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As part of this project small workshops in linear algebra where held both nationally and internationally. The main workshop website is https://sites.google.com/view/tusdcu-linearalgebraworkshop/home
A one day workshop to help bring together early stage researchers to learn and discuss topics in Linear algebra.
Linear algebra is frequently introduced to first or second year undergraduates, and afterwards its results and concepts are taken for granted. But it is the rare undergraduate who understands the full details of the Jordan Canonical Form at the first presentation. In this short course, we will devote one morning to a complete analysis of a linear operator in terms of generalised eigenvalues. We will explain the significance of the Cayley-Hamilton theorem (and why no-one states the result appropriately). In the end, we will have a thorough understanding of the structure underlying the Jordan Form. Our approach will be mostly elementary, though we may use the word ‘module’ on occasion.
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This OER presents findings from a comparative study of novice programmers engaging in face-to-face and hybrid pair programming. It explores collaboration patterns, role switching, satisfaction, and challenges, offering evidence-based insights for educators seeking to prepare students for effective teamwork in modern hybrid software development.
This OER explores novice programmers’ experiences of pair programming across face-to-face, hybrid, and remote settings. It provides insights into collaboration, role switching, satisfaction, and challenges, helping educators and students understand how to effectively prepare learners for modern hybrid software development environments.
This OER guides students through human-in-the-loop software development, demonstrating how AI tools can be effectively supervised, refined, and integrated across the Software Lifecycle. Designed for computing educators and learners, it combines agile practice, teamwork, DISC awareness, testing, and critical reflection on human–AI collaboration.
This OER introduces students to designing and developing AI-powered assistants for agile software development using Flowise (no code). Learners as a team explore Retrieval Augmented Generation (RAG) and agent-based systems, applying AI to real-world agile practices while considering technical design, evaluation, and cost-aware decision-making
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URL: https://tus.libguides.com/c.php?g=715183&p=5178010&preview=21c4fb2c61a37aeabf1e57e1276d68d3
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