Tackling the digital divide: Exploring ICT access and usage patterns among final-year upper secondary students in Italy
Main Article Content
Abstract
This study examines the access and usage of Information Communication Technologies (ICTs) outside the school environment among upper secondary students in Italy, based on data from the 2021-2022 INVALSI Field Trial. The study investigates the availability of digital devices such as desktops, laptops, and smartphones, and explores usage patterns through a questionnaire addressing the first and second digital divides, socio-demographics, and other relevant factors. The findings provide food for thought for those who need to manage technology and enhance learning. Notably, 96% of students reported having access to a computer at home for both learning and non-learning activities, and 88% had internet connectivity at home. While initial results suggest a reduction in the digital access gap, logistic regression models indicate that the first-level digital divide remains challenging for certain socio-economic groups. Using association rules data mining techniques, therefore, specific activities were identified as the most influential among students. Most of the grade 13 students possessed ICT tools and used them primarily for leisure activities such as social media, online communication platforms, entertainment videos and music, and web browsing.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons CC BY 4.0 Attribution 4.0 International License.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access)
References
Abdullah, Z., Herawan, T., Ahmad, N., & Deris, M. M. (2011). Mining significant association rules from educational data using critical relative support approach. Procedia Social and Behavioral Sciences, 28, 97–101. https://doi.org/10.1016/j. sbspro.2011.11.020
Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. ACM SIGMOD Record, 22, 207–216. https://doi.org/10.1145/170036.170072
Attewell, P. (2001). Comment: The first and second digital divides. Sociology of Education, 74, 252-259. https://doi.org/10.2307/2673277
Attewell, P., & Monaghan, D. (2015). Data mining for the social sciences: An introduction. University of California Press. https://doi.org/10.1525/9780520960596
Benecchi, A., Ciapanna, E., Bottoni, C., Frigo, A., Milan, A., & Scarinzi, E. (2021). Digitalisation in Italy: Evidence from a new regional index. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4016669
Burgess, M. C., Stermer, S. P., & Burgess, S. R. (2007). Sex, lies, and video games: The portrayal of male and female characters on video game covers. Sex roles, 57, 419-433. https://doi.org/10.1007/s11199-007-9250-0
Campodifiori, E., Figura, E., Papini, M., & Ricci, R. (2010). Un indicatore di status socio-economico-culturale degli allievi della quinta primaria in Italia. Invalsi.
Cedefop (2021). Digital skills: challenges and opportunities during the pandemic. Cedefop, https://www.cedefop.europa.eu/en/news/ digital-skills-challenges-and-opportunities-during-pandemic
Cesareo, V. (2022). Ventisettesimo rapporto sulle migrazioni 2021. Ventisettesimo rapporto sulle migrazioni 2021, 1–301. https://www.ismu.org/ ventisettesimo-rapporto-sulle-migrazioni-2021/
Chiu, M.-S. (2020). Exploring models for increasing the effects of school information and communication technology use on learning outcomes through outside-school use and socioeconomic status mediation: The ecological techno-process. Educational Technology Research and Development, 68(1), 413–436. https://doi. org/10.1007/s11423-019-09707-x
Chugh, R. & Ruhi, U. (2018). Social media in higher education: A literature review of facebook. Education and Information Technologies, 23, 605–616. https://doi.org/10.1007/s10639-017-9621-2
Crosier, D., & Sigalas, E. (2022). Towards equity and inclusion in higher education in Europe: Eurydice report. Luxembourg: Publications Office of the European Union, 2022. https://hdl.handle.net/11162/222272
Di Pietro, G. (2021). Changes in Italy’s education-related digital divide. Westminster Research. https://doi.org/10.1111/ecaf.12471
DiMaggio, P., Hargittai, E., Neuman, W. R., & Robinson, J. P. (2001). Social implications of the internet. Annual Review of Sociology, 27, 307–336. https://doi.org/10.1146/annurev.soc.27.1.307
Dindar, M. (2018). An empirical study on gender, video game play, academic success and complex problem solving skills. Computers & Education, 125, 39–52. https://doi.org/10.1016/j.compedu.2018.05.018
Fernàndez-Gutiérrez , M., Gimenez, G., & Calero, J. (2020). Is the use of ICT in education leading to higher student outcomes? Analysis from the spanish autonomous communities. Computers & Education, 157. https://doi. org/10.1016/j.compedu.2020.103969
Fraillon, J., Ainley, J., Schulz, W., Duckworth, D., & Friedman, T. (2019). IEA International computer and information literacy study. 2018 Assessment Framework. Springer International Publishing. https://doi.org/10.1007/ 978-3-030-19389-8
Gasaymeh, A. (2018). A study of undergraduate students’ use of Information and Communication Technology (ICT) and the factors affecting their use: a developing country perspective. EURASIA Journal of Mathematics, Science and Technology Education, 14(5), 1731–1746. https://doi.org/10.29333/ejmste/85118
