A platform for research: civil engineering, architecture and urbanism
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Learning Management System-Based Evaluation to Determine Academic Efficiency Performance
At present, supporting e-learning with interactive virtual campuses is a future goal in education. Models that measure the levels of acceptance, performance, and academic efficiency have been recently developed. In light of the above, we carried out a study to evaluate a model for which architecture design, configuration, metadata, and statistical coefficients were obtained using four Learning Management Systems (LMSs). That allowed us to determine reliability, accuracy, and correlation, using and integrating the factors that other researchers have previously used, only using isolated models, such as Anxiety–Innovation (AI), Utility and Use (UU), Tools Learning (TL), System Factors (SF), Access Strategies (AS), Virtual Library (VL), and Mobile Use (MU). The research was conducted over one year in nine groups. The results from an LMS Classroom, architecturally and configuration-wise, had the highest level of performance, with an average of 73% when evaluated using statistical coefficients. The LMS Classroom had a good acceptance and a greater impact: SF, 82%, AI, 80%, and VL, 43%, while out of the seven factors, those with the most significant impact on academic efficiency were TL, 80%, VL, 82%, and MU, 85%.
Learning Management System-Based Evaluation to Determine Academic Efficiency Performance
At present, supporting e-learning with interactive virtual campuses is a future goal in education. Models that measure the levels of acceptance, performance, and academic efficiency have been recently developed. In light of the above, we carried out a study to evaluate a model for which architecture design, configuration, metadata, and statistical coefficients were obtained using four Learning Management Systems (LMSs). That allowed us to determine reliability, accuracy, and correlation, using and integrating the factors that other researchers have previously used, only using isolated models, such as Anxiety–Innovation (AI), Utility and Use (UU), Tools Learning (TL), System Factors (SF), Access Strategies (AS), Virtual Library (VL), and Mobile Use (MU). The research was conducted over one year in nine groups. The results from an LMS Classroom, architecturally and configuration-wise, had the highest level of performance, with an average of 73% when evaluated using statistical coefficients. The LMS Classroom had a good acceptance and a greater impact: SF, 82%, AI, 80%, and VL, 43%, while out of the seven factors, those with the most significant impact on academic efficiency were TL, 80%, VL, 82%, and MU, 85%.
Learning Management System-Based Evaluation to Determine Academic Efficiency Performance
Brenda Juárez Santiago (author) / Juan Manuel Olivares Ramírez (author) / Juvenal Rodríguez-Reséndiz (author) / Andrés Dector (author) / Raúl García García (author) / José Eli Eduardo González-Durán (author) / Fermín Ferriol Sánchez (author)
2020
Article (Journal)
Electronic Resource
Unknown
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