Virtual reality-assisted competence recognition – supporting the employment of immigrants to the care industry
Lindgren, Eveliina; Anttila, Kaisa (2020)
Lindgren, Eveliina
Anttila, Kaisa
2020
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2020110522275
https://urn.fi/URN:NBN:fi:amk-2020110522275
Tiivistelmä
This thesis, conducted as a part of a larger research and development project, VR Fast Track, examines how virtual reality (VR)-assisted competence recognition could support the employment of immigrants to vocational jobs. The topic is approached as a whole and through an example from the care industry.
The thesis’ focus is twofold: first, examining what kind of a framework for competence recognition is most suited to structuring competences that are required in vocational jobs. Second, using this framework to generate sample use cases for VR-assisted competence recognition tasks and assessing whether such use of VR is advantageous and feasible generally and for project purposes.
An iterative service design approach was used to organize the various empirical activities executed to meet these goals. These included non-formal literature reviews on existing learning taxonomies, national competence requirements, and VR; expert interviews and workshops to collect information and validate study outputs; and hands-on testing of off-the-shelf VR solutions and software.
It was concluded that existing learning taxonomies did not meet the needs of the VR Fast Track project, so a new general competence recognition framework was built. Care-specific competence examples were then incorporated to the framework. Based on these outputs, a curriculum of VR use cases was outlined and one use case detailed to the level of implementation readiness. Moreover, a VR use case template was created, as well as a process demonstrating the use of the framework in connection with the use cases.
The thesis concluded that while VR has potential in enabling competence recognition in realistic scenarios that are not overly dependent on language skills, using off-the-shelf VR technology is not yet feasible when complex features such as interaction or multisensory experiences are required. Therefore, it is more feasible for VR Fast Track to use a lightweight VR method, such as 360° videos, whose implementation is simple, and which can also be utilized via non-VR channels. This enables the wider-scale collection of stakeholder feedback that is essential for the future development of all the thesis outputs.
The thesis’ focus is twofold: first, examining what kind of a framework for competence recognition is most suited to structuring competences that are required in vocational jobs. Second, using this framework to generate sample use cases for VR-assisted competence recognition tasks and assessing whether such use of VR is advantageous and feasible generally and for project purposes.
An iterative service design approach was used to organize the various empirical activities executed to meet these goals. These included non-formal literature reviews on existing learning taxonomies, national competence requirements, and VR; expert interviews and workshops to collect information and validate study outputs; and hands-on testing of off-the-shelf VR solutions and software.
It was concluded that existing learning taxonomies did not meet the needs of the VR Fast Track project, so a new general competence recognition framework was built. Care-specific competence examples were then incorporated to the framework. Based on these outputs, a curriculum of VR use cases was outlined and one use case detailed to the level of implementation readiness. Moreover, a VR use case template was created, as well as a process demonstrating the use of the framework in connection with the use cases.
The thesis concluded that while VR has potential in enabling competence recognition in realistic scenarios that are not overly dependent on language skills, using off-the-shelf VR technology is not yet feasible when complex features such as interaction or multisensory experiences are required. Therefore, it is more feasible for VR Fast Track to use a lightweight VR method, such as 360° videos, whose implementation is simple, and which can also be utilized via non-VR channels. This enables the wider-scale collection of stakeholder feedback that is essential for the future development of all the thesis outputs.