Datasets
Open Access
Student Acceptance of Blended Learning - primary science curriculum - China
- Citation Author(s):
- Submitted by:
- Xu LIU
- Last updated:
- Thu, 11/04/2021 - 04:51
- DOI:
- 10.21227/kx61-7732
- Data Format:
- License:
- Categories:
- Keywords:
Abstract
Blended Learning has been widely used in current basic education as a new teaching model, and how to improve the acceptance of students in Blended Learning is a hot issue that needs to be solved in the practice of teaching.
There is a paper for the dataset:
Primary science curriculum student acceptance of blended learning: structural equation modeling and visual analytics
doi: 10.1007/s40692-021-00206-8
Full Text: https://rdcu.be/cAooZ
Abstract
This paper focuses on the analysis of perceived usefulness (PU), perceived ease-of-use (PE), perceived playfulness (PP), community support (CS), and other factors that affect the acceptance of Chinese students (SA) in Blended learning of primary science curriculum. Based on technology acceptance model and Unified Theory of Acceptance and Use of Technology, an initial structural equation model is proposed. The initial structural model is for blended learning student acceptance (SA) in primary science curriculum. It contains five latent variables, and 4 latent variables can affect SA. Questionnaire responses are collected through blended learning SA questionnaire survey and analyzed using statistical methods. The questionnaire has 25 questions and collects 357 answers from all over China. Based on the reliability analysis, exploratory factor analysis, and confirmatory factor analysis of the data, the initial structural equation model is improved. According to the final structural equation model, the influence order of influencing factors on primary science curriculum blended learning SA is CS > PP > PU > PE. Based on the final model, an interactive visualization application is designed and implemented using SAP Analytics Cloud to allow users to understand the model easily and explore interactions among these factors visually. Teachers can directly see the changes of various factors through visualization, and do not need to pay attention to complex model details. This approach provides new practice for the application of theoretical models in Pedagogy.
357 questionnaire responses are collected through Blended Learning student acceptance questionnaire survey.
Dataset Files
- Student_Acceptance_of_Blended_Learning_primary_science_curriculum_China_remove_private_information.csv (43.72 kB)
- Student_Acceptance_of_Blended_Learning_primary_science_curriculum_China_remove_private_information_all_factors.csv (16.61 kB)
- Student_Acceptance_of_Blended_Learning_primary_science_curriculum_China_remove_private_information_for_final_model.csv (13.35 kB)
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Comments
Thanks for your input!
My pleasure! I write a paper for the dataset [Full Text: https://rdcu.be/cAooZ ]. You may want to view it.