We wish to thank the Vice-rectorate for Research and Knowledge Transfer of the University of Burgos for making the development of the software possible through the &#8220;VI Edici&#243;n Convocatoria Prueba Concepto: Impulso a la valorizaci&#243;n y comercializaci&#243;n de resultados de investigaci&#243;n&#8221; [VI Edition of the Call for Proof of Concept: Impulse to the valorization and marketing of research results]. We likewise thank the Educational Programs Area of the Provincial Directorate of Education and to the Special Education Center &#34;Fray Pedro Ponce de Le&#243;n&#34;, both in Burgos (Spain), and to the families of the children who agreed to participate in this pilot study with prior informed consent, without whose collaboration the software (eEarlyCare) would not have been possible. The video was edited by Alberto Calvo Rodr&#237;guez TVUBU technician and the voice over was done by Caroline Martin, from the Department of English Philology of the University of Burgos.

This protocol was performed in compliance with the procedural regulations of the Bioethical Committee of the University of Burgos (Spain). Prior to their participation, both the students and their parents and in some cases legal tutors had all provided their informed consent and had been fully made aware of the objectives of study. No financial compensation was offered for their participation.
1. Participant recruitment
<ol>
	<li>Recruit children between 0-6 years of age with a history of sp...

<ol>
	<li>S&#225;iz, M. C., G&#243;mez, A., Viguer, P., Cantero, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intervenci&#243;n+cognitiva+en+ni&#241;os+peque&#241;os+[Cognitive+intervention+in+early+children].">Intervenci&#243;n cognitiva en ni&#241;os peque&#241;os [Cognitive intervention in early children].</a> Intervenci&#243;n Temprana: Desarrollo &#243;ptimo de 0 a 6 a&#241;os [Early Intervention: Optimal development from 0-to-6 years old]. , 117-133 (2003).</li><li>Bluma, M. S., Shearer, M. S., Frohman, A. H., Hilliard, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Portage Guide to Early Education (2nd Edition). , (1978).</li><li>Josse, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Escala+de+desarrollo+psicomotor+de+la+primera+infancia+Brunet-L&#233;zine+Revisado+[Scale+of+psychomotor+development+of+early+childhood+(Brunet-L&#233;zine-Revised)].">Escala de desarrollo psicomotor de la primera infancia Brunet-L&#233;zine Revisado [Scale of psychomotor development of early childhood (Brunet-L&#233;zine-Revised)].</a> Psymt&#233;c. , (1997).</li><li>Newborg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Battelle Developmental Inventory, 2nd Edition: Examiner's manual. , (2005).</li><li>Whitebread, D., Basilio, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emergencia+y+desarrollo+temprano+de+la+autorregulaci&#243;n+en+ni&#241;os+preescolares+[The+emergence+and+early+development+of+self-regulation+in+preschool+children].">Emergencia y desarrollo temprano de la autorregulaci&#243;n en ni&#241;os preescolares [The emergence and early development of self-regulation in preschool children].</a> Profesorado. Revista de Curr&#237;culum y Formaci&#243;n del Profesorado. 16 (1), 1-20 (2012).</li><li>P&#233;rez, Y., S&#225;iz, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Escala para la medici&#243;n de habilidades funcionales en edades 0-6 a&#241;os (EHFI) [Scale for the measurement of functional abilities in 0-to-6-year olds (SFA)]. Registration number 00/2019/4253. , (2018).</li><li>Haley, S. M., Coster, W. J., Ludlow, L. H., Haltiwanger, J. T., Andrellos, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Pediatric Evaluation of Disability Inventory (PEDI) (2nd ed.). , (2012).</li><li>Bronson, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Self-regulation In Early Childhood. , (2000).</li><li>S&#225;iz, M. C., Carbonero, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metacognitive+Precursors:+An+Analysis+in+Children+with+Different+Disabilities.">Metacognitive Precursors: An Analysis in Children with Different Disabilities.</a> Brain Science. 7 (10), 1-14 (2017).</li><li>S&#225;iz, M. C., Marticorena, R., Arnaiz-Gonz&#225;lez, J. F., D&#237;ez-Pastor, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> eEarlyCare Computer application. , (2019).</li><li>Chowdhury, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Windows Presentation Foundation Development Cookbook. (1st Edition). , (2018).</li><li>Nogal, F., Marticorena, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> UBUGrades 2.0. Doctoral Degree dissertation. , (2018).</li><li>S&#225;iz, M. C., Marticorena, R., Arnaiz-Gonzalez, &. #. 1. 9. 3. ;., D&#237;ez-Pastor, J. F., Rodr&#237;guez-Arribas, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+application+for+the+registration+and+automation+of+the+correction+of+a+functional+abilities+detection+scale+in+early+care.">Computer application for the registration and automation of the correction of a functional abilities detection scale in early care.</a> Proceeding of INTED2019: 13th annual International Technology, Education and Development Conference. , 5322-5328 (2019).</li><li>Hartson, R., Pyla, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The UX book: Process and guidelines for ensuring a quality user experience. , (2012).</li><li>Bernal, R., Ram&#237;rez, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improving+the+quality+of+early+childhood+care+at+scale:+The+effects+of+"From+Zero+to+Forever".">Improving the quality of early childhood care at scale: The effects of "From Zero to Forever".</a> World Development. 118, 91-105 (2019).</li><li>American Psychiatric Association. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Diagnostic and Statistical Manual of Mental Disorders (DSM-5). (5th Edition). , (2013).</li></ol>

