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Record W2061622592 · doi:10.5539/ies.v3n1p130

The Use of Scaffolding Approach to Enhance Students' Engagement in Learning Structural Analysis

2010· article· en· W2061622592 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Education Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationReflection (computer programming)Active listeningProcess (computing)ScaffoldTeaching methodComputer scienceSeries (stratigraphy)PsychologyPedagogy

Abstract

fetched live from OpenAlex

This paper presents a reflection on the use of Scaffolding Approach to engage Civil Engineering students in learning Structural Analysis subjects. In this approach, after listening to the lecture on background theory, students are provided with a series of practice problems, each one comes with the steps, formulas, hints, and tables needed to solve the problem. Gradually, with the growing confident to apply the method as a tool to analyze structures, the amount of help provided is reduced, until finally no help is provided at all. Using this approach, only the main background of theory is needed to be lectured. The application of the method to analyze various problems is learned by students themselves by doing the series of problems engineered with gradually-reduced supports. Students’ engagement is greatly enhanced, as they are so much involved in the learning process.

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.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.089
GPT teacher head0.470
Teacher spread0.381 · 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