This paper provides a summary account of Activity-Centred Analysis and Design (ACAD). ACAD offers a practical approach to analysing complex learning situations, in a way that can generate knowledge that is reusable in subsequent (re)design work. ACAD has been developed over the last two decades. It has been tested and refined through collaborative analyses of a large number of complex learning situations and through research studies involving experienced and inexperienced design teams. The paper offers a definition and high level description of ACAD and goes on to explain the underlying motivation. The paper also provides an overview of two current areas of development in ACAD: the creation of explicit design rationales and the ACAD toolkit for collaborative design meetings. As well as providing some ideas that can help teachers, design teams and others discuss and agree on their working methods, ACAD has implications for some broader issues in educational technology research and development. It questions some deep assumptions about the framing of research and design thinking, in the hope that fresh ideas may be useful to people involved in leadership and advocacy roles in the field.
A. Grigoryan, and S. Agaian. Applied Mathematics and Sciences: An International Journal (MathSJ), volume 1 of IFIP Advances in Information and Communication Technology, page 23-39. Springer, (December 2014)
P. D, C. Veeramani, B. Shalini, and R. Karthika. International Journal of Innovative Science and Modern Engineering (IJISME), 2 (10):
41-45(September 2014)
A. Park, B. Beck, D. Fletche, P. Lam, and H. Tsang. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), page 880-883. (August 2016)
F. Haak. Information between Data and Knowledge, volume 74 of Schriften zur Informationswissenschaft, Werner Hülsbusch, Glückstadt, Gerhard Lustig Award Papers.(2021)
R. O'Donnell. (2021)cite arxiv:2105.10386Comment: First edition originally published April 2014, in hardcover book format by Cambridge University Press, and electronically on the author's website. This arXiv version corrects 100+ typos and errors, but is otherwise essentially the same.
J. Kim, P. Guo, D. Seaton, P. Mitros, K. Gajos, and R. Miller. Proceedings of the First ACM Conference on Learning @ Scale Conference, page 31–40. New York, NY, USA, Association for Computing Machinery, (2014)