A latent profile analysis of first-year university students’ academic expectations
Academic expectations are an important variable in the explanation of adaptation and academic success in higher education. This paper uses latent profile analysis as a person-centered statistical approach to classify students into groups of similar types of expectations for higher education, at the beginning of the first year in university. Participants were 2,478 first-year Portuguese students. Based on the scores of seven dimensions of expectations, we identified six classes of students. Most students (84%) presented moderate levels of expectations, while 8% and 4%, respectively, reported very high and low expectations. One class represented a group of students (4%) with high expectations for the quality of education and for political engagement and citizenship and lower expectations for social interaction and attending to social pressures. Male and older students showed more positive expectations. Students from privileged family backgrounds are more likely to present higher expectations for political engagement and citizenship experiences, and lower expectations for social interaction and leisure and attending to social pressures.
Keywords: latent profile analysis; person-centered; expectations; higher education; first-year students
Almeida, L. S., Deaño, M., Araújo, A. M., Costa, A. R., Conde, A., & Alfonso, S. (2012). Questionário de Perceções Académicas: Versão Expectativas (QPA-E) [Academic Perceptions Questionnaire (APQ) - Expectations]. Braga: Universidade do Minho; Ourense: Universidade de Vigo-Ourense.
Bergman, L. R., & Andersson, H. (2010). The person and the variable in developmental psychology. Zeitschrift für Psychologie/ Journal of Psychology, 218(3), 155-166. doi: 10.1027/0044-3409/a000025
Berlin, K. S., Williams, N. A., & Parra, G. R. (2014). An introduction to latent variable mixture modeling (part 1): Overview and cross-sectional latent class and latent profile analyses. Journal of Pediatric Psychology, 39, 174-187. doi: 10.1093/jpepsy/jst084
Blickenstaff, J. C. (2005). Women and science careers: Leaky pipeline or gender filter? Gender and Education, 17, 369−386. doi: 10.1080/09540250500145072
Böttcher, L., Araújo, N. A. M., Nagler, J., Mendes, J. F. F., Helbing, D., Herrmann, H. J. (2016). Gender gap in the ERASMUS mobility program. PLoS ONE, 11(2): e0149514. doi: 10.1371/journal.pone.0149514
Buchmann, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71, 515-541. doi: 10.1177/000312240607100401
Ceci, S. J., Ginther, D. K., Kahn, S., and Williams, W. M. (2014). Women in academic science: A changing landscape. Psychological Science in the Public Interest, 15, 75–141. doi: 10.1177/1529100614541236
Crosnoe, R., Mistry, R., & Elder Jr., G. (2002). Economic disadvantage, family dynamics, and adolescent enrollment in higher education. Journal of Marriage and the Family, 64, 690-702. doi: 10.1111/j.1741-3737.2002.00690.x
Deaño, M., Diniz, A. M., Almeida, L. S., Alfonso, S., Costa, A. R., García-Señorán, M., Conde, A., Araujo, A. M., Iglesias-Sarmiento, V., Gonçalves, P., & Tellado, F. (2015). Propiedades psicométricas del Cuestionario de Percepciones Académicas para la evaluación de las expectativas de los estudiantes de primer año en Enseñanza Superior. Anales de Psicología, 31, 280-289. doi: 10.6018/analesps.31.1.161641
Diniz, A., Alfonso, S., Araújo, A. M., Costa, A. R., Conde, A., & Almeida, L. S. (2016). Gender differences in first-year college students’ academic expectations. Studies in Higher Education. doi: 10.1080/03075079.2016.1196350
Fouad, N. A., Hackett, G., Smith, P., Kantamneni, N., Fitzpatrick, M., Haag, S., & Spencer, D. (2010). Barriers and supports for continuing in mathematics and science: Gender and educational level differences. Journal of Vocational Behavior, 77, 361-373. doi:10.1016/j.jvb.2010.06.004
Gilard, S., & Guglielmetti, C. (2011). University life of non-traditional students: Engagement styles and impact on attrition. The Journal of Higher Education, 82, 33-53. doi: 10.1353/jhe.2011.0005
Gow, L., & Kember, D. (1990). Does higher education promote independent learning? Higher Education, 19, 307-322. doi: 10.1007/BF00133895
Howard, J. A. (2005). Why should we care about student expectations?. In T. E. Miller, B. E. Bender, J. H. Schub, & Associates (Eds.), Promoting reasonable expectations: Aligning student and institutional views of college experience (pp. 10-33). San Francisco, CA: Jossey-Bass.
Huang, C. (2013). Gender differences in academic self-efficacy: A meta-analysis. European Journal of Psychology of Education, 28, 1-35. doi: 10.1007/s10212-011-0097-y
Jackson, L. M., Pancer, S. M., Pratt, M. W., & Hunsberger, B. E. (2000). Great expectations: The relation between expectancies and adjustment during the transition to university. Journal of Applied Social Psychology, 30, 2100-2025. doi: 10.1111/j.1559-1816.2000.tb02427.x
Kuh, G. D., Gonyea, R. M, & Williams, J. M. (2005). What students expect from college and what they get. In T. E. Miller, B. E. Bender, J. H. Schuh, & Associates (Eds.), Promoting reasonable expectations: Aligning student and institutional views of the college experience. San Francisco, CA: Jossey-Bass.
Lent, R. W., Brown, S. D., & Hackett, G. (2002). Social cognitive career theory. In D. Brown & Associates (Eds.), Career choice and development (pp. 255-311). San Francisco, CA: Jossey-Bass.
