eCampus_Extended_TAM

Published: 1 October 2024| Version 1 | DOI: 10.17632/4khrdkjm68.1
Contributor:
ananto tri sasongko

Description

The dataset contains 41 columns (items) and 645 rows (observations). The items are named according to their associated constructs, using abbreviations to denote the constructs. For example, Perceived Usefulness (PUS) is measured by PUS_1, PUS_2, PUS_3, PUS_4, and PUS_5, while Perceived Ease of Use (PEU) is captured by PEU_1, PEU_2, PEU_3, PEU_4, and PEU_5. Each construct includes multiple items that were measured using five-point Likert scales, where higher values indicate higher levels of agreement—from one (“strongly disagree”) to five (“strongly agree”). Perceived Enjoyment (PEN), Perceived Risk (PRI), Perceived Compatibility (PCO), and Perceived Self-Efficacy (PSE) are similarly represented by multiple items, such as PEN_1 to PEN_5, PRI_1 to PRI_5, PCO_1 to PCO_5, and PSE_1 to PSE_5, respectively. The dependent variable, Acceptance (ACC), is measured by ACC_1 to ACC_5, capturing students' acceptance of e-learning technologies. Additionally, the dataset includes demographic information such as gender, student status, schedule, and semester of study. Gender is represented with an almost equal distribution: 48% males and 52% females. Student status is coded to reflect two fields of status, such as working and regular. Semester is represented by values indicating the student’s academic standing, from first-semester to seventh-semester students. The demographic variables allow for a detailed segmentation of the student population, enabling researchers to explore differences in e-learning acceptance across different groups. The dataset is comprehensive and offers a robust foundation for analyzing the factors that influence the adoption and usage of e-learning technologies in a private university context.

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e-Learning, Higher Education, Technology

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