Many studies investigating inquiry learning in science domains have appeared over the
years. Throughout this period, inquiry learning has been regularly criticized by scholars who …

Machine learning (ML) is an emergent computerised technology that relies on algorithms
built by 'learning'from training data rather than 'instruction', which holds great potential to …

In the year 2020, the Covid-19 pandemic turned both private and public life upside down.
Teaching and learning at higher education institutions worldwide had to move online on …

We propose a conceptual framework which may guide research on fostering diagnostic
competences in simulations in higher education. We first review and link research …

Zusammenfassung Dieses Kapitel beleuchtet theoretische Grundlagen unterrichtlichen
Lehrens und Lernens und gibt einen Überblick über wichtige Ergebnisse der …

This study develops a framework to conceptualize the use and evolution of machine
learning (ML) in science assessment. We systematically reviewed 47 studies that applied …

Volume III of this landmark synthesis of research ofers a comprehensive, state-of-the-art
survey highlighting new and emerging research perspectives in science education. Building …

Constructing arguments is essential in science subjects like chemistry. For example,
students in organic chemistry should learn to argue about the plausibility of competing …

Abstract Machine learning (ML) techniques are commonly seen as an inductive learning
procedure, typically involving the identification of patterns in a specific training dataset to …

Abstract Machine learning (ML) has been increasingly employed in science assessment to
facilitate automatic scoring efforts, although with varying degrees of success (ie, magnitudes …