Individual Differences in Cognition: New Methods for Examining the Personality-Cognition Link

Abstract

Traditional studies of cognitive ability have examined the component processes and factor structure of ability tests. Theoretical and empirical studies of non-cognitive dimensions of personality have examined how individual differences in personality interact with situational stressors to affect efficient cognitive performance. Previously reported results have emphasized motivational direction and intensity effects upon cognitive performance. Using a new technique of "Synthetic Aperture Personality Assessment" (SAPA) which takes advantage of the large subject populations available on the internet, it is possible to study how basic personality dimensions relate to dimensions of cognitive ability. The SAPA procedure presents to participants small subsets of items sampled from large pools of publicly available personality and ability items. Although each participant is given only a small subset of items, with the recognition that subjects (> 65, 000) are randomly sampled and items are missing at random, it is possible to synthesize large (> 350x350) interitem correlation matrices. Individual differences in complex pattern recognition, spatial reasoning, and (self reported) standardized ability tests are moderately associated with Big 5 measures. We present the SAPA procedure in some detail and review findings relating dimensions of personality, ability, and interest.Based on a talk presented as part of a conference on "Individual differences in cognition" A symposium organized

Sense of direction: General factor saturation and associations with the Big-Five traits

“…Participants were administered items from three sets of scales using the Synthetic Aperture Personality Assessment ("SAPA") technique (Revelle, Wilt, & Rosenthal, 2010), a variant of matrix sampling procedures discussed by Lord (1955) (see also Condon & Revelle, 2014). This technique makes use of random sampling from large sets of personality and ability items in order to create synthetic correlations across a wide range of constructs even though a reasonably small subset of the items are presented to any one subject.…”

Measurement Matters

“…We also encourage further innovation in measurement development. An incomplete list of promising approaches includes: opportunistically mining students’ online learning behavior or written communication in real time (e.g., Twitter feeds, Kahn Academy databases) for meaningful patterns of behavior (D’Mello, Duckworth, & Dieterle, 2014; Ireland & Pennebaker, 2010; Kern et al, 2014); the aperture method of administering random subsets of questionnaire items to respondents so as to minimize administration time while maximizing content validity (Revelle, Wilt, & Rosenthal, 2010); recording and later coding 30-second audio snippets during everyday life (Mehl, Vazire, Holleran, & Clark, 2010); presenting hypothetical situations in narrative form and asking students what they would do in that circumstance (Oswald, Schmitt, Kim, Ramsay, & Gillespie, 2004; Ployhart & MacKenzie, 2011); asking students to make observations of their peers (Wagerman & Funder, 2007); indirectly assessing personal qualities through innovative application of factor analysis to conventionally collected data (e.g., GPA, attendance, achievement test scores) (Kautz & Zanoni, 2014; Jackson, 2012); and contacting students throughout the day to assess their momentary actions, thoughts, and feelings (Wong & Csikszentmihalyi, 1991; Zirkel, Garcia, & Murphy, 2015). In general, efforts to advance measurement of personal qualities would greatly benefit from cross-fertilization with similar efforts in personality psychology, industrial and organizational psychology, neuroscience, and economics (Heckman & Kautz, 2013; Pickering & Gray, 1999; Roberts, Jackson, Duckworth, & Von Culin, 2011; Schmidt, 2013; Schmidt & Hunter, 1998).…”

Development of a cognition-priming model describing learning in a STEM classroom

“…An example of this would be self‐efficacy and interest (affective) interacting with mental rotation and spatial visualization, interacting with the content outcomes (behavior) as proposed in this study. The affect‐behavior‐cognition distinction better known as feeling, acting, and knowing are the three major components (or facets) of human experience (Breckler, ; McGuire, ; Revelle, Wilt, & Rosenthal, ). Within science education typical approaches to access these components are surveys, interviews, and self‐reporting for affective measures; behavior measurement occurs through observation and outcomes, and cognition is measured through task completion and talk‐aloud protocols (Fowler, ).…”