INVESTIGACIÓN EN EL ÁREA DEL AUTISMO (RESEARCH IN THE AUTISM AREA)
Manuel Ojea Rúa. Catedrático de Orientación Educativa (NRP: 3492563057A0511). Doctor en Psicología- Pedagogía por la Universidad de Vigo. Pertenece al Grupo de Investigación PS1 de Psicología. En el ámbito de su trabajo, es autor de 50 libros y más de 120 artículos en revistas científícas nacionales e internacionales relacionados con el área del autismo. ORCID: https://orcid.org/0000-0002-9787-2520. MAIL: moxea@uvigo.es
Wednesday 8 May 2024
Friday 3 May 2024
COMPARATIVE ANALYSIS BETWEEN THE PERCEPTIVE-COGNITIVE SCALE AND THE EVOLUTIVE- BEHAVIOURAL SCALES TO AUTISM DIAGNOSIS
Comparative analysis between the perceptive- cognitive and the evolutive- behavioural scales to autism diagnosis.
International Journal of Humanities and Social Science Invention, 13(4), 75-81.
Prof. Manuel Ojea Rúa
University of Vigo
ORCID: https://orcid.org/0000-0002-9787-2520
KEYWORDS: Autism Spectrum Disorder. Diagnosis. Perceptive- Cognitive. Relational Nodes.
REFERENCES
Adorjan,
I., Ahmed, B., Feher, V., Torso, M., Krug, K., Esiri, M., ... & Szele, F.
G. (2017). Calretinin interneuron density in the caudate nucleus is lower in autism
spectrum disorder. Brain, 140(7), 2028- 2040. https://doi.org/10.1093/brain/awx131
American Psychiatric
Association (APA) (2013). Diagnostic and Statistical Manual of Mental
Disorders (DSM-5). Arlington, VA. https://psychiatry.org/psychiatrists/practice/dsm
Amina,
S., Falcone, C., Hong, T., Wolf- Ochoa, M. W., Vakilzadeh, G., Allen, E., ... &
Martinez- Cerdeno, V. (2021). Chandelier cartridge density is reduced in the
prefrontal cortex in autism. Cerebral Cortex, 31(6), 2944- 2951. https://doi.org/10.1093/cercor/bhaa402
Ariza,
J., Rogers, H., Hashemi, E., Noctor, S. C., & Martinez- Cerdeno, V. (2018).
The number of chandelier and basket cells are differentially decreased in
prefrontal cortex in autism. Cerebral Cortex, 28(2), 411- 420. https://doi.org/10.1093/cercor/bhw349
Dufour,
B. D., McBride, E., Bartley, T., Juarez, P., & Martínez- Cerdeño, V. (2023).
Distinct patterns of GABAergic interneuron pathology in autism are associated
with intellectual impairment and stereotypic behaviours. Autism, 27(6)
1730- 1745. DOI: 10.1177/13623613231154053.
Casanova,
M. F., Buxhoeveden, D. P., Switala, A. E., & Roy, E. (2002). Minicolumnar
pathology in autism. Neurology, 58(3), 428- 432. https://doi.org/10.1212/wnl.58.3.428
Chao,
H. T., Chen, H., Samaco, R. C., Xue, M, Chahrour, M., Yoo, J, ... & Zoghbi,
H. (2010). Dysfunction in GABA signalling mediates autism-like stereotypies and
Rett syndrome phenotypes. Nature, 468, 263- 269. https://pubmed.ncbi.nlm.nih.gov/21068835/
Courchesne, E., Mouton, P. R., Calhoun, M. E.,
Semendeferi, K., Ahrens- Barbeau, C., Hallet, M. J., ... & Pierce, K.
(2011). Neuron number and size in prefrontal cortex of children with autism. JAMA:
The Journal of the American Medical Association, 306, 2001- 2010. https://pubmed.ncbi.nlm.nih.gov/22068992/
De Felipe,
J., Lopez- Cruz, P. L., Benavides- Piccione, R., Bielza, C., Larranaga, P.,
Anderson, S., . . . & Ascoli, G. A. (2013). New insights into the
classification and nomenclature of cortical GABAergic interneurons. Nature
Reviews Neuroscience, 14(3), 202- 216. https://doi.org/10.1038/nrn3444
Gilliam, J. E.
(2001). Gilliam Asperger’s Disorder Scale. Austin, TX: Pro-Ed. https://www.txautism.net/evaluations/gilliam-aspergers-disorder-scale
Gilliam, J. E.
