The Fault in Our STARS: International Evidence that the Statistics Anxiety Rating Scale and the Revised Mathematics Anxiety Rating Scale Overlap
Jenny Terry, Robert M. Ross, Alyssa Counsell, Udi Alter, Jules L. Ellis, Nataly Beribisky, Andras N. Zsido, Patricia Garrido-Vásquez, Flavia H. Santos, Darcy Hallett, Mauricio Salgado, Tamás Nagy, İbrahim Öztürk, Oliver Lindemann, Susan Cooper, Argiro Vatakis, Yiyun Shou, Patrick A. O'Connor, Dirk Van Rooy, Christina Artemenko, Mariia M. Ostroha, Darren Rhodes, Matthew O. Parker, Nazlı Akay, Katherine Swainston, Mahmoud M. Elsherif, Fitri A. Abidin, Stefan Agrigoroaei, Robert A. Cribbie, Ilija Milovanović, Mai Helmy, Anke C. Buttner, Juan David Leongómez, Ratna Jatnika, Lee T. Copping, Tiago J. S. Lima, Nicola Palena, María Fernanda Reyes, Marina G. Drushlyak, Jacob O. Sarfo, Cristina Rodríguez, Hilal H. Şen, Anne H. van Hoogmoed, Matúš Adamkovič, Philipp Schmid, Joel R. Anderson, Gregor Stiglic, Leona Cilar Budler, Lucy V. Justice, Elise Grimm, Roberto A. Ferreira, Letizia Caso, Donncha Hanna, Daniel Ansari, Ivan Ropovik, Juneman Abraham, Desirée González, Alejandro J. Estudillo, Kristin Jankowsky, Kristel de Groot, Karel K. Himawan, Johnrev Guilaran, Omid Ghasemi, Stephanie N. L. Schmidt, Maria Flakus, Neslihan Özhan, Tessa R. Flack, Jodie E. Chapman, Gabriel Banik, Linda M. Geven, Sanne H. G. van der Ven, Jochen A. Mosbacher, Michael Batashvili, Tolga Ergiyen, Katharina Schmid, Ratri Nurwanti, Antonino Callea, Burcu Tekeş, Maxine M. C. Storm, Saadet Öztürk, Angélica P. Trassi, Rizqy A. Zein, Feyza Topçu, Kristel Mikkor, Gaetan Mertens, Merve G. Tutlu Temizyürek, Zsofia K. Takacs, James M. Clay, Conal Monaghan, Ali H. Al-Hoorie, Andrea Greco, Mauricio E. Garrido Vásquez, Charlie Lea, Karin Täht, Balazs Aczel, Ahmed Al Khateeb, Gabriella Daroczy, Lisa A. D. Webster, Kareena McAloney-Kocaman, Samantha K. Stanley, Jordan Randell, Joanna E. Lewis, Kinga Morsanyi, Iro Xenidou-Dervou, Bhasker Malu, Hans-Christoph Nuerk, Martin J. Barwood, Elizabeth R. Walters, Suzanna E. Forwood, Zoe M. Flack, Deborah S. Crossland, Erin M. Buchanan, Michael J. Platow, Andrew J. Roberts, TamilSelvan Ramis, Bruno Verschuere, Siobhán M. Griffin, Julia Bahnmueller, Shane Lindsay, Dimitri Löchner, Thomas E. Hunt, Violeta Enea, Samuel P. Hills, Zoe Leviston, Crystal N. Steltenpohl, Theresa E. Wege, Mariah Lecompte, Grace McMahon, Felix T. U. Ogba, Amy C. Warhurst, Alexander Karner, Oliver J. Clark, Katie A. Gilligan-Lee, Nicholas A. Badcock, Sophie J. Leonard, Christopher J. Hand, Ho Yan Lai, Samuel G. Penny, Olena V. Semenikhina, Felix O. Egara, Wing-Yee Cheung, Jonas De keersmaecker, Frank Scharnowski, Elizabeth Collins, Mojtaba Soltanlou, Matthew Brolly, Jordan R. Wagge, Unita W. Rahajeng, Peter E. Branney, Sophia C. Weissgerber, Fergus M. Guppy, Skylar Taylor, Andy P. Field
Submitted for publication
Resumen
Statistics anxiety is widely recognised as a barrier to student learning, and the Statistics Anxiety Rating Scale (STARS) is its most widely used self-report measure. However, it remains unclear whether the STARS captures a construct distinct from mathematics anxiety or reflects a jangle fallacy. Using a large international sample of undergraduate students (N = 6,885) from 83universities across 33 countries, we examined the empirical distinctiveness of the STARS relative to the Revised Mathematics Anxiety Rating Scale (R-MARS). Across four criteria, the evidence indicated substantial overlap. First, correlations between the STARS and R-MARS were consistently strong. Second, exploratory and confirmatory factor analyses showed that items clustered primarily by type of educational experience (e.g., tests, help-seeking, interpretation)rather than by domain, with limited and unstable domain-specific factors. Third, both scales demonstrated statistically equivalent associations with 11 theoretically related anxiety and education variables. Fourth, the R-MARS explained negligible incremental variance beyond the STARS across these outcomes. Together, the findings suggest that the STARS and R-MARS largely measure the same underlying construct. Their continued separate use risks redundancy,conceptual fragmentation, and statistical artefacts, underscoring the need for clearer construct definition and more precise measurement tools.
Integrante de CODEC
Juan David Leongómez
Profesor Titular
- Líder CODEC
- Investigador EvoCo
- Director MetaCiencia