TOWARD A THEORETICAL MODEL FOR SMART LEARNING ENVIRONMENT EVALUATION

Smart, mobile, and wearable computing advancements are transforming how people compute and interact daily. These technologies are transforming learning environments into smart learning environments capable of providing personalization for inclusive learning experiences. Several evaluation frameworks were proposed to evaluate learning environments; however, there is a scarcity of a well-explored model that considers the characteristics of a smart learning environment. This article proposed an integrated model and validated it based on the strengths and limitations of the technology acceptance model (TAM) and theory of planned behavior (TPB). The validation was conducted using a focused group of students and lecturers in the faculty of science as well as e-learning experts in Adamawa State University, Mubi-Nigeria. The data were analyzed using a thematic process. The result identified three new factors: perceived quality, perceived support, and perceived technology resources. The integrated and validated model can be used to study both the intention and actual usage of a smart learning environment in a contextual setting to inform decisions and policy regarding implementing and deploying a smart learning environment for inclusive learning experiences in educational learning

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-20
DOI
https://doi.org/10.5281/zenodo.15470020
Primary Topic
Educational Environments and Student Outcomes
Type
article
Field-Weighted Citation Impact
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article

TOWARD A THEORETICAL MODEL FOR SMART LEARNING ENVIRONMENT EVALUATION

Zenodo (CERN European Organization for Nuclear Research)
Educational Environments and Student Outcomes
article

TOWARD A THEORETICAL MODEL FOR SMART LEARNING ENVIRONMENT EVALUATION

article en

Abstract

Smart, mobile, and wearable computing advancements are transforming how people compute and interact daily. These technologies are transforming learning environments into smart learning environments capable of providing personalization for inclusive learning experiences. Several evaluation frameworks were proposed to evaluate learning environments; however, there is a scarcity of a well-explored model that considers the characteristics of a smart learning environment. This article proposed an integrated model and validated it based on the strengths and limitations of the technology acceptance model (TAM) and theory of planned behavior (TPB). The validation was conducted using a focused group of students and lecturers in the faculty of science as well as e-learning experts in Adamawa State University, Mubi-Nigeria. The data were analyzed using a thematic process. The result identified three new factors: perceived quality, perceived support, and perceived technology resources. The integrated and validated model can be used to study both the intention and actual usage of a smart learning environment in a contextual setting to inform decisions and policy regarding implementing and deploying a smart learning environment for inclusive learning experiences in educational learning

Zenodo (CERN European Organization for Nuclear Research)
Adamawa State University (NG)
Openalex Percentile: Top 56%
Educational Environments and Student Outcomes
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