org/10.1080/00220671.2013.807493
26. Diseth, A., & Kobbeltvedt, T. (2010). A mediation analysis of achievement motives, goals, learning strategies, and academic achievement. British Journal of Educational Psychology, 80, 671–687. https://doi.org/10.1348/000709910X492432
27. Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92, 1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087
28. Dweck, C. S. (1999). Self-theories: Their role in motivation, personality and development. Philadelphia, PA: The Psychology Press.
29. Dweck, C. S. (2015). Growth. British Journal of Educational Psychology, 85, 242–245. https://doi.org/10.1111/bjep.12072
30. Elliott, J. (1993). Reconstructing teacher education: Teacher development. London, UK: Falmer Press.
31. Ensminger, M. E., & Slusarcick, A. L. (1992). Paths to high school graduation or dropout: A longitudinal study of a first-grade cohort. Sociology of Education, 65, 95–113. https://doi.org/10.2307/2112677
32. Glazerman, S., Loeb, S., Goldhaber, D., Staiger, D., Raudenbusch, S., & Whitehurst, G. (2010). Evaluating teachers: The important role of value added. Washington, DC: Brown Center on Education Policy at Brookings.
33. Gormley, I. C., & Murphey, T. B. (2006). Analysis of Irish third-level college applications data. Journal of the Royal Statistical Society: Series A, Statistics in Society, 169, 361–379. https://doi.org/10.1111/j.1467-985X.2006.00412.x
34. Greene, J. J., & Forster, G. (2003). Public high school graduation and college readiness rates in the United States. Education Working Paper #3. Manhattan Institute.
35. Grimm, K. J. (2008). Longitudinal associations between reading and mathematics achievement. Developmental Neuropsychology, 33, 410–426. https://doi.org/10.1080/87565640801982486
36. Harris, D. N. (2012). How do value-added indicators compare to other measures of teacher effectiveness?. New York, NY: Carnegie Foundation.
37. Hattie, J. (2015). The applicability of visible learning to higher education. Scholarship of Teaching and Learning in Psychology, 1, 79–91. https://doi.org/10.1037/stl0000021
38. Hedeker, D., & Gibbons, R. D. (2006). Longitudinal data analysis. Hoboken, NJ: Wiley.
39. Hill, H. C., Rowan, B., & Loewenberg Ball, D. (2005). Effects of teachers' mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42, 371–406. https://doi.org/10.3102/00028312042002371
40. Hirsh, J. B., Mar, R. A., & Peterson, J. B. (2012). Psychological entropy: A framework for understanding uncertainty-related anxiety. Psychological Review, 119, 304–320. https://doi.org/10.1037/a0026767
41. Ishitani, T., & Desjardins, S. (2002). A longitudinal investigation of dropout from college in the United States. Journal of College Student Retention: Research, Theory and Practice, 4(2), 173–201. https://doi.org/10.2190/v4en-nw42-742q-2ntl
42. Johnson, V. E. (1997). An alternative to traditional GPA for evaluating student performance. Statistical Science, 12, 251–278.
43. Kim, E., & Corcoran, R. P. (2017). How engaged are pre-service teachers in the United States? Teaching and Teacher Education, 66, 12–23. https://doi.org/10.1016/j.tate.2017.03.020
44. King, R. B., & McInerney, D. M. (2014). Mapping changes in students' English and math self-concepts: A latent growth model study. Educational Psychology, 34, 581–597. https://doi.org/10.1080/01443410.2014.909009
45. Kobrin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., & Barbuti, S. M. (2008). The validity of the SAT for predicting first-year college grade point average (College Board Research Report 2008–2005). New York, NY: The College Board.
46. Leonard, D., & Gleeson, J. (1999). Context and coherence in initial teacher education in Ireland: The place of reflective inquiry. Teacher Development, 3, 49–63. https://doi.org/10.1080/13664539900200070
47. 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. https://doi.org/10.1037/0003-066x.57.9.705
48. Lynch, K. (1989). The hidden curriculum. London, UK: The Falmer Press.
49. Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103, 391–410. https://doi.org/10.1007/BF01102761
50. Martin, A. J. (2007). Examining a multidimensional model of student motivation and engagement using a construct validation approach. British Journal of Educational Psychology, 77, 413–440. https://doi.org/10.1348/000709906X118036
51. Martin, A. J. (2013). Goal orientation. In J. Hattie & E. M. Anderman (Eds.), International guide to student achievement (pp. 353–355). New York, NY: Routledge.
