Information Technology Reference
In-Depth Information
There is, of course, no need to change practices for the sake of change. However,
we argue that there are emerging needs that require revisiting some of our research
approaches, routines, and technologies. Drivers for change are amongst others:
•
“Mode II” knowledge production (Gibbons et al., 1994) in education—How to
distribute research work across practitioners and researchers, with the Web 2.0 as
a big enabler?
•
“Rich and continuous data”—how to analyze process data streams and video as
a data format, and publish how to publish on this?
•
Accountability—how to establish trust in qualitative and quantitative research
findings?
In this chapter we discuss the topic of technology-enhanced research at four lev-
els. Section one introduces two complementary technological developments that are
at the core of the present changes in research and scholarly practices: Grid tech-
nology/semantic networks that are primary enablers of “big science”, and Web
2.0 and cloud computing that are primary enablers of new more democratic and
social forms of scholarship. Section two discusses the need and possibilities for dis-
tributed and integrated learning research approaches and digital environments. We
argue that such approaches and digital tools should link (real and online) classrooms
and practice-based innovation into a larger system of educational knowledge, thus
enabling new ways of building research upon earlier outcomes and of integrating
research data and outputs for decision-making and policy. Section three discusses
some of many other methodological developments and techniques—video analysis
and process analysis—that we think have the biggest opportunities to enhance learn-
ing research. Finally, section four discusses a classic topic in epistemology—how
to develop trust in research findings—from the perspective of provenance architec-
tures. As research becomes more distributed, both socially (over people) as well
as technically (over software services), the issue of trust in the data and the find-
ings gains a new dimension, one that can be effectively addressed by computational
approaches to provenance.
In short, this chapter discusses existing and emerging technological affordances
and their possibilities to enhance learning research. Before starting this discussion
we acknowledge that research technologies are evocative and open to many inter-
pretations. How e-research will be taken up in education and what kinds of research
practices it will support will depend on our interpretations and actions, aiming to
shape and embrace it. Ours is only one out of many possible ways to address this
potential.
Grids, Clouds, and Web 2.0 for Learning Research
In the last years we have seen two rather different, nevertheless complementary,
technological developments, both yielding optimistic expectations to enhance and
