Exploring teaching approaches in higher education: Cluster analysis of faculty profiles in a Latin American university.

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Title: Exploring teaching approaches in higher education: Cluster analysis of faculty profiles in a Latin American university.
Authors: Bravo-Torres, Jack Fernando1,2, Santoveña-Casal, Sonia María1, Cevallos-Ludeña, Cinthya María3
Source: Journal of University Teaching & Learning Practice. 2026 2nd Quarter, Vol. 23 Issue 2, p1-25. 25p.
Abstract: This study investigates the teaching approaches used by faculty members at a Latin American university to identify distinct pedagogical profiles influenced by demographic, disciplinary, and institutional factors. Data were collected from 385 university lecturers using the Approaches to Teaching Inventory (S-ATI-20) within a quantitative, cross-sectional design. The analysis revealed three faculty profiles that differ in how they balance content delivery with student engagement, the extent of their pedagogical preparation, and their use of reflective teaching practices. These results suggest that teaching approaches are shaped not only by academic background and professional experience, but also by the degree of institutional support available to lecturers. While grounded in a Latin American setting, the study offers insights that may guide faculty development and teaching policy in a wide range of higher education institutions facing similar challenges. [ABSTRACT FROM AUTHOR]
Copyright of Journal of University Teaching & Learning Practice is the property of Open Access Publishing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Exploring teaching approaches in higher education: Cluster analysis of faculty profiles in a Latin American university.
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  Data: <searchLink fieldCode="AR" term="%22Bravo-Torres%2C+Jack+Fernando%22">Bravo-Torres, Jack Fernando</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Santoveña-Casal%2C+Sonia+María%22">Santoveña-Casal, Sonia María</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Cevallos-Ludeña%2C+Cinthya+María%22">Cevallos-Ludeña, Cinthya María</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+University+Teaching+%26+Learning+Practice%22">Journal of University Teaching & Learning Practice</searchLink>. 2026 2nd Quarter, Vol. 23 Issue 2, p1-25. 25p.
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  Data: This study investigates the teaching approaches used by faculty members at a Latin American university to identify distinct pedagogical profiles influenced by demographic, disciplinary, and institutional factors. Data were collected from 385 university lecturers using the Approaches to Teaching Inventory (S-ATI-20) within a quantitative, cross-sectional design. The analysis revealed three faculty profiles that differ in how they balance content delivery with student engagement, the extent of their pedagogical preparation, and their use of reflective teaching practices. These results suggest that teaching approaches are shaped not only by academic background and professional experience, but also by the degree of institutional support available to lecturers. While grounded in a Latin American setting, the study offers insights that may guide faculty development and teaching policy in a wide range of higher education institutions facing similar challenges. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of University Teaching & Learning Practice is the property of Open Access Publishing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.53761/3va9kr17
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              Text: 2026 2nd Quarter
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