CoChat
Sign Up
Cited by 35Visual and Cognitive Learning ProcessesIntelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Exploring the Assistance Dilemma: Comparing Instructional Support in Examples and Problems

McLaren, Bruce M., van Gog, Tamara, Ganoe, Craig, Yaron, David, Karabinos, Michael·2014·Lecture Notes in Computer Science
DOI 10.1007/978-3-319-07221-0_44
Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/978-3-319-07221-0_44

Cites

16 of 16 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?

  • Worked examples (WEs) have been studied in a variety of domains, and results consistently show that replacing some or all practice problems with WEs results in higher learning efficiency, where students take less time to learn the same amount of content.

    “WEs have been studied in a variety of domains [9,10,20], and the results consistently show that replacing some or all practice problems with WEs results in higher learning efficiency, where students take less time to learn the same amount of content.”

    From Exploring the Impact of Worked Examples in a Novice Programming Environment (2019) · cites this paper as [10]

  • McLaren et al. found that students in the worked example condition performed similarly in the post-test but were more efficient in finishing intervention problems and with less cognitive load, compared to students in other conditions including problem solving, erroneous worked examples, and tutored problem solving.

    “They found that students in the WE condition performed similarly in the post-test but were more efficient in finishing intervention problems and with less cognitive load, compared to students in other conditions including problem solving, erroneous worked examples, and tutored problem solving [10].”

    From Exploring the Impact of Worked Examples in a Novice Programming Environment (2019) · cites this paper as [10]

  • Previous WE studies found that students learned more efficiently with WEs, but they did not learn more, since both groups were exposed to the same learning content.

    “This is consistent with previous WE studies [10,17], where students learned more efficiently with WEs, but they did not learn more, since both groups were exposed to the same learning content.”

    From Exploring the Impact of Worked Examples in a Novice Programming Environment (2019) · cites this paper as [10]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
McLaren, B. M., van Gog, T., Ganoe, C., Yaron, D., & Karabinos, M.
Affiliations
Carnegie Mellon University (US)
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2014
Pages
354-361
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-319-07221-0_44
OpenAlex
W1196054003
Cited by
34
References
16
Citations by year
2025: 1 · 2024: 2 · 2023: 2 · 2022: 5 · 2021: 3 · 2020: 4 · 2019: 5 · 2018: 2 · 2017: 1 · 2016: 3 · 2015: 5 · 2014: 1
FWCI
5.45
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
Keywords
worked examples, problem solving, computer-assisted instruction, tutoring, erroneous examples, prior knowledge, cognitive effort, learning time, pedagogical support

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