University Culture: A quali-quantitative study on the emotional representations of online learning by psychology university students

Journal title PSICOLOGIA DELLA SALUTE
Author/s Lorenzo Colaboni, Michela Di Trani, Silvia Monaco
Publishing Year 2024 Issue 2024/1
Language English Pages 21 P. 25-45 File size 287 KB
DOI 10.3280/PDS2024-001002
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The pandemic of covid-19 has led to the conversion from face-to-face to online learning in almost every university in the world. Online learning was perceived by stu-dents as an opportunity and an impediment to the learning process and an obstacle for social contact. The main aim of this research was to explore the representations of dis-tance learning by university students. We collected 127 interviews from university stu-dents and used the paradigm of Emotional Text Mining (EMT) for their analysis. Three factors (Learning Process, University Life, Blended learning) and four clusters (Being in a Relationship, Online learning, Missed Rituality, Process of Adapting) were identified. The factors highlight an unconscious defence mechanism which “separates” the reality of online learning (without relationships) from the reality of the face-to-face learning (with relationships). The clusters show how university students represent online learning as useful at a practical level, but as an obstacle to social contact and a sense of belonging to the university culture. In addition, the interpretation of the clusters reveals an imma-ture process of adaptation of students to the post-pandemic reality. All these findings highlight face-to-face learning as a place for interaction and social sharing and necessary to feel integrated in university culture.

Keywords: online learning, emotional text mining, university culture, interviews, COVID-19

  1. Avallone F. (2004). La convivenza nelle organizzazioni. Delega, benessere, valutazione. Guerini, Milano.
  2. Greco F. and Polli A. (2020). Emotional Text Mining: Customer profiling in brand management. International Journal of Information Management, 51 (1): 101934.
  3. Armstrong-Mensah E., Ramsey-White K., Yankey B. and Self-Brown S. (2020). COVID-19 and Distance Learning: Effects on Georgia State University School of Public Health Students. Frontiers in Public Health, 8 (1): 576227.
  4. Ashraf M.A., Yang M., Zhang Y., Denden M., Tlili A., Liu J., Huang R. and Burgos D. (2021). A Systematic Review of Systematic Reviews on Blended Learning: Trends, Gaps and Future Directions. Psychology Research and Behavior Management, 14 (1): 1525–1541. DOI: 10.2147/PRBM.S33174
  5. Besser A., Flett G.L. and Zeigler-Hill V. (2022). Adaptability to a sudden transition to online learning during the COVID-19 pandemic: Understanding the challenges for students. Scholarship of Teaching and Learning in Psychology, 8 (2): 85–105.
  6. Bion W.R. (1961). Experiences in Groups. Tavistock.
  7. Blanco I.M. (1981). L’inconscio come insiemi infiniti. Einaudi Editore, Torino.
  8. Bloomfield J.G., While A.E. and Roberts J.D. (2008). Using computer assisted learning for clinical skills education in nursing: Integrative review. Journal of Advanced Nursing, 63 (3): 222–235.
  9. Bolasco S. (1999). Analisi multidimensionale dei dati (Vol. 1). Rome, Italy: Carocci.
  10. Broderick M. (2020). Representation in 21st Century Online Higher Education: How the Online Learning Culture Serves Diverse Students. IGI Global Editor.
  11. Brooks S.K., Webster R.K., Smith L.E., Woodland L., Wessely S., Greenber N. and Rubin G.J. (2020). The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. The Lancet, 395 (1): 912–920. DOI: 10.1016/S0140-6736(20)30460-
  12. Cao W., Fang Z., Hou G., Han M., Xu X., Dong J. and Zheng J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287 (1): 112934.
  13. Capogna S., De Angelis M.C. and Greco F. (2023a). The symbolic-cultural dimension of the digital transformation in HE. A comparative analysis. In ECOLHE International Conference Proceedings, https://pasithee.library.upatras.gr/ecolhe
  14. Capogna S., De Angelis M.C., Greco F. and Musella F. (2023b). The European students’ perspective of digital teaching and learning in Higher Education. In ECOLHE International Conference Proceedings, https://pasithee.library.upatras.gr/ecolhe
  15. Capogna S. and Greco F. (2022). L’università di fronte alla sfida digitale. L’esperienza italiana nella costruzione dello spazio europeo della formazione. Quaderni di Comunità: persone, educazione e welfare nella società 5.0, 2 (1): 89-125.
