It is widely acknowledged that mobility and availability are the key barriers to the effective application of e-learning approaches. Whilst the advent and variety of mobile technologies could offer a means of removing these barriers, there is a lack of research that addresses different aspects of mobile learning service quality in the education environment. This study aimed to propose a quality model that captures the most abstract and generic technical aspects of mobile learning service quality. A set of technical quality aspects was developed from a literature study with a focus on learning standards and mobile application software quality and guidelines. To demonstrate the feasibility of the proposed model, four different four case studies were conducted with the representative selected technical quality aspects in a cumulative exercise. This new non-functional technical quality mobile learning model examined
the applications by assessing all model components and analysing stakeholders' satisfaction. The empirical case study investigation highlighted a set of contextual technical quality factors that influence the choice of mobile learning applications. The case studies show the feasibility of using the proposed model to evaluate existing mobile learning applications.
The findings also indicate that there are causal relationships between learner satisfaction and the overall technical quality aspects of the proposed model. The complexity of the quality management process for mobile learning arises from the intersection between different domains, including education, pedagogy, content management, software development and mobile technologies. Despite the resemblance to a software project, mobile learning development and evaluation processes are far more complex and require analysis of components from different fields. This has a further impact on the overall cost of the quality management
process. The proposed quality model has a positive impact on
overall learning process outcomes by evaluating the technical aspects
while maintaining the quality of the mobile learning delivered.
Future research could aim to offer a comprehensive and
improved specification of the non-functional aspects, including
both technical and nontechnical factors, with a shared ontology.
It is widely acknowledged that mobility and availability are the key barriers to the effective application of e-learning approaches. Whilst the advent and variety of mobile technologies could offer a means of removing these barriers, there is a lack of research that addresses different aspects of mobile learning service quality in the education environment. This study aimed to propose a quality model that captures the most abstract and generic technical aspects of mobile learning service quality. A set of technical quality aspects was developed from a literature study with a focus on learning standards and mobile application software quality and guidelines. To demonstrate the feasibility of the proposed model, four different four case studies were conducted with the representative selected technical quality aspects in a cumulative exercise. This new non-functional technical quality mobile learning model examinedthe applications by assessing all model components and analysing stakeholders' satisfaction. The empirical case study investigation highlighted a set of contextual technical quality factors that influence the choice of mobile learning applications. The case studies show the feasibility of using the proposed model to evaluate existing mobile learning applications.The findings also indicate that there are causal relationships between learner satisfaction and the overall technical quality aspects of the proposed model. The complexity of the quality management process for mobile learning arises from the intersection between different domains, including education, pedagogy, content management, software development and mobile technologies. Despite the resemblance to a software project, mobile learning development and evaluation processes are far more complex and require analysis of components from different fields. This has a further impact on the overall cost of the quality managementprocess. The proposed quality model has a positive impact onoverall learning process outcomes by evaluating the technical aspectswhile maintaining the quality of the mobile learning delivered.Future research could aim to offer a comprehensive andimproved specification of the non-functional aspects, includingboth technical and nontechnical factors, with a shared ontology.
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