Use of mobile phones by male and female Greek students

Economides, Anastasios A.; Grousopoulou, Amalia

doi:10.1504/ijmc.2008.019822

Cited by 49 publications

(25 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cavus and Bicen (2009) indicated that males seem to use the technology more effectively than the females, thus that affects their perceptions. However, in their research on the application of mobile technologies, Economides and Grousopoulou (2008) argued that gender differences did not produce a significant difference. Although the obtained results were for the advantage of the male, the perception of m‐learning in female was above the medium level.…”

Section: Discussionmentioning

confidence: 99%

Teacher perception for m-learning: scale development and teachers' perceptions

Uzunboylu

Özdamlı

2011

Journal of Computer Assisted Learning

145

View full text Add to dashboard Cite

Successful integration of mobile learning (m-learning) technologies in education primarily demands that teachers' perception of such technologies should be determined. Therefore, the perceptions of teachers are of great significance. There is no available instrument that assesses teachers' perceptions of m-learning. Our research provided the first findings about teacher perceptions in Cyprus. This article describes the development, testing and application for a suitable instrument. Research data for the tests of reliability and validity were obtained from a sample of 467 teachers from the 32 schools surveyed in 2010. The final version of the Mobile Learning Perception Scale includes dimensions seeking teachers' feedback on three facets of the m-learning. Sub-dimensions are defined as 'Aim-Mobile Technologies Fit', 'Appropriateness of Branch', and 'Forms of M-learning Application and Tools' Sufficient Adequacy of Communication'. Validity has been established by the use of factor analysis. Internal consistency coefficient and reliability of the scale showed that this instrument can be used for the future studies. According to the results of this study, teachers exhibited above medium levels of perception towards m-learning.

show abstract

Section: Discussionmentioning

confidence: 99%

Teacher perception for m-learning: scale development and teachers' perceptions

Uzunboylu

Özdamlı

2011

Journal of Computer Assisted Learning

145

View full text Add to dashboard Cite

show abstract

“…Instead of this criterion type, questions requiring descriptions of specific verifiable behaviors appear to be promising (e.g., "In the course of the past 4 weeks, how many emails have you sent via your MI access on a typical day? "; cf., Kim and Malhotra 2005;Economides and Grousopoulou 2008). Responses to this type of queries may be collected on continuous scales without predetermined answer options or with a closed set of quantitatively anchored answer categories (Sharma et al 2009).…”

Section: Development Of Hypothesesmentioning

confidence: 99%

“…The self-report scale of MI use intensity was constructed from responses to three questions adopted from previous MI, MDS, and IS research (e.g., Tung 2004; Kim and Malhotra 2005;Turel et al 2007;Bina et al 2008;Economides and Grousopoulou 2008;Koivumäki et al 2008;Oh et al 2008;Lee et al 2008;Wei 2008;Kuo and Yen 2009). First, it was asked "How often do you currently use MI services?".…”

Section: Measurement Of MI Use Intensitymentioning

confidence: 99%

“…Especially in many Western countries, MI acceptance is considerably lagging behind the showcase markets in South Korea, Japan and Singapore (Minges 2005;Funk 2007;ITU 2009). Recent surveys suggest that only a small proportion of MNO customers who are already equipped with devices which possess the technical capability of accessing MI effectively use this capacity (Economides and Grousopoulou 2008;Koivumäki et al 2008;Mohr 2008). In addition, a considerable share of MI subscribers fails to use it intensively or even completely ceases to apply MI after the initial adoption (Lee et al 2007bKim et al 2008;Verkasalo 2008b).…”

mentioning

confidence: 99%

“…Fewer post-adoption investigations construe their dependent MI or MDS acceptance measures from MNO customers' stated intensity, frequency and/or duration of certain categories of mobile communication behaviors such as running a video stream, browsing news websites, or employing a search machine portal (e.g., FogelgrenPedersen 2005;Sugai 2007;Turel et al 2007;Bina et al 2008;Economides and Grousopoulou 2008;Koivumäki et al 2008;Lee et al 2008;Oh et al 2008;Wei 2008;Westlund and Bohlin 2008;Bouwman et al 2009). The accuracy of customers' MI-related self-estimates of their use frequencies, duration, or changes must not be taken for granted.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Determinants of self-report and system-captured measures of mobile Internet use intensity

Gerpott

2010

Inf Syst Front

View full text Add to dashboard Cite

Most research on the first adoption and subsequent use (= acceptance) of Internet access through cellular networks and portable appliances (= mobile Internet) has followed a similar pattern. It has employed survey responses of mobile network operator [MNO] customers to explain consumers' stated future use (continuance) intentions or claimed use intensities related to mobile Internet [MI] access by various beliefs about MI (e.g., perceived relative advantage, usefulness, ease of use). However, there is ample evidence suggesting that MI use intentions and self-reported use intensities are only weakly correlated with actual MI use. Therefore, the present paper develops hypotheses on how the ability of different types of variables to account for variance in MI use intensity may vary depending on whether subjectively estimated or objectively captured use serves as the criterion variable. The hypotheses are tested by analyzing actual MI use behaviors of 300 adopters in Germany, whose mobile IP traffic was extracted from an MNO's billing engine. This "system-captured" criterion measure is integrated with MI adopter responses collected by means of a standardized telephone survey. Results show that the predictors are more strongly correlated with self-rated than with system-captured MI use intensity. Up to 38% of the variance explained in selfrated use may be attributed to artifactual covariance between variables caused by common measurement methods. Factual MI use case features (MI tariff type and appliance class, fixed Internet home access availability) are better able to account for variance in both self-rated and actual MI use intensity than MI related beliefs. The findings imply that variable relationships observed in earlier MI and information system (IS) acceptance studies are likely to have been inflated by common method biases and thus may have provided spurious support for the conceptual frameworks tested. Implications of the results for future MI and IS acceptance research and for MNO seeking to forecast and to influence the MI use intensity of their customers are discussed.

show abstract

Mobile phone usage behavior: A longitudinal study of university students in Oman

Belwal

Hoque

Belwal

2022

E J Info Sys Dev Countries

View full text Add to dashboard Cite

Mobile phones have emerged as ubiquitous devices beyond simple means of communication. Students studying at tertiary‐level educational institutions are one of the major target groups for mobile companies. Notwithstanding, the educators and the marketers of mobile phones and services do not know much about their needs and mobile phone usage behavior. This study aims to determine the mobile phone needs and usage behavior of university students in Oman. The study delves upon longitudinal data collected over three different points of time in a decade and analyzes the changes in students' needs and mobile usage behavior. The findings suggest that students' preferences over time for mobile phones have changed not only for brands but also the way they patronize mobile phones and associated services. The study gives a vital lead to educators and the marketers of mobile phones and services. By understanding the mobile phone needs and usage behavior of students, educators can target their content and deliveries and marketers can target their features, apps, and services innovatively to this emerging segment.

show abstract

Use of mobile phones by male and female Greek students

Cited by 49 publications

References 32 publications

Teacher perception for m-learning: scale development and teachers' perceptions

Teacher perception for m-learning: scale development and teachers' perceptions

Determinants of self-report and system-captured measures of mobile Internet use intensity

Mobile phone usage behavior: A longitudinal study of university students in Oman

Contact Info

Product

Resources

About