In The Netherlands, the 4-Skills Scan is an instrument for physical education teachers to assess gross motor skills of elementary school children. Little is known about its reliability. Therefore, in this study the test–retest and inter-rater reliability was determined. Respectively, 624 and 557 Dutch 6- to 12-year-old children were analyzed for test re-test and inter-rater reliability. All tests took place within the school setting. The outcome measure was age-expected motor performance (in years). Results showed a small practice effect of .24 years for re-test sessions and assessment of motor skills was possible with acceptable precision (standard error of measurement = .67 years). Overall, intraclass correlation coefficient (ICC) was .93 (95% confidence interval: .92–.95) for test–retest reliability and .97 for inter-rater reliability. For the repeated measures, the smallest detectable change (SDC) was 1.84 and limits of agreement were –1.60 and 2.08 years. It can be concluded that the 4-Skills Scan is a reliable instrument to assess gross motor skills in elementary school children.
DOCUMENT
Adequate gross motor skills are an essential aspect of a child’s healthy development. Where physical education (PE) is part of the primary school curriculum, a strong curriculum-based emphasis on evaluation and support of motor skill development in PE is apparent. Monitoring motor development is then a task for the PE teacher. To fulfill this task, teachers need adequate tools. The 4-Skills Scan is a quick and easily manage- able gross motor skill instrument; however, its validity has never been assessed. Therefore, the purpose of this study was to assess the construct and concurrent validity of both 4-Skills Scans (version 2007 and version 2015). A total of 212 primary school children (6-12 years old) was requested to participate in both versions of the 4-Skills Scan. For assessing construct validity, children covered an obstacle course with video recordings for observation by an expert panel. For concurrent validity, a comparison was made with the M-ABC-2, by calculating Pearson correlations. Multivariable linear regression analyses were performed to determine the contribution of each subscale to the construct of gross motor skills, according to the M-ABC-2 and the expert panel. Correlations between the 4-Skills Scans and expert valuations were moderate, with coefficients of .47 (version 2007) and .46 (version 2015). Correlations between the 4-Skills Scans and the M-ABC-2 (gross) were moderate (.56) for version 2007 and high (.64) for version 2015. It is concluded that both versions of the 4-Skills Scans are satis- factory valid instruments for assessing gross motor skills during PE lessons.
DOCUMENT
In this study, we investigated the effects of wearing a police uniform and gear on officers’ performance during the Physical Competence Test (PCT) of the Dutch National Police. In a counterbalanced within-subjects design, twenty-seven police officers performed the PCT twice, once wearing sportswear and once wearing a police uniform. The results showed clear indications that wearing a police uniform influenced the performance on the PCT. Participants were on average 14 seconds slower in a police uniform than in sportswear. Furthermore, performing the test in uniform was accompanied by higher RPE-scores and total physiological load. It seems that wearing a police uniform during the test diminishes the discrepancy between physical fitness needed to pass the simulated police tasks in the PCT and the job-specific physical fitness that is required during daily police work. This suggests that wearing a police uniform during the test will increase the representativeness of the testing environment for the work field.
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Met huidige opleidings- en trainingsprogramma’s kan niet worden voldaan aan de groeiende vraag naar vakbekwame medewerkers op gebied van kunstmatige intelligentie (AI). Europa heeft daarom een innovatieve Europese AI-strategie nodig, die de bijscholing van werkenden kan versnellen om aan deze steeds toenemende vraag te voldoen. Doel Het project ondersteunt het Europese Pact for Skills door een strategie op het gebied van AI skills te ontwikkelen. Deze strategie moet leiden tot impact op het terugdringen van tekorten, hiaten en mismatches in skills op de arbeidsmarkt, en zorgen voor passende kwaliteit en niveaus van skills. Resultaten Verwachte resultaten en impactHet project omvat: de oprichting van een lange termijn partnerschap voor een innovatieve Europese alliantie voor AI; het ontwerpen en uitrollen van een innovatieve en duurzame strategie voor AI-skills op korte en lange termijn; het ontwikkelen, testen en uitrollen van opleidingscurricula in acht proeflocaties (5 universiteiten/hogescholen en 3 mbo-aanbieders); de aanpassing van programma's en kwalificaties aan de nieuwste marktbehoeften. het koppelen van micro-credentials aan het opleidingsaanbod Voordelen op lange termijnDe AI-skills strategie en de opleidingscurricula zullen, nadat ze zijn ontworpen en grondig getest in de praktijk, beschikbaar worden gesteld om te worden aangepast en opgeschaald in heel Europa. Op deze manier kan worden voldaan aan de huidige en toekomstige skills-behoeften van de AI-sector en kan de groei van AI-talent in Europa worden gestimuleerd. Looptijd 01 juni 2022 - 30 juni 2026 Aanpak Het project wordt als volgt uitgevoerd in negen werkpakketten: 1 – Projectbeheer en coördinatie 2 – Behoeftenanalyse 3 – Strategie voor AI-skills 4 - Ontwikkeling van een innovatief leerplan en trainingsprogramma 5 - Ontwikkeling van een certificeringssysteem 6 – Pilots in verschillende EU-landen 7 – Verspreiding en communicatie 8 – Duurzaamheid op lange termijn 9 – Kwaliteitsborging Inhoudelijk start het project met de behoeftenanalyse, waarin de skills mismatch op Europees niveau wordt geanalyseerd door o.a. de behoefte aan skills op basis van vacatures en beschikbaar relevant AI opleidingsaanbod te onderzoeken. Meer over ARISA Het vierjarige onderzoeksproject ARISA wordt gefinancierd door de Europese Unie via een Erasmus+ programma. Meer informatie vind je op de ARISA website, de ARISA Twitter en de ARISA LinkedIn. Lees ook dit artikel (ENG) over de start van ARISA.
Met huidige opleidings- en trainingsprogramma’s kan niet worden voldaan aan de groeiende vraag naar vakbekwame medewerkers op gebied van kunstmatige intelligentie (AI). Europa heeft daarom een innovatieve Europese AI-strategie nodig, die de bijscholing van werkenden kan versnellen om aan deze steeds toenemende vraag te voldoen.
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.
