A Toolkit for Promoting a Learning Innovation Safe Space (LISS) in Computing Higher Education
This research-to-practice full paper describes the concept of Learning Innovation Safe Space and the development of a toolkit that affects the teaching and learning culture of computing education by encouraging emotional safety, auton-omy and collaboration in the context of iOS development for undergraduate students in two different innovation education initiatives: a two-year program and a one-semester course. The initiatives are based on the Challenge-Based Learning framework and involved one group of forty students for the two-year program and three groups of twenty students for the one-semester undergraduate course. There are problems related to developing and maintaining a safe space in this context, such as the students' difficulty in perceiving their learning when developing innovative solutions, dealing with emotional safety issues such as imposter syndrome, and autonomously managing their learning objectives. The research is centered on defining the concept of Learning Innovation Safe Space and developing a set of tools: Asset Mapping, Future Self and Autonomous Learning Management. In this way, emotional safety, autonomous and collaborative learning among students is encouraged through the use of these tools and practices. As a qualitative research method, an action research process was used to describe the planning and execution of the experiment in the two different innovation education initiatives, as well as the use of questionnaires to evaluate the impact of using these tools to support the development of LISS. As a main contribution, the results support the development of safe learning environments for innovation using the findings of this study, which include the creation, development and evaluation of tools and practices capable of promoting emotional safety, autonomy and collaboration to deal with computing challenges and multidisciplinary learning domains.
Authors
- Lívia Karolina Silva de Oliveira (ORCID: https://orcid.org/0009-0008-7946-5770)
- Cristiano Araújo (ORCID: https://orcid.org/0000-0003-1414-7292)
- Leonardo Castillo (ORCID: https://orcid.org/0000-0002-9350-726X)
Institutions
- Universidade Federal de Pernambuco (BR)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/fie61694.2024.10893387
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00