Action research (Avison et.al)

1. Action research (Avison et.al) To make academic research relevant, researchers should try out their theories with practitioners in real situations and real organisations

2. Action research (1) • It is a qualitatively oriented iterative process involving researchers and practitioners acting together on a particular cycle of activities • problem diagnosis • action intervention • reflective learning • Focus on what people do

3. Action research (2) • It is motivated by a quest to improve and understand the world by changing it and learning how to improve it from the effects of the changes made. • Critically reflective: why does the current action not produce the required results?.

4. Action research (3) • System analysts need to apply their craft to problems that are not well defined (principles, tools, techniques) • System analysts have to address the fundamental human aspects of organisations • research bring along a “framework of concepts” to the problem situation • Learning (technology transfer) • The researcher is a participant

5. Problems, issues, suggestions • Be explicit about the research method. • action researchers must be clear about their framework of ideas, the method, techniques. that they are developing and provide rich and clear evidence from their reflections • Proper documentation is important • Explicit criteria should be defined before performing the research in order to later judge its outcomes.

6. Organizational learning and communities of practice: Toward a unified view of working, learning and innovation (Brown and Duguid) The ways people actually work usually differ fundamentally from the ways organizations describe that work in manuals, training programs. organizational charts, and job descriptions

7. Introduction • Practice is central to understanding work • Formal descriptions of work and of learning are often abstracted from actual practice. • Reliance on descriptive/espoused practice (canonical practice) can blind an organizations focus on the actual and usually valuable practices of its members (noncanonical practices). It is the actual practices that determine the success or failure of organizations • The composite concept of "learning-in-working" best represents the fluid evolution of learning through practice. • Learning is the bridge between working and innovating

8. What is practice? • Doing in a social context that give meaning and structure to what we do. • Explicit and tacit, said/unsaid, represented /assumed • What we take for granted--know-how

9. Canonical versus Noncanonical practice (1) • Actual practice versus Espoused practice • modus operandi (during) versus opus operatum (after) – • while working versus after completed • e.g: a map versus the physical landscape (raod work, parades, signs, etc)

10. Canonical versus Noncanonical practice (2) • Workers are held responsible according to formal job descriptions (canonical), despite the fact that daily evidence points to the contrary - They are held accountable to the map, not to road conditions • Lack in canonical approaches demands an alternative, non-canonical approach. • In a non-canonical approach people tell stories that is wholly unavailable in a canonical approach

11. Central Features of Work Practice (1) • Narratation • Stories act as repositories of accumulated wisdom • develop a causal map out of their experience to replace the impoverished directive route that they have been furnished by the corporation • allows people to keep track of the sequences of behavior and of their theories

12. Central Features of Work Practice (2) • Collaboration • Insight is accumulated by telling (and exchange) work-related stories to each other • Not only is the learning inseparable from working, but also individual learning is inseparable from collective learning

13. Central Features of Work Practice (3) • Social Construction • Learning is socially constructed and distributed • Workers construct a shared understanding out of bountiful conflicting and confusing data • Such an approach is highly situated and highly improvisational – bricolage

14. Learning (1) • Learning theorists have rejected transfer models, which isolate knowledge from practice, and developed a view of learning as social construction, putting knowledge back into the contexts in which it has meaning • What is learned is profoundly connected to the conditions in which it is learned (workplace learning), rather than just abstract subject matter. The central issue in learning is becoming a practitioner not learning about practice

15. Learning (2) • Work practice and learning need to be understood not in terms of the groups that are ordained (e.g. "task forces" or "trainees"), but in terms of the communities that emerge.

16. How is it possible to foster learning-in-working? (1) • central to the process are the recognition and legitimation of community practices • attempts to strip away context should be examined with caution - if training is designed so that learners cannot observe the activity of practitioners, learning is inevitably impoverished

17. How is it possible to foster learning-in-working? (1) • It is a significant challenge for design to ensure that new collaborative technologies do not exclude the implicit, extendible, informal periphery of an organization.

