ICT Use, Digital Skills and Students’ Academic Performance: Exploring the Digital Divide
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Information and communication technologies (ICTs) are an integral part of our environment, and their uses vary across generations and among individuals. Today’s student population is made up of “digital natives” who have grown up under the ubiquitous influence of digital technologies, and for whom the use of ICT is common and whose daily activities are structured around media use. The aim of this study is to examine the impact of ICT use and digital skills on students’ academic performance and to explore the digital divide in France. Data were collected through face-to-face questionnaires administered to 1323 students enrolled in three French universities. Principal component analysis, a non-hierarchical k-means clustering approach and multilevel ordered logistic regression were used for data analysis and provide four main findings: first, poor investment in ICT affects students’ results; second, the ICT training offered by universities has little impact on students’ results; third, student performance improves with the innovative and collaborative use of ICTs; fourth, the acquisition of digital skills increases students’ academic performance. The results show that the digital divide still exists, and this raises questions about the effectiveness of education policies in France. They suggest also that organizational change in universities is essential to enable an exploitation of ICT.
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The technology acceptance model (TAM) has been criticized for its limited depth in understanding individual perspectives on new systems.
“While the technology acceptance model (TAM) is widely recognized in the field [2,11,18], it has been criticized for its limited depth in understanding individual perspectives on new systems [19-21].”
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Kompetensi Digital Guru Sekolah Dasar di Kota Semarang: Analisis Multivariat
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COMPUTER LITERACY AND ACADEMIC PERFORMANCE IN UNIVERSITIES OF SOUTHERN KHYBER PAKHTUNKHWA PAKISTAN
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Impact of Access to and use of ICT in School on Students’ Perceived Performance
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Evaluating Digital Technology Access and Usage among Teachers
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Digital Inequality as Menace and Opportunity in Strategizing the Development of Educational Sphere
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Utilization of Information and Communication Technology and 21st Century Skills
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The Role and Importance of ICT Courses in Improving the Learning Outcomes of Pre-Service Teachers
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Unpacking the Digital Transformation in an Incumbent Context: The Role of Digital Skills
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Medical Skepticism in the Digital Age: An Experimental Study on Digital Health Literacy
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- Authors
- Ben Youssef, A., Dahmani, M., & Ragni, L.
- Affiliations
- GREDEG CNRS, Université Côté d’Azur, 5 rue du 22ème BCA, 06300 Nice, France
- University of Gafsa (TN)
- Centre National de la Recherche Scientifique (FR)
- Venue
- Information
- Publisher
- MDPI AG
- Published
- 2022-03-03
- Volume
- 13
- Issue
- 3
- Pages
- 129
- ISSN
- 2078-2489 (ISSN-L)
- OpenAlex
- W4214928691
- Cited by
- 174
- References
- 66
- Citations by year
- 2026: 34 · 2025: 42 · 2024: 36 · 2023: 51 · 2022: 11
- FWCI
- 34.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Information (publishedVersion, cc-by)
- HAL (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital literacy in education
- Social Sciences › Gender Studies › Gender and Technology in Education
- Physical Sciences › Computer Science › Information Systems › Educational Innovations and Technology
- Keywords
- information and communication technologies, digital skills, academic performance, digital divide, university students, digital natives, ICT training, ICT investment, cooperative learning, educational technology, education policy, France
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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