Project AVG

Evaluation of a Gifted Education Program: Effects of ability grouping of gifted students in special gifted classes in secondary schools in Rhineland-Palatinate

The Chair of Giftedness Research and Education acts as scientific supervisor of a gifted education program for secondary schools currently offered at four grammar schools (‚Gymnasien’) in Rhineland-Palatinate. In addition to regular classes, each of the schools taking part in the program offers a special gifted class to foster the development of gifted students.

One of our scientific goals is the investigation of the so-called „Big-Fish-Little-Pond“ effect (BFLPE). For the gifted classes, we assume that part of those students who were high achievers prior to their integration into the gifted classes will subsequently turn into average achievers within the context of their new classes. For many students, this „big fish“-„little fish“ transition has detrimental effects on academic self-concept. (Academic self-concept refers to statements such as „I’m gifted at maths.“) Since academic self-concept is a crucial factor in such diverse outcomes as scholastic achievement, learning behavior, course selection, career aspirations and vocational choices, the BFLPE is of great practical importance.

Interestingly, several studies have shown that, on the other hand, full-time ability grouping can improve motivation and attitude towards school and learning in gifted students. These issues will also be addressed in the context of the project. In general, little is known about the long-term outcomes of full-time ability grouping of gifted students. Therefore, besides the study of the BFLPE and related changes, the project aims at documenting developmental changes in order to help improve and optimize gifted education and to offer starting points for school development.

Results from grades 5-8

For the first results (grades 5-8) please follow this link to the official project report 2013. This report covers the data collected between 2005 and 2013.

Research Associate: Markus Feuchter, M.Sc.
Duration: since 2005
Funding: Ministry of Education, Science, Youth and Culture of Rhineland-Palatinate

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Project Big-GENDER

Big Data Meta-Analyses of Gender Differences in Students' Achievement and Achievement Motivation Based on Large-Scale Assessments

An essential requirement for any scientific and political discourse on gender differences in school (and beyond) is a reliable body of empirical knowledge on the nature, size, variability, and moderating factors of these differences. This knowledge is highly relevant for at least three reasons: It can be used (a) to learn about gender differences before university entry as plausible antecedents of still existing gender gaps in academic fields, (b) to provide scientific evidence that can help dispel the persistent stereotypes (e.g., that only boys can excel in mathematics) that may discourage girls from pursuing careers in science, technology, engineering, and mathematics (STEM), and (c) to identify target points for evidence-based decision making in educational policy (e.g., boys from families with low socioeconomic status [SES]). The main goal of this meta-analytic big data project is therefore to provide highly robust and widely generalizable knowledge on cross-national gender differences in students’ achievement and achievement motivation (concerning means and variances). To this end, we will meta-analyze individual student data from 999 representative student samples from 112 different countries/economic regions (total N > 4 million) participating in 24 cycles of international large-scale assessments covering the period from 1995 to 2015: the Trends in International Mathematics and Science Study (TIMSS; Grades 4, 8, and 12), the Progress in International Reading Literacy Study (PIRLS; Grade 4), and the Programme for International Student Assessment (PISA; 15-year-olds). This project will be the first to quantitatively synthesize this wealth of data with meta-analytic methods. Specifically, we will conduct three domain-specific meta-analyses to examine gender differences (concerning mean levels and variability) in achievement and achievement motivation in mathematics, science, and reading, respectively. We will study students’ age and SES, the selectivity of the sample (e.g., the bottom 10% or the top 5% of the achievement distributions), sociocultural indicators of gender equality, and historical changes as moderators of gender differences. Further, we will conduct one meta-analysis to examine gender differences in achievement and motivational profiles in multiple domains among three groups of top-performing students who belong to the top 5% in mathematics, science, or reading in their respective countries. To sum up, our project will provide novel insights into cross-national, temporal, and age-related trends concerning gender differences in the general student population and among top-performing students, as well as on the complex interactions between gender, the selectivity of the sample, SES, and sociocultural indicators of gender equality. BIG-GENDER  is funded by the German Research Foundation (DFG).

Research Associate: Dr. Lena Keller (University Potsdam)

Duration: 2020 - 2023

Funding: The German Research Foundation (DFG)

Cooperation partner: Prof. Dr. Martin Brunner (initial inquirer; University Potsdam)

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Project LUPE

A project aimed at a material-based promotion of primary teachers’ diagnostic competencies

The correct assessment of a student´s performance level by teachers is an important precondition for differentiated and performance-oriented learning. Furthermore, teacher judgments of student characteristics can lead to corresponding expectations for these students which in turn can influence their further development. The main purpose of the LUPE project is therefore to support the academic development of (potentially) high-performing students by promoting their teachers’ diagnostic competencies.  

The project comprises an interdisciplinary elaboration of a “Talent Development Model” with a specific reference to MINT subjects (mathematics and science).  Based on the model, domain specific materials that support primary school teachers in actively and structurally searching for and identifying (potentially) high-performing students will be developed, tested in practice, and formatively evaluated. The materials combine different approaches which can be used in a modular way („tool box metaphor“). The approaches include diagnostic task material teachers can utilise in everyday school settings and behavioural observation methods that could be used in the classroom.

Research Associate: MSc Elena Mack, MSc Psych Moritz Breit, MSc Jessica Gnas, and MSc Julia Matthes

Duration: 2018 to 2022

Funding: Bundesministerium für Bildung und Forschung (BMBF)

Cooperation partner: Prof. Dr. Miriam Vock (University Potsdam)

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Project TAD

With the talent development in achievement domains (TAD) framework, we aim to provide a general talent development framework that is applicable to a wide range of achievement domains. The overarching goal of this framework is to support empirical research by focusing on measureable psychological constructs and their meaning at different levels of talent development. The TAD framework can be used for the construction of domain-specific talent development models.  

The TAD framework is developed by the members of the International Research Collaborative for the Psychology of Talent Development (ICPT). This group, founded by Franzis Preckel and Rena Subotnik, brings together 12 researchers from different fields of psychological research on talent development, including music psychology, art psychology, educational psychology, differential psychology, giftedness research, research on expertise and instructional psychology. Members are (in alphabetical order):

  • JunProf. Dr. Jessica Golle, Universität Tübingen, Deutschland/Germany
  • Prof. Dr. Roland Grabner, Karl-Franzens Universität Graz, Österreich/Austria
  • Prof. Dr. Linda Jarvin, Paris College of Art, Frankreich/France
  • Prof. Dr. Aaron Kozbelt, Brooklyn College, New York
  • Prof. Dr. Daniel Müllensiefen, Goldsmith University of London, England/UK
  • Prof. Dr. Paula M. Olszewski-Kubilius, Northwestern University, Evanston/USA
  • Prof. Dr. Franzis Preckel, Universität Trier, Deutschland/Germany
  • Prof. Dr. Wolfgang Schneider, Universität Würzburg, Deutschland/Germany
  • Prof. Dr. Rena Subotnik, American Psychological Association, Washington/USA
  • Prof. Dr. Miriam Vock, Universität Potsdam, Deutschland/Germany
  • Prof. Dr. Frank C. Worrell, University of California, Berkeley/USA

The TAD project is supported by the Karg foundation and the Siemens foundation.

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