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Fashioning of Students' Research Competence Through Technology of Project Activities

2020· article· en· W3088156682 on OpenAlexvenueno aff
Sholpan Sh. Khamzina, Aigul M. Utilova, Tattigul Shakenova, Gulmira Suleimenova, Ella Y. Sarsembayeva, Gulomkodir М. Bobizoda

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2020
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)PsychologyMedical educationEngineeringMedicineSocial psychology

Abstract

fetched live from OpenAlex

Objective: The authors provide justifications for changing the current education system, updating the teaching and methodological approach in school specialised education. The paper investigates the issue of fashioning students' research competence through the technology of project activities. Background: Project activity has become widely used since it combines the theoretical and practical parts of the science under study, which allows to set up a connection between its components. Research competence is an integral feature of a student's personality, which manifests itself in a willingness to take an active research position. Method: The authors conducted an experiment to study the problem of improving the quality of students' knowledge upon studying biology in senior school. The participants in the experiment were 120 students of the 10th and 11th years of a specialised school for children with psychological disorders. Results: The authors developed a methodology for the fashioning of research competence. The results of the conducted pedagogical experiment confirmed the validity of the initial assumptions regarding the influence of the use of research teaching methods in biology lessons aimed at improving the quality of biological education. Conclusion: Through project activities, students with intellectual disabilities learn to work in a team. Despite the fact that teamwork is uniting, each of the students learns to independently set the purpose and tasks of the study, analyse the sources presented, present the results of their activities to others. The main signs of project activity include the fact that students learn the technique and technology of working with the project. Project activity allows for the fashioning of students' research competence during the lesson, thereby enabling students to unleash their potential.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.100
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.100
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.005
Scholarly communication0.0060.005
Open science0.0020.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.231
GPT teacher head0.431
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2020
Admission routes1
Has abstractyes

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