18. Innovating • Communities-of-practice continuously develop rich, fluid and noncanonical world view to bridge the gap between their organization's static canonical view and the challenge of changing practice • The source of innovation lies on the interface between an organization and its environment. And the process of innovating involves actively constructing a conceptual framework, imposing it on the environment, and reflecting on their interaction. • Challenge for organizations to recognise the fact that its existence depends on noncanonical practice

19. Conclusion • For working, learning, and innovating to thrive collectively they must be linked in theory and in practice - more closely, more realistically, and more reflectively than is generally the case.

20. CSCW: Four Characters in Search of a Context (Bannon and Schmidt) A framework for approaching the issue of cooperative work and its possible computer support This part of the presentation is partly based on lecture notes in SIF8058-Samhandlingsteknologi by Monica Divitini (thanks M..)

21. Humans work together! • Relying on contributions from others, • Communicating work results to others, • Jointly taking decisions, • Collaborating with colleagues in the work place, • Coordinating activities with others, • Having meetings and discussing matters,……

22. Using computers for cooperation • Computers are traditionally used for supporting single user productivity: • Word processors, spread sheets, databases, drawing packages, etc… • Cheaper networking increases connectivity and provides new opportunities for human-human communication: • E-mail, news groups, chat, etc… • Connectivity is the basis for supporting cooperation, but much more can be provided!

23. What is CSCW • Computer-supported cooperative work is a research field dealing with questions like: • How can people use computers and networks to do cooperative work? • What happens to human-human cooperation when the computer stands in the way? • Do we know enough about human-human cooperation to be able to support it? • How can we design systems to better support cooperation in distributed groups?

24. Computer Supported Cooperative Work (CSCW) “CSCW should be conceived as an endeavor to understand the nature and requirements of cooperative work with the objective of designing adequate computer-based technologies.“ (Bannon & Schmidt, 1989)

25. What is Groupware then? • A multi-user program that lets the members of a distributed group work together by: • Providing group members with communication facilities, • Letting them share their files and data, • Making them aware of each others’ existence. • Groupware is the product (program) resulting from the research done in the CSCW field.

26. Groupware versus CSCW? • CSCW: • Focus on • workplace activities, • organizational impact of technology, • co-evolution of the technology and the groups using it, • Interdisciplinary: Social scientists and technologists. • Groupware: • Focus on • computer systems, • the design of the computer systems, • Mainly a technical discipline.

27. Core issues for CSCW • Articulating cooperative work • Sharing an information space • Adapting the technology to the organisation, and vice versa

28. Articulating cooperative work • Articulation consists of all the tasks needed "to coordinate a particular task, including scheduling subtasks, recovering from errors, and assembling resources." • a CSCW application should support at least two interacting "levels of language". • Formal • Informal / cultural • Promote awareness of work and workers

29. Sharing an information space • Decision making requires access to information and knowledge. • Sharing information and knowledge is important for distributed, indirect collaboration. • Human beings have different work strategies, which affects the result of their work.. • Important to know the originator of the information (transparency). • Information is dependent on the context it was produced in. • How do we represent the problem context when that context has disappeared? • Is information neutral? • Conflicting organizations often produce biased information!

30. Adapting the technology to the organisation… • considerations regarding how the system will be used, and how use will influence future needs must be adressed (social interaction and structure greatly influences technical design) • Demands an adequate understanding of the workplace (interaction style, power and authority, etc) • Studies are needed to address these questions

31. Conclusion • Changes in technology induce changes in the work organization and changes in this organization will influence how the analyst should design an appropriate system

32. Qualitative Methods in Empirical Studies of Software Engineering Seaman 1999

33. Focus of the paper • Show how qualitative methods can be adapted and incorporated into the designs of empirical studies in software engineering. • Qualitative methods force the researcher to delve into the complexity of the problem rather than abstract it away - Thus the results are richer and more informative.

