Becoming more specific: Measuring and modeling teachers' perceived usefulness of ICT in the context of teaching and learning
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Teachers' ICT self-efficacy and perceived usefulness of ICT are strongly related to their actual integration of ICT in learning environments.
“Moreover, research has shown that teachers' ICT self-efficacy and perceived usefulness of ICT are strongly related to their actual integration of ICT in learning environments (Chien, Wu, & Hsu, 2014;Scherer, Siddiq, & Teo, 2015).”
From Taking a future perspective by learning from the past – A systematic review of assessment instruments that aim to measure primary and secondary school students' ICT literacy (2016) · cites this paper as Scherer, Siddiq, & Teo, 2015
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References 74 · Cited by 220
- Authors
- Scherer, R., Siddiq, F., & Teo, T.
- Affiliations
- University of Oslo (NO)
- University of Macau (MO)
- Corresponding author
- Scherer, Ronny
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 88
- Pages
- 202-214
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W605564329
- Cited by
- 220
- References
- 74
- Citations by year
- 2026: 15 · 2025: 12 · 2024: 25 · 2023: 24 · 2022: 19 · 2021: 30 · 2020: 31 · 2019: 18 · 2018: 16 · 2017: 14 · 2016: 12 · 2015: 3
- FWCI
- 75.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Murdoch University Research Portal (submittedVersion)
- Topics
- Social Sciences › Education › Education and Technology Integration
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- perceived usefulness, information and communication technologies, teachers, ICT integration in classrooms, teacher self-efficacy, ICT use, teacher age, construct measurement, multidimensional construct, technology acceptance, Bayesian structural equation modeling
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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