  16. Carli R. (1990). Il processo di collusione nelle rappresentazioni sociali. Rivista di Psicologia clinica, 4 (3): 282-296.
  17. Cook D.A., Levinson A.J., Garside S., Dupras D.M., Erwin P.J. and Montori V.M. (2010). Instructional Design Variations in Internet-Based Learning for Health Professions Education: A Systematic Review and Meta-Analysis. Academic Medicine, 85 (5): 909–922.
  18. Corbetta P. (2014). Metodologia e tecniche della ricerca sociale (pp. 283-316). Bologna: il Mulino.
  19. Costado Dios M.T. and Piñero Charlo J.C. (2021). Face-to-Face vs. E-Learning Models in the COVID-19 Era: Survey Research in a Spanish University. Education Sciences, 11 (6): 293.
  20. Fornari F. (1976). Simbolo e codice: Dal processo psicoanalitico all’analisi istituzionale, 148-165. Feltrinelli Editore.
  21. Fornari F. (1979). I fondamenti di una teoria psicoanalitica del linguaggio. Torino: Bollati Boringhieri.
  22. Fornari F. (1981). Simbolo e codice: dal processo psicoanalitico all’analisi istituzionale. Milano: Feltrinelli.
  23. Giuliano L. and La Rocca G. (2012). L’analisi automatica e semi-automatica dei dati testuali-II: II. Strategia di ricerca e applicazioni. LED Edizioni Universitarie.
  24. Gore J., Fray L., Miller A., Harris J. and Taggart W. (2021). The impact of COVID-19 on student learning in New South Wales primary schools: An empirical study. The Australian Educational Researcher, 48 (4): 605–637.
  25. Greco F. (2016). Integrare la disabilità: Una metodologia interdisciplinare per leggere il cambiamento culturale. Franco Angeli, 1-143.
  26. Hamilton L., Boman J., Rubin H. and Barleen S. (2019). Examining the impact of a university mentorship program on student outcomes. International Journal of Mentoring and Coaching in Education, 8, 19. DOI: 10.1108/IJMCE-02-2018-0013
  27. Henderson M., Selwyn N. and Aston R. (2017). What works and why? Student perceptions of ‘useful’ digital technology in university teaching and learning. Studies in Higher Education, 42 (8): 1567–1579. DOI: 10.1080/03075079.2015.100794
  28. Jaques E. (1955). New Directions in Psychoanalysis. London: Tavistock Pubblications.
  29. Kaparounaki C.K., Patsali M.E., Mousa D.-P.V., Papadopoulou E.V.K., Papadopoulou K.K.K. and Fountoulakis K.N. (2020). University students’ mental health amidst the COVID-19 quarantine in Greece. Psychiatry Research, 290 (1): 113111.
  30. Keane T., Linden T., Hernandez-Martinez P. and Molnar A. (2022). University Students’ Experiences and Reflections of Technology in Their Transition to Online Learning during the Global Pandemic. Education Sciences, 12 (7): 453.
  31. Lancia F. (2020). User’s Manual: Tools for text analysis. T-Lab version Plus, 2020.
  32. Lancia F. (2012). The Logic of the T-LAB Tools Explained. Retrieved [26/10/2023] from http://www.tlab.it/en/toolsexplained.php
  33. Lebart L. and Salem A. (1994). Statistique textuelles. Paris: Dunod.
  34. Lowenthal P. and Dennen V. (2020). Social Presence and Identity in Online Learning. London: Routledge.
  35. McCutcheon K., Lohan M., Traynor M. and Martin D. (2015). A systematic review evaluating the impact of online or blended learning vs. Face-to-face learning of clinical skills in undergraduate nurse education. Journal of Advanced Nursing, 71 (2): 255–270.
