Authors:Jon E. Grant, Katherine Lust and Samuel R. Chamberlain
, relatively little is known about the associations between problematic use of smartphones, academicperformance, and addictive behaviors in university settings. Therefore, this study sought to examine both the occurrence of problematic use of smartphones in a
Background and aims: Prior research on Internet dependency has examined various individual traits as contributing factors. Since domain-specific traits tend to have higher abilities to explain outcome variables, this study investigates a technology-related specific trait, i.e., computer playfulness, as a predictor of Internet dependency, and their influence on Internet usage patterns and academic performance. Methods: A sample of 267 college students was surveyed to examine these relationships. In addition to demographic information, the questionnaire contained measurement scales to assess playfulness, Internet dependency as well as work/study-related and social-related uses of the Internet. Results: Survey data indicate that playfulness significantly predicts Internet dependency (ΔR2 = 19%). Playfulness is also significantly related to students’ grade point average (p <.001), as well as Internet use for social purposes (p <.022), and its impacts are fully mediated by Internet dependency. It was also found that neither playfulness nor Internet dependency is significantly associated with Internet use for work/study purposes. Conclusions: Playfulness, as a domain-specific individual trait, is a powerful predictor of Internet dependency, which is positively related to social use of the Internet, and negatively related to student academic performance.
. (2010). A pályakezdő orvosok jövőképe és egészségi állapota. Lege Artis Medicinae, 20 (6–7), 423–429.
Salanova, M., Schaufeli, W.B., Martínez, I.M., & Breso, E. (2010). How obstacles and facilitators predict academic
Authors:Paweł A. Atroszko, Cecilie Schou Andreassen, Mark D. Griffiths and Ståle Pallesen
Recent research has suggested that for some individuals, educational studying may become compulsive and excessive and lead to ‘study addiction’. The present study conceptualized and assessed study addiction within the framework of workaholism, defining it as compulsive over-involvement in studying that interferes with functioning in other domains and that is detrimental for individuals and/or their environment.
The Bergen Study Addiction Scale (BStAS) was tested — reflecting seven core addiction symptoms (salience, mood modification, tolerance, withdrawal, conflict, relapse, and problems) — related to studying. The scale was administered via a cross-sectional survey distributed to Norwegian (n = 218) and Polish (n = 993) students with additional questions concerning demographic variables, study-related variables, health, and personality.
A one-factor solution had acceptable fit with the data in both samples and the scale demonstrated good reliability. Scores on BStAS converged with scores on learning engagement. Study addiction (BStAS) was significantly related to specific aspects of studying (longer learning time, lower academic performance), personality traits (higher neuroticism and conscientiousness, lower extroversion), and negative health-related factors (impaired general health, decreased quality of life and sleep quality, higher perceived stress).
It is concluded that BStAS has good psychometric properties, making it a promising tool in the assessment of study addiction. Study addiction is related in predictable ways to personality and health variables, as predicted from contemporary workaholism theory and research.
convenience as per our judgement at least. There exist quite a number of other single figure indicators of academicperformance such as the A-index (Jin 2006 )and the R-index (Jin et al. 2007 ) to name a few. Nevertheless, they are not as easily calculted
A tanulmány célja a középiskolás diákok tanulmányi és nem tanulmányi
eredményességének vizsgálata az egészségmagatartás és tanulmányi eredményesség
egyes faktorai alapján létrehozott klaszterek által. A minta 48 középiskola
tanulóit tartalmazza hazánk hét régiójából és Budapestről, valamennyi évfolyam
(9–12) bevonásával (n = 2 864). Klaszteranalízis alapján négy
tanulói klaszter vált elkülöníthetővé: a deviáns (rossz egészségmagatartás és
tanulmányi eredményesség), flegma (jobb egészségmagatartás, rosszabb tanulmányi
eredményesség), stresszes (jobb egészségmagatartás, rosszabb mentális egészség
és tanulmányi eredményesség) és kiegyensúlyozott (jobb egészségmagatartás és jó
tanulmányi teljesítmény) klaszterek. Eredményeink alapján a nem, az évfolyam és
a területi elhelyezkedés tekintetében a klasztertagságok megoszlásában jelentős
különbségek mutathatóak ki.
Authors:Alireza Abbasi, Jörn Altmann and Junseok Hwang
Although there are many studies for quantifying the academic performance of researchers, such as measuring the scientific
performance based on the number of publications, there are no studies about quantifying the collaboration activities of researchers.
This study addresses this shortcoming. Based on three measures, namely the collaboration network structure of researchers,
the number of collaborations with other researchers, and the productivity index of co-authors, two new indices, the RC-Index and CC-Index, are proposed for quantifying the collaboration activities of researchers and scientific communities. After applying these
indices on a data set generated from publication lists of five schools of information systems, this study concludes with a
discussion of the shortcomings and advantages of these indices.
Authors:Mu-Hsuan Huang, Han-wen Chang and Dar-Zen Chen
have been regarded as the most significant output indicating the research
performance of universities. This paper uses ISI Essential Science
Indicators (ESI) database to investigate the academic performance of
research-oriented universities in Taiwan, adopting the bibliometric method from
both quantitative and qualitative perspectives. The data cover the time span
for 11 years from 1993 to 2003. The performance indicators applied in this
study includes the number of papers, the number of citations, the average
citations per paper, the number of highly cited papers, the number of hot
papers, and the number of top papers. The research performance and the strength
of those universities are revealed in this study, and it is found that National
Taiwan University leads among these universities though each university still
shows strengths in various specific fields.