Teachers’ and students’ Internet use – the intelemetric number
Author(s):
András Buda (presenting / submitting)
Conference:
ECER 2015
Format:
Poster

Session Information

16 SES 05.5 PS, General Poster Session

General Poster Session

Time:
2015-09-09
12:30-14:00
Room:
Poster Area
Chair:

Contribution

When computers and the Internet appeared and started to gain ground, penetration stood in the center of investigations, the most common aspect of the approach was about accessibility versus inaccessibility. However, the participants at the conference called The Lifelong Learning and New Technologies Gap held in 1999 at theUniversityofPennsylvaniaremarked that the exclusive utilization of this dichotomous difference-inducing dimension has no validity. The simple indices of availability might be considerably misleading and be influenced by several economical and cognitive factors. This change in attitude soon seeped into researches, and besides accessibility more and more investigations dealt with the presence and absence of skills necessary for using tools, and the issues analyzing the aim, content and quality of use became vital, as well.

Within the researches the investigation of negative consequences gained high priority, since apart from the numerous positive aspects of the expanding technology new types of deviations had appeared, especially amongst the young. Scientific publications spoke about Internet addiction as early as at the late nineties, a notion that was defined through the length of Internet use by the first researches. Chebbi (2000) put the maximum healthy dosage of Internet use at 19 hours per week; however, according to Young (1998), those people may be considered addicts who spend at least 38 hours a week or 8 hours a day on the Internet. Nevertheless, Xu and their colleagues (2012) made it clear that it is not enough to investigate the length of time spent with the Internet to find out whether someone is an addicted user. Apart from the quantity indices quality features might bear some importance too, therefore, beyond examining the time spent in front of the Internet, it is also necessary to disclose the impact the medium has on personal relationships and free-time habits.

Yet, finding the definition and clarifying the theoretical bases of “Internet Addiction” caused some problems and generated fierce debates during the investigations. This is why in line with the diversity of approaches several different scales have been developed to measure Internet addiction. It is known from Laconi’s study (2014) that the most popular of these are the Internet Addiction Test (IAT) and the Problematic Internet Use Scale (PIUS). These tests, however, always approach addiction on theoretical bases, they do not examine its manifestations realized in actual activities.

Despite all these, there are few measuring tools at present that would start by measuring the skills needed to use the Internet. The most widely-known of these is the list of questions used by Eurostat, in which six task groups were established in relation to Internet use in order to classify the respondents based on their use of the Internet. Researchers examine how many of these tasks the participants can carry out and based on their responses they are classified into three groups: people with low-, medium- and high-level Internet use skills.

The measuring tool assembled by us (intelemetric.unideb.hu) has improved this activity-centered approach by mixing it with the formerly used aspects and the current practice. The document contains questions whose answers can determine with the help of a hundred point scale the degree of importance the Internet plays in a person’s life. This numerical value is the so called “Intelemetric Number”, with the assistance of which all persons may be delegated to a group out of five: beginner, basic, advanced, networked, addicted.

The poster we intend to present does not only wish to introduce the measuring tool to the audience but we are also determined to reveal the findings and experiences that came to life during the implementation of this new tool.

