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Record W3043794403 · doi:10.46654/ij.24889849.e6620

GEOGEBRA SOFTWARE: A VERITABLE PEDAGOGICAL TOOL FOR IMPROVING STUDENTS’ ACHIEVEMENT IN GEOMETRY

2015· article· en· W3043794403 on OpenAlexaff
Nwoke Bright Ihechukwu, Okorie Chidi

Bibliographic record

VenueInternational Journal of Advanced Academic Research · 2015
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Assessment
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMathematics educationSoftwareGeometryComputer scienceCalculus (dental)Engineering drawingMathematicsProgramming languageEngineering

Abstract

fetched live from OpenAlex

The study investigated the impact of Geogebra Software on students' achievement in geometry. The study was carried out in Owerri Municipal Council of Imo State. The study was a quasiexperimental research type adopting the pre-test post test non-equivalent control design. A sample of 114 senior secondary two (SS II) students was used for the study. The instrument for data collection was researchers made objective test with reliability coefficient of 0.80 determined using Kuder-Richardson (KR 20 ) formula. The experiment group was taught geometry using Geogebra software while the control group was taught using conventional approach. The data generated was analyzed using mean and standard deviation to answer research questions while the hypotheses were tested using ANCOVA statistical tool at 0.05 level of significance. The result of the study revealed that Geogebra software was effective in improving students' achievement in geometry irrespective of gender. Based on the result, it was recommended that Geogebra software should be introduced in secondary schools to enable teachers use them for teaching mathematics.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.172
GPT teacher head0.512
Teacher spread0.341 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2015
Admission routes1
Has abstractyes

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