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Record W1545341613 · doi:10.5539/ies.v8n6p162

Features of the Information and Communication Technology Application by the Subjects of Special Education

2015· article· en· W1545341613 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 · 2015
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSpecial educationMathematics educationPsychologyComputer literacyLiteracyInformation and Communications TechnologyMedical educationPedagogyComputer scienceMedicine

Abstract

fetched live from OpenAlex

The main purpose of this study is to reveal the features of information and communication technologies application by the subjects of education in the conditions of special (correctional) school type VIII, and to identify the level of computer literacy of special education. The study was conducted on the basis of the State Budgetary Special (Correctional) Educational Institution of the Republic of Mordovia (SBS(C) EI RM) for the students and pupils with disabilities in the “Saransk special (correctional) general education school Type VIII”, Saransk (Russia). During the experiment, each group of respondents (teachers, students with intellectual disabilities and their parents) was offered the specially developed questionnaires. The assessment of responses was made by the following criteria: completeness of elementary computer skills the subjects possess; proficiency in computer programs and electronic products; degree of independence and the frequency of their application in practice. The results show us that the computer literacy of subjects is low. During the study we revealed that the use of modern information technologies is associated with certain difficulties, associated not only with the deficiency of computer and special software, but also with a low level of knowledge and skills of work on a personal computer among the subjects of special education.

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)0.000
metaresearch head score (Gemma)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.035
GPT teacher head0.349
Teacher spread0.315 · 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