The authors declare that they have no competing financial interests.

When using the software, it is recommended that the teacher or therapist record the development of each child&#39;s functional abilities over at least for two sessions. The scale contains 114 items, 11 functional areas, which are divided into 33 functional subareas and the assessment should be the result of observation in natural contexts. In addition, the software allows early-care professionals to record evaluation data with ease and to analyze the data displayed in individual and group graphs, highlighting the develop...

Observation at early ages: what and how to observe
Early childhood assessment in ordinary family contexts and at school is performed using the observational method. Hence, the evaluator must adhere to a precise observational process, the key to an accurate diagnosis and, therefore, to a successful training1. There are many development inventories that provide guidelines for assessment: The Portage Guide2, the Brunet L&#233;zine Scale3, and the Battelle Developmental Inventory4, among others. These tools are based on internationally agreed standards set by the scientific community in the field of human evolutionary development. Although these tools analyze developmental areas (Psychomotor, Cognitive, Communication and Language, and Autonomy and Socialization), recent studies5 have proposed new tools that can also analyze these areas. These studies point out that the observational method from birth provides pointers of immense utility to early intervention and for the early detection of pathologies. However, the observational processes at these ages are complex, as they depend on behavioral observations recorded in natural contexts, which are not always easy to carry out.
Within this framework, the assessment of the acquisition of functional abilities at early ages is of great interest to parents, educators, and therapists alike. Any such assessment is of relevance for children who have been diagnosed or who are at risk of developing some disability. Early detection of developmental disorders is essential for the early diagnosis and intervention. Observational study from birth will provide indicators of this early detection and intervention5. Currently there are various tools (development inventories, scales, tests, etc.) for measuring development at those ages. The instruments that can currently be applied are developmental inventories, some of which are standardized. However, some of those instruments may require knowledge of psychometric techniques and the results are not automatically displayed on screen. For this reason, it is important to develop other tools that are easier to use and interpret.
&#160; &#160;
Preparation of software for recording and interpreting data from the processes of contextual observation processes at early ages
The software development was, therefore, considered of relevance, which would assist the observers (therapist, educator, etc.) to record and to interpret the results of their observations. This protocol and software, eEarlyCare, can be used both in educational centers that work with children with disabilities and in therapeutic intervention centers aimed at this group. This is why from now on the term &#34;user &#34;will be used, which includes both students and patients, depending on the place where the intervention is carried out. In particular, a software that could facilitate the recording and the interpretation of data gathered in natural contexts from the observation of functional abilities among children from 0 to 6 years old. This software, eEarlyCare, is based on the functional abilities scale6 [Scale for the measurement of Functional Abilities in children between 0-6 years old] (SFA); this scale includes the measurement of 11 areas of development (Food Autonomy, Personal Care and Hygiene, Independently and dress and undresses, Sphincter control, Functional mobility, Communication and Language, Interactive symbolic play, Daily life routines, Adaptive behavior). Also, it was in turn, inspired by the Portage Guide2, the Pediatric Evaluation of Disability Inventory (PEDI)7, and the works of Bronson8, as well as Whitebread and Basilio4 on social skills at ages 0-6, the Brunet-L&#233;zine Scale3, developmental inventories for children aged 0-67, and the Assessment Scale of the precursors9 to social skills. This tool is a computer application that is used for registering the results of each user assessment in longitudinal follow-ups (quarterly, monthly, annual, etc.). It is a referential aspect for the therapist with regard to the intervention, and for other professionals who work with children in early childhood with suspected dysfunctionalities. In addition, the software10 can automatically produce comparisons between the development of the functional abilities of different users, regardless of whether they are at the same intervention center, thereby facilitating the definition of common aspects for collaborative work.
In particular, this software is based on mainstream technologies (e.g., Windows Presentation Foundation Development -WPF-11), a technological innovation that integrates advanced graphics to produce accurate graphic results12 and a positive computer user-experience. The quality of the graphs improves the visualizations and the interactivity available with other tools such as spreadsheets. The application can store the data locally on relational databases and upload the information onto the cloud to be shared. In addition, the classic client-server architecture is also supported. These features make it easy to record the data that are collected from the observations and to process the results for visualization. Also, once registered, it is very easy to export the data. This allows the data to be used in powerful statistical packages to apply data mining techniques, such as supervised (classification and/or regression) and unsupervised (grouping) machine learning.