(2005). Gilliam Autism Rating Scale GARS-2 (2ª ed.). México: PROED.
www.proedlatinoamerica.com
Gilliam,
J. E. (2010). Escala de Evaluación del Autismo
de Gilliam. México: Rústica. ISBN: 13:
9789707293656
Hadjikhani,
N., Zürcher, N. R., Rogier, O., Ruest, T., Hippolyte, L., Yehezkel Ben- Ari,
Y., ... & Lemonnier, E. (2015). Improving emotional face perception in autism
with diuretic bumetanide: A proof-of-concept behavioural and functional brain
imaging pilot study. Autism, 19(2) 149- 157. DOI: 10.1177/1362361313514141
Hashemi,
E., Ariza, J., Rogers, H., Noctor, S. C., & Martinez- Cerdeno, V. (2017). The
number of parvalbumin-expressing interneurons is decreased in the prefrontal
cortex in autism. Cerebral Cortex, 27(3), 1931- 1943. https://doi.org/10.1093/cercor/bhw021
Hof,
P. R., Glezer, I. I., Conde, F., Flagg, R. A., Rubin, M. B., Nimchinsky, E. A.,
... & Vogt- Weisenhorn, D. M. (1999). Cellular distribution of the
calcium-binding proteins parvalbumin, calbindin, and calretinin in the
neocortex of mammals: Phylogenetic and developmental patterns. Journal of
Chemical Neuroanatomy, 16(2), 77- 116. https://doi.org/10.1016/s0891-0618(98)00065-9
Hutsler,
J. J., & Zhang, H. (2010). Increased dendritic spine densities on cortical
projection neurons in autism spectrum disorders. Brain Research, 1309,
83- 94. https://doi.org/10.1016/j.brainres.2009.09.120
Lawrence,
Y. A., Kemper, T. L., Bauman, M. L., & Blatt, G. J. (2010). Parvalbumin-,
calbindin-, and calretinin-immunoreactive hippocampal interneuron density in
autism. Acta Neurologica Scandinavica, 121(2), 99- 108. https://doi.org/10.1111/j.1600-0404.2009.01234.x
Lord, C., Rutter, M., & Le Couteur, A.
(1994). Autism Diagnosis Interview–Revised: a revised version of a diagnostic interview
for caregivers of individuals with possible pervasive developmental disorders. Journal
of Autism and Developmental Disorders 24, 659- 685. DOI: 10.1007/BF02172145
Lord, C., Rutter,
M., DiLavore, P. C., & Risi, S. (1999). Autism Diagnostic Observation Schedule:
Manual. Los Angeles, CA: Western Psychological Services.
https://link.springer.com/article/10.1023/A:1005592401947
Ojea,
M. (2023a). Autism: new conceptual propositional hypothesis. European Journal
of Theoretical and Applied Sciences, 1(6), 115- 124. https://ejtas.com/index.php/journal/article/view/437
Ojea, M. (2024a).
Autism Perceptual- Behavioural Precision Scale. European Journal of
Theoretical and Applied Sciences, 2(1), 18- 45. DOI: 10.59324/wjtas.2024.2(1).02.
https://ejtas.com/index.php/journal/article/view/555
Ojea, M. (2024b). Escala
perceptivo- cognitiva de diagnóstico del trastorno del espectro autista
revisada (EPPC-TEA-R). RIP: REGAGE23e00084280417. ISBN: 978-84-09-59160-2. Editions Kindle Direct Publishing. https://www.amazon.es/dp/B0CW1L8BTH
Pizzarelli,
R., & Cherubini, E. (2011) Alterations of GABAergic signalling in autism
spectrum disorders. Neural Plasticity, 297153 (12 pp.). https://pubmed.ncbi.nlm.nih.gov/21766041/
Ploeger,
A., Raijmakers, M. E., van der Maas, H. L., & Galis, F. (2010) The association
between autism and errors in early embryogenesis: what is the causal mechanism?
Biological Psychiatry, 67, 602- 607. https://pubmed.ncbi.nlm.nih.gov/19932467/
Rutter, M., Le Couteur, A., & Lord, C. (2003). Autism
diagnostic interview revised (ADI-R). Los Angeles, CA: Western
Psychological Services. DOI: https://doi.org/10.1007/978-1-4419-1698-3_894
Wang,
Y., Zhang, P., & Wyskiel, D. R. (2016). Chandelier cells in functional and
dysfunctional neural circuits. Frontiers in Neural Circuits, 10, 33.
