Skip to main navigation menu Skip to main content Skip to site footer

Articles/Articoli

Vol. 12 No. 2 (2021): Evaluation, feedback, equity: a challenge in education

Emotional Feedback in evaluation processes: Case studies in the University context

DOI
https://doi.org/10.3280/ess2-2021oa11911
Submitted
settembre 7, 2021
Published
2021-12-21

Abstract

In the face of the growing number of students with disabilities enrolled at the University, it is necessary to rethink the educational and teaching proposals from an inclusive perspective. This necessarily implies careful planning of even one of the most delicate phases of the teaching and learning process for all students: the final exam of a discipline. An event full of expectations and anxieties, very often attention to the construction of a welcoming environment becomes essential to provide the basis for a welcoming atmosphere and success, especially for students with Specific Learning Disorders (SpLDs) or disabilities. Therefore, this contribution, starting from a pilot study conducted by the University of Macerata, analyzes the role of Emotional Feedback in the assessment procedures in university contexts.

 

References

  1. Beck J.E. (2004). Using response times to model student disengagement. In: Proceedings of the ITS2004 Workshop on Social and Emotional Intelligence in Learning Environments, 20: 88-95.
  2. Ceccacci S., Generosi A., Cimini G., Faggiano S., Giraldi L., and Mengoni M. (2021). Facial coding as a means to enable continuous monitoring of student’s behavior in e-Learning. Proceedings of the First Workshop on Technology Enhanced Learning Environments for Blended Education (teleXbe2021), January 21-22, 2021, Foggia, Italy.
  3. Coggi C. (2019). Innovare la didattica e la valutazione in Università: Il progetto IRIDI per la formazione dei docenti. Milano: FrancoAngeli.
  4. D’Angelo I. and Del Bianco N. (eds.) (2019). Inclusion at the University. Studies and Practices. Milano: FrancoAngeli.
  5. D’Angelo I., Giaconi C., Del Bianco N., and Perry V. (2020). Students’ Voice and Disability: Ethical and methodological reflections for Special Pedagogy research. Education Sciences & Society-Open Access, 11(1): 112-123.
  6. D’Errico F., Paciello M., and Cerniglia L. (2016). When emotions enhance students’ engagement in e-learning processes. Journal of e-Learning and Knowledge Society, 12(4): 9-23.
  7. Falchikov N., and Boud D. (2007). Assessment and emotion: The impact of being assessed. In: David Boud, Nancy Falchikov, Rethinking assessment in higher education. London: Routledge.
  8. Generosi A., Ceccacci S., Faggiano S., Giraldi L., and Mengoni M. (2020). A Toolkit for the Automatic Analysis of Human Behavior. HCI Applications in the Wild, Advances in Science, Technology and Engineering Systems Journal, 5(6): 185-192.
  9. Giaconi C. (2015). Qualità della Vita e adulti con disabilità. Percorsi di ricerca e prospettive inclusive. Milano: FrancoAngeli.
  10. Giaconi C., Capellini S. A., Del Bianco N., Taddei A. and D’Angelo I. (2019). Study Empowerment for inclusion. Education Sciences and Society-Open Access, 9(2): 166-183.
  11. Giaconi C., and Del Bianco N. (2019). In azione: Prove di inclusione. Milano: FrancoAngeli.
  12. Giannandrea L. (2019). Valutazione, feedback, tecnologie in Tecnologie per l’educazione. In: Rivoltella P.C., Rossi, P.G. (Eds.), Tecnologie per l’educazione, Pearson: Milano.
  13. Goldberg, B., Sottilare, R., Brawner, K., and Holden, H. (2011). Predicting learner engagement during well-defined and ill-defined computer-based intercultural interactions. In Proc. 4th Int. Conf. Affective Comput. Intell. Interaction, 538-547.
  14. Hattie J. and Clarke S. (2018). Visible Learning: Feedback. New York: Routledge.
  15. Hussain M., Zhu W., Zhang W., and Abidi S. M. R. (2018). Student engagement predictions in an e-learning system and their impact on student course assessment scores. Computational intelligence and neuroscience. Doi: 10.1155/2018/6347186.
