Abstract
Academic engagement describes students’ investment in academic learning and achievement and is an important indicator of students’ adjustment to university life, particularly in the first year. A tridimensional conceptualization of academic engagement has been accepted (behavioral, emotional and cognitive dimensions). This paper tests the dimensionality, internal consistency reliability and invariance of the University Student Engagement Inventory (USEI) taking into consideration both gender and the scientific area of graduation. A sample of 908 Portuguese first-year university students was considered. Good evidence of reliability has been obtained with ordinal alpha and omega values. Confirmatory factor analysis substantiates the theoretical dimensionality proposed (second-order latent factor), internal consistency reliability evidence indicates good values and the results suggest measurement invariance across gender and the area of graduation. The present study enhances the role of the USEI regarding the lack of consensus on the dimensionality and constructs delimitation of academic engagement.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alrashidi, O., Phan, H. P., & Ngu, B. H. (2016). Academic engagement: An overview of its definitions, dimensions, and major conceptualisations. International Education Studies, 9(12), 41–52. https://doi.org/10.5539/ies.v9n12p41.
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for Educational and Psychological Testing. Washington. In DC. USA: American Psychological Association.
American Psychological Association. (1954). Technical recommendations for psychological tests and diagnostic techniques. Psychological Bulletin, 51(2), 201–238. https://doi.org/10.1037/h0053479.
Antúnez, Á., Cervero, A., Solano, P., Bernardo, I., & Carbajal, R. (2017). Engagement: A new perspective for reducing dropout through self-regulation. In J. A. González-Pienda, A. Bernardo, J. C. Núñez, & C. Rodríguez (Eds.), Factors affecting academic performance (pp. 25–46). New York, NY, USA: Nova Science Publishers.
Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the student engagement instrument. Journal of School Psychology, 44(5), 427–445. https://doi.org/10.1016/j.jsp.2006.04.002.
Appleton, J. J., Christenson, S. L., & Furlong, M. J. (2008). Student engagement with school: Critical conceptual and methodological issues of the construct. Psychology in the Schools, 45(5), 369–386. https://doi.org/10.1002/pits.20303.
Bakker, A. B., Schaufeli, W. B., Leiter, M. P., & Taris, T. W. (2008). Work engagement: An emerging concept in occupational health psychology. Work and Stress, 22(3), 187–200. https://doi.org/10.1080/02678370802393649.
Banta, T. W., Pike, G. R., & Hansen, M. J. (2009). The use of engagement data in accreditation, planning, and assessment. New Directions for Institutional Research, 2009(141), 21–34. https://doi.org/10.1002/ir.284.
Barkley, E. F. (2010). Student engagement techniques: A handbook for college faculty. San Francisco. CA, USA: John Wiley & Sons.
Bernardo, A., Cervero, A., Esteban, M., Tuero, E., Casanova, J. R., & Almeida, L. S. (2017). Freshmen program withdrawal: Types and recommendations. Frontiers in Psychology, 8, 1–11. https://doi.org/10.3389/fpsyg.2017.01544.
Bollen, K. A. (1989). Structural equations with latent variables. New York, NY, USA: Wiley. https://doi.org/10.1002/9781118619179.
Bologna Declaration. (1999) The European higher education area. Joint declaration of the European ministers of education, June 19, Bologna. https://www.eurashe.eu/library/bologna_1999_bologna-declaration-pdf/
Bresó, E., Schaufeli, W. B., & Salanova, M. (2011). Can a self-efficacy-based intervention decrease burnout, increase engagement, and enhance performance? A quasi-experimental study. Higher Education, 61(4), 339–355. https://doi.org/10.1007/s10734-010-9334-6.
Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York, NY, USA: The Guildford Press.
Carter, C. P., Reschly, A. L., Lovelace, M. D., Appleton, J. J., & Thompson, D. (2012). Measuring student engagement among elementary students: Pilot of the student engagement instrument— Elementary version. School Psychology Quarterly, 27(2), 61–73. https://doi.org/10.1037/a0029229.
Chapman, C., Laird, J., Ifill, N., & KewalRamani, A. (2011). Trends in high school dropout and completion rates in the United States: 1972–2009 (No. compendium report 2012–006). National Center for Education Statistics http://nces.ed.gov/pubsearch
Chen, F. F., Sousa, K. H., & West, S. G. (2005). Teacher’s corner: Testing measurement invariance of second-order factor models. Structural Equation Modeling: A Multidisciplinary Journal, 12(3), 471–492. https://doi.org/10.1207/s15328007sem1203_7.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5.