Moneta, L., & Kuh, G. D. (2005). When expectations and realities collide: Environmental influences on student expectations and student experiences. In T. E. Miller, B. E. Bender, J. H. Schuh & Associates (Eds.), Promoting reasonable expectations: Aligning student and institutional views of college experience (pp. 65-83). San Francisco, CA: Jossey-Bass.
Muthén, L. K., & Muthén, B. O. (2012). Mplus: Statistical analysis with latent variables. User’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
Nightingale, S. M., Roberts, S., Tariq, V., Appleby, Y, Barnes, L., Harris, R. A., Dacre-Pool, L., & Qualter, P. (2013). Trajectories of university adjustment in the United Kingdom: Emotion management and emotional self-efficacy protect against initial poor adjustment. Learning and Individual Differences, 27, 174-181. doi: 10.1016/j.lindif.2013.08.004
Páramo-Fernández, M., Araújo, A. M., Tinajero-Vacas, C., Almeida, L. S., & Rodríguez-González, M. S. (2017). Predictors of students’ adjustment during the transition to university in Spain. Psicothema, 29(1), 67-72. doi: 10.7334/psicothema2016.40
Pascarella, E .T., & Terenzini, P. T. (2005). How college affects students: A third decade of research. San Francisco: Jossey-Bass.
Pascarella, E. T., Pierson, C. T. Wolniak, G. C., & Terenzini, P. T. (2004). First-generation college students: Additional evidence on college experiences and outcomes. The Journal of Higher Education, 75, 249-284. doi: 10.1353/jhe.2004.0016
Pascarella, E. T., Wolniak, G. C., Pierson, C. T., & Terenzini, P. T. (2003). Experiences and outcomes of first-generation students in community colleges. Journal of College Student Development, 44, 420-429. doi: 10.1353/csd.2003.0030
Patton, W., Creed, P., & Spooner-Lane, R. (2005). Validation of the short form of the Career Development Inventory – Australian Version with a sample of university students. Australian Journal of Career Development, 14(3), 49-59. doi: 10.1177/103841620501400308
Pike, G. R., Hansen, M. J., & Childress, J. E. (2014). The influence of students’ pre-college characteristics, high school experiences, college expectations, and initial enrollment characteristics on degree attainment. Journal of College Retention: Research, Theory & Practice, 16, 1-23. doi: 10.2190/CS.16.1.a
Pleitz, J. D., MacDougall, A. E., Terry, R. A., Buckley, M. R., &
Campbell, N. J. (2015). Great expectations: Examining the discrepancy between expectations and experience on college student retention. Journal of College Student Retention: Research, Theory & Practice, 17, 88-104. doi: 10.1177/1521025115571252
Richardson, J. T. E. (2013). Approaches to studying across the adult life span: Evidence from distance education. Learning and Individual Differences, 26, 74-80. doi: 10.1016/j.lindif.2013.04.012
Saavedra, L., Araújo, A. M., Taveira, M.C., & Vieira, C.M. (2014). Dilemmas of girls and women in engineering: A study in Portugal. Educational Review, 66, 330-344. doi: 10.1080/00131911.2013.780006
Sánchez-Sandoval, Y., & Verdugo, L. (2016). Desarrollo y validación de la Escala de Expectativas de Futuro en la Adolescencia (EEFA). Anales de Psicología, 32(2), 545-554. doi: 10.6018/analesps.32.2.205661
Sax, L., & Harper, C. E. (2007). Origins of the gender gap: Pre-college and college influences on differences between men and women. Research in Higher Education, 48, 669-694. doi: 10.1007/s11162-006-9046-z
Smith, J. S., & Wertlieb, E. C (2005). Do first-year college studentsʼ expectations align with their first-year experiences? NASPA Journal, 42(2), 153-174. doi: 10.2202/1949-6605.1470
Tein, J.-Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling, 20, 640-657. doi: 10.1080/10705511.2013.824781
Twenge, J. M., & Campbell, W. K. (2001). Age and birth cohort differences in self-esteem: A cross temporal meta-analysis. Personality and Social Psychology Review, 5, 321-344. doi: 10.1207/S15327957PSPR0504_3
Vuong, M., Brown-Welty, S., & Tracz, S. (2010). The effects of self-efficacy on academic success of first-generation college sophomore students. Journal of College Student Development, 51, 50-64. doi: 10.1353/csd.0.0109
Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus. Chichester, UK: John Wiley & Sons Ltd.
Copyright (c) 2019 Servicio de Publicaciones, University of Murcia (Spain)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The works published in this journal are subject to the following terms:
1. The Publications Service of the University of Murcia (the publisher) retains the property rights (copyright) of published works, and encourages and enables the reuse of the same under the license specified in paragraph 2.
2. The works are published in the online edition of the journal under a Creative Commons Attribution-NonCommercial 4.0 (legal text). You can copy, use, distribute, transmit and publicly display, provided that: i) you cite the author and the original source of publication (journal, editorial and URL of the work), ii) are not used for commercial purposes, iii ) mentions the existence and specifications of this license.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
3. Conditions of self-archiving. Is allowed and encouraged the authors to disseminate electronically pre-print versions (version before being evaluated and sent to the journal) and / or post-print (version reviewed and accepted for publication) of their works before publication, as it encourages its earliest circulation and diffusion and thus a possible increase in its citation and scope between the academic community. RoMEO Color: Green.