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Figueredo, J.M.; Molero-Jurado, M.D.M.; Vico-Sánchez, M.F.; Alonso-Delgado, S.H.; Rosales-Jiménez, J.J.; Torres-Rojas, M.C.; Zorrilla-Lozano, A.; Segura-Morillas, M.J.; Pérez-Fuentes, M.D.C. D-VET Education and Academic Engagement and Academic Burnout. Encyclopedia. Available online: https://encyclopedia.pub/entry/51290 (accessed on 05 July 2024).
Figueredo JM, Molero-Jurado MDM, Vico-Sánchez MF, Alonso-Delgado SH, Rosales-Jiménez JJ, Torres-Rojas MC, et al. D-VET Education and Academic Engagement and Academic Burnout. Encyclopedia. Available at: https://encyclopedia.pub/entry/51290. Accessed July 05, 2024.
Figueredo, José María, María Del Mar Molero-Jurado, María Francisca Vico-Sánchez, Salvador Hilario Alonso-Delgado, José Javier Rosales-Jiménez, María Concepción Torres-Rojas, Amparo Zorrilla-Lozano, María José Segura-Morillas, María Del Carmen Pérez-Fuentes. "D-VET Education and Academic Engagement and Academic Burnout" Encyclopedia, https://encyclopedia.pub/entry/51290 (accessed July 05, 2024).
Figueredo, J.M., Molero-Jurado, M.D.M., Vico-Sánchez, M.F., Alonso-Delgado, S.H., Rosales-Jiménez, J.J., Torres-Rojas, M.C., Zorrilla-Lozano, A., Segura-Morillas, M.J., & Pérez-Fuentes, M.D.C. (2023, November 08). D-VET Education and Academic Engagement and Academic Burnout. In Encyclopedia. https://encyclopedia.pub/entry/51290
Figueredo, José María, et al. "D-VET Education and Academic Engagement and Academic Burnout." Encyclopedia. Web. 08 November, 2023.
D-VET Education and Academic Engagement and Academic Burnout
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This entry is adapted from the peer-reviewed paper 10.3390/ejihpe13110174

In Spain, vocational education and training (VET) is a type of non-university higher education leading to the award of Higher Vocational Training Technician qualifications, with a MECES 1 level (Spanish Framework of Qualifications for Higher Education), equivalent in the context of the European Union to an EQF 5 level (European Qualification Framework).

distance learning vocational training quality of education academic satisfaction

1. The Quality of Distance Vocational Education and Training Education and Training

So far, there is no unanimity on how to assess the quality of e-learning in higher education [1]. Moreover, all the proposed models are based on or have been designed for the evaluation of e-learning at the university level. Distance vocational education and training (D-VET) is substantially different from e-learning in university education, and the application of an instrument designed based on a model generated for the university environment is not appropriate unless it is adapted to the specific characteristics of D-VET. For example, in Spain, and specifically in Andalusia, the management of D-VET is centralised by the Department of Educational Development and Vocational Training of the Andalusian Regional Government so that all the centres that offer these courses use the same LMS (learning management system) based on the Moodle platform, and the assessment of students is strongly conditioned by the regulations of the regional education administration so that teachers have little autonomy in configuring the LMS for the presentation of contents, as well as methods for assessing and grading the students. In contrast, universities enjoy greater autonomy in these issues. Although both high-level VET and university education operate on higher education, the underlying concepts are clearly different; VET revolves around the students acquiring practical skills and perhaps less theoretical knowledge [2]; hence, the focus of these teachings is different, and the entry requirements in these studies are different, amongst other aspects.
From certain theoretical perspectives, the quality of the educational service has been taken as a reference to assess the degree of academic satisfaction in students [3], including aspects such as the attitude and behaviour of the teacher or the usability of the LMS or virtual environment; in fact, satisfaction is a construct necessarily related to the pedagogical practices and infrastructure of the institutions, infrastructure that in the case of distance learning is basically reflected in the LMS or virtual environment.
The precedents of academic satisfaction are as follows: the usability of the LMS or virtual environment and the attitude or behaviour of the teacher.
From a perspective focused on students’ psychological well-being, satisfaction in the academic environment can be defined as the psychological well-being and enjoyment perceived by students when they carry out experiences linked to their role as students [4] (Medrano and Pérez, 2010). The importance of students’ academic satisfaction lies in their ability to influence academic performance [5][6] or student retention or dropout [7], among other aspects.
On the other hand, the usability of a system can be understood as a quality attribute that evaluates the ease of use of user interfaces [8], with one of its components being the degree of user satisfaction, which is measured in terms of the degree of pleasantness of the design of the virtual environment. Studies on the usability of the virtual learning environment at university levels are frequent [9][10][11][12][13][14]. However, in D-VET, and specifically in Spain, only two studies have been documented, both carried out in the Balearic Islands, with the aim of assessing perceived usability, either by D-VET teachers [15] or by students [16]. D-VET in Andalusia uses a LMS based on the Moodle platform. The Moodle platform is the most-used LMS for remote D-Vet in Spain [17].

