In this study, a data feedback program to improve teachers’ science and technology (S&T) teaching skills was designed and tested. The aim was to understand whether and how the four design principles underlying this program stimulated the intended teacher support. We examined how teachers in different …

Design and development practitioners such as those in game development often have difficulty comprehending and adhering to the European General Data Protection Regulation (GDPR), especially when designing in a private sensitive way. Inadequate understanding of how to apply the GDPR in the game development …

Design education has a nuanced relationship with examples. Although they are considered useful teaching tools, their use is often restricted to illustrating the design theories and principles around which the curriculum is structured. In contrast, professional designers view examples as autonomous entities …

In de accountancybranche heersen een aantal kenmerken die ervoor hebben gezorgd dat de adoptie van automatisering, digitalisering en data-analyse achterloopt. Dit heeft een aantal redenen: door de hoge werkdruk is er soms geen kans om te innoveren; de omzet is toereikend, waardoor de nut en noodzaak …

Although learning analytics benefit learning, its uptake by higher educational institutions remains low. Adopting learning analytics is a complex undertaking, and higher educational institutions lack insight into how to build organizational capabilities to successfully adopt learning analytics at scale. …

Brochure from the Inauguration of Klaas Dijkstra, professor Computer Vision and Data Science

This video offers a concise exploration of the distinctions between Data Science, AI, Machine Learning, and Deep Learning. Starting with the foundational role of Data Science, it navigates through the various machine learning categories and touches upon the capabilities and constraints of Deep Learning. …

This video provides small and medium enterprises (SMEs) with a concise breakdown of the costs involved in initiating a data science project. It categorizes expenses into three primary areas: personnel, infrastructure, and data-related costs. Through a practical example of a marketing agency’s venture …

This final installment in our e-learning series offers a comprehensive look at the current impact and future potential of data science across industries. Using real-world examples like medical image analysis and operational efficiencies at Rotterdam The Hague Airport, we showcase data science’s transformative …

Here, we delve into Demand Forecasting via Machine Learning, dissecting how to predict future demand using time-sensitive data. Westveer highlights key forecasting models, from the basic Simple Exponential Smoothing to the advanced SARIMA, applied to an electricity production dataset. The session, encapsulating …