Patrick C. Kyllonen

Learning and Individual Differences: Process, Trait, and Content Determinants.

Intelligence and Human Resources - Past, Present and Future Individual Differences in Learning and Memory - Psychometrics and the Single Case Minding Our Ps and Qs - On Finding Relationships Between Learning and Intelligence Investigating the Paths Between Working Memory, Intelligence, Knowledge and Complex Problem Solving Performances via Brunswik-Symmetry Intelligence and Visual and Auditory Information Processing Individual Differences in Priming - the Roles of Implicit Facilitation From Prior Processing Learning, Automaticity and Attention - an Individual Differences Approach The Structure of Ability Profile Patterns - a Multidimensional Scaling Perspective on the Structure of Intellect Investigating Theoretical Propositions Regarding Mental Abilities - Their Structure, Growth and Influence Exploiting the Speed-Accuracy Trade-Off Personality and Skill - a Cognitive-Adaptive Framework Measuring and Understanding G - Experimental and Correlational Approaches Individual Differences in Motivational Mechanisms - Traits and Skills Mining on the No-Mans Land Between Intelligence and Personality Sensory Processes Within the Structure of Human Cognitive Abilities Searching for Determinants of Superior Performance in Complex Domains Individual Differences in Reasoning and the Heuristics and Biases Debate Learner Profiles - Valuing Individual Differences Within Classroom Communities Traits and Knowlegde as Determinants of Learning and Individual Differences - Putting it all Together.

Using the Standardized Letters of Recommendation in Selection: Results from a Multidimensional Rasch Model.

In an effort to standardize academic application procedures, the authors developed the Standardized Letters of Recommendation (SLR) to capture important cognitive and noncognitive qualities of graduate school candidates. The SLR, which consists of seven scales, is applied to an intern-selection scenario. Both professor ratings (n = 414) during the application process and mentor ratings of the selected students (n = 51) are collected using the SLR. A multidimensional Rasch investigation suggests that the SLR displays satisfactory internal consistency, model fit, and item fit. The two cognitive scales, knowledge and analytical skills, are found to be the best predictors for intern selection. The professor ratings are systematically higher than the mentor ratings. Possible reasons for the rating discrepancies are discussed. Also, implications for how the SLR can be used and improved in other selection situations are suggested.

General Noncognitive Outcomes

The core goals for education systems in the twenty-first century have shifted from teaching clearly defined knowledge and skills to promoting lifelong learners who are eager, as well as able, to face the demands and challenges of a truly global society. As a reflection of the emerging policy interest in a more comprehensive definition of adolescent and young adult success, national and international large-scale assessments (LSAs) have started broadening their focus to include noncognitive outcomes in addition to achievement results. In this chapter we describe the opportunities and challenges associated with noncognitive outcome assessments, with a special focus on the implementation in the Programme for International Student Assessment (PISA) 2015. We provide research-based rationales why LSAs should focus on noncognitive outcomes, which specific outcomes deserve most attention, and how measurement approaches can be enhanced for more validity and efficiency. Two main categories of noncognitive outcomes are described in more detail: first, constructs that can be tied back to the Big Five model of human personality; second, variables representing well-being or general quality of life indicators, comprising factors such as health, subjective well-being, and psychological functioning. Examining the interplay between cognitive and noncognitive factors is essential to better understand what policies can promote learning and prepare students to face twenty-first century challenges. National and international LSAs can shed light on the factors that are most strongly associated, either positively or negatively, with student development. The success of LSAs as helpful tools and monitoring systems for policy makers and educators will depend to a growing extent on how well they can serve the policy and public demand for enhanced measurement of noncognitive outcomes.

Connecting Noncognitive Development to the Educational Pipeline

Understanding the educational pipeline has been of great importance to educators and policymakers as both groups seek ways to help students navigate it successfully. The broadest description of the educational pipeline includes a series of important transitions: persistence through high school, graduation from high school, entry into postsecondary education, persistence through postsecondary education, completion of postsecondary education, and entry into the workforce (Ewell, Jones, & Kelly, 2003; Gandara, 2006).