Jul 122018
 

The Promises and Pitfalls of Self-report Data for Motivation and Strategy Use: The Congruence of Theory, Self-reported Data Collection, Analysis and Reported Results

Self-report Data

Deadline: August 31th, 2018

While self-report measures are ubiquitous in the educational research literature, the benefits of self-report are often maligned. Rather than discarding or ignoring data generated from self-report measures of cognitive processing and motivation, research is needed to determine when and if self-report measures can contribute to our collective understanding of theory surrounding these constructs. This special issue will examine how self-report accurately reflects the constructs of cognitive and motivational processing, how these measures influence analytic choices, and how these measures ultimately influence our interpretations of study findings.

Without understanding the ripple effects of the choice of self-report on other aspects of the research process, the reported findings of these studies and their consequences on theories and practices remain in question. Providing empirical and theoretical support for the use of self-report (or not) can help clarify some of these pressing issues. Methodologies to investigate self-report will cover both qualitative and quantitative examinations of these issues. Potential contributions to this special issue should include studies in the areas of learning strategy use and motivation/emotion for learning. Empirical and theoretical contributions are welcomed. Studies should address two of three following questions:

  1. In what ways do self-report instruments reflect the conceptualizations of the constructs suggested in theory related to motivation or strategy use?
  2. How does the use of self-report constrain the analytical choices made with that self-report data?
  3. How do the interpretations of self-report data influence interpretations of study findings?

Papers will be synthesized by three leading international scholars who are recognized as international experts (Phil Winne, Peggy Van Meter, and Reinhard Pekrun) in the measurement of their respective constructs. This special issue is based on the initiative of the Network for Learning Strategies Group based out of the University of Antwerp. All articles will be thoroughly reviewed according to standards of Frontline Learning Research, an official EARLI journal.

If you are interested in contributing to this call, please send a 400-500-word abstract to Luke Fryer (fryer@hku.hk) by August 31th, 2018.

The guest editors,
Dr. Dan Dinsmore
Dr. Luke K. Fryer

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