https://doi.org/10.3389/fncir.2016.00033
Wilson,
T. W, Rojas, D. C., Reite, M. L., Teale, P. D., & Rogers,
S. J. (2007). Children and adolescents with autism exhibit reduced MEG
steady-state gamma responses. Biological Psychiatry, 62, 192- 197. https://pubmed.ncbi.nlm.nih.gov/16950225/
World Health Organization. (1992). ICD 10: Mental and behavioural
disorders: Clinical descriptions and guidelines for follow-up. World Health
Organization. United Nations Organization (UN). https://www.who.int/publications/i/item/9241544228
World Health
Organization. (2020). ICD 11-R: Mental and behavioural disorders:
clinical descriptions and guidelines for follow-up. World Health Organization. United
Nations Organization (UN). https://icd.who.int/en
Zaitsev,
A. V., Gonzalez-Burgos, G., Povysheva, N. V., Kroner, S., Lewis, D. A., &
Krimer, L. S. (2005). Localization of calcium-binding proteins in physiologically
and morphologically characterized interneurons of monkey dorsolateral prefrontal
cortex. Cerebral Cortex, 15(8), 1178- 1186. https://doi.org/10.1093/cercor/bhh218
Wednesday 3 April 2024
ESCALA DE DIAGNÓSTICO DEL AUTISMO
OURENSE- GALICIA
https://urldefense.com/v3/__https://www.facebook.com/share/v/EK8csuLBRy3dp1c2/__;!!D9dNQwwGXtA!QyGrYh5zlJfwwBdQrkvwbfQ4j6MYbbh0rVmJZS2-ct-pSCN1iTp48qLhrKcXJ60fI9iRIb6RQH7K8s0EzQ$
DIARIOS: "LA VOZ DE GALICIA" y "FARO DE VIGO": "Alicia, una de las tres mil caras del trastorno autista en Ourense".
2 DE ABRIL DE 2024
DÍA MUNDIAL DEL AUTISMO:
LA VOZ DE GALICIA, 3 DE ABRIL DE 2024
El prof. Manuel Ojea Rúa expone las últimas investigaciones científicas relacionadas con el trastorno del espectro autista:
Monday 1 April 2024
2 DE ABRIL DE 2024: DÍA INTERNACIONAL DEL AUTISMO
CELEBRANDO EL DÍA MUNDIAL DEL AUTISMO: 2 DE ABRIL DE 2024
CONCRECIÓN DE LA TEORÍA CÍCLICA GLOBAL EN LAS PERSONAS CON TRASTORNO DEL ESPECTRO AUTISTA (SESIÓN II)
Prof. Dr. Manuel Ojea Rúa
Ver vídeo explicativo:
En la compañía de familias y profesionales de la psicología, la educación y la medicina:
Sunday 31 March 2024
LA TEORÍA CÍCLICA GLOBAL (TCG)
INICIACIONES A LA NUEVA TEORÍA PROPOSICIONAL DEL TRASTORNO DEL ESPECTRO AUTISTA (LA TCG)
Thursday 28 March 2024
ESCALA DE DIAGNÓSTICO- REVISADA (DIAGNOSTIC SCALE-REVISED)
Autism Spectrum Disorder Diagnostic Scale- Revised.
European Journal of Theoretical and Applied Sciences, 2(2), 382-395.
Abstract
The diagnostic conclusions were based on the gaussian curve found from the typical scores obtained from the direct scores obtained in the ten dimensions of the analysis, made up of three dimensional categories, whose percentage weighting is as follows: 1) the procedural category (60%), 2) the social dimensional category (20%), and 3) the behavioural dimensional category (20%), the overall sum of which allows the diagnostic conclusions of the disorder to be drawn, both at a general level and according to the specific level of ASD. The percentage levels are justified by the empirical studies of the study. Thus, the stepwise linear regression analysis carried out includes two dimensions corresponding to the procedural category as basic predictors of the disorder: I) semantic retrieval (Beta: .90, R2: .82), and II) relationship between retrieval (Beta: .57) and interconcepts or relationships (R2: .82). 57) and interconcepts or relationships between information (Beta: .35), being the overall constant (Beta: .92, R2: .84), ahead of the social or behavioural dimensions, which supports the importance of the procedural dimension, especially related to the development of nodes or relationships between information content in determining the specific criteria for the diagnosis of ASD.
Keywords:Autism Spectrum Disorder, Diagnosis, Cognitive Networks, Global Theory
References:
American Psychiatric Association (APA)
(2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5).
Arlington, VA. https://psychiatry.org/psychiatrists/practice/dsm
Barnea-Goraly,
N., Eliez, S., Hedeus, M., Menon, V., White, C. D., Moseley, M., & Reiss A.
L. (2003). White matter tract alterations in fragile X syndrome: preliminary
evidence from diffusion tensor imaging. Am J Med Genet B, 118, 81–88. DOI: 10.1002/ajmg.b.10035
Biederman, J., Spencer, T. J., Petty, C., Hyder, L.
L., O’Connor, K. B., Surman, C. B., & Faraone, S. V. (2012). Longitudinal
course of deficient emotional self-regulation CBCL profile in youth with ADHD: prospective
controlled study. Neuropsychiatric Disease and Treatment, 8,
267–276. DOI:10.2147/NDT.S29670. https://pubmed.ncbi.nlm.nih.gov/22848182/
Brunberg, J.A., Jacquemont,
S., Hagerman, R. J., Berry-Kravis, E. M., Grigsby, J., Leehey, M. A., ... &
Hagerman, P. J. (2002). Fragile X permutation carriers: characteristic MR
imaging findings of adult male patients with progressive cerebellar and
cognitive dysfunction. Am J Neuroradiol, 23, 1757–1766. https://pubmed.ncbi.nlm.nih.gov/12427636/
Eycke, K.
