Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor
Integrity signals
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Cites
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Claims the paper makes
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?
Liu et al.'s work shows that worked examples are beneficial to undergraduate students in the first few problems they solve but less beneficial for later problems in the students' homework set.
“In an intelligent tutoring system for teaching and practicing propositional logic problems in discrete math, Liu et al. 's [9] work shows that WEs are beneficial to undergraduate students in the first few problems they solve but less beneficial for later problems in the students' homework set.”
From Exploring the Impact of Worked Examples in a Novice Programming Environment (2019) · cites this paper as [9]
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 [9]
Cites
When problem solving is superior to studying worked examples.
Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001) · Journal of Educational Psychology · doi:10.1037/0022-0663.93.3.579 · Cited by 548 · see citing works
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Exploring the Impact of Worked Examples in a Novice Programming Environment
Zhi, R., Price, T. W., Marwan, S., Milliken, A., Barnes, T., & Chi, M. (2019) · Proceedings of the 50th ACM Technical Symposium on Computer Science Education · doi:10.1145/3287324.3287385 · Cited by 55 · see citing works
Self-citation
- Authors
- Liu, Z., Mostafavi, B., & Barnes, T.
- Affiliations
- North Carolina State University (US)
- Corresponding author
- Liu, Zhongxiu
- Mostafavi, Behrooz
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 347-353
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2465948590
- Cited by
- 10
- References
- 1
- Citations by year
- 2021: 2 · 2020: 3 · 2019: 3 · 2018: 1 · 2017: 1
- FWCI
- 0.90
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- worked examples, problem solving, computer-assisted instruction, scaffolding, student proficiency, open-ended problem solving
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.
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