34. What are Qualititative Methods • Data in the form of words and pictures • Data is richer and carries more information, but is harder to analyze than quantative data • Can be either objective or subjective • Methods designed to elicit perceptions feelings and opinions • Loosely grouped into data collection and data analysis methods

35. Data collecting methods Data collection • Participant observation • Interviewing Coding • glue between qualitative and quantitative methods Data analysis • Generating theory • Constant comparison Method • Cross-Case analysis • Confirmation of theory….

36. Participant observation (1) • Collecting data by observing the subject. • Different techniques • Think aloud protocols • Logging keystrokes (often used in usability-studies) • Communication between systems developers (e.g meetings) • Subjects/informants get affected • Behave unobtrusively, and do not disrupt • Keep notes confidential

37. Participant observation (2) • Data gathering • Field notes (transcripts and comments) • Audio, video • Forms - when special kind of information is being collected. • Often relevant when combining qualitative and quantitative methods • Makes it easy to code into quantitative variables • To ensure validity and consistency, Rater agreement exercises could be used • Comparison of data from two independent observers (using the same form, and given the same set of criteria’s)

38. Interview (1) • To reveal historical data, opinions and impressions, identification of terminology, etc… • Could be used in combination with observations (to help clarify things) • Several types: • Unstructured (open ended) • semi-structured (mixture of open-ended and specific questions) • Structured (specific questions)

39. Interview (2) • Data gathering tools • Field notes (like observational data) • Interview guide (in open ended interviews) • help in organizing the interview • Using audiotape is recommended

40. Combining qualitative and quantitative methods • Extract values for quantitative variables from qualitative data  Coding • Examples: • Number of participants in a meeting • Length of a meeting • Code complexity • Etc… • Be careful when coding information that is subjective in nature

41. Generating theory • Extract from a set of field notes a statement or proposition/hypothesis that is supported in multiple ways by the data. • Often referred to as “grounded theory” methods because the theories, or propositions, are “grounded” in the data

42. Constant comparison method (1) Method: • Attaching labels (codes) to text in the field notes. • Grouping into patterns according to labels • Writing field memo articulating propositions or observations synthesized from the labelled data.

43. Constant comparison method (2) iterative process • after every round of coding and analysis, there is more data collection to be done which provides an opportunity to check any propositions that have been formed. • Ensures representativeness later in the study because we are able to choose cases according to the course of the study

44. Cross-Case analysis • Looking at the data in many different ways • For example: • cases can be partitioned into two groups based on some attribute (e.g. number of people involved, type of product, etc.), and then examined to see what similarities hold within each group, and what differences exist between the two groups. • compare pairs of cases to determine variations and similarities. • divide the data based on data source (interviews, observations, etc.).

45. Confirmation of theory (1) • Strengthening or “confirming” a proposition after it has been generated from the data. • Hypothesis cannot be proven, it can only be supported or refuted, and this is true using either quantitative or qualitative evidence, or both.

46. Confirmation of theory (2) • Qualitative methods have the advantage of providing more explanatory information, and help in refining a proposition to better fit the data. • Important to ensure validity of the qualitatively methods used to generate a proposition

47. Confirmation of theory Ensuring validity (1) • Ensuring representativeness later in the study because we are able to choose cases according to the course of the study • Research effects • Presence of researcher affects subjects behavior • Researchers lose their objectivity by involving themselves

48. Confirmation of theory Ensuring validity (2) • Triangulation • gather different types of evidence to support a proposition (e.g using different sources, using different methods, analyz the data using different methods, etc) • Anomalies in the data • Extreme cases that are eliminated in statistical analysis, but treated as friends in qualitative analysis because they play an important role in shaping a proposition.

49. Confirmation of theory Ensuring validity (2) • Negative case analysis • Searching for evidence that might contradict a generated proposition, revise the proposition to cover the negative evidence, re-checking the new proposition against existing and newly collected data, and then continuing the search for contradictory evidence. • Replication • preserve the conditions set forth in the theory being tested. • Member checking • Getting feedback from the subjects