Satisfação com o ensino online em universitários: Análise estrutural de uma escala
DOI:
https://doi.org/10.22235/cp.v17i2.3193Palavras-chave:
satisfação com ensino online, ensino superior, educação a distância, validade, confiabilidadeResumo
O objetivo deste estudo foi analisar a estrutura interna e a confiabilidade da Student Satisfaction Survey (SSS) em estudantes universitários peruanos. Participaram 458 estudantes (mulheres = 69,9 %; Midade = 27,76 anos; DPidade = 4,41 anos). O SSS foi estudado por meio de análise fatorial confirmatória (CFA) e modelação exploratória de equações estruturais (ESEM). Quanto aos resultados, o modelo original de cinco dimensões obteve índices de ajuste favoráveis com ESEM, mas as interações entre as dimensões aluno-professor e aluno-aluno se sobrepõem, por isso, foi analisado um modelo quatro dimensões que apresentou melhor evidência psicométrica. A confiabilidade das pontuações e de construto apresentaram magnitudes aceitáveis. Conclui-se que o SSS possui propriedades psicométricas adequadas.
Downloads
Referências
Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133-148. https://doi.org/10.1080/01587919.2018.1553562
Álvarez, M., Gardyn, N., Iardelevsky, A., & Rebello, G. (2020). Segregación educativa en tiempos de pandemia: Balance de las acciones iniciales durante el aislamiento social por el Covid-19 en Argentina. Revista Internacional de Educación para la Justicia Social, 9(3), 25-43.
Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., Sulijaya, B., & Puspitawati, R. (2020). Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. BMC Medical Education, 20(1), 1-8. https://doi.org/10.1186/s12909-020-02312-0
Asparouhov, T., & Muthén, B. O. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. http://doi.org/10.1080/10705510903008204
Asparouhov, T., Muthen, B., & Morin, A. J. S. (2015). Bayesian structural equation modeling with cross-loadings and residual covariances. Journal of Management, 41(6), 1561-1577. http://doi.org/10.1177/0149206315591075
Ato, M., López-García, J. J., & Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. Anales de Psicología, 29(3), 1038-1059. https://doi.org/10.6018/analesps.29.3.178511
Basith, A., Rosmaiyadi, R., Triani, S. N., & Fitri, F. (2020). Investigation of online learning satisfaction during COVID 19: In relation to academic achievement. Journal of Educational Science and Technology, 6, 265-275. https://doi.org/10.26858/est.v1i1.14803
Baturay, M. H. (2011). Relationships among sense of classroom community, perceived cognitive learning and satisfaction of students at an e-learning course. Interactive Learning Environments, 19(5), 563-575. https://doi.org/10.1080/10494821003644029
Benites, R. (2021). La educación superior universitaria en el Perú post-pandemia. Políticas y Debates públicos. https://repositorio.pucp.edu.pe/index/handle/123456789/176597
Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243-1289. https://doi.org/10.3102/0034654309333844
Best, B., & Conceição, S. C. O. (2017). Transactional distance dialogic interactions and student satisfaction in a multi-institutional blended learning environment. European Journal of Open, Distance and e-Learning, 20(1), 138-152.
Brown, T. A. (2015). Confirmatory factor analysis for applied research (2a ed.). Guilford Press.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. En K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 445-455). Sage.
Chen, W. S., & Tat Yao, A. Y. (2016). An empirical evaluation of critical factors influencing learner satisfaction in blended learning: a pilot study. Universal Journal of Educational Research, 4(7), 1667-1671. https://doi.org/10.13189/ujer.2016.040719
Chung, E., Subramaniam, G., & Dass, L. C. (2020). Online learning readiness among university students in Malaysia amidst COVID19. Asian Journal of University Education, 16(2), 46-58.
