Madeleine Bieg

1.4k total citations
17 papers, 937 citations indexed

About

Madeleine Bieg is a scholar working on Experimental and Cognitive Psychology, Social Psychology and Cognitive Neuroscience. According to data from OpenAlex, Madeleine Bieg has authored 17 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Experimental and Cognitive Psychology, 7 papers in Social Psychology and 5 papers in Cognitive Neuroscience. Recurrent topics in Madeleine Bieg's work include Education, Achievement, and Giftedness (9 papers), Grit, Self-Efficacy, and Motivation (6 papers) and Mind wandering and attention (5 papers). Madeleine Bieg is often cited by papers focused on Education, Achievement, and Giftedness (9 papers), Grit, Self-Efficacy, and Motivation (6 papers) and Mind wandering and attention (5 papers). Madeleine Bieg collaborates with scholars based in Germany, Canada and Switzerland. Madeleine Bieg's co-authors include Thomas Goetz, Nathan C. Hall, Reinhard Pekrun, Oliver Lüdtke, Kyle Hubbard, Anastasiya A. Lipnevich, Eva S. Becker, Anna‐Lena Roos, Fabio Sticca and Ilka Wolter and has published in prestigious journals such as PLoS ONE, Psychological Science and Frontiers in Psychology.

In The Last Decade

Madeleine Bieg

17 papers receiving 902 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Madeleine Bieg Germany 11 569 426 359 152 118 17 937
Wondimu Ahmed Netherlands 11 495 0.9× 444 1.0× 458 1.3× 150 1.0× 170 1.4× 19 951
Daeun Park South Korea 11 503 0.9× 567 1.3× 319 0.9× 302 2.0× 91 0.8× 25 1.0k
Jaana Viljaranta Finland 22 520 0.9× 518 1.2× 833 2.3× 293 1.9× 336 2.8× 59 1.4k
Kyla Haimovitz United States 8 413 0.7× 382 0.9× 339 0.9× 233 1.5× 176 1.5× 12 899
Roger Norgate United Kingdom 10 305 0.5× 171 0.4× 324 0.9× 343 2.3× 209 1.8× 18 841
Tomoe Kanaya United States 13 198 0.3× 242 0.6× 256 0.7× 342 2.3× 166 1.4× 27 788
Miraca U. M. Gross Australia 16 788 1.4× 337 0.8× 639 1.8× 128 0.8× 156 1.3× 34 1.2k
Eric Smith United States 8 414 0.7× 380 0.9× 255 0.7× 142 0.9× 100 0.8× 14 832
Stephanie V. Wormington United States 17 587 1.0× 590 1.4× 475 1.3× 165 1.1× 199 1.7× 28 1.1k
Riikka Hirvonen Finland 19 274 0.5× 350 0.8× 533 1.5× 429 2.8× 171 1.4× 47 1.0k

Countries citing papers authored by Madeleine Bieg

Since Specialization
Citations

This map shows the geographic impact of Madeleine Bieg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Madeleine Bieg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madeleine Bieg more than expected).

Fields of papers citing papers by Madeleine Bieg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Madeleine Bieg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Madeleine Bieg. The network helps show where Madeleine Bieg may publish in the future.