In this study, the classification techniques are of specific utility for personalized learning13. The architecture can be seen in Figure 1 and Figure 2. In Figure 1, the functionality of cloud storage is used as a safeguard, in case of data security problems and potential loss and corruption of data when exchanged between applications. Additionally, the software can also operate in a classic network-based client-server architecture with a database (Figure 2) with all data exchanges taking place between clients (these are concepts that are used in the field of computer science). These platforms provide authentication mechanisms and restricted access, which ensure privacy and data protection, while facilitating interaction with fully developed applications. The final result is an application interface that is designed14 for early-care professionals, so that they can use Learning Analytics techniques in a simple way and refer to them, in order to follow up the degree of each student&#8217;s development in each evaluation area of the scale15.
The application also offers a general profile of each user in each of the functional areas and subareas (Table 1). It also produces a comparison between all users at any one center. In brief, it produces a personalized analysis of the intervention needs of the different users. In addition, it helps early-care professionals with their intervention programs, as it can flag up areas in which users might or might not show similar developmental patterns. All these results guide the type of intervention programs that can be used together, rather than those that have to be designed individually. The data that are linked to this interface are the SFA scores of the users that are measured on a Likert scale from 1 to 5. Those scores can be compared with the maximum developmental age scores linked to each SFA dimension. The software can also link the chronological age of each user to the developmental age of each SFA dimension; a relevant aspect for the detection of intervention areas from among which to prioritize the areas for treatment.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Functional area</td>
			<td>Functional sub-area</td>
		</tr>
		<tr>
			<td rowspan="2">1. Food Autonomy</td>
			<td>1. Food Texture</td>
		</tr>
		<tr>
			<td>2. Use of utensils</td>
		</tr>
		<tr>
			<td rowspan="5">2. Personal Care and Hygiene</td>
			<td>3. Dental Hygiene</td>
		</tr>
		<tr>
			<td>4. Hairstyle</td>
		</tr>
		<tr>
			<td>5. Nasal Care</td>
		</tr>
		<tr>
			<td>6. Handwashing</td>
		</tr>
		<tr>
			<td>7. Face and body wash</td>
		</tr>
		<tr>
			<td rowspan="2">3. Independently dresses and undresses</td>
			<td>8. Dressing and undressing (waist upwards)</td>
		</tr>
		<tr>
			<td>Dressing and undressing (waist downwards)</td>
		</tr>
		<tr>
			<td>4. Sphincter control</td>
			<td>9. Sphincter control</td>
		</tr>
		<tr>
			<td rowspan="8">5. Functional mobility</td>
			<td>10. Upper extremity</td>
		</tr>
		<tr>
			<td>11. Transfers in WC</td>
		</tr>
		<tr>
			<td>12. Transfers on a chair</td>
		</tr>
		<tr>
			<td>13. Mobility and bed transfers</td>
		</tr>
		<tr>
			<td>14. Mobility in the bathtub</td>
		</tr>
		<tr>
			<td>15. Mobility indoors</td>
		</tr>
		<tr>
			<td>16. Transport of objects</td>
		</tr>
		<tr>
			<td>17. Outdoor Mobility</td>
		</tr>
		<tr>
			<td rowspan="3">6. Communication and Language</td>
			<td>18. Word comprehension</td>
		</tr>
		<tr>
			<td>19. Understanding phrases</td>
		</tr>
		<tr>
			<td>20. Functional use of communication</td>
		</tr>
		<tr>
			<td rowspan="2">7. Resolution of tasks in social contexts</td>
			<td>21. Solving Problems</td>
		</tr>
		<tr>
			<td>22. Information about yourself</td>
		</tr>
		<tr>
			<td rowspan="3">8. Interactive and symbolic play</td>
			<td>23. Interactive Play</td>
		</tr>
		<tr>
			<td>24. Interaction with the peer group</td>
		</tr>
		<tr>
			<td>25. Play with objects</td>
		</tr>
		<tr>
			<td rowspan="2">9. Daily life routines</td>
			<td>26. Guidance in time</td>
		</tr>
		<tr>
			<td>27. Homework</td>
		</tr>
		<tr>
			<td rowspan="5">10. Adaptive behavior</td>
			<td>28. Self-harm behavior</td>
		</tr>
		<tr>
			<td>29. heteroagressiveness (harming others)</td>
		</tr>
		<tr>
			<td>30. Destruction of objects</td>
		</tr>
		<tr>
			<td>31. Disruptive behaviour (cry, shout, laugh without reason)</td>
		</tr>
		<tr>
			<td>32. Stereotypes</td>
		</tr>
		<tr>
			<td>11. Attention</td>
			<td>33. Attention</td>
		</tr>
	</tbody>
</table>
Table 1: List of functional areas and subareas.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60247/60247fig01.jpg" /> 
Figure 1: Architecture of the proposal of automation of the correction of the Scale functionality of cloud storage. <a href="https://www.jove.com/files/ftp_upload/60247/60247fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/60247/60247fig02.jpg" /> 
Figure 2: Architecture of the proposal of automation of the correction of the Scale functionality classic network. <a href="https://www.jove.com/files/ftp_upload/60247/60247fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Therapists and intervention professionals can use this assessment protocol and the software implementation for the assessment of functional abilities and their development in early childhood between 0 and 6 years of development. The software can be used with children within that age range, although it is especially useful for children with suspected impaired development of functional abilities. It is likewise especially useful at Special Education Centers. The Research question is whether, having observed the functional abilities of children, the use of a computer tool will facilitate the recording and the interpretation of the results for the therapist.

