22 SES 11 A, Paper Session
In recent years, increasing attention has been paid by educational research to the potential of interaction and feedback to enact active learning (Wiltbank, 2019; Ranieri, Raffaghelli & Bruni, 2018). This latter is meant a student-centred approach enabling students to actively engage in the learning process through collaborative group, project work, practice and dialogue, problem-based learning, and so on (Winstone, Nash, Parker, & Rowntree, 2017). Pedagogies centring their focus on learners, indeed, are seen as providing better strategies to enhance higher-order cognitive skills’ development including critical thinking, problem solving and design thinking, all crucial to cope with the increasing complexity of contemporary societies.
Researchers with different backgrounds have stressed the importance of both feedback and interaction within active learning environments, arguing for the relevance they have particularly in mobilising prior knowledge (Hattie & Shirley, 2019), reducing cognitive overload (Sweller, 1994), shortening the “discrepancies between current understanding or performance and a desired goal and knowledge” (Laurillard, 2012, p. 83), fostering the awareness of cognitive conflicts and the generation of a network of meanings (Rivoltella & Rossi, 2019) to promote self-regulation processes and revision of conceptual knowledge (Laurillard, 2012). In this perspective, hints are provided on how to go beyond the “empathy gap” which occurs between teachers and students in terms of feedback delivery’s perception for increasing its effectiveness (Hattie & Yates, 2014; Hattie & Timperley, 2007). As far as interaction is concerned, it is considered as one of the main dimensions of the Laurillard (2002) conversational framework and, more generally, of interactionist models, which attribute to the teachers the responsibility of creating responsive learning environments.
In line with these theoretical and empirical understandings, teachers and instructional designers are adopting digital technologies and reshaping the learning spaces, be physical and virtual, to improve teaching (Tonelli, Grion & Serbati, 2018). Technologies are increasingly ubiquitous, supporting new forms of interaction especially within large size classes. Studies, indeed, show how technology enhanced teaching may provide opportunities to improve students’ participation even in the context of higher education, where the problem of involving a large number of students through active teaching is increasingly pressing (Ranieri, Raffaghelli, & Bruni, 2018).
In this context, the University of Florence has been called to innovate its programmes devoted to the preparation of social educators with the introduction of more practical and experiential activities in large size classes (about 250 students for class). The challenges leading the design process can be summarised as follows: (i) taking a step onwards a merely theoretical approach to put students in concrete situations of problem solving through active learning, collaborative work, and partly self-directed activities; (ii) building solid professionalism in diversified disciplinary sectors; (iii) contrasting students’ dropout; (iv) containing costs by avoiding the proliferation of courses; (v) defining a transferable teaching model to be applied to other courses.
To face the previously mentioned challenges a pilot module with experiential orientation has been designed and tested within the course of New technologies for education and training (6 ECTS). This mandatory module was a 18 hours course, of which at least 16 hours involving presential teaching. It was based on following model: 1 hour of online individual work to familiarise with the platform and access a selection of learning materials (e.g., a video lecture, or an article, or an advanced organizer, etc.), 3 face-to-face meetings (+ 1 to recover any absences), 1 hour of online work to reflect on the entire path and collect final questionnaires. Each lecture was provided with a similar structure that is: i) a short initial phase of "alignment", for sharing objectives, activating pre-existing knowledge, preparing their own devices according to the BYOD (bring your own device) approach; ii) two explanation cycles, practical activities in a small group with the production of a digital artefact, feedback from the teacher and peers; iii) a metacognitive exercise and the final test. 460 students attended the module in the first cycle: 47% of them was less than 20 years old, while the 35% was aged between 20 and 24; almost all students (95%) owned a high school degree and a very little component (5%) already had a degree; as for job experiences, 30% has never worked, 20% just started working, and 12% has worked since one year, while the remaining 38% has been working for several years. In order to evaluate the results of this pilot module, especially with regards to its structure and the way how it stimulated students’ participation and active involvement, different tools were adopted, including i) structured (closed answers questionnaires) and not structured tools (open answers questionnaires inspired to scenario based testing and students’ digital artefact) to measure learning results in terms of knowledge and skills related to ICT for education and training; ii) a final questionnaire aimed the measuring teachers’ and students’ satisfaction as well as perceptions related to the sustainability of the instructional planning, gathered through questionnaires, rating scales, and logbooks; iii) self-assessment tools. The tools were applied according to a pre-post design.
Since the focus of the paper is on active learning and technology enhanced interaction, this presentation focuses on students’ involvement and reaction to highlight the strengths and weaknesses of the implemented model. First of all, almost all students (95%) ended the module according to the planned timeline. Secondly, students’ results indicate that engagement brought to positive attainments: for each lecture the average score was respectively 26/30 (first meeting), 28/30 (second), 27/30 (third), and 28/30 (fourth), suggesting that active involvement of students may increase the level of learning results. The final questionnaire covering all topics dealt within the module got an average score of 28/30. Further data concerns students’ satisfaction that shows how learners appreciate the overall approach (average score 8/10) as well as specific aspects such as the immediacy of feedback, the engagement in concrete activities, the challenging nature of tasks which led them to develop new competences. As far as weaknesses are concerned, they mainly refer to technical and cultural aspects. From a technical point of view, some students felt to be not able enough in terms of digital skills to use the platform for performing the planned activities. In addition, the wi-fi connection was unstable and this generated anxiety. From a cultural point of view, students proved to be not prepared for active learning: somehow, since they are generally supposed to be passive learners, which means that they just have to register what the teachers transmit, they were disoriented in front of teachers asking them not only to be good listeners but also to engage with authentic tasks. The time of active learning is now, but an overall cultural shift is needed on the side of both teachers and students to make it possible, be classes of large size or not, be technology used or not!
Hattie, J. & Shirley, S. (2019). Visible learning: Feedback. Abingdon-New York: Routledge. Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. Hattie, J., & Yates, G. (2013). Visible Learning and the Science of How We Learn. Abingdon-New York: Routledge. Laurillard, D. (2012). Teaching as Design Science. Abingdon-New York: Routledge.Laurillard, 2012. Ranieri, M., Raffaghelli, J., & Bruni, I. (2018). Game-based student response system: Revisiting its potentials and criticalities in large-size classes. Active learning in higher education, 18(1), 25–35. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295–312. Rivoltella, P. C., & Rossi, P. G. (2019). Il corpo e la macchina [The body and the machine], Brescia: Morcelliana. Tonelli, D., Grion, V., & Serbati, A. (2018). L’efficace interazione fra valutazione e tecnologie: evidenze da una rassegna sistematica della letteratura. Italian Journal of Educational Technology, 26(3), 6–23. Wiltbank, L., Williams, K., Salter, R., Marciniak, L., Sederstrom, E., McConnell, M., Offerdahl, E., Boyer, J., & Momsen, J. (2019). Student perceptions and use of feedback during active learning: a new model from repeated stimulated recall interviews. Assessment & Evaluation in Higher Education, 44, 3, 431–448. Winstone, N. E., Nash, R. A., Parker, M., & Rowntree, J. (2017). Supporting Learners' Agentic Engagement with Feedback: A Systematic Review and a Taxonomy of Recipience Processes. Educational Psychologist, 52(1), 17–37.
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