D., & Müller, U. (2018). Drawing links between the autism cognitive profile
and imagination: executive function and
processing bias in imaginative drawings by children with and without autism, Autism,
22(2), 149–160. DOI: 10.1177/1362361316668293. https://pubmed.ncbi.nlm.nih.gov/29490482/
Gotham, K. O, Marvin, A. R., Taylor, J. L., Warren,
Z., Anderson, C. M., Law, P. A., ... & Lipkin, P. H. (2015). Characterizing
the daily life, needs, and priorities of adults with autism spectrum disorder
from interactive autism network data. Autism, 19(7), 794-804. https://pubmed.ncbi.nlm.nih.gov/25964655/
Hardan, A. Y., Minshew, N. J.,
& Keshavan, M. S. (2000). Corpus callosum size in autism. Neurology, 55,
1033–1036. DOI: 10.1212/wnl.55.7.1033
Heatherton, T. F. (2011). Neuroscience of self and
self- regulation. Annual Review of Psychology, 62, 363–390.
DOI:10.1146/annurev.psych.121208.131616. Neuroscience of self and self-regulation. (apa.org)
Hessl, D., Rivera, S. M.,
& Reiss, A. L. (2004). The neuroanatomy and neuroendocrinology of fragile X
syndrome. Ment Retard Dev Disabil Res Rev, 10, 17–24. DOI: 10.1002/mrdd.20004
Jacquemont, S., Hagerman, R.
J., Leehey, M., Grigsby, J., Zhang, L., Brunberg, J. A., ... & Hagerman, P.
J. (2003). Fragile X permutation tremor/ataxia syndrome: molecular, clinical,
and neuroimaging correlates. Am J Hum Genet, 72, 869–878. DOI: 10.1086/374321
Kates, W. R., Folley, B. S.,
Lanham, D. C., Capone, G. T., & Kaufmann, W. E. (2002). Cerebral growth in
Fragile X syndrome: review and comparison with Down syndrome. Microsc Res
Tech, 57,159–167. DOI: 10.1002/jemt.10068
Keenan, E. G., Gotham, K., & Lerner, M. D. (2018).
Hooked on a feeling: Repetitive cognition and internalizing symptomatology in
relation to autism spectrum symptomatology. Depression, 22(7),
814-824. https://pubmed.ncbi.nlm.nih.gov/28747070/
Mazefsky, C. A.,
Collier, A., Golt, J., & Siegle; G. J. (2020). Neural features of sustained
emotional information processing in autism spectrum disorder.
Autism, 24(4) 941–953. DOI: 10.1177/1362361320903137. Neural features of sustained emotional information
processing in autism spectrum disorder - PubMed (nih.gov)
Mazefsky, C. A., Herrington, J., Siegel, M., Scarpa,
A., Maddox, B. B., Scahill, L., & White, S. W. (2013). The role of emotion
regulation in autism spectrum disorder. Journal of the American Academy of Child &
Adolescent Psychiatry, 52, 679–688. DOI:10.1016/j.jaac.2013.05.006. The role of emotion regulation in autism spectrum
disorder - PubMed (nih.gov)
Mazefsky, C. A., Pelphrey, K. A., & Dahl, R. E.
(2012). The need for a broader approach to emotion regulation research in
autism. Child Development Perspectives, 6(1), 92–97. https://doi.org/10.1111/j.1750-8606.2011.00229.x
Mottron, L., Dawson, M., Soulières, I.,
Hubert, B., & Burack, J. (2006). Enhanced perceptual functioning in autism:
An update, and eight principles of autistic perception. Journal of Autism
and Developmental Disorders, 36(1), 27–43. DOI: 10.1007/s10803-005-0040-7
Ojea, M. (2023). Autism: New Conceptual
Propositional Hypothesis. European Journal of Theoretical and Applied
Sciences, 1(6), 115-124. DOI: 10.59324/ejtas.2023.1(6).1. https://ejtas.com/index.php/journal/article/view/437https://urldefense.com/v3/__https://doi.org/10.47191/rajar/v9i11.02__;!!D9dNQwwGXtA!Wf1YF2svOKrdruFpxQZ0fbl2ooOJV6K0bHIkBwP09Xv-DhCXgKpevaG-bGT5rFObD-7Xuof44hAgZHEdgPs$
Ojea,
M. (2024a). Escala perceptivo- cognitiva de diagnóstico del trastorno del
espectro autista revisada (EPPC-TEA-R). Registro de la propiedad
intelectual: REGAGE23e00084280417.
ISBN-13: 978-84-09-59160-2. Ediciones:
Kindle Direct Publishing. https://www.amazon.es/dp/B0CW1L8BTH
Ojea, M.
