Technology-based learning environments
M. Moatari; E. pazouki; R. Ebrahimpour; M.R. Rezaee
Abstract
Background and Objectives: Today, e-learning is considered as a transformational technology and an important tool in the process of education and educational activities. On the other hand, the need to learn English as the first language in the world in order to exchange information and communicate with ...
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Background and Objectives: Today, e-learning is considered as a transformational technology and an important tool in the process of education and educational activities. On the other hand, the need to learn English as the first language in the world in order to exchange information and communicate with other nations in order to use up-to-date knowledge is undeniable, so the use of information technology to produce and provide educational services to improve English language teaching and learning is effective. Identifying the effective factors in achieving learning is one of the important and researched cases. Since the factors affecting learning are very wide and extensive, it is important to identify these factors in solving the problems and shortcomings of the educational system. One of these factors is cognitive style. People use different learning styles according to their individual differences. Cognitive style can be defined as the way people process new information and experiences in their minds; therefore, it is necessary to create a personalized environment based on the cognitive style of individuals in order to better adapt the educational strategy to the needs and abilities of the user and increase the efficiency of the learning process. In this research, Riding’s cognitive style, which divides people into two dimensions, verbal-imagery and wholistic-analytic, is used as an effective factor in learning. This study aims to predict the cognitive style of riding, based on the mouse movement of users in a language teaching software. In this regard, the language training software was designed and implemented, in which all the user's mouse movements are recorded on a millisecond scale when reading the English text and using the media designed in the software. Next, by using machine learning methods and interactive data stored from users while working with the software, an intelligent model was presented that categorizes people in two dimensions based on Riding’s cognitive style. This research is practical in terms of purpose.Methods: In this study, Peterson’s cognitive style test is used to extract learners' cognitive style with the aim of constructing labeled data. Also, individuals’ mouse data is recorded when interacting with software, and artificial intelligence-based machine learning algorithms and models are used to build intelligent models for classifying and predicting individuals' cognitive styles. The process of training and building smart models is done through labeled data. Finally, the models used are evaluated by comparing the results of the cognitive style test and the outputs of the intelligent models. In the exams, male and female students aged between 22 and 35, with bachelor's and master's degrees familiar with English participated.Findings: Users stored interactive data was used as the input to the five classifiers of the decision tree, neural network, nearest neighbor, support vector machine, and random forest. Patterson test results were also used as labels for these models; thus, individuals were categorized into two dimensions based on Riding’s cognitive style. The best classification was related to the decision tree with 90% accuracy in the verbal-imagery dimension and 87% accuracy in the wholist-analytic dimension of the results of this research.Conclusion: According to the findings of this study, the designed language teaching system can intelligently extract the cognitive style of people when reading the English passage with appropriate accuracy. Therefore, in the future, the ability to provide personalized content in accordance with the cognitive style of people can be added to the designed software.
Educational Technology - Public education
M. Vakilisadeghi; R. Noori; O. Ebadati
Abstract
Today, business, economics and society has been transformed by information technology. Many traditional ways of earning money have evolved and new methods and values have come to the fore. In this regard, Study of the e-business system in today's complex and turbulent world is essential. Despite the ...
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Today, business, economics and society has been transformed by information technology. Many traditional ways of earning money have evolved and new methods and values have come to the fore. In this regard, Study of the e-business system in today's complex and turbulent world is essential. Despite the fact that some businesses succeed in their field of work, there are many businesses that fail, because of selecting inappropriate business model. So, this study which has been done to identify successful e-business models using machine learning techniques. Quantitative survey was used to doing research. 105 businesses with a eTrust were selected to find the best successful electronic business model. The instrument used to collect data was a questionnaire. Analyzing collected data shoes the best business model for the success of businesses in Iran, are e-shop model and the advertising. The results of the k-means algorithm and ID3 show that of the 12 criteria considered in choosing the best model for success, two criteria; including the development of IT tools and company strategy have the most important role for the success of trusted businesses.
