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Determining the potential of educational information and communications technology for enhancing teaching and learning is the subject of a great deal of research activity. This paper argues that the technologies employed to enhance learning can also be exploited for the enhancement of research. Recorded learner–system interactions, dynamically captured computer screen activity and visual attention tracking all provide sources of rich process data that can be triangulated with tradition learning outcome (product) data. Such multiple data source approaches can be used in various research design and methodological contexts—design experiments, microgenetic experiments, case studies and so on. Process‐analytic methods can reveal the fine details of an individual’s learning trajectory and permit the effects of short‐timescale interventions upon longer term learning outcomes to be assessed. In this paper, three illustrations of technology‐enhanced research (TER) are described. The first example (switchER) illustrates an iterative learner‐centred design cycle. The second example (Hyperproof) illustrates how process data can elucidate individual differences in learning. The third example (PATSy, VL‐PATSy) demonstrates how an established online e‐learning system can be used as a tool for identifying students’ clinical reasoning difficulties and how it can then be extended by having additional learning support resources added to it together with a context‐sensitive, rule‐based delivery system. The paper concludes with a discussion of broader TER issues such as the need to anticipate and plan for the analysis of large amounts of rich data. It concludes by suggesting some further ways in which TER might be exploited and provides links to some potentially useful TER tools and resources.
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Richard Cox (2007) studied this question.
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