Christensen, M. (2017). Work engagement and job crafting. In M. Christensen, P. Ø. Saksvik, & M. Karanika-Murray (Eds.), The positive side of occupational health psychology (pp. 79–90). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-66781-2_7.
Christenson, S. L., & Reschly, A. L. (2010). Check & connect: Enhancing school completion through student engagement. In B. Doll, W. Pfohl, & J. Yoon (Eds.), Handbook of youth prevention science (pp. 327–334). New York, NY, USA: Routledge.
Christenson, S. L., Reschly, A. L., & Wylie, C. (Eds.). (2012). Handbook of research on student engagement. New York, NY, USA: Springer. https://doi.org/10.1007/978-1-4614-2018-7.
Coates, H. (2005). The value of student engagement for higher education quality assurance. Quality in Higher Education, 11(1), 25–36. https://doi.org/10.1080/13538320500074915.
Coetzee, M., & Oosthuizen, R. M. (2012). Students’ sense of coherence, study engagement and self-efficacy in relation to their study and employability satisfaction. Journal of Psychology in Africa, 22(3), 315–322. https://doi.org/10.1080/14330237.2012.10820536.
Costa, A. R., & Marôco, J. (2017). Inventário de envolvimento académico dos estudantes do Ensino Superior (USEI). In L. S. Almeida, M. R. Simões, & M. M. Gonçalves (Eds.), Adaptação, desenvolvimento e sucesso académico dos estudantes do ensino superior: Instrumentos de avaliação (pp. 33–44). Braga, Portugal: ADIPSIEDUC.
Costa, A. R., Araújo, A. M., & Almeida, L. S. (2014). Envolvimento académico de estudantes de engenharia: Contributos para a validação interna e externa de uma escala de avaliação. Revista Eletrónica de Psicologia, Educação e Saúde, 4(1), 142–155 http://www.revistaepsi.com.
Crutzen, R., & Peters, G.-J. Y. (2017). Scale quality: Alpha is an inadequate estimate and factor-analytic evidence is needed first of all. Health Psychology Review, 11(3), 242–247. https://doi.org/10.1080/17437199.2015.1124240.
Davidov, E., Meuleman, B., Cieciuch, J., Schmidt, P., & Billiet, J. (2014). Measurement equivalence in cross-national research. Annual Review of Sociology, 40(1), 55–75. https://doi.org/10.1146/annurev-soc-071913-043137.
Dılekmen, M. (2007). Orientation program and adaptation of university students. Psychological Reports, 101(7), 1141–1144. https://doi.org/10.2466/PR0.101.7.1141-1144.
Eccles, J., & Wang, M.-T. (2012). So what is student engagement anyway? In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 133–145). Boston, MA. USA: Springer. https://doi.org/10.1007/978-1-4614-2018-7_6.
Edwards, M. C., Houts, C. R., & Wirth, R. J. (2017). Measurement invariance, the lack thereof, and modeling change. Quality of Life Research, 27, 1–9. https://doi.org/10.1007/s11136-017-1673-7.
Elmore, G. M., & Huebner, E. S. (2010). Adolescents’ satisfaction with school experiences: Relationships with demographics, attachment relationships, and school engagement behavior. Psychology in the Schools, 47(6), 525–537. https://doi.org/10.1002/pits.20488.
Finn, J. D., & Zimmer, K. S. (2012). Student engagement: What is it? Why does it matter? In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 97–131). Boston, MA. USA: Springer. https://doi.org/10.1007/978-1-4614-2018-7_5.
Finney, S. J., & DiStefano, C. (2013). Non-normal and categorical data in Structural Equation Modeling In G. R. Hancock & R. O. Mueller (Eds.), Structural Equation Modeling: A second course (2nd ed., pp. 439–492). Charlotte, NC, USA: Information Age Publishing.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. https://doi.org/10.2307/3151312.
Fredricks, J. A. (2015). Academic engagement. In J. D. Wright (Ed.), International encyclopedia of the social & behavioral sciences (2nd ed., Vol. 1, pp. 31–36). San Diego, CA, USA: Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.26085-6
Fredricks, J. A., & McColskey, W. (2012). The measurement of student engagement: A comparative analysis of various methods and student self-report instruments. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 763–782). Boston, MA, USA: Springer. https://doi.org/10.1007/978-1-4614-2018-7_37
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059.