  16. Johns J. and Woolf B. (2006). A dynamic mixture model to detect student motivation and proficiency. AAAI, 163-168.
  17. Karyotis C., Doctor F., Iqbal R., James A.E., and Chang V. (2017). Affect Aware Ambient Intelligence: Current and Future Directions. In: Aztiria A., Augusto J. C. and Orlandini A. (eds.) State of the Art in AI Applied to Ambient Intelligence (Vol. 298). USA: Ios Press.
  18. Kaur A. Mustafa A. Mehta L., and Dhall A. (2018). Prediction and Localization of Student Engagement in the Wild, 2018 Digital Image Computing: Techniques and Applications (DICTA). Australia: Canberra.
  19. Kaur, A., Noman, M. and Nordin H. (2017). Inclusive assessment for linguistically diverse learners in higher education. Assessment & Evaluation in Higher Education, 42(5): 756-771.
  20. Le Boterf G. (2000). Costruire le competenze individuali e collettive. Napoli: Guida.
  21. Mehrabian A. (1996). Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in temperament. Current Psychology, 14(4): 261-292.
  22. Paviotti G., D’Angelo I., Capellini S. A. and Giaconi, C. (2021). Inclusion in university contexts and the role of internships in the education of students with disabilities: Critical issues, perspectives and good practices. Education Sciences & Society-Open Access, 12(1): 197-218.
  23. Pentaraki A. and Burkholder G.J. (2017). Emerging Evidence Regarding the Roles of Emotional, Behavioural, and Cognitive Aspects of Student Engagement in the Online Classroom. European Journal of Open, Distance and E-learning, 20(1): 1-21.
  24. Perla L. (2018). Formare il docente alla didattica universitaria: il cantiere dell’innovazione. Riflessioni sull’innovazione didattica universitaria. Interventi alla tavola rotonda GEO (30 giugno 2017), 79-88.
  25. Pino M., and Mortari L. (2014). The Inclusion of Students with Dyslexia in Higher Education: A Systematic Review Using Narrative Synthesis. DYSLEXIA, 20: 46-369.
  26. Rivera C.J., Wood C. L, James M. and Williams S. (2019). Improving Study Outcomes for College Students With Executive Functioning Challenges. Career Development and Transition for Exceptional Individuals, 42(3): 139-147.
  27. Romeo F.P. (2020). Sollecitare la resilienza. Emergenze educative e strategie didattiche. Trento: Erickson.
  28. Romeo F.P. (2021a). Investimento affettivo nei processi di insegnamento-apprendimento. Tre criteri per la didattica a distanza nelle emergenze. Open Journal of IUL University, 2(1): 267-279.
  29. Romeo F.P. (2021b). Gli adolescenti dell’era Covid. Emergenze, disagio esistenziale e immagini del domani. In: A. Mongelli, a cura, Altri modi di apprendere. Sociologia, Psicologia e Pedagogia in dialogo. Napoli: Diogene Edizioni.
  30. Rossi P.G., Pentucci M., Fedeli L., Giannandrea L. and Pennazio V. (2018). From the informative feedback to the generative feedback. Education Sciences & Society-Open Access, 9(2): pp. 83-107.
  31. Rossi P.G. (2011). Didattica enattiva. Complessità, teorie dell'azione, professionalità docente: Complessità, teorie dell’azione, professionalità docente. Milano: FrancoAngeli.
  32. Russell J.A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6): 1161-1178.
  33. Sroufe L. A. (2000). Lo sviluppo delle emozioni. I primi anni di vita. Milano: Raffaello Cortina.
  34. Whitehill J., Serpell Z., Lin Y., Foster A. and Movellan J.R. (2014). The Faces of Engagement: Automatic Recognition of Student Engagement from Facial Expressions. IEEE Transactions on Affective Computing, 5(1): 86-98.
  35. Wilde A. and Avramidis E. (2011). Mixed feelings: towards a continuum of inclusive pedagogies. Education, 39(1): 83-101.
  36. Xiao X. and Wang J. (2017). Understanding and Detecting Divided Attention in Mobile MOOC Learning. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2411-2415.

Metrics

Metrics Loading ...

Most read articles by the same author(s)

<< < 1 2 3 4 > >>