Cited by 22Innovative Teaching and Learning MethodsIntelligent Tutoring Systems and Adaptive LearningEducation, Achievement, and Giftedness

The effectiveness of volition support (VoS) in promoting students’ effort regulation and performance in an online mathematics course

Kim, ChanMin, Bennekin, Kimberly N.·2016·Instructional Science

Integrity signals

Registry

Crossref · 10.1007/s11251-015-9366-5

Cites

69 of 69 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?

  • Many of these assistants offered multiple supports to students, such as Alex, the AI described as a virtual change agent in Kim and Bennekin's (2016) study.

    “Many of these assistants offered multiple supports to students, such as Alex , the AI described as a virtual change agent in Kim and Bennekin's (2016) study.”

    From Artificial intelligence in higher education: the state of the field (2023) · cites this paper as Kim and Bennekin, 2016

Cites

Flagged first, then by citations

2 of the 71 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Kim, C., & Bennekin, K. N.
Affiliations
University of Georgia (US)
Corresponding author
  • Kim, ChanMin
  • Bennekin, Kimberly N.
Venue
Instructional Science
Published
2016-08
Volume
44
Issue
4
Pages
359-377
ISSN
  • 0020-4277 (ISSN-L)
  • 1573-1952
OpenAlex
W2518352923
Cited by
22
References
71
Citations by year
2026: 1 · 2025: 1 · 2024: 7 · 2023: 4 · 2022: 2 · 2021: 3 · 2020: 2 · 2018: 1 · 2017: 1
FWCI
1.56
Type
journal article
Language
en
Open access
closed
Locations
Instructional Science (publishedVersion)
Funders
The Office of the Vice President for Research, The University of Georgia, U.S.A.
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
Keywords
effort regulation, student motivation, academic performance, online mathematics courses, community college students, goal formation, action control, emotion control, student self-regulation

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