DEVELOPING A MODEL FOR EVALUATING SMART LEARNING ENVIRONMENTS: A CONCEPTUAL APPROACH

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
2025-05-21
DOI
https://doi.org/10.5281/zenodo.15482109
Primary Topic
Mobile Learning in Education
Type
article
Field-Weighted Citation Impact
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article

DEVELOPING A MODEL FOR EVALUATING SMART LEARNING ENVIRONMENTS: A CONCEPTUAL APPROACH

Zenodo (CERN European Organization for Nuclear Research)
Mobile Learning in Education
article

DEVELOPING A MODEL FOR EVALUATING SMART LEARNING ENVIRONMENTS: A CONCEPTUAL APPROACH

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 45%
Mobile Learning in Education
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