52. 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
53. Martin, A. J., & Liem, G. A. (2010). Academic personal bests (PBs), engagement, and achievement: A cross-lagged panel analysis. Learning and Individual Differences, 20, 265–270. https://doi.org/10.1016/j.lindif.2010.01.001
54. Mattern, K. D., & Patterson, B. F. (2011a). The relationship between SAT scores and retention to the fourth year: 2006 validity sample (College Board Statistical Report 2011–2006). New York, NY: The College Board.
55. Mattern, K. D., & Patterson, B. F. (2011b). The relationship between SAT scores and retention to the third year: 2006 validity sample (College Board Statistical Report 2011–2006). New York, NY: The College Board.
56. McCoach, D. B., Madura, J., Rambo-Hernandez, K. E., O'Connell, A. A., & Welsh, M. (2013). Longitudinal data analysis. In T. Teo (Ed.), Handbook of quantitative methods for educational research (pp. 199–230). Rotterdam, The Netherlands: Sense.
57. McDonald, R. P., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness of fit. Psychological Bulletin, 107(2), 247–255. https://doi.org/10.1037/0033-2909.107.2.247
58. McManus, I. C., Woolf, K., Dacre, J., Paice, E., & Dewberry, C. (2013). The academic backbone: Longitudinal continuities in educational achievement from secondary school and medical school to MRCP(UK) and the specialist register in UK medical students and Doctors. BMC Medicine, 11, 242–269. https://doi.org/10.1186/1741-7015-11-242
59. MET Project (2012). Asking students about teaching: Student perception surveys and their implementation. Seattle, WA: Bill and Melinda Gates Foundation.
60. Metallidou, P., & Vlachou, A. (2010). Children's self-regulated learning profile in language and mathematics: The role of task value beliefs. Psychology in the Schools, 47, 776–788. https://doi.org/10.1002/pits.20503
61. Mok, M. M. C., McInerney, D. M., Zhu, J., & Or, A. (2015). Growth trajectories of mathematics achievement: Longitudinal tracking of student academic progress. British Journal of Educational Psychology, 85, 154–171. https://doi.org/10.1111/bjep.12060
62. Morisano, D., Hirsh, J. B., Peterson, J. B., Pihl, R. O., & Shore, B. M. (2010). Setting, elaborating, and reflecting on personal goals improves academic performance. Journal of Applied Psychology, 95, 255–264. https://doi.org/10.1037/a0018478
63. Musset, P. (2010). Initial teacher education and continuing training policies in a comparative perspective: Current practices in OECD countries and a literature review on potential effects. OECD Education Working Papers, No. 48, OECD. https://doi.org/10.1787/5kmbphh7s47h-en
64. Muthen, B. O., & Khoo, S. T. (1998). Longitudinal studies of achievement growth using latent variable modeling. Learning and Individual Differences, 10, 73–101. https://doi.org/10.1016/s1041-6080(99)80135-6
65. Muthen, B., & Muthen, L. (2011). Mplus (Version 6.12) [Computer software]. Los Angeles, CA: Author.
66. Noble, J., & Sawyer, R. (2002). Predicting different levels of academic success in college using high school GPA and ACT composite score, ACT Research Report Series 2002-4. Retrieved from http://files.eric.ed.gov/fulltext/ED469746.pdf
67. O'Flaherty, J., & Gleeson, J. (2017). Irish student teachers' levels of moral reasoning: Context, comparisons, and contributing influences. Teachers and Teaching: Theory and Practice, 23(1), 59–77.
68. Organisation for Economic Co-operation and Development (OECD) (1991). Reviews of national policies for education: Ireland. Paris, France: Author.
69. Organisation for Economic Co-operation and Development (OECD) (2005). Teachers matter: Attracting, developing and retaining effective teachers. Paris, France: Author.
70. Pascarella, E. T., Pierson, C. T., Wolniak, G. C., & Terenzini, P. T. (2004). First-generation college students: Additional evidence on college experiences and outcomes. Journal of Higher Education, 75, 249–284.
71. Pascarella, E., & Terenzini, P. (2005). How college affects students, Volume 2: A third decade of research. San Francisco, CA: Jossey-Bass.