Method

The questionnaire enabling us to get the intelemetric number contains 20 questions, the answers can be given on a six point scale ranging from zero to five. The questions look at the intensity of various activities, and ten plus ten of them ask about daily and weekly frequencies, respectively. We first carried out a pilot research with the new tool in the autumn of 2014 in Hungary, at the University of Debrecen. We asked full time, teacher training majors to fill out the questionnaire (Cronbach's α = 0.77) available online. We chose this because of two reasons. Firstly, this way we could map the characteristics of a group that is the pioneer in the utilization of modern technology. Computers and the Internet are practically inevitable for students in higher education, for every requirement, syllabus, material, and grade can be accessible via the Internet. Secondly, it is also vital to learn about the characteristics of this group because these students will turn teachers and will set examples to their students through their work and value system, so it is crucial to get to know the image they convey so that we can modify it during our training if necessary. More than one third of the invited students, 89 of them, answered the questions. Three students came out as beginners, forty-four of them went into the basic group, thirty-seven scored advanced requirements, five turned out to be networked users, and there was no one declared an addicted. It is important to note that eighty percent of the respondents entirely or almost entirely agreed with their classification! However, if we had taken Young’s (1998) division into account, a great majority of the students, and, according to Chebbi’s view (2000), almost everyone, should have been considered an Internet addict, as the participants spend an average 3.63 hours per day on the Internet deriving data from their accounts. Surveys are currently conducted using the measurement tools modified as per the experiences from the pilot and the suggestions of the participants. We wish to study three groups: students of grades 4-8, those in grades 8-12 and teachers, and 100 respondents from the first age group have already replied the questions. The data will be processed with the help of the SPSS program.

Expected Outcomes

Results of the data collection currently in progress can be utilized in several different ways. On the one hand, this will make available a new tool for studying attitudes to the Internet which is not based on the analysis of cognitive or mental states but of practical activities. On the other, by mapping age group characteristics teachers can use more expedient teaching methods during their pedagogical work. As for utilized methods they can take into account their students’ usual activities, they can use more adequate and efficient solutions. The data show us which the areas are where students’ and teachers’ activities differ significantly. The differences thus pinpointed must be taken on by teacher training and further education programs so that the level of teachers’ knowledge and efficiency may improve. The study can also have an impact on the persons studied, which was pointed out by a student completing the questionnaire. She wrote: “It is useful for me as well, now I got a clearer picture of my Internet using habits.” Therefore, in addition to the direct effects, there is an indirect effect, too. The questions make respondents confront their own characteristics, thus they might change their previous activities due to the questionnaire.

References

Chebbi, P., Koong, K. S., & Liu L, (2000). Some Observations on internet addiction disorder research, Graduate studies program in computer information systems southern University at New Orleans New Orleans, LA 70126, USA. J Info Syst Educ. 11. 97–104. Demetrovics, Z., Szeredi, B., & Rozsa, S. (2008). The three-factor model of Internet addiction: The development of the Problematic Internet Use Questionnaire. Behavior Research Methods, 40(2), 563–574. Guertler, D., Rumpf, H.-J., Bischof, A., Kastirke, N., Petersen, K. U., John, U., & Meyer, C. (2014). Assessment of problematic Internet use by the Compulsive Internet Use Scale and the Internet Addiction Test: A sample of problematic and pathological gamblers. European Addiction Research, 20, 75–81. Laconi, S., Rodgers, R. F., & Chabrol, H. (2014). The measurement of Internet addiction: A critical review of existing scales and their psychometric properties. Computers in Human Behavior 41 (2014) 190–202. Lortie, C. L., & Guitton, M. J. (2013). Internet addiction assessment tools: Dimensional structure and methodological status. Addiction Review, 108(7), 1207–1216. Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among college students. Computers in Human Behavior, 16, 13–29. Spada, M. M. (2014). An overview of problematic Internet use. Addictive Behaviors, 39, 3–6. Young, K. S. (1998). Caught in the Net – How to recognize the signs of Internet addiction – and a winning strategy for recovery. New York: John Wiley & Sons, Inc. Xu, J., Shen L. X., Yan, C. H., Hu, H., Yang, F., Wang, L., Kotha, S. R., Zhang, L. N., Liao, X. P., Zhang, J., Ouyang, F. X., Zhang, J. S., & Shen, X. M. (2012): Personal characteristics related to the risk of adolescent internet addiction: a survey is Shanghai, China. Abstract. BMC Public Health. Retrieved March 28, 2014 from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3563549/

Author Information

András Buda (presenting / submitting)
University of Debrecen
Institute of Educational Studies
Debrecen

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