Fredricks, J. A., McColskey, W., Meli, J., Mordica, J., Montrosse, B., & Mooney, K. (2011). Measuring student engagement in upper elementary through high school: A description of 21 instruments (No. Issues & Answers report, REL 2011–No. 098). Washington, DC, USA: Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Southeast. http://ies.ed.gov/ncee/edlabs
Fredricks, J. A., Filsecker, M., & Lawson, M. A. (2016). Student engagement, context, and adjustment: Addressing definitional, measurement, and methodological issues. Learning and Instruction, 43, 1–4. https://doi.org/10.1016/j.learninstruc.2016.02.002.
Gilardi, S., & Guglielmetti, C. (2011). University life of non-traditional students: Engagement styles and impact on attrition engagement styles and impact on attrition. The Journal of Higher Education, 82(1), 33–53. https://doi.org/10.1080/00221546.2011.11779084.
Green, S. B., & Yang, Y. (2009). Reliability of summed item scores using structural equation modeling: An alternative to coefficient alpha. Psychometrika, 74(1), 155–167. https://doi.org/10.1007/s11336-008-9099-3.
Handelsman, M. M., Briggs, W. L., Sullivan, N., & Towler, A. (2005). A measure of college student course engagement. The Journal of Educational Research, 98(3), 184–192. https://doi.org/10.3200/JOER.98.3.184-192.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.
Hirschi, A. (2012). Callings and work engagement: Moderated mediation model of work meaningfulness, occupational identity, and occupational self-efficacy. Journal of Counseling Psychology, 59(3), 479–485. https://doi.org/10.1037/a0028949.
Hodson, P., & Thomas, H. (2003). Quality assurance in higher education: Fit for the new millennium or simply year 2000 compliant? Higher Education, 45(3), 375–387. https://doi.org/10.1023/A:1022665818216.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118.
Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2018). semTools: Useful tools for Structural Equation Modeling (R package version 0.4–15.930) [Computer Software]. https://cran.r-project.org/package=semTools
Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758–773. https://doi.org/10.1080/03075079.2011.598505.
Kaplan, R. M., & Saccuzzo, D. P. (2013). Psychological testing: Principles, applications & issues (8th ed.). Belmont. CA, USA: Wadsworth.
Kelley, K., & Pornprasertmanit, S. (2016). Confidence intervals for population reliability coefficients: Evaluation of methods, recommendations, and software for composite measures. Psychological Methods, 21(1), 69–92. https://doi.org/10.1037/a0040086.
Kember, D., & Leung, D. Y. P. (2009). Development of a questionnaire for assessing students’ perceptions of the teaching and learning environment and its use in quality assurance. Learning Environments Research, 12(1), 15–29. https://doi.org/10.1007/s10984-008-9050-7.
Klem, A. M., & Connell, J. P. (2004). Relationships matter: Linking teacher support to student engagement and achievement. Journal of School Health, 74(7), 262–273. https://doi.org/10.1111/j.1746-1561.2004.tb08283.x.
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York, NY, USA: The Guildford Press.
Kong, Q., Wong, N.-Y., & Lam, C.-C. (2003). Student engagement in mathematics: Development of instrument and validation of construct. Mathematics Education Research Journal, 15(1), 4–21. https://doi.org/10.1007/BF03217366.
Krause, K.-L., & Coates, H. (2008). Students’ engagement in first-year university. Assessment & Evaluation in Higher Education, 33(5), 493–505. https://doi.org/10.1080/02602930701698892.
Kuh, G. D. (2001). Assessing what really matters to student learning: Inside the National Survey of student engagement. Change: The Magazine of Higher Learning, 33(3), 10–17. https://doi.org/10.1080/00091380109601795.
Kuh, G. D. (2005). Student engagement in the first year of college. In M. L. Upcraft, J. N. Gardner, & B. O. Barefoot (Eds.), Challenging and supporting the first-year student: A handbook for improving the first year of college (pp. 86–107). San Francisco: Jossey-Bass.
Kuh, G. D. (2009). The National Survey of student engagement: Conceptual and empirical foundations. New Directions for Institutional Research, 2009(141), 5–20. https://doi.org/10.1002/ir.283.
Lee, J.-S. (2014). The relationship between student engagement and academic performance: Is it a myth or reality? The Journal of Educational Research, 107(3), 177–185. https://doi.org/10.1080/00220671.2013.807491.
Lin, S.-H., & Huang, Y.-C. (2018). Assessing college student engagement: Development and validation of the student course engagement scale. Journal of Psychoeducational Assessment, 36(7), 694–708. https://doi.org/10.1177/0734282917697618.
