Transforming Community Q&A System Content into Learning Objects

Technical advancements and expertise have progressed significantly compared to previous centuries, demanding efficient and fast methods for acquiring knowledge. This work explores the potential of Q&A systems by transforming their content into Learning Objects. Q&A systems offer quick answers and problem-solving without extensive study of scripts and documentation. The concept of Learning Objects is thoroughly analyzed and defined, with a focus on decomposing content into smaller units. Learning Objects are created and mapped to Q&A content at the lowest level of decomposition. Additionally, the composition of educational components from Q&A content is examined, emphasizing reusability and decomposability. The proposed transformation method is implemented through experiments involving manual and automated identification of Learning Objects, creating a tree structure of functionality increments. Reverse transformation of content is also described, with experiments conducted for both manual and automated processes.