Díaz, V. M., Urbano, E. R., & Berea, G. M. (2013). Ventajas e inconvenientes de la formación online. Revista Digital de Investigación en Docencia Universitaria, 7(1), 33-43. https://doi.org/10.19083/ridu.7.185
DiStefano, C., Liu, J., Jiang, N., & Shi, D. (2018). Examination of the weighted root mean square residual: Evidence for trustworthiness? Structural Equation Modeling: A Multidisciplinary Journal, 25(3), 453-466. https://doi.org/10.1080/10705511.2017.1390394
Dominguez-Lara, S. (2018a). Propuesta de puntos de corte para cargas factoriales: una perspectiva de confiabilidad de constructo. Enfermería Clínica, 28(6), 401-402. https://doi.org/10.1016/j.enfcli.2018.06.002
Dominguez-Lara, S. (2018b). Reporte de las diferencias confiables en el perfil del ACE-III. Neurología, 33(2), 138-139. http://doi.org/10.1016/j.nrl.2016.02.022
Dominguez-Lara, S., Gravini-Donado, M., Moreta-Herrera, R., Quistgaard-Alvarez, A., Barboza-Zelada, L. A., & De Taboada, L. (2022). Propiedades psicométricas del Student Adaptation to College Questionnaire - Educación Remota en estudiantes universitarios de primer año durante la pandemia. Campus Virtuales, 11(1), 81-93. https://doi.org/10.54988/cv.2022.1.965
Donnellan, M. B., & Rakhshani, A. (2023). How does the number of response options impact the psychometric properties of the Rosenberg Self-Esteem Scale? Assessment, 30(6), 1737-1749. https://doi.org/10.1177/10731911221119532
Ekwunife-Orakwue, K. C., & Teng, T. L. (2014). The impact of transactional distance dialogic interactions on student learning outcomes in online and blended environments. Computers & Education, 78, 414-427. https://doi.org/10.1016/j.compedu.2014.06.011
Eryilmaz, M. (2015). The effectiveness of blended learning environments. Contemporary Issues in Education Research, 8(4), 251-256. https://doi.org/10.19030/cier.v8i4.9433
Etikan, I. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1. https://doi.org/10.11648/j.ajtas.20160501.11
Gignac, G. E., Bates, T. C., & Jang, K. (2007). Implications relevant to CFA model misfit, reliability, and the Five Factor Model as measured by the NEO-FFI. Personality and Individual Differences, 43(5), 1051-1062. https://doi.org/10.1016/j.paid.2007.02.024
Gravetter, F., & Wallnau, L. (2014). Essentials of Statistics for the Behavioral Sciences. Wadsworth.
Gravini-Donado, M. L., Mercado-Peñaloza, M., & Dominguez-Lara, S. (2021). College Adaptation Among Colombian Freshmen Students: Internal Structure of the Student Adaptation to College Questionnaire (SACQ). Journal of New Approaches in Educational Research, 10(2), 251-263. http://doi.org/ 10.7821/naer.2021.7.657
Hanna, D. E., Glowacki-Dudka, M., & Runlee, S. (2000). 147 practical tips for teaching online groups. Atwood.
Hanson, J., Bangert, A., & Ruff, W. (2016). A validation study of the what’s my school mindset? Survey. Journal of Educational Issues, 2(2), 244-266.
Hunsley, J., & Marsh, E. J. (2008). Developing criteria for evidence-based assessment: An introduction to assessment that work. En J. Hunsley & E. J. Marsh (Eds.), A guide to assessments that work (pp. 3-14). Oxford University Press.
Jan, S. K. (2015). The relationships between academic self-efficacy, computer self-efficacy, prior experience, and satisfaction with online learning. American Journal of Distance Education, 29(1), 30-40. https://doi.org/10.1080/08923647.2015.994366
Kang, D., & Park, M. J. (2022). Interaction and online courses for satisfactory university learning during the COVID-19 pandemic. The International Journal of Management Education, 20(3), 100678. https://doi.org/10.1016/j.ijme.2022.100678
Khan, J., & Iqbal, M. J. (2016). Relationship between student satisfaction and academic achievement in distance education: a case study of AIOU Islamabad. FWU Journal of Social Sciences, 10(2), 137-145.
Kong, S. C., Looi, C. K., Chan, T. W., & Huang, R. (2017). Teacher development in Singapore, Hong Kong, Taiwan, and Beijing for e-learning in school education. Journal of Computers in Education, 4(1), 5-25. https://doi.org/10.1007/s40692-016-0062-5
Kuo, Y. C. (2014). Accelerated online learning: Perceptions of interaction and learning outcomes among African American students. American Journal of Distance Education, 28(4), 241–252. https://doi.org/10.1080/08923647.2014.959334
Kuo, Y. C., Belland, B. R., Schroder, K. E., & Walker, A. E. (2014). K-12 teachers’ perceptions of and their satisfaction with interaction type in blended learning environments. Distance Education, 35(3), 360-381. https://doi.org/10.1080/01587919.2015.955265
Kuo, Y. C., Walker, A. E., Belland, B. R., & Schroder, K. E. E. (2013). A predictive study of student satisfaction in online education programs. International Review of Research in Open and Distributed Learning, 14(1), 16-39. https://doi.org/10.19173/irrodl.v14i1.1338
Lara, L., Monje, M. F., Fuster-Villaseca, J., & Dominguez-Lara, S. (2021). Adaptación y validación del Big Five Inventory para estudiantes universitarios chilenos. Revista Mexicana de Psicología, 38(2), 83-94.
