Editorial to the special issue current methodological issues in educational large-scale assessments. Part 2

in Psychological Test and Assessment Modeling (2017), 59

COMPLEX PROBLEM SOLVING IN UNIVERSITY SELECTION

Doctoral thesis (2016)

The choice between what you want now and what you want most. Self-control explains academic achievement beyond cognitive ability

in Personality and Individual Differences (2016), 94

Achieving a university degree is a demanding long-term goal, and students often show varying levels of academic achievement despite similar intellectual abilities. In order to help students, researchers ... [more ▼]

Achieving a university degree is a demanding long-term goal, and students often show varying levels of academic achievement despite similar intellectual abilities. In order to help students, researchers thereby need to understand the origins of these individual differences. However, it remains unclear whether self-control is important for students' academic achievement beyond their general cognitive ability. To answer this question,N= 150 German university students completed a measure of general cognitive ability as well as a German translation of the Brief Self-Control Scale. Grade point average (GPA) served as an objective indicator of academic achievement, complemented by personal ratings as a measure of subjective academic achievement (SAA). Both cognitive ability and self-control explained substantial amounts of variance in GPA; however, only self-control accounted for variance in SAA. The study's keyfinding was that self-control indeed contributed to explaining GPA and SAA, even when cognitive ability was controlled for. On the basis of these results, we argue that self-control holds important explanatory value for both objective and subjective academic achievement, and we discuss the results' practical relevance with regard to student success at university. [less ▲]

Editorial to the special issue current methodological issues in educational large-scale assessments. Part 1

in Psychological Test and Assessment Modeling (2016), 58

Assessing subjective university success with the Subjective Academic Achievement Scale (SAAS).

Poster (2015)

Assessing complex problem solving skills with Multiple Complex Systems.

in Thinking & Reasoning (2015), 21

„Was du heute kannst besorgen…“: Selbstkontrolle erklärt Studienerfolg über Intelligenz hinaus.

Scientific Conference (2015)

Complex Problem Solving and intelligence. A meta-analysis

in Intelligence (2015), 53

The Utility of Complex Problems in University Selection

Scientific Conference (2014, April 30)

The role of strategy knowledge for the application of strategies in complex problem solving tasks

in Technology, Knowledge and Learning (2014), 19

Education in the twenty-first century must prepare students to meet the challenges of a dynamic and interconnected world. However, assessment of students’ skills tends to focus primarily on static tasks ... [more ▼]

Education in the twenty-first century must prepare students to meet the challenges of a dynamic and interconnected world. However, assessment of students’ skills tends to focus primarily on static tasks. Therefore, it is not known whether knowledge about successful strategies displayed on static tasks can be transferred to interactive and dynamic environments. This study investigated whether students’ knowledge of a certain strategy (i.e., vary-one-thing-at-a-time, VOTAT) that was assessed in a paper-and-pencilbased scientific reasoning task as well as their fluid intelligence and learning orientation would be sufficient to explain variance in the application of the VOTAT strategy in solving an interactive complex problem solving (CPS) task (i.e., CPS strategy). Furthermore, we analyzed whether CPS strategy mediated the relation between the predictors (i.e., scientific reasoning, learning orientation, fluid intelligence) and CPS performance. The sample consisted of N = 3,191 Finnish students attending the 6th and 9th grades. Results revealed that all predictors were significantly related to CPS strategy, but a substantial amount of variance in CPS strategy remained unexplained (DeltaR-Square = .583). Furthermore, CPS strategy mediated the relation between the predictors and CPS performance. Three implications are discussed: Different demands on the problem solver, knowledge transfer from static versus interactive tasks, or metastrategic knowledge may explain the unexplained variance in CPS strategy. Additionally, the results of our mediation analyses emphasize the importance of measuring strategies via logfiles to gain a deeper understanding of determinants of students’ CPS performance. Finally, fostering motivational factors such as students’ learning orientation yields small improvements in CPS performance. [less ▲]