2. Mediators of Academic Satisfaction: Academic Engagement and Academic Burnout

Both the availability of teaching staff and the quality of the teacher–student interaction, encouraging student participation, as well as the design of the virtual environment adapted to their abilities, contribute to improving students’ academic engagement. Likewise, systematic reviews by Nortvig et al. [18], Paton et al. [2], and Bagriacik-Yilmaz and Banyard [19] show that both the presence of a high teacher in the online environment and the quality of course design are associated with higher levels of academic engagement and academic satisfaction. Academic engagement is understood as the student’s sense of well-being in the face of a given academic challenge [20]. In turn, high levels of academic engagement are related to high levels of student academic satisfaction in e-learning [18][21][22].
On the other hand, if researchers understand academic burnout as an antagonist of academic engagement, it is logical to think that it has inverse effects on academic satisfaction. In fact, some research has highlighted the negative relationship between burnout and academic satisfaction [5][23], although this relationship has been less studied than the relationship between academic engagement and satisfaction. Academic burnout is understood as a persistent and detrimental state of mind toward studies consisting of emotional exhaustion, feelings of detachment from academic tasks, and perceptions of low ability or efficacy in relation to academic studies [24]. Likewise, the poor design of the virtual environment as well as a limited teacher–student interaction caused by low teacher availability, could be a trigger for academic burnout when these circumstances are perceived as stressful, and the students perceive themselves as unable to cope with them. In fact, a positive relationship between study obstacles and academic burnout has been observed [5][24].

3. Predictors of Academic Engagement and Academic Burnout: Obstacles and Challenges Faced by Students in Distance Vocational Education and Training

Students who perceive greater obstacles in relation to their studies experience more burnout and less academic engagement, while higher perceived study facilitators are related to lower levels of burnout and higher levels of academic engagement [5]. A systematic review by Kara et al. [25] identified the challenges and obstacles faced by adult learners in distance learning as related to the management of family life, education, and work, to the learning itself (lack of prior knowledge, lack of concentration for study, etc.), to technical difficulties (insufficient computer skills), to the behaviour of the teaching staff or to the materials and difficulty of the course. It is logical to think that the perception of these circumstances as difficult to cope with determines the appearance of burnout syndrome. In fact, from the perspective of the theory of job demands and resources [26], job demands and resources have direct and indirect effects on work stress and motivation, and this assertion is extensible to the academic environment [27][28]. Thus, students who perceive greater demands (obstacles) and fewer personal resources to cope with them develop higher levels of burnout [28]. Given that academic demands are generally the main predictors of academic burnout [28], the obstacles and challenges faced by distance learners in the online mode could precede the occurrence of burnout, i.e., they precede burnout and, therefore, these challenges (which are ultimately personal circumstances) could be considered as a predictor variable of burnout [29].