  36. McCutcheon K., O’Halloran P. and Lohan M. (2018). Online learning versus blended learning of clinical supervisee skills with pre-registration nursing students: A randomised controlled trial. International Journal of Nursing Studies, 82 (1): 30–39.
  37. Odriozola-González P., Planchuelo-Gómez Á., Irurtia M.J. and de Luis-García R. (2020). Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university. Psychiatry Research, 290: 113108.
  38. Peimani N. and Kamalipour H. (2021). Online Education in the Post COVID-19 Era: Students’ Perception and Learning Experience. Education Sciences, 11 (10): 633.
  39. Perry T., Findon M. and Cordingley P. (2021). Remote and Blended Teacher Education: A Rapid Review. Education Sciences, 11 (8): 453.
  40. Rowe M., Frantz J. and Bozalek V. (2012). The role of blended learning in the clinical education of healthcare students: A systematic review. Medical Teacher, 34 (4): e216–e221. DOI: 10.3109/0142159X.2012.64283
  41. Santomauro D.F., Mantilla Herrera A.M., Shadid J., Zheng P., Ashbaugh C., Pigott D.M., Abbafati C., Adolph C., Amlag J.O., Aravkin A.Y., Bang-Jensen B.L., Bertolacci G.J., Bloom S.S., Castellano R., Castro E., Chakrabarti S., Chattopadhyay J., Cogen R.M., Collins J.K., Ferrari A.J. (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet, 398 (10312): 1700–1712. DOI: 10.1016/S0140-6736(21)02143-
  42. Savaresi S.M. and Boley D.L. (2004). A comparative analysis on the bisecting K-means and the PDDP clustering algorithms. Intelligent Data Analysis, 8 (4): 345–362. DOI: 10.3233/IDA-2004-840
  43. Schein E.H. (1985). Cultura d’azienda e leadership (E. Cotronei, Trad.). Guerini, Milano.
  44. Sim S.P.-L., Sim H.P.-K. and Quah C.-S. (2021). Online Learning: A Post Covid-19 Alternative Pedagogy for University Students. Asian Journal of University Education, 16 (4): 137.
  45. Son C., Hegde S., Smith A., Wang X. and Sasangohar F. (2020). Effects of COVID-19 on College Students’ Mental Health in the United States: Interview Survey Study. Journal of Medical Internet Research, 22 (9): e21279. DOI: 10.2196/2127
  46. Steinbach M., Karypis G. and Kumar V. (2000). A comparison of document clustering techniques.
  47. Telfener U. (2011). Apprendere i contesti: strategie per inserirsi in nuovi ambiti di lavoro. Milan, IT: Raffaello Cortina.
  48. Wallace S., Schuler M. S., Kaulback M., Hunt K. and Baker M. (2021). Nursing student experiences of remote learning during the COVID-19 pandemic. Nursing forum, 56 (3): 612–618.
  49. Wang X., Hegde S., Son C., Keller B., Smith A. and Sasangohar F. (2020). Investigating Mental Health of US College Students During the COVID-19 Pandemic: Cross-Sectional Survey Study. Journal of Medical Internet Research, 22 (9): e22817. DOI: 10.2196/2281
  50. Warfvinge P., Löfgreen J., Andersson K., Roxå T. and Åkerman C. (2022). The rapid transition from campus to online teaching – how are students’ perception of learning experiences affected? European Journal of Engineering Education, 47 (2): 211–229. DOI: 10.1080/03043797.2021.194279
  51. Zickar M.J. and Keith M.G. (2023). Innovations in Sampling: Improving the Appropriateness and Quality of Samples in Organizational Research. Annual Review of Organizational Psychology and Organizational Behavior, 10 (1): 315–337.

Lorenzo Colaboni, Michela Di Trani, Silvia Monaco, University Culture: A quali-quantitative study on the emotional representations of online learning by psychology university students in "PSICOLOGIA DELLA SALUTE" 1/2024, pp 25-45, DOI: 10.3280/PDS2024-001002