I have become increasingly frustrated with the literature on educational technology and online learning, in part because so often the connection between theory and practice in applied / action research seems to be entirely absent. I am not quite satisfied with research which claims to be situated within a “framework” rather than to be testing any specific hypothesis deriving from a theory or theoretical perspective. In research on how we use technology to enhance learning, I believe we need to have a plausible model of learning, a plausible model of teaching, and a clear articulation of the desired outcomes from our teaching practice. I would actually go further, and question whether we should be focussing more on teaching than learning, since it is the teaching side of the equation that we engage in, and over which we have some level of control. It does not seem appropriate especially in a university, to answer basic questions about the nature of teaching and learning with motherhood statements about “student-centered learning” and terminology which seems to derive more from political correctness than scholarly investigation.
The choice of whether we focus on teaching or learning alone seems to me to have theoretical implications which should follow through into our practice. For example, with a focus on (social constructivist / student-centred) learning, we are implicitly favouring inductive models through which students build on what they already know and follow their interests and strengths. With a focus on teaching, we are externalising domains of knowledge, setting learning objectives, and defining the things to be learned at the end of a course of study irrespective of the student’s individual knowledge base or interests. We need to be clear about our purpose and intent, because there are strong implications for practice, depending on which position we adopt.
So here are some questions that I believe deserve due consideration. When we engage in educational / instructional design, is it appropriate to consider teaching and learning without having a position on the nature of knowledge representation and epistemology? Is it appropriate to consider the effect of “learning styles” or interface design on learning without a good understanding of cognitive processing, perceptual processing, memory and attention? In taking account of learning styles, are we aiming to build all modes of learning for each individual (work on areas of weakness as well as, or in preference to areas of strength) or are we focussed on relative fairness in terms of assessment (allowing everyone to focus on their areas of strength and hide their weaknesses)?
In designing simulations or replacing practical classes with virtual projects, can you really consider or measure learning outcomes without a fairly comprehensive understanding of the whole process of learning? Which learning outcomes are relevant indicators of good teaching? Which learning outcomes are indicators of inherent student ability / skill? Are short-term learning outcomes or long-term learning outcomes the ones to focus on? Do our educational theories speak to which outcomes are relevant? Does our rhetoric on desired graduate attributes speak to what indicators should be important?
Convenience measures do not make for good science if they do not measure things relevant to a theoretical position. The fact that something has been measured does not substitute for a theory. Quantitative analyses and statistical differences between groups do not by themselves constitute good research if they are not theoretically grounded and do not form critical tests of specific hypotheses. The fact that a data set is compatible with a theoretical position is no great contribution to science if the same data set is compatible with a range of other theoretical positions, and a different data set from the same study would not have allowed rejection of any competing theories.
In thinking about theory in this area, I am repeatedly drawn to the position that educational technology research is not a discipline area by itself, but provides a potential context for data which speak to theoretical questions from core discipline areas such as cognitive science, social psychology and computer science. It is important for us to ensure that any research questions relate back to core discipline areas rather than building an entirely self-referential data set around a single piece of technology or learning design.