Youth’s Perspectives of Computational Design in Making-based Coding Activities

There are increasing calls to introduce coding in K-12 in creative ways that provide opportunities for personal expression. Computational design projects include computational concepts fundamental to computer science to generate 2D and 3D models that can potentially be personally meaningful. We developed and implemented making-based coding activities for youth that combine computational design and 3D printing tools and allow the participants to design and fabricate free-choice projects. To investigate how young persons engaged in computational design and which aspects demotivated them, we used a mixed-methods approach that included semi-structured interviews and questionnaires. We took field notes and collected students’ artifacts to triangulate the data wherever possible. The results show that 3D printing, creating unique aesthetics, enhanced personalization, and ownership of design models are crucial elements for engaging youth in computational design. We discuss the implications of our exploratory study and suggest directions for future work in developing computationally rich making-based activities

NuzzleBug: Debugging Block-Based Programs in Scratch

While professional integrated programming environments support developers with advanced debugging functionality, block-based programming environments for young learners often provide no support for debugging at all, thus inhibiting debugging and preventing debugging education. In this paper we introduce NuzzleBug, an extension of the popular block-based programming environment Scratch that provides the missing debugging support. NuzzleBug allows controlling the executions of Scratch programs with classical debugging functionality such as stepping and breakpoints, and it is an omniscient debugger that also allows reverse stepping. To support learners in deriving hypotheses that guide debugging, NuzzleBug is an interrogative debugger that enables to ask questions about executions and provides answers explaining the behavior in question. In order to evaluate NuzzleBug, we survey the opinions of teachers, and study the effects on learners in terms of debugging effectiveness and efficiency. We find that teachers consider NuzzleBug to be useful, and children can use it to debug faulty programs effectively. However, systematic debugging requires dedicated training, and even when NuzzleBug can provide correct answers learners may require further help to comprehend faults and necessary fixes, thus calling for further research on improving debugging techniques and the information they provide.Comment: To appear at the 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE '24), April 14--20, 2024, Lisbon, Portuga

An Overview of Mindwave Applications: Study Cases

Brain-computer interfaces (BCIs) have diverse applications across various research domains. In healthcare, individuals with disabilities in communication and controlling prosthetic devices are aided. Beyond healthcare, BCIs integrate seamlessly into Internet of Things (IoT) and smart environments, enabling intuitive device control and interaction, enhancing user experiences. In neuromarketing and advertising, BCIs help decipher consumers’ preferences and emotional responses to products and services, providing businesses with profound insights into consumer behavior. In education and self-regulation, BCIs monitor and regulate students’ cognitive states. BCIs use sensors and hardware to capture brain signals, with non-invasive electroencephalography (EEG) technology being a pivotal component. Preliminary studies analyzing cognitive load using EEG signals and the Mindwave device pave the way for measuring student learning outcomes, shedding light on cognitive and neurological learning processes. Our research explores these parameters, particularly the Mindwave system, aiming to understand brain function across domains. To this end, we conduct a range of diversified studies, trying to better grasp parameters such as attention, concentration, stress, immersion, and fatigue during various tasks. Ultimately, our work seeks to harness BCIs’ potential to improve our understanding of brain function and enhance various areas of knowledge