Mandernach, B. J. (2015). Assessment of student engagement in higher education: A synthesis of literature and assessment tools. International Journal of Learning, Teaching and Educational Research, 12(2), 1–14. https://doi.org/10.1073/pnas.94.17.9499.
Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/biomet/57.3.519.
Marôco, J. (2014). Análise de equações estruturais: Fundamentos teóricos, software & aplicações (2nd ed.). Pêro Pinheiro, Portugal: ReportNumber.
Maroco, J., Maroco, A. L., & Campos, J. A. D. B. (2014). Student’s academic efficacy or inefficacy? An example on how to evaluate the psychometric properties of a measuring instrument and evaluate the effects of item wording. Open Journal of Statistics, 04(06), 484–493. https://doi.org/10.4236/ojs.2014.46046.
Marôco, J., Marôco, A. L., Campos, J. A. D. B., & Fredricks, J. A. (2016). University student’s engagement: Development of the university student engagement inventory (USEI). Psicologia: Reflexão e. Crítica, 29(21), 1–12. https://doi.org/10.1186/s41155-016-0042-8.
Marsh, H. W., Lüdtke, O., Muthén, B. O., Asparouhov, T., Morin, A. J. S., Trautwein, U., & Nagengast, B. (2010). A new look at the big five factor structure through exploratory structural equation modeling. Psychological Assessment, 22(3), 471–491. https://doi.org/10.1037/a0019227.
McCoach, D. B., Gable, R. K., & Madura, J. P. (Eds.). (2013). Evidence based on relations to other variables: Bolstering the empirical validity arguments for constructs. In Instrument development in the affective domain (3rd ed., pp. 209–248). New York, NY, USA: Springer. https://doi.org/10.1007/978-1-4614-7135-6_6
McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ, USA: Routledge. https://doi.org/10.4324/9781410601087.
Millsap, R. E., & Yun-Tein, J. (2004). Assessing factorial invariance in ordered-categorical measures. Multivariate Behavioral Research, 39(3), 479–515. https://doi.org/10.1207/S15327906MBR3903_4.
National Research Council, & Institute of Medicine. (2004). Engaging schools: Fostering school students’ motivation to learn. Washington. In DC. USA: National Academies Press. https://doi.org/10.17226/10421.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of research (Vol. 2). San Francisco. CA, USA: Jossey-Bass.
R Core Team. (2018). R: A language and environment for statistical computing (version 3.5.1) [computer software]. Vienna, Austria: R Foundation for Statistical Computing https://www.r-project.org/.
R Studio Team. (2018). RStudio: Integrated development for R (version 1.1.456) [Computer Software]. Boston: RStudio, Inc. http://www.rstudio.com/.
Raykov, T. (2001). Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints. The British Journal of Mathematical and Statistical Psychology, 54, 315–323. https://doi.org/10.1348/000711001159582.
Reis, D., Xanthopoulou, D., & Tsaousis, I. (2015). Measuring job and academic burnout with the Oldenburg burnout inventory (OLBI): Factorial invariance across samples and countries. Burnout Research, 2(1), 8–18. https://doi.org/10.1016/j.burn.2014.11.001.
Reschly, A. L., & Christenson, S. L. (2012). Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 3–19). Boston, MA, USA: Springer. https://doi.org/10.1007/978-1-4614-2018-7_1
Revelle, W. (2018). Psych: Procedures for psychological, psychometric, and personality research (R package version 1.8.4) [Computer software]. Evanston: Northwestern University. https://cran.r-project.org/package=psych.
Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145–154. https://doi.org/10.1007/s11336-008-9102-z.
Rios, J., & Wells, C. (2014). Validity evidence based on internal structure. Psicothema, 26(1), 108–116. https://doi.org/10.7334/psicothema2013.260.
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223–237. https://doi.org/10.1080/00223891.2015.1089249.
Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–21. https://doi.org/10.18637/jss.v048.i02.
McNamara, A., Arino de la Rubia, E., Zhu, H., Ellis, S., & Quinn, M. (2018). skimr: Compact and flexible summaries of data (R package version 1.0.3) [Computer software]. https://cran.r-project.org/package=skimr
Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514. https://doi.org/10.1007/BF02296192.
Schaufeli, W. B., & Bakker, A. B. (2010). Defining and measuring work engagement: Bringing clarity to the concept. In A. B. Bakker & M. P. Leiter (Eds.), Work engagement: A handbook of essential theory and research (pp. 10–24). New York: Psychology Press.
