Abstract

Background: Prelicensure nursing students face significant cognitive challenges as they balance academic coursework with rigorous clinical training [1]. These demands often exceed cognitive capacity, leading to cognitive overload which hinders information processing and retention [2]. Cognitive load refers to the mental effort required to process information within working memory; while cognitive overload occurs when intrinsic, extraneous, and germane demands exceed this capacity [3,4]. Integrating technology-driven strategies offers opportunities to optimize working memory and enhance learning outcomes.

Purpose: The purpose of this integrative review was to synthesize current evidence on factors influencing cognitive load and examine technology-based interventions designed to mitigate cognitive overload in nursing education.

Methods: Using Whittemore and Knafl’s framework for integrative reviews [5], five electronic databases were searched for articles published between 2020 and 2025. Twenty-two studies informed this review.

Results: Technology-enhanced strategies to reduce intrinsic and extraneous load include adaptive learning platforms, simulation-based training, virtual reality, and digital cognitive aids. These tools, combined with scaffolding and multimodal instruction, reduce unnecessary mental effort and improve cognitive processing while enhancing meaningful learning.

Conclusion: Leveraging technology informed by cognitive load principles helps minimize cognitive demands and prevent overload, thereby promoting effective learning without overwhelming students [6,7]

Notes

References:

1. Smith, N. E., Barbé, T., & Randolph, J. (2022). Application of the cognitive load theory in prelicensure nursing education: a quantitative measurement focusing on instructional design. International Journal of Nursing Education Scholarship, 19(1). https://doi.org/10.1515/ijnes-2021-0127

2. Yiin, S. J., & Chern, C. L. (2023). The effects of an active learning mechanism on cognitive load and learning achievement: A new approach for pharmacology teaching to Taiwanese nursing students. Nurse Education Today, 124, 105756.

3. Sweller, J. (2011). Cognitive load theory. In Psychology of learning and motivation (Vol. 55, pp. 37-76). Academic Press.

4. Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1–16. https://doi.org/10.1007/s11423-019-09701-3

5. Whittemore, R., & Knafl, K. (2005). The integrative review: updated methodology. Journal of advanced nursing, 52(5), 546-553.

6. Andersen, B. L., Jørnø, R. L., & Nortvig, A.-M. (2022). Blending adaptive learning technology into nursing education: A scoping review. Contemporary Educational Technology, 14(1), ep333. https://doi.org/10.30935/cedtech/11370

7. Aebersold, M., & Gonzalez, L. (2023). Advances in Technology Mediated Nursing Education| OJIN: The Online Journal of Issues in Nursing. Online Journal of Issues in Nursing, 28(2).

Description

Prelicensure nursing students face increased cognitive load from combined academic and clinical demands that impair information processing. This integrative review of 22 studies explores technology-driven interventions to mitigate cognitive overload. Findings show adaptive platforms, simulation technology, and intentional use of digital aids, paired with scaffolding and multimodal instruction, optimize working memory and support reduced intrinsic and extrinsic loads, improving learning outcomes.

Author Details

Joset Brown, EdD, MSN, RN, CNE; Dione Sandiford, PhD, MSN, CNE, CHSE; Caroline Meza, PhD, RN, CEN, NPD-BC, AHN-BC

Sigma Membership

Iota Alpha at-Large

Type

Presentation

Format Type

Text-based Document

Study Design/Type

Integrative Review

Research Approach

Other

Keywords:

Emerging Technologies, Teaching and Learning Strategies, Nursing Education, Cognitive Load, Educational Technology

Conference Name

37th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Toronto, Ontario, Canada

Conference Year

2026

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

Date of Issue

2026-09-07

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Leveraging Technology to Mitigate Cognitive Load in Nursing Education: An Integrative Review

Toronto, Ontario, Canada

Background: Prelicensure nursing students face significant cognitive challenges as they balance academic coursework with rigorous clinical training [1]. These demands often exceed cognitive capacity, leading to cognitive overload which hinders information processing and retention [2]. Cognitive load refers to the mental effort required to process information within working memory; while cognitive overload occurs when intrinsic, extraneous, and germane demands exceed this capacity [3,4]. Integrating technology-driven strategies offers opportunities to optimize working memory and enhance learning outcomes.

Purpose: The purpose of this integrative review was to synthesize current evidence on factors influencing cognitive load and examine technology-based interventions designed to mitigate cognitive overload in nursing education.

Methods: Using Whittemore and Knafl’s framework for integrative reviews [5], five electronic databases were searched for articles published between 2020 and 2025. Twenty-two studies informed this review.

Results: Technology-enhanced strategies to reduce intrinsic and extraneous load include adaptive learning platforms, simulation-based training, virtual reality, and digital cognitive aids. These tools, combined with scaffolding and multimodal instruction, reduce unnecessary mental effort and improve cognitive processing while enhancing meaningful learning.

Conclusion: Leveraging technology informed by cognitive load principles helps minimize cognitive demands and prevent overload, thereby promoting effective learning without overwhelming students [6,7]