The Use of Mobile Technology for M-learning in Improving Economics
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This study is aimed at examining the effect of the use of mobile technology in academic activities at the University of KwaZulu-Natal. In order to identify determinants of students' academic performance in the College of Law and Management Studies at UKZN, this study conducted regressions with a recorded data in two different educational production functions, namely Ordinary Least Squares and Logistic Regression Model. The production function method was adopted to examine and explain the effect of mobile technology in education. The mobile technology was treated as the factor determinant for a...
This study is aimed at examining the effect of the use of mobile technology in academic activities at the University of KwaZulu-Natal. In order to identify determinants of students' academic performance in the College of Law and Management Studies at UKZN, this study conducted regressions with a recorded data in two different educational production functions, namely Ordinary Least Squares and Logistic Regression Model. The production function method was adopted to examine and explain the effect of mobile technology in education. The mobile technology was treated as the factor determinant for academic performance, as shown: Pij = beta1 + beta2hours of study + beta3class attendance + beta4tutorial attendance + beta5m-technology + beta6race + beta7gender + beta8location + uij (1). The cumulative distribution function was used to examine the probability of passing economics, provided that a student is using mobile technology during studying. Logit (Pij) = Yi beta + Ui (2). The overall results show that students that are using mobile technology perform better than those that isolate the usefulness of mobile technology.
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