Cited by 84Online Learning and AnalyticsDigital Education and SocietyEducational and Technological Research

Are We on Our Way to Becoming a “Helicopter University”? Academics’ Views on Learning Analytics

Howell, Joel A., Roberts, Lynne D., Seaman, Kristen, Gibson, David C.·2018·Technology, Knowledge and Learning

Integrity signals

Registry

Crossref · 10.1007/s10758-017-9329-9

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Students are not willing to disclose all data for AI applications despite anticipated benefits.

    “Initial study results indicate (Howell et al., 2018;Viberg et al., 2022;West, Heath, et al., 2016;West, Huijser, et al., 2016a, 2016b) that students are not willing to disclose all data for AI applications despite anticipated benefits.”

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Authors
Howell, J. A., Roberts, L. D., Seaman, K., & Gibson, D. C.
Affiliations
Curtin University (AU)
Corresponding author
Howell, Joel A.
Venue
Technology, Knowledge and Learning
Published
2017-08-02
Volume
23
Issue
1
Pages
1-20
ISSN
  • 2211-1662 (ISSN-L)
  • 2211-1670
OpenAlex
W2741878607
Cited by
84
References
42
Citations by year
2026: 2 · 2025: 4 · 2024: 3 · 2023: 29 · 2022: 8 · 2021: 17 · 2020: 13 · 2019: 6 · 2018: 2
FWCI
6.88
Type
journal article
Language
en
Open access
closed
Locations
  • Technology Knowledge and Learning (publishedVersion)
  • eSpace (Curtin University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Information Systems › Digital Education and Society
  • Physical Sciences › Computer Science › Information Systems › Educational and Technological Research
Keywords
learning analytics, higher education academics, ethics of learning analytics, academic perceptions, student privacy, data-driven learning, stakeholder collaboration

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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