References

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  2. Paton, R.M.; Fluck, A.E.; Scanlan, J.D. Engagement and retention in VET MOOCs and online courses: A systematic review of literature from 2013 to 2017. Comput. Educ. 2018, 125, 191–201.
  3. Vergara-Morales, J.; Del Valle, M.; Diaz, A.; Perez, M.V. Adaptacion de la escala de satisfaccionacademica en estudiantes universitarios chilenos. Psicol. Educ. 2018, 24, 99–106.
  4. Medrano, L.A.; Pérez, E. Adaptación de la escala de satisfacción académica a la población universitaria de Córdoba. Summa Psicol. 2010, 7, 5–14.
  5. Martínez-Martínez, I.M.; Bresó-Esteve, E.; Llorens-Gumbau, S.; Grau-Gumbau, R. Bienestar Psicológico en estudiantes Universitarios: Facilitadores y Obstaculizadores del desempeño académico. Ann. Psychol. 2005, 21, 170–180. Available online: https://revistas.um.es/analesps/article/view/27261 (accessed on 30 October 2023).
  6. Tejedor, F.J.T. Poder explicativo de algunos determinantes del rendimiento en los estudios universitarios. Rev. Esp. Pedagog. 2003, 61, 5–32. Available online: http://www.jstor.org/stable/23764435 (accessed on 27 September 2023).
  7. Salimon, M.G.; Sanuri, S.M.M.; Aliyu, O.A.; Perumal, S.; Yusr, M.M. E-learning satisfaction and retention: A concurrent perspective of cognitive absorption, perceived social presence and technology acceptance model. J. Syst. Inf. Technol. 2021, 23, 109–129.
  8. Nielsen, J. Usabilidad 101: Introducción a La Usabilidad. Available online: https://www.nngroup.com/articles/usability-101-introduction-to-usability/ (accessed on 2 November 2022).
  9. Fernández-Coca, A.; Lirola, F.; Ordinas, C. El rediseño total del aula digital bajo una estrategia en 360°, a partir de la escucha al usuario. In Proceedings I Congreso Internacional, Campus Digitales en Educación Superior; Universidad de Extremadura, Servicio de Publicaciones: Cáceres, Spain, 2018; pp. 45–48. Available online: https://dehesa.unex.es:8443/bitstream/10662/8659/1/978-84-09-07196-8.pdf (accessed on 27 September 2023).
  10. Katsanos, C.; Tselios, N.; Xenos, M. Perceived usability evaluation of learning management systems: A first step towards standardization of the System Usability Scale in Greek. In Proceedings of the 16th Panhellenic Conference on Informatics, Piraeus, Greece, 5–7 October 2012; pp. 302–307.
  11. Sabater, F.R.L.; Pérez, A. La usabilidad percibida y el grado de satisfacción en la plataforma moodle de la UIB a partir del cuestionario SUS. In Proceedings of the XVIII Congreso Internacional EDUTEC” Educación y Tecnología Desde Una Visión Transformadora, Riobamba, Ecuador, 17–20 November 2015.
  12. Melton, J. The LMS Moodle: A usability evaluation. Lang. Issues 2006, 11, 1.
  13. Orfanou, K.; Tselios, N.; Katsanos, C. Perceived usability evaluation of learning management systems: Empirical evaluation of the System Usability Scale. Int. Rev. Res. Open Dis. 2015, 16, 227–246.
  14. Revythi, A.; Tselios, N. Extension of technology acceptance model by using system usability scale to assess behavioral intention to use e-learning. Educ. Inf. Technol. 2019, 24, 2341–2355.
  15. Lirola-Sabater, F.; Pérez-Garcias, A. La usabilidad percibida por los docentes de la Formación Profesional a distancia en las Islas Baleares. Pixel-Bit 2020, 59, 183–200.
  16. Lirola-Sabater, F.; Pérez-Garcias, A. La evaluación del entorno virtual de la Formación Profesional a distancia, en Baleares, a partir del cuestionario PSSUQ por parte de los alumnos. In EDUcación y TECnología: Propuestas Desde la Investigación y la Innovación Educativa; Serrano-Inzunza, M.J., Campos-Pinto, V.C., Pantoja-Mejías, V., Silva_Quiroz, J.E., Eds.; Universidad de Santiago de Chile (USACH): Santiago de Chile, Chile, 2017; pp. 441–444.
  17. Nava-Seneque, M.S. Revisión sistemática de la literatura del uso de Moodle en Formación Profesional en España. DiM-UAB 2023, 41. Available online: https://raco.cat/index.php/DIM/article/view/417204 (accessed on 27 September 2023).
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  19. Bagriacik Yilmaz, A.; Banyard, P. Engagement in distance education settings: A trend analysis. Turk. Online J. Distance Educ. 2020, 21, 101–120.
  20. Parra, P.; Pérez, C. Propiedades psicométricas de la escala de compromiso académico, UWES-S (versión abreviada), en estudiantes de psicología. Rev. Educ. Cienc. Salud. 2010, 7, 128–133.
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  25. Kara, M.; Erdoğdu, F.; Kokoç, M.; Cagiltay, K. Challenges faced by adult learners in online distance education: A literature review. Open Prax. 2019, 11, 5.
  26. Bakker, A.B.; Demerouti, E. La teoría de las demandas y los recursos laborales. Rev. Psicol. Trab. Organ. 2013, 29, 107–115.
  27. Merhi, R. Factores Psicológicos Predictores del Bienestar y el Éxito Académico en Estudiantes Universitarios. Un Abordaje Desde la Teoría de Demandas y Recursos . Ph.D. Thesis, Universidad Nacional de Educación a Distancia, Madrid, Spain, 2021. Available online: https://www.researchgate.net/publication/352978264_Factores_psicologicos_predictores_del_bienestar_y_el_exito_academico_en_estudiantes_universitarios_Un_abordaje_desde_la_teoria_de_demandas_y_recursos_Psychological_factors_predictors_of_well-being_and?channel=doi&linkId=60e19f1092851ca944a786f9&showFulltext=true (accessed on 27 September 2023).
  28. Merhi, R.; Sánchez-Elvira-Paniagua, A.; Palací, F.J. The Role ofPsychologicalStrengths, CopingStrategies and Well-Being in thePredictionofAcademicEngagement and Burnout in First-YearUniversityStudents . Acción Psicol. 2018, 15, 51–68.
  29. Kenny, D.A. Moderator Variables. Available online: https://davidakenny.net/cm/moderation.htm (accessed on 15 September 2018).
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Subjects: Psychology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
José María Figueredo
,
María del Mar Molero-Jurado
,
María Francisca Vico-Sánchez
,
Salvador Hilario Alonso-Delgado
,
José Javier Rosales-Jiménez
,
María Concepción Torres-Rojas
,
Amparo Zorrilla-Lozano
,
María José Segura-Morillas
,
María del Carmen Pérez-Fuentes
View Times: 226
Revisions: 2 times (View History)
Update Date: 09 Nov 2023
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