Visual authoring of virtual reality conversational scenarios for e-learning.

The COVID-19 pandemic has led to face-to-face activities being developed in a virtual format that often offers a poor experience in areas such as education. Virtual Learning Environments have improved in recent years thanks to new technologies such as Virtual Reality or Chatbots. However, creating Virtual Learning Environments requires advanced programming knowledge, so this work is aimed to enable teachers to create these new environments easily. This work presents a set of extensions for App Inventor that facilitate the authoring of mobile learning apps that use Chatbots in a Virtual Reality environment, while simultaneously monitoring of student activity. This proposal is based on integrating block-based languages and Business Process Model and Notation diagrams. The developed extensions were successfully implemented in an educational app called Let's date!. A quantitative analysis of the use of these extensions in App Inventor was also carried out, resulting in a significant reduction in the number of blocks required. The proposed contribution has demonstrated its validity in creating virtual learning environments through visual programming and modelling, reducing development complexity.

Block-Based Development of Mobile Learning Experiences for the Internet of Things.

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor's standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.