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Articles

The impact of digital skills on educational outcomes: evidence from performance tests

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Pages 137-162 | Received 24 Sep 2015, Accepted 24 Dec 2015, Published online: 26 Feb 2016
 

Abstract

Digital skills are increasingly important for labour market outcomes and social participation. Do they also matter for academic performance? This paper investigates the effects of digital literacy on educational outcomes by merging data from the Italian National Assessment in secondary schools with an original data-set on performance tests of Internet skills for tenth-grade students. Our identification strategy relies on a rich set of individual, family, school and classroom control variables that are not commonly available in previous studies. The findings indicate that, overall, Internet skills have a positive impact on academic achievement. This effect is stronger for students with low academic performance or low family background. It is also stronger for students in technical or vocational schools.

JEL classification:

Acknowledgements

We acknowledge financial support for data gathering from CISEPS, University of Milan Bicocca and from “Regione Lombardia”–European Social Fund. We also thank the Italian National Institute for the Evaluation of the School System (INVALSI) for providing data from the Italian National Assessment.

Funding

This work was supported by the regione Lombardia - European Social Fund and CISEPS.

Notes

1. Digital literacy generally refers to the ability to process information using digital technology in a multi-modal environment (e.g. Gilster Citation1997; Rivoltella Citation2008; Meyers, Erickson, and Small Citation2013). More specifically, digital literacy has been defined as “the ability to read and interpret media (text, sound, images), to reproduce data and images through digital manipulation, and to evaluate and apply new knowledge gained from digital environments.” (Jones-Kavalier and Flannigan Citation2006).

2. These studies also find that Internet information skills are particularly poor among young people.

3. Jackson (Citation2008) focuses on the social and psychological effects of Internet use rather than its cognitive effects.

4. See also Junco and Cotten (Citation2012) for the effects of multitasking on academic performance.

5. Among related studies, Eshet-Alkali and Amichai-Hamburger (Citation2004) present results from a performance-based pioneering study designed to examine the performance of users of different age groups in tasks that require the use of different types of digital literacy skills.

6. The tool was pre-tested in five classrooms in the Milan area. The final version of the test consists of 32 open-ended or closed-ended questions. Students were asked to evaluate the content of actual web pages, to analyse website addresses and browsers’ search results, and to demonstrate their knowledge of the working logic of websites popular among youths, such as Facebook, YouTube, Yahoo Answers and Wikipedia. The survey was carried out with computer-assisted web interviewing, using the LimeSurvey open source application. A researcher was present during the entire duration of the test, in order to avoid cheating among students or from the web and to provide solutions to technical problems.

7. National INVALSI tests were introduced in Italian schools in 2008, with the purpose of evaluating school productivity by using standardised tests in Reading and math.

8. We used the so-called SIDI code, used by INVALSI to identify each student, to match the two data-set. However, in some of the questionnaires data needed to anonymously obtain the codes from schools were randomly missing.

9. In the Italian school system, students must obtain an assessment of 6 out of 10 in each subject in order to be admitted to the next year, otherwise they have to repeat their class.

10. Involvement in extracurricular activities is an indicator of teamwork ability, self-confidence and the ability to succeed in competitive situations. Controlling for this variable helps isolating important self-selection factors such as ability, background and general motivation (Lipscomb Citation2007).

11. A detailed description of these variables is provided in section 4.2.

12. Also this result is in line with previous empirical literature showing that generally girls perform better than boys in reading. See Guiso et al. (Citation2008).

13. Checchi, Rettore, and Girardi (Citation2015) present a counterfactual evaluation of the effect of ICT resources at school on student achievements. They find a positive impact of the programme on reading score but only in the bottom tail of the distribution, while the remaining part of the distribution is virtually unaffected.

14. However, research comparing men and women in their ability to solve actual tasks online does not show substantial differences (Hargittai Citation2002; Hargittai and Shafer Citation2006; Van Deursen and Van Dijk Citation2011). Malamud and Pop-Eleches (Citation2011) find that girls spend less time using computers and have lower computer skills.

15. Regarding print reading, mathematics and science, among boys moderate users perform better than rare and intensive users, and rare and intensive users perform at around the same levels; instead, among girls, the relationship is negatively linear with a slight curve, meaning that rare users achieve slightly lower scores than moderate users, but they perform much better than intensive users. With respect to the new dimension of “digital reading performance”, male intensive users tend to perform better than rare users, while among girls intensive users tend to perform at around the same level as rare users. Also, the negative association found between the use of ICT at school and digital reading performance is significantly weaker for males.

16. Obviously, this does not mean that the number of books in the home are causally related to students’ academic performance. Rather, they proxy systematic differences in socio-economic background that are causally related to achievement.

17. See also Section 4.

18. We estimated the model also distinguishing only between liceo students and other schools (technical and vocational) students. The coefficients of ICT ability is lower for liceo students for both math and reading and the difference is statistically significant in both cases.

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