Our studies conducted in the ProLearn project (Professional learning in a changing society) of computer engineers points towards open-source software projects as dynamic epistemic communities providing rich sources of distributed knowledge. Pieces of codes and chunks of knowledge are swiftly distributed and shared internationally. How can we as researchers understand the structure and representations of these objects? What properties do they convey to attract potential learners? Following a ‘materialistic’ trajectory, this presentation focuses on the object-side of the relation. The potential and attracting power of open knowledge is not necessarily restricted to software developing communities. Understanding the structure of open ended knowledge can provide educators with important clues on how to organize learning experiences that nourish ties to knowledge cultures. This presentation aims to report on work-in-progress and invite conference participants to reflect on some of the key problems.

Theories on object-relations have recently gained new attention in the social sciences and in educational research (e.g., Engeström, Puonti, & Seppänen, 2003; Knorr Cetina, 2001; Lash, 2003; Law & Singleton, 2003). Inspired by actor network theory (Callon, 1986; Latour, 1987; Law, 1992 and others), human and non-human actors can be seen as dynamically involved in constructing social worlds. In this tradition, Knorr Cetina (1997; , 2001) submits the idea of “knowledge objects” as characterized by a changing and unfolding nature and a lack of completeness. Our studies of computer engineers conducted in the ProLearn project (professional learning in a changing society) point towards open-source software projects as evolving knowledge objects providing rich sources of distributed knowledge. Research questions are as follows: How can we as researchers understand the structure and representations of knowledge objects? What properties do they convey to attract potential learners? This presentation aims to report work-in-progress and invite conference participants to reflect on the key problems.

 

According to Nespor (1994) in the book Knowledge in Motion, activity distant in space and time is transported into particular settings through material recourses and representations (i.e. textbooks and representational technologies). When it comes to human learning, information represented in various forms is often involved in the process (Boshuizen & Schijf, 1998). However, the idea of representations as how we generate images of the object ‘out there’ raises some fundamental methodological problems. This standpoint supports an ontological commitment to essentialism, “the idea that discrete objects exist independent of our perception of them” (Woolgar, 1988:25). This is regarded “…as one of the more significant constraints which this tradition imposes upon our efforts to understand science” (ibid). The problem is said to be rooted in the hypothetical dualism between representation and object.

 

The meaning mediated by a representation is not necessarily understood by resemblance, but may require interpretation. Following existential and hermeneutic philosophy, interpretations are necessary for human understanding (Anderson, Hughes, & Sharrock, 1986). ‘Intentionality’ is a contiguous notion in this regard. From a phenomenological perspective, intentionality is a broader concept than representations, designating the ‘towardness’ or ‘aboutness’ of conscious states (Agre, 1997). For example, when a team of software engineers discuss a piece of code they are working on, the activity is oriented towards a specified object. Thus, human activity is described as intentional since it’s about and towards something. Can consciousness, agency and intentionality also be represented in the profile of objects?

 

According to Knorr Cetina (2001), knowledge objects flows through expert communities in multiple forms (or in her words: “instantiations”) ranging from figurative to material realizations. Possible representations of such objects in a software developing community are design patterns in programming, logical flow charts and ongoing documentation of a project. Several of the software engineers studied in the ProLearn project declare that they gain new knowledge from open source communities on a regular basis. For example, a consulting engineer for a medium sized software corporation asserts:

 

 

How is knowledge represented in this example? Traces of someone’s problem solving, or “... how they where thinking” is somehow represented in the code. The source code is a series of instructions written by a programmer by means of a compiler or interpreter. This is a program-form that is applied as input to a translator (Daintith & Illingworth, 2004). The source is written in a particular code language (i.e. java or c++) that is comprehensible by human beings. Source codes must be further converted to object codes (or machine language) for computers to be able to read and execute the program. In other words, the knowledge object is represented in multiple forms, depending on the interpreting actor.

 

The potential and attracting power of open knowledge is not necessarily restricted to software developing communities. The philosophy of open source is picked up and applied with success in online encyclopedias (e.g., wikis), in molecular biology through the BiOS-licenses (see www.bios.net). Knowledge in an open form may embody further potential when it comes to develop learning-experiences in a networked knowledge society.

 

Theoretical concerns discussed above are grounded in the ongoing ProLearn study. The research design is partly longitudinal, focusing on professional education and the transition to work-life. It’s considered longitudinal “in the sense that a cohort of professionals (N=40 with 10 from each group) is interviewed at the end of their basic education, then after two years of employment and finally there is a follow-up five years after graduation” (Lahn & Jensen, 2005:3). This presentation draws on extracts from documentary data, in-depth interviews, focus-groups and learning logs.