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Record W4226343765 · doi:10.5430/wjel.v12n3p10

A Framework for Learning Combined Problem Solving Skills

2022· article· en· W4226343765 on OpenAlexvenueno aff
M. Sharma, Bushra Sumaiya, Kumud Kant Awasthi, Rashmi Mehrotra

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsDeskVariety (cybernetics)Presentation (obstetrics)CognitionComputer scienceWork (physics)Test (biology)Subject (documents)Cognitive skillPsychologyMathematics educationArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

Problem-solving is an important part of a well-rounded 2nd-century education. In his essay "Cognition in the Wild," Hutchins advises readers to look about their local region for artifacts that were not created by the combined efforts of multiple individuals, but also mentions but the only one in their region is the one in their area. A little stone on his desk was the thing that passed this test. Collaboration has a tremendous influence on our everyday lives. Researchers are continuously engaged in situations that need us to employ social skills to coordinate with other people, whether it is in schools, the workplace, or our personal lives. Tasks that need numerous students to work together to achieve a team goal, such as a final report, integrated analysis, or a joint presentation, are common in project-based work. Combined problem solving is rarely taught as a stand-alone ability separate from a specific subject. As a result, combined learning activities are frequently integrated into specialized courses of study, such as science, mathematics, and history, in school-based settings. Cooperative conflict resolution has been highlighted as a highly promising exercise that relies on a broad variety of social or cognitive abilities and can be tested in school settings where skills might well be evaluated or taught. The author of this work conducts a thorough investigation of problem-solving abilities. People with high problem-solving abilities can analyze issues, determine the severity of the situation, and weigh the pros and cons of various solutions. Employees who get problem-solving training in the workplace can collaborate more effectively with coworkers, clients, partners, or suppliers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.314
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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