(2024b). Autism Perceptual- Behavioural Precision Scale. European Journal of
Theoretical and Applied Sciences, 2(1), 18-45. DOI: 10.59324/wjtas.2024.2(1).02.
https://ejtas.com/index.php/journal/article/view/555
Ojea,
M. (2024c). Escala perceptivo- cognitiva de diagnóstico del trastorno del espectro
autista revisada (EPPC-TEA-R). Amazón esp.: Kindle Direct Publishing. https://www.amazon.es/dp/B0CW1L8BTH
Oldehinkel, M., Mennes, M., Marquand, A., Charman, T.,
Tillmann, J., Ecker, C., … & Buitelaar, J. K. (2019). Altered connectivity
between cerebellum, visual, and sensory-motor networks in autism spectrum disorder:
results from the EU-AIMS longitudinal European autism project. Biological
Psychiatry: Cognitive Neuroscience and Neuroimaging, 4, 260–270.
DOI: 10.1016/j.bpsc.2018.11.010. Altered Connectivity Between Cerebellum,
Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from
the EU-AIMS Longitudinal European Autism Project - PubMed (nih.gov)
Pitskel, N. B., Bolling, D. Z., Kaiser, M. D.,
Pelphrey, K. A., & Crowley, M. J. (2014). Neural systems for cognitive
reappraisal in children and adolescents with autism spectrum disorder. Developmental
Cognitive Neuroscience, 10, 117–128. DOI: 10.1016/j.dcn.2014.08.007.
Neural
systems for cognitive reappraisal in children and adolescents with autism
spectrum disorder - PubMed (nih.gov)
Shehzad,
Z., Kelly, C., Reiss, P. T., Cameron- Craddock, R., Emerson, J. W., McMahon,
K., ... & Milham, M. P. (2014). A multivariate distance-based analytic
framework for connectome- wide association studies. Neuroimage, 93,
74–94. DOI:10.1016/j.neuroimage.2014.02.024. [PDF] A multivariate distance-based analytic framework for
connectome-wide association studies | Semantic Scholar
Siegle, G.
J., D’Andrea, W., Jones, N., Hallquist, M. N., Stepp, S. D., Fortunato, A., …
& Pilkonis, P. A. (2015). Prolonged physiological reactivity and loss:
Association of pupillary reactivity with negative thinking and feelings. International
Journal of Psychophysiology, 98(2), 310–320. https://doi.org/10.1016/j.ijpsycho.2015.05.009
Weiss, J. A.,
Thomson, K., & Chan, L. (2014). A systematic literature review of emotion
regulation measurement in individuals with autism spectrum disorder. Autism
Res, 7(6),
629–48. https://pubmed.ncbi.nlm.nih.gov/25346416/
World Health
Organization. (1992). ICD 10: Mental and behavioral disorders: Clinical
descriptions and guidelines for follow-up. World Health Organization. United
Nations Organization (UN). https://www.who.int/publications/i/item/9241544228
World Health Organization. (2020). ICD 11-R: Mental
and behavioral disorders: clinical descriptions and guidelines for follow-up.
World Health Organization. United Nations Organization (UN). https://icd.who.int/en
Wednesday 13 March 2024
LA FP BÁSICA: UNA TRAMPA EN LA DIVERSIDAD
LA FORMACIÓN PROFESIONAL BÁSICA: LA ALTERNATIVA FALLIDA A LA EDUCACIÓN CONVENCIONAL EN EL ALUMNADO CON NEAE
Manuel Ojea Rúa
Diario LA REGIÓN, 13/03/2024
FP Básica: la incoherencia de la FP actual... seguir leyendo
Thursday 7 March 2024
PÓSTER PRESENTADO AL CONGRESO AUTISMO PUEBLA (MÉXICO)
CONGRESO AUTISMO PUEBLA (MÉXICO)
LA TEORÍA CÍCLICA GLOBAL EXPLICATIVA DEL PENSAMIENTO EN PERSONAS CON TRASTORNO DEL ESPECTRO AUTISTA
Friday 16 February 2024
PROGRAMAS DE ATENCIÓN A LA DIVERSIDAD O METODOLOGÍA DIDÁCTICA REGULAR (INSTITUTIONAL PROJECTS OF DIVERSITY VS. REGULAR DIDACTIC)
PhD. Manuel Ojea Rúahttps://orcid.org/0000-0002-9787-2520
Google Scholar Link : https://scholar.google.com/citations?view_op=view_citation&hl=en&user=12fpHDQAAAAJ&sortby=pubdate&authuser=2&citation_for_view=12fpHDQAAAAJ:1W67FsDfIBAC
Linkedin Link : https://www.linkedin.com/posts/international-journal-of-multidisciplinary-research-and-analysis-790a321b9_article-title-institutional-projects-of-activity-7163855543852253184-UeW0?utm_source=share&utm_medium=member_desktopZenodo Link : https://zenodo.org/records/10664584Europub Link : https://europub.co.uk/articles/730903Index Copernicus Link : https://journals.indexcopernicus.com/search/article?articleId=3840209
Linkedin Link : https://www.linkedin.com/posts/international-journal-of-multidisciplinary-research-and-analysis-790a321b9_article-title-institutional-projects-of-activity-7163855543852253184-UeW0?utm_source=share&utm_medium=member_desktop
ABSTRACT
