Speaker
Description
Following the global pandemic, our research group at CERN has developed a new virtual learning format called a Digital Learning Module (DLM), which consists of a series of pre-recorded explanatory and experiment videos, interactive elements (e.g., quizzes, shortcuts), interactive screen experiments, and expert interviews, all integrated in a module that is openly available online. So far, a DLM has been created about the topic of Positron Emission Tomography (PET).
Aiming to derive general design principles that can be employed in the design of future DLMs, the first part of my PhD project is to qualitatively evaluate the PET DLM. For this, various theoretical design principles from existing literature have been considered – e.g., the Cognitive Affective Theory of Learning with Media, the Variation Theory of Learning, and the Predict-Observe-Explain method. These design principles have been compared to the ones employed in the PET DLM.
Currently, semi-structured interviews are being conducted with high-school students as they engage with the PET DLM, using a think-aloud protocol. A qualitative content analysis of the interview transcripts will determine whether the employed design principles address the learning goals of the PET DLM. This set of general design principles will be the foundation of future DLMs.