Schaufeli, W. B., Martinez, I. M., Marques-Pinto, A., Salanova, M., & Bakker, A. B. (2002). Burnout and engagement in university students: A cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464–481. https://doi.org/10.1177/0022022102033005003.
Senior, C., & Howard, C. (2015). Editorial: The state of the art in student engagement. Frontiers in Psychology, 6, 1–2. https://doi.org/10.3389/fpsyg.2015.00355.
Sheppard, S. L. (2011). School engagement: A ‘danse macabre’? Journal of Philosophy of Education, 45(1), 111–123. https://doi.org/10.1111/j.1467-9752.2010.00782.x.
Sinval, J., Marques-Pinto, A., Queirós, C., & Marôco, J. (2018). Work engagement among rescue workers: Psychometric properties of the Portuguese UWES. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.02229.
Sireci, S. G., & Padilla, J.-L. (2014). Validating assessments: Introduction to the special section. Psicothema, 26(1), 97–99. https://doi.org/10.7334/psicothema2013.255.
Streiner, D. L. (2003). Starting at the beginning: An introduction to coefficient alpha and internal consistency. Journal of Personality Assessment, 80(1), 99–103. https://doi.org/10.1207/S15327752JPA8001_18.
van de Schoot, R., Lugtig, P., & Hox, J. J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9(4), 486–492. https://doi.org/10.1080/17405629.2012.686740.
van de Schoot, R., Schmidt, P., & De Beuckelaer, A. (Eds.). (2015). Measurement invariance. Lausanne, Switzerland: Frontiers Media https://doi.org/10.3389/978-2-88919-650-0
Vasalampi, K., Salmela-Aro, K., & Nurmi, J.-E. (2009). Adolescents’ self-concordance, school engagement, and burnout predict their educational trajectories. European Psychologist, 14(4), 332–341. https://doi.org/10.1027/1016-9040.14.4.332.
Wierstra, R. F. A., Kanselaar, G., van der Linden, J. L., Lodewijks, H. G. L. C., & Vermunt, J. D. (2003). The impact of the university context on European students’ learning approaches and learning environment preferences. Higher Education, 45(4), 503–523. https://doi.org/10.1023/A:1023981025796.
Wigfield, A., Guthrie, J. T., Perencevich, K. C., Taboada, A., Klauda, S. L., McRae, A., & Barbosa, P. (2008). Role of reading engagement in mediating effects of reading comprehension instruction on reading outcomes. Psychology in the Schools, 45(5), 432–445. https://doi.org/10.1002/pits.20307.
Wolf-Wendel, L., Ward, K., & Kinzie, J. (2009). A tangled web of terms: The overlap and unique contribution of involvement, engagement, and integration to understanding college student success. Journal of College Student Development, 50(4), 407–428. https://doi.org/10.1353/csd.0.0077.
Wonglorsaichon, B., Wongwanich, S., & Wiratchai, N. (2014). The influence of students school engagement on learning achievement: A structural equation modeling analysis. Procedia - Social and Behavioral Sciences, 116, 1748–1755. https://doi.org/10.1016/j.sbspro.2014.01.467.
Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s α, Revelle’s β, and Mcdonald’s ωH: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70(1), 123–133. https://doi.org/10.1007/s11336-003-0974-7.
Zinbarg, R. E., Revelle, W., & Yovel, I. (2007). Estimating ωh for structures containing two group factors: Perils and prospects. Applied Psychological Measurement, 31(2), 135–157. https://doi.org/10.1177/0146621606291558.
Zumbo, B. D., Gadermann, A. M., & Zeisser, C. (2007). Ordinal versions of coefficients alpha and Theta for likert rating scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29. https://doi.org/10.22237/jmasm/1177992180.
Acknowledgments
Jorge Sinval received funding from the William James Center for Research, Portuguese Science Foundation (FCT UID/PSI/04810/2013).
Leandro S. Almeida and Joana R. Casanova received funding from CIEd – Research Centre on Education, projects UID/CED/1661/2013 and UID/CED/1661/2016, Institute of Education, University of Minho, through national funds of FCT/MCTES-PT.
Joana R. Casanova received funding from the Portuguese Science Foundation (FCT) as a Doctoral Grant, under grant agreement number SFRH/BD/117902/2016.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Ethical Approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Ethics Research Committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Sinval, J., Casanova, J.R., Marôco, J. et al. University student engagement inventory (USEI): Psychometric properties. Curr Psychol 40, 1608–1620 (2021). https://doi.org/10.1007/s12144-018-0082-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12144-018-0082-6