The HCI community has a strong tradition of merging discourse and practice, whilst drawing upon and involving users’ and practitioners’ experience and behaviors. 
This practice is crystallized in the courses and programs of study developed and led by HCI educators and offered to undergraduate and post-graduate students. Furthermore the creation of open educational resources (OERs) and massive open online courses (MOOCs) suggests that informal and independent learning may also have a role to play in the evolution and innovation of academic curricula.
Regarding to the phenomenon, there are two aspects of the course curriculum: first, establishment of course discipline as an academic autonomy and flexibility to adapt interdisciplinary development, and second, academic responsibility for requirements of learners to develop human resources as academic researchers and engineers in industry area. For both demands, any kinds of visualization of learning contents and activity for the course should be provided.
This workshop provides an opportunity to combine international perspectives of teaching with a reflection on the HCI component of the 2013 revision of the ACM/IEEE computer curriculum document [3,4].  It provides an opportunity to compare and discuss experiences from both HCI and Web Science communities. It will provide an opportunity to consolidate learnings amongst practitioners drawing out connections with previous work on curriculum definition [1,2,5,7] and further sharing of identified good practice [4].


Educationally, merging discourse and practice and drawing upon and involving user communities our repertoire of approaches is broad; typically nuanced to our particular national, cultural and organizational contexts. In the HCI classroom, lecture hall and lab we seek ideally to preserve and mirror the practice of the HCI researcher and specialists.  However we observe that some distance has arisen between our routine educational activities and processes and the educational outcomes which we are pursuing for our students to achieve.
Though the academic discipline such as HCI globally consists of core/common knowledge which reflects concurrent research work, both lecturer experiences and structure of curriculum may bias the teaching and learning of participants. The consistency of teaching content in a course is sometimes shifted when the core/common curriculum is introduced. Fortunately, each course provides contents of teaching and learning as in text as syllabus, the consistency of the course and structure of curriculum can be extracted [9-11].
The traditional and pragmatic approaches to teaching can be seen as a consequence of balancing available expertise, preferences, workloads and academic expectations. Furthermore, there is an inevitable tension within any stated curriculum between the formal definition and specification necessary for accreditation and standardization, and the realities of educational institutions as it is practiced. The challenge generated by these tensions is deepened by the need to constantly evolve and respond to contemporaneous educational needs and the wants of business and technology.
In business there is an increasing demand for well-informed and technically skilled graduates and postgraduates. Too often, however, students are being taught and guided through sets of fundamentals that were identified and established when computing and informatics were first emerging as a discipline.
Also, student’s responses such as learning activity and their impression through the course immediately presented and exchanged using the social media applications, in particular on open courses. These responses should be evaluated as the academic reputation of the course for learner’s satisfaction [12].  Also, industrial society, as an acceptor of developed human resources in academic institutes, are sensitive for performances of graduates.
The evolution of rapidly changing and increasingly diverse and sophisticated web-based systems provides evidence to justify revising our definitions of the core computing/informatics curriculum. Additional evidence can be derived from web scientists who are establishing a research framework that studies the theory and practice of social machines [6,8]. These insights and understandings are highly valuable in advancing our understanding of how we manage, build and evolve the web and its associated human interactions.


  1. Adamczyk, P. D., &Twidale, M. B. (2007). Supporting multidisciplinary collaboration: requirements from novel HCI education. Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 1073–1076). New York, NY, USA: ACM. doi:10.1145/1240624.1240787
  2. ACM. (1992). ACM SIGCHI curricula for human-computer interaction. New York, NY, USA.
  3. ACM Curriculum 2013 website
  4. Fincher, S., Cairns, P., & Blackwell, A. (2012). A contextualised curriculum for HCI. Proceedings of the 2012 ACM annual conference extended abstracts on Human Factors in Computing Systems Extended Abstracts (pp. 2707–2710). New York, NY, USA: ACM. doi:10.1145/2212776.2212701.
  5. Hascoët M. and Rodriguez, N. June 4 – June 6 2008. Curricula of HCI and Computer Graphics: From Theory to Practice. In Proceedings of the Sixth LACCEI International Latin American and Caribbean Conference for Engineering and Technology (LACCEI’2008) “Partnering to Success: Engineering, Education, Research and Development” (Tegucigalpa, Honduras).
  6. Meira, S. R. L., Buregio, V. A. A., Nascimento, L. M., Figueiredo, E., Neto, M., Encarnacao, B., & Garcia, V. C. (2011). The Emerging Web of Social Machines. Proceedings of the 2011 IEEE 35th Annual Computer Software and Applications Conference (pp. 26–27). Washington, DC, USA: IEEE Computer Society. doi:10.1109/COMPSAC.2011.12.
  7. Sahami, M., Roach, S., Cuadros-Vargas, E., & Reed, D. (2012). Computer science curriculum 2013: reviewing the strawman report from the ACM/IEEE-CS task force. Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 3–4). New York, NY, USA: ACM. doi:10.1145/2157136.2157140.
  8. White, S., & Vafopoulos, M. (2012). Web science: expanding the notion of computer science. Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 349–354). New York, NY, USA: ACM. doi:10.1145/2157136.215724
  9. Mima, H. (2006). Structuring and Visualizing the Curricula with MIMA Search, Proceedings of APRU DLI conference 2006 (pp.70-77).
  10. Sekiya, T., Matsuda, Y., Yamaguchi, K. (2009) Analysis of Curriculum Structure Based on LDA, Proceedings of the World Congress on Engineering and Computer Science 2009 (pp.561-566).
  11. Sekiya, T., Matsuda, Y., Yamaguchi, K. (2010) Analysis of Computer Science Related Curriculum on LDA and Isomap, Proceedings of ACM ITiCSE’10 (pp.48-52).
  12. Okumura, M. (2013) Social Media Mining (in Japanese), IEICE Fundamental Review, Vol.6, No.4, pp.285-293.