The teaching and learning of students with Autism Spectrum Disorder (ASD) requires the design of diversity projects at the different institutional levels of the educational centre. However, if these projects are not well adapted to the specific needs of the students, they will not achieve the expected effective results. In a study conducted with a total of 145 participants from different schools, it was shown that the presence of specific institutional educational projects was not a sufficient condition to respond effectively to the needs of the participants, whose curricular and social improvements were not shown to be significant (sig: .66). Even in the absence of these high-scale projects, when the usual methodology was well adapted to the specific needs of students with ASD, the improvements found in the academic and social, that´s coded as dependent variable (DV): improving, domains were highly significant (sig: .00) in terms of the use of meaningful didactics based on the creation of networks of relationships between informative content or highly meaningful learning. Now, the interactive constant of both components, i.e. the intersection of a project design when these have been appropriately adapted to the particular needs, then both variables became the explanatory variance of the academic and social of DV of students with ASD (constant t for the sum of nodal relationships + project: 3.70 (sig: .00), to which was added the explanatory variance of the students' age intervals (constant t for the sum of nodal relationships + project + age: 4.07, sig: .00): 3.70 (sig: .00), to which was also added the explanatory variance of the students´age intervals (constant t for the sum of nodal relationships + project + age: 4.07, sig: .00). 70 (sig: .00), to which the explanatory variance of the students´ age intervals were also added (constant t for the sum of nodes + project + age: 4.07, sig: .00). In conclusion, the design of general institutional projects, even if they cover all levels of education, are not effective on their own unless they are specifically tailored to the particular needs of the target student’s variable: “improving”.
KEYWORDS:
Autism spectrum disorder. Significant learning. Educational projects. Adapted regular teaching.
REFERENCES
1) American Psychiatric Association (APA) (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://www.psychiatry.org/psychiatrists/practice/dsm
2) Aracı, N., Melekoğlu, M. A., & Çetin, M. E. (2023). Impact of a mnemonic strategy on learning science concepts for middle school students with specific learning disabilities. Learning Disabilities: A Contemporary Journal 2(1), 69–85. https://psycnet.apa.org/record/2024-32302-005
3) Baddeley, A. D. (1999). Essentials of human memory. Washington: Psychology Press. https://psycnet.apa.org/record/1999-02729-000
4) Baker, S., Gersten, R., & Lee, D. (2002). A synthesis of empirical research on teaching mathematics to low-achieving students. The Elementary School Journal, 103, 51–73. https://www.researchgate.net/publication/249134736_A_Synthesis_of_Empirical_Research_on_Teaching_Mathematics_to_Low-Achieving_Students
5) Biancarosa, G., & Snow, C. E. (2004). Reading next. A vision for action and research in middle and high school literacy: A report to Carnegie Corporation of New York. Washington, DC: Alliance for Excellence in Education. https://media.carnegie.org/filer_public/b7/5f/b75fba81-16cb-422d-ab59-373a6a07eb74/ccny_report_2004_reading.pdf
6) Boekaerts, M., & Cascallar, E. (2006). How far have we moved toward the integration of theory and practice in self-regulation? Educational Psychology Review, 18(3), 199–210. https://www.researchgate.net/publication/227279167_How_Far_Have_We_Moved_Toward_the_Integration_of_Theory_and_Practice_in_Self-Regulation
7) Boon, R. T., Urton, K., Grünke, M., & Rux, T. A. (2019). Mnemonic strategies in mathematics instruction for students with learning disabilities: A narrative review. Learning Di¬sabilities: A Multidisciplinary Journal, 24(1), 49–62. https://doi.org/10.18666/LDMJ- 2019-V24-I2-9901
8) Caron, M. J., Mottron, L., Berthiaume, C., & Dawson, M. (2006). Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism. Brain, 129, 1789–802. https://pubmed.ncbi.nlm.nih.gov/16597652/
9) Carter, E. W., Common, E. A., Sreckovic, M. A., Huber, H. B., Bottema-Beutel, K., Gustafson, J. R., ... & Hume, K. (2014). Promoting social competence and peer relationships for adolescents with autism spectrum disorders. Remedial and Special Education, 35(2), 91–101. https://doi.org/10.1177/07419332513514618
10) Center on Multi-Tiered Systems of Support. (2022). Implementation. https://mtss4success.org/implementation
11) Cioca, L., & Nerisanu, R. A. (2020). Enhancing creativity: Using visual mnemonic devices in the teaching process in order to develop creativity in students. Sustainability, 12(5), 1985. https://doi.org/10.3390/su12051985
12) Cook, B., & Cook, S. (2013). Unravelling evidence-based practices in special education. The Journal of Special Education, 47(2), 71–82. https://doi.org/10.1177/0022466911420877
13) Cook, B., & Odom, S. L. (2013). Evidence-based practices and implementation science in special educa¬tion. Exceptional Children, 79(2), 135–144. https://doi.org/10.1177/001440291307900201
