TDT 37 Organisations and ICT («Digitalization in practice»)


Teacher & course responsible: Eric Monteiro,


Format: The course is student-driven. There is no ordinary lecturing, only brief injections from the teacher. There are 5 sessions, one for each of the topics we cover. Students are divided into groups and will for every session present written and orally one assigned paper from the topic of that session.


NOTE:  Due to format, there are maximum 20 students. All students need to enroll by contacting Eric Monteiro by email and receive a confirmation ( )


Language: Open to English-speaking students

Credits: 3,75 credits (“studiepoeng”)

Exam: Oral exam


Reading list


The papers on the reading list will be made electronically available from the NTNU domain for the students.


We cover 5 topics, one pr. session. For each topic, the first paper (in grey box) on the list is presented by the teacher. The other papers are assigned, one to each group of students, for written and oral presentation during our sessions.


1. Design vs use of technology


Design of technology is anticipating a future patterns of use. But are these expectations well founded? How accurate are our expectations of future use during design? And what do users – in practice - do when using the technology?


Les Gasser. (1986). The integration of computing and routine work. ACM Trans. on Office Information Systems, 4(3):205 - 225.


E Nygren and P Henriksson, (1992) Reading the medical record. Analysis of physicians’ ways of reading the medical record, Computer methods and programs in medicine, 39: 1 - 12


Farshchian, B.A., Vilarinho, T. and Mikalsen, M., (2017). From episodes to continuity of care: A study of a call center for supporting independent living. Computer Supported Cooperative Work (CSCW), 26(3), pp.309-343.


L. Suchman and R. Trigg. (1991) Understanding practice: video as a medium for reflection and design. In Joan Greenbaum and Morten Kyng, editors, Design at work, pages 65-90. Lawrence Erlbaum Associates.


Svanæs, Dag, Ole Andreas Alsos, and Yngve Dahl. (2010) Usability testing of mobile ICT for clinical settings: Methodological and practical challenges. International Journal of Medical Informatics 79.4: e24-e34.


2. Digital transformation


Digital transformation is a process. Digital technologies are a necessary but hardly sufficient condition. How does this process unfold over time? What and who drives it – or does it unfold ‘automatically’ by itself?


E Monteiro and V Hepsø. (1998) Diffusion of information infrastructure: mobilization and improvisation, In Information systems: current issues and future challenges, TJ Larsen, L Levine and JI DeGross (eds.), IFIP, pp. 255 - 273.


S Sahay and D Robey, (1996). Transforming work through information technology: a comparative case study of geographic information systems in county government, Information Systems Research, 7(1):63-92.


Brynjolfsson, E., Rock, D. and Syverson, C., (2017). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. National Bureau of Economic Research.


Leonardi, P.M., (2013). When does technology use enable network change in organizations? A comparative study of feature use and shared affordances. MIS Quarterly, pp.749-775.


WJ Orlikowski. Improvising organisational tranformation over time: a situated change perspective, Information Systems Research, 7(1):63 - 92, 1996.


3. User (= customer?) centred design


The importance of engaging the user/ customer in the process of developing digital solutions is emphasised in many areas – in user-centred design, in agile software development and in participatory design. What are the different arguments that underpin the motivation – and what is the empirical evidence for the benefits of user participation?


Kensing, F. and Blomberg, J. (1998). Participatory design: Issues and concerns. Computer supported cooperative work (CSCW), 7(3-4), pp.167-185.


Hope, K.L. and Amdahl, E., (2011). Configuring designers? Using one agile project management methodology to achieve user participation. New Technology, Work and Employment, 26(1), pp.54-67.


Bratteteig, T., & Wagner, I. (2016). Unpacking the notion of participation in participatory design. Computer Supported Cooperative Work (CSCW), 25(6), 425-475. 

Ina Wagner. (1992) A web of fuzzy problems: confronting the ethical issues. Communications of the ACM, 36(6):94-101, 1993. Also published in Participatory Design Conference (PDC) '92.


M. Hatling og K. H. Sørensen. (1998) The construction of user participation. In The specter of participation, Knut H. Sørensen (ed.), Scandinavian Univ. Press.


4. Collaborate


Information systems are traditionally individually oriented in the sense of being focused on the needs of an individual user. This is fundamentally different for collaborative information systems (“computer supported cooperative work”, CSCW), where the aim is to support collaboration between groups of users. We look at similarities and differences between CSCW and more traditional systems.


Jonathan Grudin. (1989) Why groupware applications fail: Problems in design and evaluation. Office: Technology and People, 4(3):245-264, June 1989.


Winthereik, B. R., & Vikkelsø, S. (2005). ICT and integrated care: some dilemmas of standardising inter-organisational communication. Computer Supported Cooperative Work (CSCW), 14(1), 43-67.


Wanda J. Orlikowski. (1992) Learning from Notes : organizational issues in groupware implementation. In CSCW '92, pages 362 - 369, 1992.


Jirotka, Marina, et al. (2005). Collaboration and trust in healthcare innovation: The eDiaMoND case study. Computer Supported Cooperative Work (CSCW), 14(4), pp. 369-398.


 Gutwin, Carl, Reagan Penner, and Kevin Schneider. (2004) Group awareness in distributed software development. Proceedings of the 2004 ACM conference on Computer supported cooperative work. ACM.


5. Data-driven knowing


There is a considerable push, not to say hype, around data-driven data science (big data, AI and/ or machine learning), to automate or radically transform how previously manual, qualitative tasks are done in business and public organizations. In practice, what does data-driven knowing and decision-making look like and how will it evolve?


JS Brown and P Duguid. Organizational learning and communities-of-practise: toward a unified view of working, learning and innovation, Organization Science, 2(1):40-57, 1991.


Passi, S. and Jackson, S.J. (2018). Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), pp.1-28.


Gunnar Ellingsen and Eric Monteiro. (2003) Mechanisms for producing working knowledge: enacting, orchesterating and organizing, Information and Organization, 13(3): 203 - 229.


Jones, Matthew. (2019) What we talk about when we talk about (big) data. The Journal of Strategic Information Systems 28, no. 1: 3-16.


Marcus, G., 2018. Deep learning: A critical appraisal. arXiv preprint arXiv:1801.00631.