
Our Pedagogy
COMPUTING & TECHNOLOGY QUALITY FRAMEWORK


Project Based Learning
We use project-based learning to provide learners with the opportunity to apply and consolidate their knowledge and understanding. Design is an important but overlooked aspect of computing. Our courses focus on key projects that you will create and add to your portfolio! We use project-based learning activities that enable students to apply and consolidate their knowledge and understanding.

Semantic Waves
We teach new concepts by first unpacking complex terms and ideas. There are several technical terms that have precise technical meanings in the world of computing. In many of our programs we explore these ideas first in unplugged and familiar contexts, then repacking this new understanding into the original concept. This approach also known as semantic waves can help learners develop a secure understanding of complex concepts.

Culturally Relevant Pedagogy
For computing to be relevant, engaging, and accessible to all, a lot of thought is put in our curriculum, materials, and teaching practices. Students find learning to be highly interactive and enjoyable when they are able to personally relate and apply their interests and experiences to the projects they build. Our instructors will draw on the breadth of students’ experiences and cultural knowledge, facilitate projects that have personal meaning for learners, and discuss issues or problems that students find most passionate about!
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Distilling Big Concepts
Exploring the world of computing and technology can be intimidating especially when things begin to become technical. As a result we often use the “Big Word Alert!” which support students' acquisition of knowledge, through the use of BIG key concepts, terms, and vocabulary. We distill concepts by first identifying and then breaking down concepts or theories into fundamental learning components and then provide opportunities for students to build their understanding from there. Glossaries with concept maps, and regular recall and revision will support this approach.

A to Z, starting with Y
Our lessons focus not just on exploring things on a surface level, but inquisitively diving deep into core topics. We strive to make our programs as wide and deep as possible by providing learning activities with different levels of direction, scaffolding, and support that promote learning. But most importantly we begin by getting students to ask and understand the “why?”. Why are they learning the things they do and why things are the way they are? By adding additional context for example historical background learners will be better engaged and encouraged for greater independence in learning.

Adaptive Learning
Every individual is unique with different learning preferences and habits. Therefore instead of trying to conform students into a rigid curriculum or lesson plan we try to customize and adapt learning outcomes according to one's ability and progress. For instance when teaching programming we would focus first on code 'reading' activities, before code writing. The rate at which new concepts are introduced is dependent on a student's ability to review and interpret code. Learning follows a methodical approach from reading, tracing, explaining and finally writing code.
Our Learning Pillars
Leveraging AI Technologies
We teach students how to work with AI, not rely on it.
By learning to prompt, evaluate, and apply AI tools thoughtfully, they turn AI into a creative and problem-solving partner.
Google's Gemini
Students explore how to use Google Gemini to generate ideas, solve problems, and enhance their learning. They also learn to use AI thoughtfully and responsibly.
GPT
Used as a thinking companion to explore ideas and break down complex concepts. Students learn to ask better questions and evaluate AI responses critically.
GitHub Copilot
Introduces students to real-world coding workflows. They learn to read, refine, and debug AI-assisted code while strengthening fundamentals.
Perplexity
Supports smart, responsible research in an AI-driven world. Students learn to verify sources and think critically about information.
Our Focus
Computational thinking develops students’ skills in problem solving through algorithmic thinking and design. Acquisition of programming language skills is usually a part of this area of learning. Computational thinking, as defined by Jeannette M. Wing , is a way people solve problems and that it is not about trying to get people to think like computers. This often involves thinking and problem-solving processes to reformulate a seemingly difficult task into one we know how to solve.
Thus, computational thinking, is a fundamental skill for everyone, not just computer scientists and programmers. Systems thinking develop students in the design and creation of systems and solutions through processes in problem definition, system analysis, and systems design.
Our Focus
Computational thinking develops students’ skills in problem solving through algorithmic thinking and design. Acquisition of programming language skills is usually a part of this area of learning. Computational thinking, as defined by Jeannette M. Wing , is a way people solve problems and that it is not about trying to get people to think like computers. This often involves thinking and problem-solving processes to reformulate a seemingly difficult task into one we know how to solve.
Thus, computational thinking, is a fundamental skill for everyone, not just computer scientists and programmers. Systems thinking develop students in the design and creation of systems and solutions through processes in problem definition, system analysis, and systems design.
Thus, computational thinking is a fundamental skill for everyone, not just computer scientists and programmers. Systems thinking develop students in the design and creation of systems and solutions through processes in problem definition, system analysis, and systems design.
Our Focus
Computational thinking develops students’ skills in problem solving through algorithmic thinking and design. Acquisition of programming language skills is usually a part of this area of learning. Computational thinking, as defined by Jeannette M. Wing , is a way people solve problems and that it is not about trying to get people to think like computers. This often involves thinking and problem-solving processes to reformulate a seemingly difficult task into one we know how to solve.
