Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 313

The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.

Technology-related knowledge, skills, and attitudes of pre- and in-service teachers: The current situation and emerging trends

Open access
Seufert, Sabine, Guggemos, Josef, Sailer, Michael·2021·Computers in Human Behavior

Abstract

This is the introductory article for the special issue "Technology-related knowledge, skills, and attitudes of pre- and in-service teachers". It (1) specifies the concept of technology-related knowledge, skills, and attitudes (KSA) of teachers, (2) presents how these KSA are currently assessed, and (3) outlines ways of fostering them among pre- and in-service teachers. The eight articles in the special issue are structured accordingly, and we demonstrate how they contribute to knowledge in these three areas. Moreover, we show how the afterword to the special issue widens the perspective on technology integration by taking into account systems and cultures of practice. Due to their quantitative empirical nature, the eight articles investigate technology at the current state of the art. However, the potential of artificial intelligence has not yet been fully exploited in education. We provide an outlook on potential developments and their implications on teachers' technology-related KSA. To this end, we introduce the concept of augmentation strategies.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.chb.2020.106552

Cites

76 of 76 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 76 references

Cited by

See all 313

Metadata

Authors
Seufert, S., Guggemos, J., & Sailer, M.
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2021-02
Volume
115
Pages
106552
ISSN
0747-5632 (ISSN-L)
OpenAlex
W3083578468
Cited by
313
References
76
FWCI
31.38
Type
journal article
Language
en
Open access
hybrid

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.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Technology-related knowledge, skills, and attitudes of pre- and in-service teachers: The current situation and emerging trends. https://app.cochat.ai/papers/10.1016/j.chb.2020.106552
The paper
Seufert, S., Guggemos, J., & Sailer, M. (2021). Technology-related knowledge, skills, and attitudes of pre- and in-service teachers: The current situation and emerging trends. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2020.106552

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.