Python Programming 2024/1 – MRSM Tun Abdul Razak

*UMP STEM Lab Python Programming Synopsis can be found here.

30 students and teachers from MRSM Tun Abdul Razak Pekan  had participated in this program. Students have gone through activities such as creating a video game, named as Slider Game, using Python Programming.

The Slider Game is a puzzle game where players move a character within a grid to reach a goal. The challenge is to navigate the player and hit the enemies. This game helps beginners learn programming concepts and develop problem-solving skills. It started off by learning Python, a beginner-friendly language, and use the Pygame library to create the game environment, handle graphics, and manage user input. Students later progress to understand the basics like variables, loops, and conditionals. They later proceed to implement movement and collision detection, adding winning conditions and polish the game with features like scoring.

Developing a game reinforces programming concepts.It enhances logical thinking and creativity. The interactive nature of games keeps learners motivated. Games provide immediate feedback, helping learners correct mistakes quickly.

Thank you Fadhillah for coordinating the communication between UMP STEM Lab and the participants.

mBlock Programming 2024/2 – SMK Seri Saujana

A synopsis of the program can be retrieved via the following link.

In the program, 30 participants from SMK Seri Saujana were introduced to mBlock programming, learning to use its graphical interface to create sequences of instructions. They explored sequential programming, conditional statements, and loops through hands-on tutorials. These foundational skills were applied in two projects: a Snake game and a Pac-Man game. In the Snake game, they programmed the snake’s movement, growth, and collision detection, while in the Pac-Man game, they navigated a maze, collected points, and avoided ghosts. This approach provided a comprehensive understanding of programming concepts and their practical applications.

Appreciation to Cikgu Hans for coordinating the communication between the participants and UMP STEM Lab.

 

Publication 2024/2 – Assessing Information Literacy Levels Among Underprivileged Communities

SCImago Journal & Country Rank

Today digital literacy is crucial for personal and professional growth, understanding and improving Media and Information Literacy (MIL) among underprivileged communities is more important than ever. I’m excited to share my recently published study 🙂 in the Journal of Media Literacy Education (Vol. 16, Iss. 2, 2024 Q2). This journal documented the work with regards to the levels of MIL within the underprivileged/underrepresented communities, uncovering both strengths and areas needing improvement.

This work is inspired by the experiences gained through the Celik Digital @ UMP STEM Lab project, in collaboration with the UNESCO Information for All Programme (IFAP) back in 2020, where the four dimensions of MIL were explored: access, evaluate, create, and awareness. This foundation laid the groundwork for this research, focusing on underprivileged communities in Pahang, Malaysia, during 2021-2022. Understanding the unique challenges faced by these communities, the study sought to break the cycle of poverty by enhancing information and media literacy.

Motivated by the previous work and need to provide targeted interventions, this study aimed to assess the MIL levels among 366 participants from underprivileged backgrounds. Rooted in the UNESCO MIL framework, we concentrated on evaluating the participants’ abilities to retrieve, critically evaluate, and manage information, as well as their awareness of data privacy.

The findings revealed several critical insights:

  1. Digital Literacy and online behavior, where it highlighted varying levels of digital literacy among the participants. While some showed proficiency in basic digital tasks, there were significant gaps in higher-order skills such as critical evaluation and ethical content creation.
  2. Awareness of data privacy was another crucial aspect assessed in this study. It became evident that while some participants were aware of basic privacy practices, there was a need for more comprehensive education on protecting personal information online.
  3. The findings emphasized the importance of targeted interventions tailored to the specific needs of underprivileged communities. Enhancing critical thinking skills, promoting effective online communication strategies, and fostering a deeper understanding of digital security were identified as key areas for improvement.

I believe this study offer some input for policymakers, educators, and community organizations. By understanding the unique challenges faced by underprivileged communities, targeted interventions can be developed to narrow the digital divide. Enhancing MIL within these communities is not just about providing access to technology but also about equipping individuals with the skills needed to navigate the digital world responsibly and effectively.

By focusing on enhancing digital literacy among underprivileged communities, individuals (including the vulnerable segment of underprivileged communities) are empowered to make informed decisions, protect their privacy, and engage meaningfully in the digital society.

 

Computational Thinking and AI in Robotics

UMPSA STEM Lab Robotics module now expanding to include Computational Thinking (CT) and Artificial Intelligence (AI) 🙂 . This new modules build on the foundation of the lab’s existing Arduino robotics curriculum, taking students from basic robotics to advanced AI applications.

The Arduino modules (programming & robotics) introduce participants to programming concepts and the fundamentals of robotics using Arduino, an open-source platform. Students learn about digital and analog input/output, integrating and programming sensors, and controlling actuators. They get hands-on experience with various sensors such as infrared (IR) sensors, ultrasonic sensors, and accelerometers. Additionally, they learn about Pulse Width Modulation (PWM) for motor speed control.

By the end of the module, participants build their own line-following or obstacle-avoidance robots using a two-wheel miniature robot. This hands-on project not only reinforces their learning but also sparks their interest in the endless possibilities of robotics.

Introducing Computational Thinking in Robotics
This new Computational Thinking (CT) and AI in Robotics module takes this learning a step further. Participants will now look into the strategic aspects of robotics, focusing on how to make their two-wheel miniature robot choose the best path from the start to the destination on a track. This involves:

  1. Decompose – Breaking down the mission into smaller tasks, such as detecting lines, making turns, and avoiding obstacles.
  2. Patterns – Identifying patterns in the robot’s environment and behavior to predict and plan the robot’s movements.
  3. Abstractions – Simplifying complex tasks by focusing on the essential details needed to solve a problem.
  4. Algorithms – Developing step-by-step instructions for the robot to follow, ensuring it navigates the track efficiently.
  5. Logical Reasoning – Using logical conditions to decide when the robot should turn, go straight, or stop.
  6. Evaluation – Testing and refining the robot’s performance to ensure it follows the shortest or fastest route accurately.

Through coding and hands-on experimentation, students will program their Arduino robots to follow lines (either black or white) and navigate through the track using CT principles. This practical approach helps them understand and apply CT concepts in real-world scenarios.

The activity doesn’t stop with CT. We further extend the module to include AI in robotics, focusing on image processing as a key application. Using the ESP camera onboard the robots, participants will capture and classify images. They will engage in image augmentation, generating multiple images with different sizes, tilts, and orientations to create a diverse dataset.

The training process involves teaching the AI model to recognize patterns and classify images accurately. Once the best model is generated, it is deployed onto the Arduino platform. Participants then code their robots to use this AI model, enabling them to scan images, follow lines, and perform tasks such as picking and placing items accordingly.

The modules are designed to provide students with a comprehensive understanding of both computational thinking and AI. By integrating these concepts into their robotics projects, students gain valuable skills that are highly relevant in today’s technology-driven world.

From understanding the basics of robotics to developing sophisticated AI models, participants at UMP STEM Lab are equipped with the knowledge and experience to tackle complex problems creatively and effectively. Our hands-on approach ensures that learning is both engaging and practical, preparing students for future challenges in STEM fields.

Let’s explore, learn, and innovate.