Learning Environment Design – ED403 MicroLED

 Learning Environment Design – ED403 MicroLED

In this blog post, I will be reflecting on the preparation and planning process I undertook for my microteaching presentation. This task is part of Learning Task 7 (LT7) for ED403 and focuses on the Micro Learning Environment Design (MicroLED). The objective was to design a short, focused lesson and present it in a way that aligns with sound pedagogical practices.

For this purpose, I selected EE461 – Special Topics in Electrical and Electronics Engineering, a final-year course within the Bachelor of Engineering in Electrical and Electronics (BENGEE) program. The topic chosen for the 15-minute microteaching session was “Mastering Machine Learning – Classification Workflow”.

Design Attributes Considered

Audience:

Understanding my audience was key. These are final-year engineering students with prior exposure to machine learning concepts through EE211. Therefore, I was able to go beyond introductory content and dive deeper into practical applications using MATLAB. I made sure to use real-world biomedical data (heart sounds) to keep the session relatable and application-oriented.

Objectives/Learning Outcomes:

The lesson was aligned with the course’s broader learning outcomes, particularly in analytical thinking, computational proficiency, and applied technical knowledge. I developed clear lesson outcomes that would help students:

  • Understand the classification workflow

  • Apply MATLAB for model training

  • Interpret evaluation metrics like accuracy and confusion matrix

Delivery Method:

The session was designed for interactive, visual delivery. I used annotated slides and embedded MATLAB code demonstrations to show the actual process of training and evaluating a model. Questions I kept in mind while preparing included:

  • Can students clearly follow the workflow visually and conceptually?

  • Are the MATLAB tools used accessible and familiar?

  • Does the explanation pace align with their prior knowledge?

Content:

The content focused on a practical classification example using Heart Sound data. I introduced Mel-Frequency Cepstral Coefficients (MFCCs) for feature extraction and used MATLAB’s toolboxes to handle training and evaluation. Real-world context enhanced the students’ understanding of how machine learning can be used in biomedical diagnostics.

Assessment Strategy:

I included a formative assessment where students analyzed the confusion matrix of a pre-trained model. This allowed them to reflect on model performance and understand where classification errors occur.

Student Engagement:

Students were encouraged to think critically by linking the lesson to broader applications beyond healthcare, such as speech recognition or vibration diagnostics. This sparked curiosity and demonstrated the transferable value of the techniques discussed.

Time Factor:

Since the microteaching was limited to 15 minutes, I made sure the session was tightly structured. Key concepts were introduced briefly but clearly, and hands-on parts were paced carefully to ensure comprehension without information overload.

Watch the MicroLED Presentation

Here is the link to my MicroLED video presentation:
🎥 https://drive.google.com/file/d/1_nyvXChIHJUmK3ui8d9ODwT-onlSwcz7/view?usp=sharing

Resources Used

  • MATLAB Central File Exchange – Heart Sound Classifier

  • Audio samples, MATLAB toolboxes for classification, and MFCC feature extraction



Comments

Post a Comment

Popular posts from this blog

Learning Technologies: Shaping the Future of Higher Education Globally and in the Pacific

Learning technologies are rapidly reshaping education, creating opportunities for students and educators to extend far beyond traditional classrooms. Globally, digital advancements like Massive Open Online Courses (MOOCs), interactive softwares, and diverse multimedia platforms have made education more accessible, customizable, and engaging. However, while these global trends point to a promising future, their impact must be carefully contextualized, particularly in the Pacific Islands. In the global context, learning technologies facilitate personalized learning experiences and promote higher-order thinking skills such as critical reasoning, creativity, and problem-solving. Platforms like Coursera, UDEMY and edX enable learners worldwide to engage with top-tier institutions, breaking geographic barriers and democratizing education. This benefits educators with increased flexibility, leveraging digital tools to tailor their instructional methods to students' unique learning styles ...
Read more

E-Learning and the Future of Higher Education in the Pacific

Image
  In an age where technology is deeply integrated into our everyday lives, higher education (HE) must evolve to stay relevant and accessible. E-learning, once considered an enhancement, is now a necessity. From virtual classrooms to AI-powered assessment tools, the way students learn and teachers teach has transformed dramatically in the last decade—and it’s only growing faster !! Revolutionary union of social media and education   BYOD: Learning in Your Pocket Bring Your Own Device (BYOD) is no longer a trend—it’s a baseline expectation in many higher education institutions. Students bring smartphones, tablets, and laptops into classrooms or log in from home, allowing learning to happen beyond the traditional brick-and-mortar setup. In the Pacific Island Countries (PICs), BYOD has made learning more accessible in remote areas where university labs may not be easily reachable. However, it's essential to strike a balance between accessibility and data privacy, especially with...
Read more