Fynn Junge
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Fynn Junge has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Jens Möller
Institute for Psychology of Learning and Instruction, Kiel University, Kiel, Germany
3 shared publications - Julian F. Lohmann
Leibniz Institute for Science and Mathematics Education
3 shared publications - Ruth Trüb
University of Applied Sciences and Arts Northwestern Switzerland, Basel, Switzerland
2 shared publications - Stefan Daniel Keller
Pädagogische Hochschule Zürich, Zürich, Schweiz
2 shared publications - Andrea Horbach
Leibniz Institute for Science and Mathematics Education (IPN), Kiel, Germany
1 shared publication - Fabian Wolff
Bielefeld University, Bielefeld, Germany
1 shared publication
Latest Publications
- Open Access
- 7 October 2026
- Published by Elsevier in Applied Studies in Innovative Learning and Teaching
- Vol. 3
Color-based signaling of argumentative elements: An empirical analysis of its impact on the assessment of EFL argumentative essays
- 7 October 2026
- Published by Elsevier in Applied Studies in Innovative Learning and Teaching
- Vol. 3
Open AccessColor-based signaling of argumentative elements: An empirical analysis of its impact on the assessment of EFL argumentative essays
- Open Access
- 1 August 2026
- Published by American Psychological Association (APA) in Journal of Educational Psychology
- Vol. 118 (6) , 941-960
Testing teacher judgments comprehensively: Accuracy, halo, frame of reference, strategy, and personality effects in holistic and analytic assessments of student essays.
- 1 August 2026
- Published by American Psychological Association (APA) in Journal of Educational Psychology
- Vol. 118 (6) , 941-960
Open AccessTesting teacher judgments comprehensively: Accuracy, halo, frame of reference, strategy, and personality effects in holistic and analytic assessments of student essays.
- Open Access
- 18 May 2026
- Published by Springer Nature in Social Psychology of Education
- Vol. 29 (1)
Examining students’ implicit academic self-concepts and intrinsic values in a comprehensive framework integrating key elements of expectancy-value theory, dimensional comparison theory, and theory on vocational interests
Implicit academic self-concepts and intrinsic values describe students’ automatically activated perceived abilities and attitudes towards school subjects. In the present research, we examined these implicit constructs within the context of a framework that integrates key elements of three prominent theories from the field of educational psychology: expectancy-value theory, dimensional comparison theory, and theory on vocational interests. To this end, we developed four go/no-go association tasks (GNATs) to measure implicit math and German self-concepts and values. Furthermore, we examined the formation and impact of these implicit constructs using cross-sectional data from a sample of 946 ninth- and tenth-graders from German high schools. Guided by three central research questions, we found (1) evidence for the validity of the GNATs to measure students’ implicit self-concepts and values in math, (2) that implicit math self-concepts and values appear to be influenced by dimensional comparisons (where students compare their achievements in different subjects), but not by social comparisons (where students compare their achievements with those of other students), and (3) that implicit math self-concepts predict students’ vocational interests over and above their achievements, explicit self-concepts, and explicit values in math and German. Our research also demonstrated the benefit of combining key elements from different theories of educational psychology to gain a deeper understanding of the relationships between students’ achievements, self-concepts, values, and vocational interests. Moreover, it is of great practical relevance as it highlights the importance of implicit self-concepts and values for students.
- 18 May 2026
- Published by Springer Nature in Social Psychology of Education
- Vol. 29 (1)
Open AccessExamining students’ implicit academic self-concepts and intrinsic values in a comprehensive framework integrating key elements of expectancy-value theory, dimensional comparison theory, and theory on vocational interests
Implicit academic self-concepts and intrinsic values describe students’ automatically activated perceived abilities and attitudes towards school subjects. In the present research, we examined these implicit constructs within the context of a framework that integrates key elements of three prominent theories from the field of educational psychology: expectancy-value theory, dimensional comparison theory, and theory on vocational interests. To this end, we developed four go/no-go association tasks (GNATs) to measure implicit math and German self-concepts and values. Furthermore, we examined the formation and impact of these implicit constructs using cross-sectional data from a sample of 946 ninth- and tenth-graders from German high schools. Guided by three central research questions, we found (1) evidence for the validity of the GNATs to measure students’ implicit self-concepts and values in math, (2) that implicit math self-concepts and values appear to be influenced by dimensional comparisons (where students compare their achievements in different subjects), but not by social comparisons (where students compare their achievements with those of other students), and (3) that implicit math self-concepts predict students’ vocational interests over and above their achievements, explicit self-concepts, and explicit values in math and German. Our research also demonstrated the benefit of combining key elements from different theories of educational psychology to gain a deeper understanding of the relationships between students’ achievements, self-concepts, values, and vocational interests. Moreover, it is of great practical relevance as it highlights the importance of implicit self-concepts and values for students.
- Open Access
- 13 September 2024
- Published by Elsevier in International Journal of Artificial Intelligence in Education
- Vol. 35 (3) , 1178-1217
Neural Networks or Linguistic Features? - Comparing Different Machine-Learning Approaches for Automated Assessment of Text Quality Traits Among L1- and L2-Learners’ Argumentative Essays
- 13 September 2024
- Published by Elsevier in International Journal of Artificial Intelligence in Education
- Vol. 35 (3) , 1178-1217
Open AccessNeural Networks or Linguistic Features? - Comparing Different Machine-Learning Approaches for Automated Assessment of Text Quality Traits Among L1- and L2-Learners’ Argumentative Essays