Advances in temporal analysis in learning and instruction

Main Article Content

Inge Molenaar


This paper focuses on a trend to analyse temporal characteristics of constructs important to learning and instruction. Different researchers have indicated that we should pay more attention to time in our research to enhance explanatory power en increase validity. Constructs formerly viewed as personal traits, such as self-regulated learning and motivation, are now conceptualized as a series of events that unfold over time. This raises new questions with regard to the temporal characteristics of these constructs and their dynamic interplay with learner and context characteristics. Even though the value of analyzing temporal characteristics slowly becomes evident a number of challenges need to be tackled in order to make progress in de field of learning and instruction. First, we need to be aware of the paradigm shift that temporal analysis entails. Second, a common understanding of different dimensions of time and the position of temporal characteristics therein  can facilitate our time related research dialogue. Third, a better understanding how to answer time related questions with appropriate methodological approaches needs to emerge. Fourth, researching temporal characteristics entails segmenting time which procedures are needed for.  Fifth, temporal data are mostly collected at the micro level, whereas most theory is defined at a macro level; consequently we need to bridge these differences in the granularity used between collecting, coding and theorizing to enhance meaning making.  Finally, so far most examples of time related research are explorative or comparative studies, the next step is to move toward confirmative studies which constitutes the “Holy Grail” of temporal analysis.

Article Details

How to Cite
Molenaar, I. (2014). Advances in temporal analysis in learning and instruction. Frontline Learning Research, 2(4), 15–24.
Author Biography

Inge Molenaar, Radboud University

Dr. Inge Molenaar is assistant professor at the Radboud University Nijmegen, Behavioural Science Institute. Her main interests are technology and innovation in education working towards differentiated and adaptive instruction that facilitate students’ optimal talent development. Temporal analysis offer a powerful way to make new steps forward in this field.  Her research focuses on the development of intelligent tutors (Atgentive) for adaptive scaffolding of metacognition and self-regulated learning. She also is the initiator and CEO of the e-learning application Ontdeknet. The development of the Dutch national educational repository for elementary and secondary education (Wikiwijs) made her an expert on educational metadata standards and the adaptive assignment of learning content. She received several national and international awards and grants for her work.


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