Tag: Academia – Projects

Reimagining the Engineering Classroom: New Collection on GenAI and the Cognitive Learning Curve

260701 – Discover Education eFlyer_Reimagining Engineering Pedagogy Balancing Cognitive Development and Generative AI in Computational Learning

When Springer Nature first approached me to submit a proposal for a new journal collection, it happened to be Week 5 of the lecture semester. As I stood in front of my class, a realization crossed my mind about how much the landscape of teaching has shifted.

Today’s students have an incredible wealth of resources right at their fingertips. With the rise of Generative AI (GenAI), sourcing facts, generating code, or finding answers is no longer a challenge. Information is practically instantaneous.

But as educators, we face a dilemma – well, at least, I do.

You can ask AI to generate an answer, but you cannot outsource “understanding.” True understanding is an internal, deeply personal cognitive process. It is that suara hati (the inner voice) where a student rationalizes a problem, wrestles with the logic, and finally externalizes it by explaining or applying it.

In engineering education, where technological breakthroughs move at breakneck speed, simply banning or restricting AI in the classroom is an outdated approach. Yet, granting unfettered access without a proper pedagogical framework presents a dangerous risk: it dilutes the actual human learning curve and breeds cognitive dependency. How do we ensure our future engineers are still learning how to think, not just how to prompt?

Driven by this exact tension, I submitted a proposal that was recently accepted by Springer Nature’s Discover Education journal: “Reimagining Engineering Pedagogy: Balancing Cognitive Development and Generative AI in Computational Learning.” 🙂

The ultimate aim of this collection is to create a collaborative space where we can learn from best practices, empirical observations, and innovative frameworks developed by educators across the global engineering segment. We want to uncover how to design learning environments where GenAI acts as a technical accelerant without bypassing the essential human cognitive processing required for true mastery.

Join the Conversation & Submit Your Work

To all fellow engineering educators, researchers, and practitioners out there: if you are actively navigating this paradigm shift in your classrooms—whether in electrical, mechanical, civil, chemical, or software engineering—I warmly invite you to submit your research, case studies, or conceptual frameworks to this collection.

Let’s work together to shape the future of how engineering is taught.

View the official collection webpage and submission guidelines here: Click here to view the Collection Webpage

Note: The official Call for Papers document containing the detailed scope and submission timelines is attached below/on the website for your reference. Please feel free to reshare this call within your academic networks! Looking forward to your valuable submissions.

Publication 2026/3 – Empowering STEM Outreach Programs Through Collaborative Innovation

This year marks a meaningful milestone for the UMPSA STEM Lab — ten years of exploring how we can make STEM learning more engaging, accessible, and relevant. What started as a small initiative has gradually grown into a vibrant community of student mentors, university advisors, collaborators, teachers, and learners who share a common goal: nurturing curiosity and building meaningful digital making skills.

Thank you to all the student mentors, university advisors, and collaborators who have contributed to this journey. The STEM Lab is a collective effort of dedication, creativity, and willingness to experiment, refining teaching modules, and continuously improving the way STEM activities are delivered.

Over the past decade, the STEM Lab has served not only as an outreach platform but also as a space for pedagogical exploration. One of the central questions guiding our work has always been: What is the best way to introduce digital making and engineering thinking to learners? Through workshops, classroom activities, and collaborative programs, we have explored various approaches to make STEM learning more experiential and meaningful.

The programs focuses on developing effective teaching approaches for digital making skill sets and engineering concepts for school children and university students. Engineering concepts such as microcontrollers, IoT systems, FPGA-based digital design, and AI can often feel abstract when taught purely through lectures. The STEM Lab therefore serves as a platform to explore how these concepts can be delivered through hands-on, project-based learning, allowing students to connect theoretical knowledge with practical system development. In this sense, the lab functions as a living environment for engineering education, where ideas about teaching and learning can be tested and refined.

A major component of our work revolves around physical computing. Learning becomes far more engaging when students can interact with the physical world. Over the years, our modules have incorporated a wide range of microcontrollers (Arduino, ESPs), Raspberry Pi single-board computers, and embedded platforms, allowing learners to build systems that sense, respond, and interact with their environment. Through projects involving sensors, actuators, and robotics, students experience firsthand how software and hardware come together to create interactive systems.

Alongside hardware development, programming has always been a central pillar of the lab’s activities. To support learners with different levels of experience, we adopt a gradual progression from block-based programming to line-based programming. Beginners can quickly explore ideas through visual programming environments, while more advanced learners transition toward structured coding, developing deeper understanding of programming logic and computational thinking.

In recent years, the lab has also expanded into AI and embedded intelligence. Using platforms such as Edge Impulse, learners can experiment with edge AI applications such as image classification, demonstrating how machine learning models can run directly on embedded devices. These activities introduce students to the growing field of intelligent systems, where sensing, data processing, and decision-making can occur at the edge.

More recently, the STEM Lab has begun integrating FPGA-based modules into its learning ecosystem. By exposing learners to hardware-level digital design and parallel processing concepts, these modules provide a deeper understanding of how modern embedded systems are built. Together, these platforms form a learning progression, from physical computing to embedded systems, edge AI, and advanced digital architectures.

Looking back over the past ten years, the most meaningful outcome is not simply the number of workshops conducted or technologies introduced. Rather, it is the community that has grown around the STEM Lab. Many of our former mentors have continued their journeys in engineering, research, and education, carrying forward the spirit of exploration that began in the lab.

As we move into the next decade, we hope to continue expanding this ecosystem, strengthening collaborations with educators, researchers, and industry partners while refining how digital making and embedded systems are taught. The future of technology will require not only technical expertise but also creativity, curiosity, and collaboration. These are the values that the STEM Lab strives to cultivate.

To everyone who has been part of this journey — mentors, advisors, collaborators, teachers, and learners — thank you for contributing your time, ideas, and passion. The past ten years have been an incredible learning experience, and the next chapter promises to be just as exciting.