14) Cook, B., Cook, S. C., & Collins, L. W. (2016). Terminology and evidence-based practice for students with emotional and behavioral disorders: Exploring some devilish details. Beyond Behavior, 25(2), 4–13. https://doi.org/10.1177/107429561602500202
15) Council of Europe. (2018). CEFR companion volume with new descriptors. https://www.researchgate.net/publication/338178234_Council_of_Europe_2018
_Common_European_Framework_of_Reference_for_Languages_
Learning_Teaching_Assessment_Companion_Volume_with_
New_Descriptors_Strasbourg_Council_of_Europe_Publishing_Authors_B_North_E
16) Dembo, M. H., & Eaton, M. J. (2000). Self- regulation of academic learning in middlelevel schools. Elementary School Journal, 100(5), 473–490. https://www.jstor.org/stable/1002280
17) Dunn, M., & Miller, D. (2016). Improving story writing: Integrating the story mnemonic stra¬tegy with iPad apps for art and keyboarding. International Journal for Research in Learning Disabilities, 3(1), 11–28. https://www.semanticscholar.org/paper/Improving-Story-Writing%3A-Integrating-the-Story-with-Dunn-Miller/d9444d49593320391a1127fade56be4843b6e323
18) Fleury, V. P., Hedges, S., Hume, K., Browder, D., Thompson, J., Fallin, K., El Zein, F., Reutebuch, C., & Vaughn, S. (2014). Addressing the academic needs of adolescents with autism spectrum disorder in secondary education. Remedial and Special Education, 35(2), 68–79. https://doi.org/10.1177/0741932513518823
19) Frith, C. (2004). Is autism a disconnection disorder? The Lancet Neurology, 3(10), 577. https://doi.org/10.1016/s1474-4422(04)00875-0
20) Frith, U. (1989). Autism: Explaining the enigma. Oxford: Blackwell. https://www.scirp.org/(S(lz5mqp453edsnp55rrgjct55))/reference/referencespapers.aspx?referenceid=1268296
21) Frost, K. M., Brian, J., Gengoux, G. W., Hardan, A., Rieth, S. R., Stahmer, A., & Ingersoll, B. (2020). Identifying and measuring the common elements of naturalistic developmental behavioral interventions for autism spectrum disorder: Development of the NDBI-Fi. Autism. 24(8), 2285-97. https:// doi. org/10. 1177/ 13623 61320 944011.
22) Gersten, R., Chard, D., Jayanthi, M., Baker, S., Morphy, P., & Flojo, J. (2009). A meta-analysis of mathematics instructional interventions for students with learning disabilities: A technical report. Los Alamitos, CA: Instructional Research Group.
23) Gore, M. C. (2010). Inclusion strategies for secondary classrooms: Keys for struggling learners. Corwin Press: SAGE. https://doi.org/10.4135/9781483350424
24) Happé, F. G. (1999). Autism: Cognitive deficit or cognitive style? Trends in Cognitive Sciences, 3(6), 216–222. Doi: 10.1016/s1364-6613(99)01318-2
25) Happé, F., & Frith, U. (2006). The weak central coherence account: Detail- focused cognitive style in autistic spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–25. https://pubmed.ncbi.nlm.nih.gov/16450045/
26) Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112. https://journals.sagepub.com/doi/abs/10.3102/003465430298487
27) Hume, K., Odom, S. L., Steinbrenner, J. R., DaWalt, S., Hall, L. J., Kraemer, B. ... & Bolt, D. M. (2022). Efficacy of a School-Based Comprehensive Intervention Program for Adolescents with Autism. Exceptional Children, 88(2), 23–240. DOI:10.1177/00144029211062589. https://pubmed.ncbi.nlm.nih.gov/33449225/
28) Larkan-Skinner, K., & Shedd, J. M (2021). Real-Time Data and Predictive Analytics: Where Does IR Fit? New Directions for Institutional Research, 2020(185-186), 11–24. DOI:10.1002/ir.20326. https://onlinelibrary.wiley.com/doi/abs/10.1002/ir.20326
29) Liu, A. Y, Lacoe, J., Lipscomb, S., Halmson, J., Johson, D. R., Thurlow, M. ... & Sllverberg, M. (2018). Preparing for life after high school: The characteristics and experiences of youth in special education. Findings from the national longitudinal transition study 2012. Vol. 3: Comparisons over Time (Full Report) (NCEE 2018-4007). Washington, DC: U.S. Department of Education, Institute of Education Sciences. https://files.eric.ed.gov/fulltext/ED580934.pdf
30) Lubin, J., & Polloway, E. A. (2016). Mnemonic instruction in science and social studies for students with learning problems: A review. Learning Disabilities: A Contemporary Journal, 14(2), 207–224. https://www.semanticscholar.org/paper/Mnemonic-Instruction-in-Science-and-Social-Studies-Lubin-Polloway/e2eb55c26e0cde6a31c33ead248288def86625f4
31) Maenner, M. J., Shaw, K. A., & Baio, J. (2020). Prevalence of autism spectrum disorder among children aged 8 years autism and developmental disabilities monitoring network, 11 sites, United States, 2016. MMWR Surveillance Summaries, 69(4), 1–12. https://doi.org/10.15585/mmwr.ss6904a1
32) Mandinach, E. B. (2012). A perfect time for data use: Using data-driven decision making to inform practice. Educational Psychologist, 47(2), 71–85. DOI: 10.1080/00461520.2012.667064.
