Engineering education must adapt to evolving societal and technological demands, addressing challenges like high dropout rates, limited student engagement, and the need for inclusive, hands-on learning environments. MEXLEfirst reimagines the introduction to electrical engineering through a multimodal, scalable, and accessible learning platform. Central to the approach is the Lab-in-a-Box system: a modular hardware kit paired with an integrated Web App that supports both structured and self-guided learning. Unlike existing modular learning systems, MEXLEfirst integrates real-time nodal analysis with image recognition to provide immediate and adaptive feedback on student circuits. This paper outlines MEXLEfirst's hardware architecture, software integration, and pedagogical framework, emphasizing its innovative approach to scalable, accessible, and impactful education in electrical engineering.

This paper shows an approach practiced in the field of learning basic electronics now for more than 10 years. The practicalities have been developed by trial and error as well as intensive discussions with the students. The paper focuses on (1) the learning strategy and learning environment and (2) the reflections on the background and goals for effective learning. The described learning strategy is based mainly on problem-based learning and self-directed learning. The learning activity is guided by the 3H-learning approach (Head, Heart and Hands). Special focus also is put on side topics like (1) changing from teacher to trainer, (2) balancing the different aspects in the projects, (3) valuing the learning support by the peer group and (4) motivating the "engineer inside" instead of keeping the "pupil" alive. This paper will help to open the "fences" around students which limit their inside motivation and such as their energy and put them to an open learning environment.

Speech processing using multichannel microphone systems is often based on slowly adapting, linear filters. These systems are able to extract a single source from a mixture (and suppress the others)-if the speech radiation can be described by a linear and time-invariant transfer function. Here, we test this assumption using a two-channel microphone array and a human talker as the speech source. We measure correlations between the signals received by the two microphones for individual phonemes using the magnitude squared coherence. Stationarity is addressed by comparing optimal filters between different phoneme pairs using the system distance. We find that, in particular for fricatives, the coherence of the speech signals radiated to different directions is very low. We also find, that the transfer functions from the mouth to the microphones differ significantly between vowels, depending on the locations of the two microphones. These measurements show that the general mixing model does not hold for speech for arbitrary microphone setups, and that multichannel microphone systems have to be carefully designed.

In this paper we present the Java Fieldbus Control Framework (JFCF) which provides an object oriented programming framework for the rapid creation of concurrent control tasks for fieldbus-based automation systems. Our framework is implemented in Java which is going to become more popular in the field of industrial control, due to the advent of dedicated Java real-time systems and the RealTime Specification for Java (RTSJ). We further describe an example application built within our framework consisting of an open Java control for a CANopen automation system featuring a SCARA robot arm, a transfer system and further peripheral fieldbus devices. Four independent tasks run concurrently to establish the overall automation process. In order to meet real-time requirements, the framework will be extended to comply to the RTSJ in the future. The reusability of object oriented software and the portability of Java code results in a reduction of costs for software creation and maintenance.