Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning

M. Jabeen; M. Imran; M. Rafiq

doi:10.1177/09610006241256394

Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning

M. Jabeen
, M. Imran
, M. Rafiq

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

1 Citation (Scopus)

Original language	English
Pages (from-to)	937-951
Number of pages	15
Journal	Journal of Librarianship and Information Science
Volume	57
Issue number	3
DOIs	https://doi.org/10.1177/09610006241256394
Publication status	Published - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education
SDG 17 Partnerships for the Goals

Keywords

Data Science
Smart phones

Access to Document

10.1177/09610006241256394

Cite this

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title = "Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning",

keywords = "Data Science, Smart phones",

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language = "English",

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TY - JOUR

T1 - Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning

AU - Jabeen, M.

AU - Imran, M.

AU - Rafiq, M.

PY - 2025

Y1 - 2025

KW - Data Science

KW - Smart phones

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M3 - Article

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JF - Journal of Librarianship and Information Science

IS - 3

ER -

Smartphone technology adoption of university students for distance learning in Pakistan: COVID-19 data-driven decision tree learning

UN SDGs

Keywords

Access to Document

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Cite this