33) McFarland, J., Hussar, B., Zhang, J., Wang, X., Wang, K., Hein, S. ... & Barmer, A. (2019). The condition of education 2019 (NCES 2019-144). IES. National Center for Education Statistics. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2019144
34) Morin, K. L., Sam, A., Tomaszewski, B., Waters, V., & Odom, S. L. (2021). Knowledge of evidence-based practices and frequency of selection among school-based professionals of students with autism. The Journal of Special Education, 55(3), 143–152. DOI: 10.1177/0022466920958688. journalofspecialeducation.sagepub.com
35) Mursi, N. B., Sulaimani, M. F. (2022). Influence of context related factors on Saudi special education teacher´s understanding of evidence, evidence- based, and evidence- based practices. Problems of Education in the 21st Century, 80(4), 588–600. https://doi.org/10.33225/pec/22.80.588
36) Odom, S. L., Collet-Klinenberg, L., Rogers, S., & Hatton, D. (2010). Evidence-based practices in interventions for children and youth with autism spectrum disorders. Preventing School Failure: Alternative Education for Children and Youth, 54, 275–282. https://www.tandfonline.com/doi/full/10.1080/10459881003785506
37) Ojea, M. (2023). Autism: New conceptual propositional hypothesis. European Journal of Theoretical and Applied Sciences, 1(6), 115–124. https://ejtas.com/index.php/journal/article/view/437
38) Reichow, B., & Volkmar, F. R. (2011). Evidence-based practices in autism: Where we started. In B. Reichow, P. Doehring, D. V. Cicchetti, & F. R. Volkmar (Eds.), Evidence-based practices and treatments for children with autism (pp. 3–10). Springer. https://psycnet.apa.org/record/2010-25555-001
39) Selçuk, Z. (2018). Eğitim psikolojisi [Education Psychology]. Nobel Akademi. https://www.academia.edu/36316637/E%C4%9Fitim_Psikolojisi
40) Spencer, T., Detrich, R., & Slocum, T. A. (2012). Evidence-based practice: A framework for making effective decisions. Education and Treatment of Children, 35(2), 127–151. https://doi.org/10.1353/etc.2012.0013
41) Test, D. W., Smith, L. E., & Carter, E. W. (2014). Equipping youth with autism spectrum disorders for adulthood: Promoting rigor, relevance, and relationships. Remedial and Special Education, 35(2), 80–90. https://doi.org/10.1177/0741932513514857
42) Vaughn, S., Gersten, R., & Chard, D. J. (2000). The underlying message in LD intervention research: Findings from research syntheses. Exceptional Children, 67, 99–114. https://psycnet.apa.org/record/2001-00001-007
43) Vaughn, S., Wanzek, J., Murray, C. S. (2012). Intensive interventions for students struggling in reading and mathematics. A Practice Guide. Portsmouth, NH: Center on Instruction at RMC Research Corporation. https://files.eric.ed.gov/fulltext/ED531907.pdf
44) Wong, C., Odom, S. L., Hume, K., Cox, A. W., Fettig, A., Kucharczyk, S. ... & Schultz, T. R. (2015). Evidence based practices for children, youth, and young adults with autism spectrum disorder: A comprehensive review. Journal of Autism and Developmental Disorders, 45, 1951–1966. https://doi.org/10.1007/s10803-014-2351-z
45) Yamamoto, S. H., & Alverson, C. Y. (2023). Post-high school outcomes of students with autism spectrum disorder and students with intellectual disability: Utilizing predictive analytics and state data for decision making. Journal of Intellectual Disabilities, 27(3) 633–647. DOI: 10.1177/17446295221100039. journals.sagepub.com/home/jid
46) Zhang, J., Martella, R. C., Kang, S., & Yenioglu, B. Y. (2023). Response to Intervention (RTI)/ Multi-Tiered Systems of Support (MTSS): A nationwide analysis. Journal of Educational Leadership and Policy Studies, 7(2), 1–26. https://files.eric.ed.gov/fulltext/EJ1396417.pdf
47) Ziviani, J., Wilkinson, S., Hinchliffe, F., & Feeney, R. (2015). Mapping allied health evidence-based practice: providing a basis for organisational realignment. Australian Health Review, 39(3), 295–302. https://doi.org/10.1071/AH14161