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    Analysis of the Relationship between University Students’ Problematic Internet Use and Loneliness
    (2018) Hebebci, Mustafa Tevfik; Shelley, Mack
    The computer is part of the information and communication age, and the Internet today is the most used communication tool. Studies have shown that there is a relationship between problematic Internet use and loneliness. The aim of this study was to investigate the relationship between problematic Internet use sub-scales and loneliness. In this study, data were collected from the college students at an Anatolian University in Turkey. The participants of this study consisted of 392 undergraduates. Of the participants, 43% are male (n 167) and 57% female (n 225). The average age for the participants is 22 years old. The Problematic Internet Use Scale and the University of California, Los Angeles (UCLA) Loneliness Scale were used as data collection instruments. In the present study, structural equation modeling (SEM) procedures are used to explore the relationships that exist among the variables. The findings of the study revealed that while university students’ social benefit/social comfort of Internet has a direct effect on their excessive Internet use and negative consequences, it is related to the loneliness level indirectly. In addition, it is seen in the research model that with an increase in the negative consequences of the Internet, the loneliness level was raised. Another result from the study is that when university students’ excessive Internet use increased, their loneliness level decreased.
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    Transfer of Learning in Mathematics, Science, and Reading among Students in Turkey: A Study Using 2009 PISA Data
    (Necmettin Erbakan Univ, 2013) Shelley, Mack; Yildirim, Atila
    Using Program for International Student Achievement (PISA) 2009 data we study the transfer of knowledge among reading, mathematics, and science among Turkish students. Both Science and Reading are significant predictors of Mathematics scores, although clearly Science is a much stronger predictor; the transfer from Science to Mathematics is much greater than is the transfer from Reading to Mathematics. SCHOOLID is the single strongest predictor of Mathematics outcomes, likely reflecting the importance of socioeconomic and regional or urban/rural differences in the quality of education available to students. Both Mathematics and Reading are significant predictors of Science scores, although Mathematics is a stronger predictor; the transfer from Mathematics to Science is greater than is the transfer from Reading to Science. SCHOOLID is a weaker predictor of Science outcomes than are Mathematics scores, suggesting that the importance of socioeconomic and regional or urban/rural differences in the quality of education available to students may have slightly less consequence for Science outcomes than does the transfer effect from Mathematics to Science. Both Science and Mathematics are significant predictors of Reading scores, but the transfer from Science to Reading is much more robust than the transfer from Mathematics to Reading. SCHOOLID and Science are nearly identically strong predictors of Reading outcomes, suggesting that the importance of socioeconomic and regional or urban/rural differences in the quality of education available is on a par with the Science transfer to Reading. Implications of these findings are discussed.