Semi-automatic assembly of learning resources

Technology Enhanced Learning is a research field that has matured considerably over the last decade. Many technical solutions to support design, authoring and use of learning activities and resources have been developed. The first datasets that reflect the tracking of actual use of these tools in real-life settings are beginning to become available. In this article, we present an exploratory study that relies on these datasets to support semi-automatic assembly of learning activities and resources for specific contexts. Starting from learning designs and other online sources that describe well designed learning experiences as they were used in practice, we derive sequencing patterns that capture re-occurring patterns of activities. A semi-automatic assembly framework uses these patterns to support teachers in the design and authoring of course activities. We present a case study that integrates recommendation support for sequencing activities as well as associated resources in the LAMS learning activity environment. Results indicate that the perceived usefulness is high: both teachers with expertise in the use of learning design tools as well as teachers with no background knowledge in the area indicate that the recommendations helped them in the authoring process. In addition, they feel more confident using learning design tools when support is provided that is driven by best practice knowledge.

► We extract sequencing patterns from existing learning designs. ► We present algorithms that rely on patterns to support learning design authoring. ► We present a user study that assesses the usefulness and usability of the approach. ► We identify future research areas to support recommendation of learning sequences.