72. Perry, R. P., Hladkyj, S., Pekrun, R. H., Clifton, R. A., & Chipperfield, J. G. (2005). Perceived academic control and failure in college students: A three-year study of scholastic attainment. Research in Higher Education, 46, 535–569. https://doi.org/10.1007/s11162-005-3364-4
73. Pinxten, M., Marsh, H. W., De Fraine, B., van den Noortgate, W., & van Damme, J. (2014). Enjoying mathematics or feeling competent in mathematics? Reciprocal effects on mathematics achievement and perceived math effort expenditure. British Journal of Educational Psychology, 84, 152–174. https://doi.org/10.1111/bjep.12028
74. Raudenbush, S. W. (2001). Comparing personal trajectories and drawing causal inferences from longitudinal data. Annual Review of Psychology, 52, 501–525. https://doi.org/10.1146/annurev.psych.52.1.501
75. Ready, D. D. (2013). Associations between student achievement and student learning: Implications for value-added school accountability models. Educational Policy, 27, 92–120. https://doi.org/10.1177/0895904811429289
76. Rescorla, L., & Rosenthal, A. S. (2004). Growth in standardized ability and achievement test scores from 3rd to 10th grade. Journal of Educational Psychology, 96(1), 85–96. https://doi.org/10.1037/0022-0663.96.1.85
77. Rumberger, R. W. (1995). Dropping out of middle school: A multilevel analysis of students and schools. American Educational Research Journal, 32, 583–625.
78. Schunk, D. H. (2008). Learning theories: An educational perspective. Upper Saddle River, NJ: Pearson Education.
79. 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, NY: Routledge.
80. Shin, T. (2007). Comparison of three growth modeling techniques in the multilevel analysis of longitudinal academic achievement scores: Latent growth modeling, hierarchical linear modeling, and longitudinal profile analysis via multidimensional scaling. Asia Pacific Education Review, 8, 262–275. https://doi.org/10.1007/bf03029261
81. Shin, T., Davison, M. L., Long, J. D., Chen, C. K., & Heistad, D. (2013). Exploring gains in reading and mathematics achievement among regular and exceptional students using growth curve modelling. Learning and Individual Differences, 23, 92–100. https://doi.org/10.1016/j.lindif.2012.10.002
82. Strenta, A. C., & Elliot, R. (1987). Differential grading revisited. Journal of Educational Measurement, 24, 281–291.
83. Strenta, A. G., Elliott, R., Adair, R., Matier, M., & Scott, J. (1994). Choosing and leaving science in highly selective institutions. Research in Higher Education, 35, 513–547. https://doi.org/10.1007/BF02497086
84. Stumpf, H., & Stanley, J. C. (2002). Group data on high school grade point averages and scores on academic aptitude tests as predictors of institutional graduation rates. Educational and Psychological Measurement, 62, 1042–1052. https://doi.org/10.1177/0013164402238091
85. Teaching Council (2011). Initial teacher education: Criteria and guidelines for programme providers. Maynooth, Ireland: Author. Available at: http://www.teachingcouncil.ie/_fileupload/Teacher%20Education/Final%20Criteria%20and%20Guidelines%20for%20Existing%20Progs%20Aug2011.pdf
86. Teaching Council of Ireland (2013). Guidelines on school placement. Available at: http://www.teachingcouncil.ie/_fileupload/Teacher%20Education/School%20Placement/School%20Placement%20Guidelines.pdf
87. Travers, C. J., Morisano, D., & Locke, E. A. (2015). Self-reflection, growth goals, and academic outcomes: A qualitative study. British Journal of Educational Psychology, 85, 224–241. https://doi.org/10.1111/bjep.12059
88. Walvoord, B. E. (2010). Assessment clear and simple (2nd ed.). San Francisco, CA: Jossey-Bass.
89. Weisberg, D., Sexton, S., Mulhern, J., & Keeling, D. (2009). The widget effect: Our national failure to acknowledge and act on differences in teacher effectiveness. Washington, DC: The New Teacher Project.
90. ® scores, high school grades, and SES. Educational Assessment, 20, 23–45. https://doi.org/10.1080/10627197.2015.997614
91. Worrell, F., Brabeck, M., Dwyer, C., Geisinger, K., Marx, R., Noell, G., & Pianta, R. (2014). Assessing and evaluating teacher preparation programs. Washington, DC: American Psychological Association.
92. Yuan, K. H., & Bentler, P. M. (2000). Three likelihood-based methods for mean and covariance structure analysis with nonnormal missing data. Sociological Methodology, 30(1), 165–200. https://doi.org/10.1111/0081-1750.00078
93. Zwick, R. (2006). Higher education admission testing. In R. Brennan (Ed.), Educational measurement (4th ed., pp. 647–679). Westport, CT: American Council on Education, Praeger.