Am 24. November 2021 präsentierten Jeff Hennico, Robert Reuter & Armin Weinberger ihre Studie zum Thema „Factors Affecting the Teaching of Computational Thinking in Fundamental Schools: A Path Analysis“ auf der EAPRIL2021, der 15. jährlichen Konferenz „for practitioner research on improving learning“.
Auch wenn diese Studie kein direktes Produkt unseres Erasmus+ Projekts war, wirft sie doch ein interessantes Licht darauf, was Lehrerinnen und Lehrer über „Computational Thinking“ in der Grundschule denken. Und sie hat die Verbindungen zwischen zwei Partnereinrichtungen gestärkt.
Factors Affecting the Teaching of Computational Thinking in Fundamental Schools: A Path Analysis
Computational thinking (CT) in fundamental education is an emerging topic in research about educational policies and practices around the globe. In Luxembourg, CT was introduced as a learning topic in fundamental schools in 2020. This situation offers a unique opportunity to investigate how various factors influence emerging CT teaching practices. Based on a revised version of the Technology Acceptance Model (Inan & Lowther, 2010), a research-based path model of CT teaching was developed, emphasising the influence of teachers’ beliefs and readiness on CT teaching practices. It investigated the effects of demographic factors, teaching approaches, ICT proficiency, previous CT experience, and overall support for technology integration on readiness, beliefs, and CT teaching practices. The current study reveals that teachers are interested in teaching CT. However, they hold a widespread misconception (Fessakis & Prantsoudi, 2019), confusing CT with programming or technology use. ICT proficiency is indeed associated with beliefs about CT and readiness for teaching CT. Readiness for teaching CT, beliefs about CT, and previous CT experience are the strongest predictors for CT teaching practices. In line with Cuny et al. (2010), the current study highlights the importance of training teachers to accurately define CT and to identify good practices.