This short paper describes the first prototyping of a self-evaluation process of Curriculum Agility at a Faculty of Technology in Sweden. The process comprises guided, semi-structured, individual interviews at different organisational levels within the faculty, a joint narrative based on those interviews, prioritizing development strategies per level, and jointly mapping them on importance and implementation time. The self-evaluation is part of and based on the research on the principles of Curriculum Agility. The results show the interplay in timely curriculum change for futureproof engineering education between the teaching staff, the systems and the people who control the systems. The self-evaluation brings together the different perspectives and perceptions within the faculty and gives insight in how those affect he willingness towards and occurrence of curriculum development. This work in progress indicates how doing such a qualitative self-evaluation paves the road for transparent strategic dialogues on a holistic level about what to give attention and organize differently.
We investigated to what extent correctional officers were able to apply skills from their self-defence training in reality-based scenarios. Performance of nine self-defence skills were tested in different scenarios at three moments: before starting the self-defence training programme (Pre-test), halfway through (Post-test 1), and after (Post-test 2). Repeated measures analyses showed that performance on skills improved after the self-defence training. For each skill, however, there was a considerable number of correctional officers (range 4–73%) that showed insufficient performance on Post-test 2, indicating that after training they were not able to properly apply their skills in reality-based scenarios. Reality-based scenarios may be used to achieve fidelity in assessment of self-defence skills of correctional officers.Practitioner summary: Self-defence training for correctional officers must be representative for the work field. By including reality-based scenarios in assessment, this study determined that correctional officers were not able to properly apply their learned skills in realistic contexts. Reality-based scenarios seem fit to detect discrepancies between training and the work field. Abbreviations: DJI: Dutch National Agency for Correctional Insitutes; ICC: Intraclass Correlation Coefficient.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
