Paradigmatic Issues in State-of-the-Art Research Using Process Data - Winne, Phil (Frontline Learning Research, 2019)
Learning science is enthusiastically adopting new instruments to gather physiological and other forms of event data to represent mental states and series of them that reflect processes. In an attempt to provoke more thought about this kind of research, I suggest paradigmatic issues relating to data, analyses of them and interpretations of results. I advocate we not label these data as “objective.” Instead, we share a subjective interpretation of them. I argue propositions about validity need more nuance. Bounds on generalization related to so-called ecological validity are rarely empirically justified. When researchers transform raw data before analysis and when analytic methods partition variance, interpretations of results omit key qualifications. I posit emotion and motivation be positioned in theory as moderators rather than mediators because agentic, self-regulating learners make and revise knowledge by choosing forms of cognitive engagement in a context where they interpret arousal. I note that researchers’ anchor interpretations of process data in learners’ accounts. This creates a tautology that troubles usual notions of reliability. Finally, I recommend research involving process data turn more toward helping learners identify conditions of learning that spark arousal so learners can regulate motivation and emotion. This leads to a surprise: Treating learners as individuals and helping them identify triggers of arousal may recommend learning science cast emotions and motivation as epiphenomena.