Larson, R. B. (2018). Controlling social desirability bias. International Journal of Market Research, 61(5), 534-547. http://doi.org/10.1177/1470785318805305
Li, C. (2016a). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavioral Research Methods, 48, 936-949. https://doi.org/10.3758/s13428-015-0619-7
Li, C. (2016b). The performance of ML, DWLS, and ULS estimation with robust corrections in structural equation models with ordinal variables. Psychological Methods, 21(3), 369-387. https://doi.org/10.1037/met0000093
Lloret-Segura, S., Ferreres-Traver, A., Hernández-Baeza, A., & Tomás-Marco, I. (2014). El análisis factorial exploratorio de los ítems: una guía práctica, revisada y actualizada. Anales de psicología, 30(3), 1151-1169. http://doi.org/10.6018/analesps.30.3.199361
Luo, N., Zhang, M., & Qi, D. (2017). Effects of different interactions on students’ sense of community in e-learning environment. Computers & Education, 115, 153-160. https://doi.org/10.1016/j.compedu.2017.08.006
Magadán-Díaz, M., & Rivas-García, J. I. (2022). Gamificación del aula en la enseñanza superior online: el uso de Kahoot. Campus Virtuales, 11(1), 137-152. https://doi.org/10.54988/cv.2022.1.978
Marsh, H. W., Morin, A. J. S., Parker, P. D., & Kaur, G. (2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual Review of Clinical Psychology, 10(1), 85-110. http://doi.org/10.1146/annurev-clinpsy-032813-153700
Martín-Rodríguez, Ó., Fernández-Molina, J. C., Montero-Alonso, M. Á., & González-Gómez, F. (2015). The main components of satisfaction with e-learning. Technology, Pedagogy and Education, 24(2), 267-277. https://doi.org/10.1080/1475939X.2014.888370
Mbwesa, J. K. (2014). Transactional distance as a predictor of perceived learner satisfaction in distance learning courses: A case study of bachelor of education arts program, University of Nairobi, Kenya. Journal of Education and Training Studies, 2(2), 176-188. https://doi.org/10.11114/jets.v2i2.291
McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. https://doi.org10.1037/1082-989X.7.1.64
Mohamed, E., Ghaleb, A., & Abokresha, S. (2021). Satisfaction with online learning among Sohag University students. Journal of High Institute of Public Health, 51(2), 84-89. https://doi.org/10.21608/jhiph.2021.193888
Moore, M. (1993). Three types of interaction. En K. Harry, M. John & D. Keegan (Eds.), Distance education theory (pp. 19-24). Routledge.
Moore, M. G. (1997). Theory of transactional distance. En D. Keegan (Ed.), Theoretical Principles of Distance Education (pp. 22-38). Routledge.
Moore, M. G. (2007). Theory of transactional distance. En M. G. Moore (Ed.). Handbook of distance education (pp. 89-101). Lawrence Erlbaum.
Moore, M., & Kearsley, G. (2005). Distance education: A system view. Thomson-Wadsworth.
Moreta-Herrera, R., Vaca-Quintana, D., Quistgaard-Álvarez, A., Merlyn-Sacoto, M.-F., & Dominguez-Lara, S. (2022). Análisis psicométrico de la Escala de Cansancio Emocional en estudiantes universitarios ecuatorianos durante el brote de COVID-19. Ciencias Psicológicas, 16(1), e-2755. https://doi.org/10.22235/cp.v16i1.2755
Muñiz, J. (2003). Teoría clásica de los tests. Pirámide.
Muñiz, J., Elosua, P., & Hambleton, R. K. (2013). Directrices para la traducción y adaptación de los test: segunda edición. Psicothema, 25(2), 151-157. https://doi.org/10.7334/psicothema2013.24
Muthén, L. K., & Muthén, B.O. (1998-2015). Mplus User’s Guide. Muthén & Muthén.
Nortvig, A. M., Petersen, A. K., & Balle, S. H. (2018). A Literature review of the factors influencing e‑learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electronic Journal of E-learning, 16(1), 46-55.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decision. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.1177/002224378001700405
Onditi, E. O., & Wechuli, T. W. (2017). Service quality and student satisfaction in higher education institutions: A review of literature. International Journal of Scientific and Research Publications, 7(7), 328-335.
Palloff, R. M., & Pratt, K. (2001). Lessons from the cyberspace classroom. The realities of online teaching. Jossey-Bass.
Palmer, S. R., & Holt, D. M. (2009). Examining student satisfaction with wholly online learning. Journal of Computer Assisted Learning, 25(2), 101-113. https://doi.org/10.1111/j.1365-2729.2008.00294.x
Pérez-Gil, J. A., Chacón, S. & Moreno, R. (2000). Validez de constructo: el uso de análisis factorial exploratorio-confirmatorio para obtener evidencias de validez. Psicothema, 12, 442-446.
Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16(1), 1-26. https://doi.org/10.1186/s41239-019-0136-3
Ponterotto, J., & Charter, R. (2009). Statistical extensions of Ponterotto and Ruckdeschel’s (2007) reliability matrix for estimating the adequacy of internal consistency coefficients. Perceptual and Motor Skills, 108(3), 878-886. https://doi.org/10.2466/PMS.108.3.878-886
Ramo, N. L., Lin, M. A., Hald, E. S., & Huang-Saad, A. (2021). Synchronous vs. asynchronous vs. blended remote delivery of introduction to biomechanics course. Biomedical Engineering Education, 1, 61-66. https://doi.org/10.1007/s43683-020-00009-w
Rubia, J. M. (2019). Revisión de los criterios para validez convergente estimada a través de la VarianRubiaza Media Extraída. Psychologia, 13(2), 25-41. https://doi.org/10.21500/19002386.4119
Sánchez-González, M., & Castro-Higueras, A. (2022). Mentorías para profesorado universitario ante la Covid-19: evaluación de un caso. Campus Virtuales, 11(1), 181-200. https://doi.org/10.54988/cv.2022.1.1000
Shackelford, J. L., & Maxwell, M. (2012). Sense of community in graduate online education: Contribution of learner to learner interaction. The International Review of Research in Open and Distributed Learning, 13(4), 228-249. https://doi.org/10.19173/irrodl.v13i4.1339
Strachota, E. (2003). Student satisfaction in online course: An analysis of the impact of learner-content, learner-instructor, learner-learner and learner-technology interaction [Disertación doctoral]. University of Wisconsin- Milwaukee.
Strachota, E. (2006). The use of survey research to measure student satisfaction in online courses. University of Missouri-St. Louis.
Teo, T. (2010). A structural equation modelling of factors influencing student teachers’ satisfaction with e-learning. British Journal of Educational Technology, 41(6), 150-152. https://doi.org/10.1111/j.1467-8535.2010.01110.x
Thurmond, V., & Wambach, K. (2004). Understanding interactions in distance education: A review of the literature. International Journal of Instructional Technology and Distance Learning, 1(1), 9-26.
Torrado, M., & Blanca, M. J. (2022). Assessing satisfaction with online courses: Spanish version of the Learner Satisfaction Survey. Frontiers in Psychology, 13, 875929. https://doi.org/10.3389/fpsyg.2022.875929
Vásquez-Pajuelo, L. (2019). Aprendizaje online: satisfacción de los universitarios con experiencia laboral. Review of Global Management, 5(2), 28-43. https://doi.org/10.19083/rgm.v5i2.1234
Vergara-Morales, J., Rodríguez-Vera, M., & Del Valle, M. (2022). Evaluación de las propiedades psicométricas del Cuestionario de Autorregulación Académica (SRQ-A) en estudiantes universitarios chilenos. Ciencias Psicológicas, 16(2), e-2837. https://doi.org/10.22235/cp.v16i2.2837
Watermeyer, R., Crick, T., Knight, C., & Goodall, J. (2020). COVID-19 and digital disruption in UK universities: afflictions and affordances of emergency online migration. Higher Education, 81(3), 623-641. https://doi.org/10.1007/s10734-020-00561-y
Waters, S., & Russell, W. (2016). Virtually ready? Pre-service teachers’ perceptions of a virtual internship experience. Research in Social Sciences and Technology, 1(1), 1-23.
Wei, H. C., Peng, H., & Chou, C. (2015). Can more interactivity improve learning achievement in an online course? Effects of college students’ perception and actual use of a course-management system on their learning achievement. Computers & Education, 83, 10-21. https://doi.org/10.1016/j.compedu.2014.12.013
West, S. G., Taylor, A. B., & Wu, W. (2012). Model fit and model selection in structural equation modeling. En R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling (pp. 209-231). Guilford.
Ye, J-H., Lee, Y-S., & He, Z. (2022). The relationship among expectancy belief, course satisfaction, learning effectiveness, and continuance intention in online courses of vocational-technical teachers college students. Frontiers in Psychology, 13, 904319. https://doi.org/10.3389/fpsyg.2022.904319
Yılmaz, A., & Karataş, S. (2017). Development and validation of perceptions of online interaction scale. Interactive Learning Environments, 26(3), 337-354. http://doi.org/10.1080/10494820.2017.1333009
Publicado
Como Citar
Edição
Secção
Licença
Direitos de Autor (c) 2023 Universidad Católica del Uruguay
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição 4.0.
