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Record W3211483805 · doi:10.32920/ryerson.14660814.v1

The visual construction of the individual education plan and parent involvement

2021· preprint· en· W3211483805 on OpenAlexaffabout
Elizabeth MacLagan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPlan (archaeology)Perspective (graphical)Individualized Education ProgramProcess (computing)SemioticsOrder (exchange)Special educationAccommodationPsychologySign (mathematics)PedagogyMathematics educationComputer scienceLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

In educative practices, planning documents play an important role in communicating the educational needs of students with disabilities. The Individual Education Plan (IEP) is the main document that facilitates and enables accommodation for students with special education requirements. The IEP describes a student’s individual learning outcomes and services based on his or her level of educational performance (Griangreco, 1994). Research on the IEP work process has demonstrated that it can be confusing, frustrating, or ineffective in many cases (Ng, 2013). By taking the parents’ perspective and experience in the creation of the IEP, one can seek to understand why this can be such a taxing communicative process. As the literature can attest, there is great emphasis on parent involvement and positive outcomes in the IEP work process. However, parent input does not appear to be of great value or importance within the IEP document. In order to address the problem of poor parent involvement in the creation of the IEP, the IEP document template must be carefully analyzed. By taking the perspective of the parents in the IEP work process, the following research questions will be addressed: Primary Research Question • How do the textual and visual constructions of the IEP document elicit parent involvement in individual education planning? When analyzing IEP documents, the visual construction and the layout can be examined in order to understand why parent involvement may be limited. Written language can be analyzed by semiotic theory, which studies a system of signs, including a sign, signifier, and signified (Warner, 1990). Semiotic analysis questions what constitutes representation and the use of signs and sign systems to make messages (Nuessel, 2012). Thus, using semiotic analysis can help to understand how parents perceive the IEP document in practice. By gaining a richer understanding of the IEP template, one can hypothesize how parental involvement is communicated in the IEP work process. In considering the composition of a document, effective design enables the reader to understand information by visually grouping elements into units and indicating order through visual hierarchy (Martin, 1989). By referring to the document design and layout of a textual document, one can assess and interpret cues such as order, proximity, visual hierarchy, and visual prominence. Further, through the implementation of a semiotic content analysis of IEP templates employed across Ontario school boards, the notion of parent involvement can be better understood.

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)0.009
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.037
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.051
GPT teacher head0.355
Teacher spread0.304 · 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 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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