Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design
Course satisfaction surveys play a relevant role in Higher Education, aiding in the quality assessment of courses and informing academic promotions. Nonetheless, understanding potential biases and influential factors within these surveys is crucial to their equitable utilization within universities....
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/70140 |
| Acceso en línea: | http://hdl.handle.net/10230/70140 http://dx.doi.org/10.1007/s44322-025-00030-3 |
| Access Level: | acceso abierto |
| Palabra clave: | Learning design Learning environment Learner satisfaction Institutional analytics Biases |
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Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning designMarques, FrancielleHernández-Leo, DaviniaCastillo, CarlosLearning designLearning environmentLearner satisfactionInstitutional analyticsBiasesCourse satisfaction surveys play a relevant role in Higher Education, aiding in the quality assessment of courses and informing academic promotions. Nonetheless, understanding potential biases and influential factors within these surveys is crucial to their equitable utilization within universities. This study delves into a deconstruction of satisfaction ratings considering three learning design factors (content, methodology, and workload) and their interplay with student grades. Especially emphasizing the need for institutional analytics to engage in Generative Uncertainty, aiding productive inquiries using data. Institutional analytics of the 2021–2022 and 2022–2023 survey results from a Spanish university revealed that learning design aspects strongly correlate with students’ holistic perception of a course. The correlation between student grades and student satisfaction related to learning design is either weak or moderate. These analytical findings imply that there may be bias in students’ responses to course satisfaction surveys (e.g., lower grades leading to lower satisfaction). However, this bias doesn’t consistently manifest.This work is co-funded by MICIU/AEI/https://doi.org/10.13039/501100011033 (PID2020-112584RB-C33, PID2023-146692OB-C33, CEX2021-001195-M) and the Department of Research and Universities of the Government of Catalonia (SGR 00930). Hernández-Leo (Serra Húnter) also acknowledges the support by ICREA under the ICREA Academia programme. Castillo also acknowledges support from the EU-funded projects "SoBigData + + " (grant agreement 871042), "FINDHR" (grant agreement 101070212).Springer202520252025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/70140http://dx.doi.org/10.1007/s44322-025-00030-3http://hdl.handle.net/10230/70140reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésJournal of New Approaches in Educational Research. 2025 March;14(1):9info:eu-repo/grantAgreement/ES/2PE/PID2020-112584RB-C33info:eu-repo/grantAgreement/ES/3PE/PID2023-146692OB-C33info:eu-repo/grantAgreement/EC/H2020/871042info:eu-repo/grantAgreement/EC/HE/101070212© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the mate‑rial. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/701402026-05-29T05:05:01Z |
| dc.title.none.fl_str_mv |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| title |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| spellingShingle |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design Marques, Francielle Learning design Learning environment Learner satisfaction Institutional analytics Biases |
| title_short |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| title_full |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| title_fullStr |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| title_full_unstemmed |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| title_sort |
Beyond bias in student satisfaction surveys: exploring the role of grades and satisfaction with the learning design |
| dc.creator.none.fl_str_mv |
Marques, Francielle Hernández-Leo, Davinia Castillo, Carlos |
| author |
Marques, Francielle |
| author_facet |
Marques, Francielle Hernández-Leo, Davinia Castillo, Carlos |
| author_role |
author |
| author2 |
Hernández-Leo, Davinia Castillo, Carlos |
| author2_role |
author author |
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Learning design Learning environment Learner satisfaction Institutional analytics Biases |
| topic |
Learning design Learning environment Learner satisfaction Institutional analytics Biases |
| description |
Course satisfaction surveys play a relevant role in Higher Education, aiding in the quality assessment of courses and informing academic promotions. Nonetheless, understanding potential biases and influential factors within these surveys is crucial to their equitable utilization within universities. This study delves into a deconstruction of satisfaction ratings considering three learning design factors (content, methodology, and workload) and their interplay with student grades. Especially emphasizing the need for institutional analytics to engage in Generative Uncertainty, aiding productive inquiries using data. Institutional analytics of the 2021–2022 and 2022–2023 survey results from a Spanish university revealed that learning design aspects strongly correlate with students’ holistic perception of a course. The correlation between student grades and student satisfaction related to learning design is either weak or moderate. These analytical findings imply that there may be bias in students’ responses to course satisfaction surveys (e.g., lower grades leading to lower satisfaction). However, this bias doesn’t consistently manifest. |
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2025 |
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2025 2025 2025 |
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http://hdl.handle.net/10230/70140 http://dx.doi.org/10.1007/s44322-025-00030-3 http://hdl.handle.net/10230/70140 |
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http://hdl.handle.net/10230/70140 http://dx.doi.org/10.1007/s44322-025-00030-3 |
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Inglés |
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Journal of New Approaches in Educational Research. 2025 March;14(1):9 info:eu-repo/grantAgreement/ES/2PE/PID2020-112584RB-C33 info:eu-repo/grantAgreement/ES/3PE/PID2023-146692OB-C33 info:eu-repo/grantAgreement/EC/H2020/871042 info:eu-repo/grantAgreement/EC/HE/101070212 |
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