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Affective learning assessment of beginning nursing students

  • Susan A. Seibert EMAIL logo , Ashley N. Carter , Christina F. Buxton and Erin M. Reynolds
Published/Copyright: May 19, 2025

Abstract

Objectives

Nursing education commonly includes aspects of cognitive, psychomotor, and affective learning. Subsequently, the evaluation of student affective learning has been recognized as an important aspect within educational processes. Affective learning is crucial to professional nursing role development. However, a gap in the literature exists in measuring and evaluating affective learning in nursing students. Using the taxonomy developed by Krathwohl, Bloom, and Masia (1964. Taxonomy of educational objectives, handbook II: affective domain. Philadelphia: David McKay Company, Inc.), faculty developed a tool for students to rate their perceived level of affective learning.

Methods

Faculty launched a quality improvement project to evaluate the accuracy of student self-assessments of affective learning at the end of their first nursing course.

Results

Student and expert identification of the level of affective learning were not statistically different, which demonstrated that students accurately identified their affective level. The sample demonstrated competency through the first level of affective learning (i.e., receiving).

Conclusions

Cultivating professional values can significantly impact the lives of patients and communities. Use of the tool may lead to a deeper understanding of student nurse development of affective competencies.


Corresponding author: Dr. Susan A. Seibert, DNP, RN, CNE, Kinney College of Nursing and Health Professions, University of Southern Indiana, 8600 University Boulevard, Evansville, IN 47712, USA, E-mail:

Acknowledgment

Thank you to our colleague Pamela Miller, DNP, FNP-BC, CPNP-PC, for contributing her time and expertise as a reviewer for this study. We appreciate her passion for nursing and nursing education.

  1. Research ethics: The University of Southern Indiana Internal Review Board granted Exempt Status for this study.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors contributed to the design, analysis, interpretation, drafting, and editing of this study and manuscript.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors have no conflict of interest with the manuscript’s content or the publishing company.

  6. Research funding: No funding was used or granted for this study.

  7. Data availability: Not applicable.

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Received: 2024-08-26
Accepted: 2025-04-30
Published Online: 2025-05-19

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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