Gebhardt, E., Thomson, S., Ainley, J., && Hillman, K (2019). What have we learned about gender differences in ICT? In Gender differences in computer and information literacy: An in-depth analysis of data from ICILS (pp. 69–73). https://doi.org/10.1007/ 978-3-030-26203-7_6
Gómez-Gonzalvo, F., Molina, P., & Devìs-Devìs, J. (2020). Which are the patterns of video game use in spanish school adolescents? gender as a key factor. Entertainment Computing, 34. https://doi.org/10.1016/j.entcom.2020. 100366
Goudeau, S., Sanrey, C., Stanczak, A., Manstead, A., & Darnon, C. (2021). Why lockdown and distance learning during the covid-19 pandemic are likely to increase the social class achievement gap. Nature Human Behaviour, 5(10), 1273–1281. https://doi.org/10.1038/s41562-021-01212-7
Greenberg, B. S., Sherry, J., Lachlan, K., Lucas, K., & Holmstrom, A. (2010). Orientations to video games among gender and age groups. Simulation & Gaming, 41(2), 238–259. https://doi.org/10.1177/1046878108319930
Han, J., & Pei, J. (2000). Mining frequent patterns by pattern-growth. ACM SIGKDD Explorations Newsletter, 2, 14–20. https://doi.org/10.1145/ 380995.381002
Heo, H., & Kang, M. (2010). Impacts of ICT use on school learning outcome. In F. Scheuermann, & F. Pedró (Eds.), Assessing the effects of ICT in education. Indicators, criteria and benchmarks for international comparisons (pp. 189-198). European Commission Joint Research Centre. https://erte.dge.mec.pt/sites/default/files/Recursos/Estudos/assessingtheeffectsofictineducation.pdf
ISTAT. (2020a). Il rapporto Istat sul BES. ISTAT. https://www.istat.it/it/ files//2021/03/BES_2020.pdf
ISTAT. (2020b). Italian multipurpose survey on households. ISTAT. https://www.istat.it/wp-content/uploads/2014/08/ISTAT_MFR_AVQ_2020_IT-2.zip
Kenny, E. (2017). Settlement in the digital age: Digital inclusion and newly arrived young people from refugee and migrant backgrounds. Centre for Multicultural Youth. https://www.cmy.net.au/wp-content/uploads/2020/03/ Settlement-in-the-digital-age_Jan2017.pdf
Ludvìk, E., Łukasz, T., Milan, K., Maria, P., & Gabriela, P. (2020). How do first year university students use ICT in their leisure time and for learning purposes? International Journal of Cognitive Research in Science, Engineering and Education, 8(2), 35–52. https://doi.org/10.5937/IJCRSEE2002035E
Nachmias, R., Mioduser, D., & Shemla, A. (2001). Information & Communication Technologies usage by students in an Israeli high school: Equity, gender, and inside/outside school learning issues. Education and Information Technologies, 6, 43–52. https://doi.org/10.1023/A:1011367212148
OECD. (2017). Pisa 2018 ICT familiarity questionnaire. OECD Publishing. https://www.oecd.org/pisa/data/2018database/CY7_201710_QST_MS_ICQ_ NoNotes_final.pdf
OECD. (2023). PISA 2022 Assessment and Analytical Framework. OECD Publishing.
https://doi.org/https://doi.org/10.1787/dfe0bf9c-en
Ola Lindberg, J., & Sahlin, S. (2011). Bridging school-subjects and distances in upper secondary schools. Campus-Wide Information Systems, 28(3), 144–153. https://doi.org/10.1108/10650741111145670
Olofsson, A. D., Lindberg, O. J., & Fransson, G. (2018). Students’ voices about information and communication technology in upper secondary schools. The International Journal of Information and Learning Technology, 35(2), 82–92. https://doi.org/10.1108/IJILT-09-2017-0088
Phan, M. H., Jardina, J. R., Hoyle, S., & Chaparro, B. S. (2012). Examining the role of gender in video game usage, preference, and behavior. In Proceedings of the human factors and ergonomics society annual meeting, Vol.56 (pp.1496– 1500). Sage Publications. https://doi.org/10. 1177/1071181312561297
Raschka, S. (2018). Mlxtend: Providing machine learning and data science utilities and extensions to python’s scientific computing stack. Journal of Open Source Software, 3(24), 638.
Riggins, F., & Dewan, S. (2005). The digital divide: Current and future research directions. Journal of the Association for Information Systems, 6:298–337. https://doi.org/10.17705/1jais.00074.
SANFO, J.-B. M. B. (2023). Examining student ICT use and learning outcomes: Evidence from Japanese Pisa data. Computers and Education Open, 4. https://doi.org/10.1016/j.caeo.2023.100141
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53. https://doi.org//10.5116/ijme.4dfb.8dfd
Tuszynski, J., & Khachatryan, M. H. (2013). Package ‘Catools’. https://cran.r-project.org/web/packages/caTools/caTools.pdf
van Dijk, J. (2005). The deepening divide: Inequality in the information society. SAGE Publications. https://doi.org/10.4135/9781452229812
Vassilakopoulou, P., & Hustad, E. (2023). Bridging digital divides: A literature review and research agenda for information systems research. Information Systems Frontiers, 25(3), 955–969. https://doi.org/10.1007/s10796-020-10096-3
Wastiau, P., Blamire, R., Kearney, C., Quittre, V., Van de Gaer, E., & Monseur, C. (2013). The use of ICT in education: a survey of schools in europe. European Journal of Education, 48(1), 11–27. https://doi.org/10.1111/ejed.12020
Xiao, F. & Sun, L. (2022). Profiles of student ICT use and their relations to background, motivational factors, and academic achievement. Journal of Research on Technology in Education, 54(3), 456–472. https://doi.org/10.1080/15391523. 2021.1876577
Zhang, C. & Zhang, S. (2002). Association rule mining: models and algorithms. Springer. https://doi.org/10.1007/3-540-46027-6