Co-authorship network of co-authors of Madeleine Bieg

This figure shows the co-authorship network connecting the top 25 collaborators of Madeleine Bieg. A scholar is included among the top collaborators of Madeleine Bieg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Madeleine Bieg. Madeleine Bieg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Krannich, Maike, Thomas Goetz, Anna‐Lena Roos, et al.. (2022). Predictive validity of state versus trait challenge and boredom for career aspirations. Learning and Instruction. 81. 101596–101596. 9 indexed citations
2.
Bieg, Madeleine, et al.. (2020). Well-Being as a Precursor and Consequence of Micro-Processes in a Group Psychotherapy With Forensic Patients. Frontiers in Psychiatry. 11. 409–409. 1 indexed citations
3.
Roos, Anna‐Lena, Thomas Goetz, Martin Voracek, et al.. (2020). Test Anxiety and Physiological Arousal: A Systematic Review and Meta-Analysis. Educational Psychology Review. 33(2). 579–618. 83 indexed citations
4.
Krannich, Maike, Thomas Goetz, Anastasiya A. Lipnevich, et al.. (2018). Being over- or underchallenged in class: Effects on students' career aspirations via academic self-concept and boredom. Learning and Individual Differences. 69. 206–218. 49 indexed citations
5.
Sticca, Fabio, Thomas Goetz, Madeleine Bieg, et al.. (2017). Examining the accuracy of students’ self-reported academic grades from a correlational and a discrepancy perspective: Evidence from a longitudinal study. PLoS ONE. 12(11). e0187367–e0187367. 93 indexed citations
6.
Roos, Anna‐Lena, Madeleine Bieg, Thomas Goetz, et al.. (2017). Experiencing more anxiety than expected? : trait and state mathematics anxiety in high achieving students. 36–37. 1 indexed citations
7.
Bieg, Madeleine, et al.. (2017). Befragung zur MINT-Studienfach- und -Berufswahl von Abiturientinnen und Abiturienten in Baden-Württemberg. KOPS (University of Konstanz). 24–32. 1 indexed citations
8.
Bieg, Madeleine, Thomas Goetz, Fabio Sticca, et al.. (2017). Teaching methods and their impact on students’ emotions in mathematics: an experience-sampling approach. ZDM. 49(3). 411–422. 51 indexed citations
9.
Roos, Anna‐Lena, Thomas Goetz, Madeleine Bieg, et al.. (2017). Test anxiety and physiological arousal : a systematic review. 653. 1 indexed citations
10.
Nett, Ulrike E., Madeleine Bieg, & Melanie M. Keller. (2017). How Much Trait Variance Is Captured by Measures of Academic State Emotions?. European Journal of Psychological Assessment. 33(4). 239–255. 23 indexed citations
11.
Goetz, Thomas, Eva S. Becker, Madeleine Bieg, et al.. (2015). The Glass Half Empty: How Emotional Exhaustion Affects the State-Trait Discrepancy in Self-Reports of Teaching Emotions. PLoS ONE. 10(9). e0137441–e0137441. 61 indexed citations
12.
Bieg, Madeleine, Thomas Goetz, Ilka Wolter, & Nathan C. Hall. (2015). Gender stereotype endorsement differentially predicts girls' and boys' trait-state discrepancy in math anxiety. Frontiers in Psychology. 6. 1404–1404. 93 indexed citations
13.
Roos, Anna‐Lena, Madeleine Bieg, Thomas Goetz, et al.. (2015). Experiencing more mathematics anxiety than expected? Contrasting trait and state anxiety in high achieving students. High Ability Studies. 26(2). 245–258. 22 indexed citations
14.
Bieg, Madeleine, Thomas Goetz, & Anastasiya A. Lipnevich. (2014). What Students Think They Feel Differs from What They Really Feel – Academic Self-Concept Moderates the Discrepancy between Students’ Trait and State Emotional Self-Reports. PLoS ONE. 9(3). e92563–e92563. 63 indexed citations
15.
Bieg, Madeleine, Thomas Goetz, & Kyle Hubbard. (2013). Can I master it and does it matter? An intraindividual analysis on control–value antecedents of trait and state academic emotions. Learning and Individual Differences. 28. 102–108. 88 indexed citations
16.
Goetz, Thomas, Madeleine Bieg, Oliver Lüdtke, Reinhard Pekrun, & Nathan C. Hall. (2013). Do Girls Really Experience More Anxiety in Mathematics?. Psychological Science. 24(10). 2079–2087. 297 indexed citations
17.
Götz, Thomas, Madeleine Bieg, & Nathan C. Hall. (2012). Do girls really experience more math anxiety than boys. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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