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A Proposed Remedy for Grievances about Self-Report Methodologies
Author(s) -
Philip H. Winne
Publication year - 2020
Publication title -
frontline learning research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.51
H-Index - 7
ISSN - 2295-3159
DOI - 10.14786/flr.v8i3.625
Subject(s) - listing (finance) , property (philosophy) , context (archaeology) , geodetic datum , data science , computer science , scale (ratio) , epistemology , psychology , history , geography , cartography , business , archaeology , finance , philosophy
This special issue’s editors invited discussion of three broad questions. Slightly rephrased, they are: How well do self-report data represent theoretical constructs? How should analyses of data be conditioned by properties of self report data? In what ways do interpretations of self-report data shape interpretations of a study’s findings? To approach these issues, I first recap the kinds of self-report data gathered by researchers reporting in this special issue. With that background, I take up a fundamental question. What are self-report data? I foreshadow later critical analysis by listing facets I observe in operational definitions of self-report data: nature of the datum, topic, property, setting or context, response scale, and assumptions setting a stage for analyzing data. Discussion of these issues leads to a proposal that ameliorates some of them: Help respondents become better at self reporting.

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