Conference Agenda

The teaching of analog and nonlinear electronics in engineering programs often faces challenges related to the abstract nature of circuit behavior and the limited perceptual feedback provided by traditional laboratory practices. This paper explores the use of project-based learning through audio-centered applications as a pedagogical strategy to enhance conceptual understanding, practical skills, and student engagement. The study was conducted within an undergraduate Mechatronics Engineering course focused on electronic design and integrated two complementary projects: a ten-band multiband VU meter based on analog signal conditioning and visualization, and a set of guitar effects pedals emphasizing nonlinear amplification and frequency response shaping. The projects were implemented following a structured project-based learning framework that included stages of circuit analysis, simulation, prototyping, debugging, and system integration. Learning outcomes were evaluated through project deliverables, technical performance of the implemented circuits, instructor observation, and qualitative analysis of recurrent design errors and solutions. The results indicate that audio-based projects facilitate the assimilation of key concepts in analog and nonlinear electronics, including multistage amplification, clipping and distortion mechanisms, frequency response, biasing techniques, and practical implementation constraints. Immediate auditory and visual feedback allowed students to identify design issues more efficiently and strengthened the connection between theoretical principles and practical implementation. Additionally, higher levels of student autonomy and engagement were observed compared to highly guided traditional laboratory activities. These findings suggest that audio-based project-based learning constitutes an effective approach for teaching analog and nonlinear electronics in undergraduate engineering education.

This mixed study explores the relationship between thinking styles (TS) and opportunity recognition capability (OR). We sampled engineers and technicians currently studying engineering as a second profession and engineering post-degree. Respondents have a predominant rational TS. Age and work experience have a positive relationship with rational TS. There is a difference in OR level between technical and post-degree respondents. Age, work experience, entrepreneurship experiences, and tenure have a positive correlation with OR level. We found clues to that respondents’ rational thinking style, could have a positive effect on OR. We triangulated the quantitative results by a semantic analysis of the item statements. This work contributed to entrepreneurial cognition research questioning the theory of OR as the result of a simple structural alignment between structural knowledge and market events. Also, for engineering education we explore the relationship between engineering students' cognitive processes and entrepreneurial skills.

This project presents the design of a Hass avocado peeling and pitting machine. The main objective is to develop an efficient, safe, and accessible mechanism that automates the stages of transport, peeling, seed extraction, and pulping.
To achieve this, the physical characteristics of the fruit, the mechanical properties of the seed, and the application of pneumatic systems in the food industry are analyzed. The design incorporates a conveyor belt calculated according to technical standards, a seed drilling and extraction system using a piston and drill bit, and a pulper based on rollers driven by an industrial geared motor.
The results show that it is possible to implement a robust mechanized system adaptable to national production capacities, making this process more efficient and accessible.

The use of generative artificial intelligence (GenAI) tools in introductory computer science courses can support learning, but it also entails the risk that these tools may be used as a substitute for students’ own reasoning. This paper presents, as its main contribution, an analysis of the detection of non-formative use of GenAI in a mandatory assignment of a Computer Science 1 course. The course included the use of explicit instructional guidelines, recommendations, and activities for formative GenAI use. The study was conducted during the second semester of 2025. Throughout the course, activities integrating GenAI were implemented with a focus on formative roles. An automated rubric was designed to identify coding patterns that are not expected in first-semester students. The results of the automated analysis were contrasted with students’ performance in oral assessment sessions. The results show that 42% (5 out of 12) of the submitted assignments exhibited strong indications of non-formative GenAI use, evidenced by a mismatch between the characteristics and complexity of the submitted code and the level of understanding demonstrated during the corresponding oral assessment.