<table>
	<tbody>
		<tr>
			<td>eEarlyCare software</td>
			<td>Authors and University of Burgos. Register number 00/2019/3855</td>
			<td></td>
			<td>Computer application to implement SFA</td>
		</tr>
		<tr>
			<td>Scale for the measurement of functional abilities in 0-6 years old (SFA)</td>
			<td>Authors and University of Burgos. Register number 00/2019/4253</td>
			<td></td>
			<td>Scale for the measurement of functional abilities in 0-6 year olds</td>
		</tr>
	</tbody>
</table>

measuring the functional abilities of children aged 3-6 years old with observational methods and computer tools

The analysis of functional abilities and their development in early childhood (0-6 years old) are fundamental aspects among young children with certain types of developmental difficulties that can facilitate prevention, through programmed interventions adapted to the needs of each user (student or patient). There are, however, few investigations to date, that have analyzed the use of automated tools for recording and interpreting the results of the initial assessment. Here, a protocol is presented to examine the functional abilities in early childhood in young children, aged between 3-6 years old, with intellectual disabilities, but the protocol can also be used for ages 0 to 6 years. The protocol makes use of a computer application, eEarlyCare, that facilitates the interpretation of the results of systematic observations, which are recorded in natural environments by professionals trained in early intervention. The software can be used to analyze 11 functional areas (Food Autonomy, Personal Care and Hygiene, Dressing and Undressing Independently, Sphincter Control, Functional Mobility, Communication and Language, Daily Life Routines, Adaptive Behavior and Attention) and a total of 114 different behaviors. Its use facilitates the analysis of the observed abilities and greatly assists early intervention. Compared to other observational methods, it allows a more efficient use of personal and material resources. The use of the computer application facilitates the recording of the observation results, which helps with organization and reflection on the observations. The software displays the observation results on-screen compared to normal developmental parameters. This information can be referred to for decision-making about the most suitable intervention program for each user (student or patient). Likewise, clustering techniques are applied to analyze the relation between the type of intellectual disabilities and functional development identified with the software, a relation that is intended to serve as a guide for early-care professional intervention.

The present study recruited 11 participants with confirmed diagnoses [both moderate (development quotient = DQ 40-65) and severe (DQ 39-60) intellectual disabilities]. The protocol was tested in a pilot project over 20 months at a Special Education Center. All the diagnoses for this study had been confirmed by a multidisciplinary team in accordance with DSM-5, using the Brunet L&#233;zine Scale, as the degree of affectation was beyond the scope of other scales such as the Wechsler Preschool and Primary Scale of Intellige...

Watch this Scientific Journal Video about Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools at JoVE.com

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

We present a protocol to use a computational tool to record and analyze the functional abilities of children aged 3-6 years old. The protocol facilitates the comparison of these abilities throughout their development and can be used to assess developmental difficulties.

The analysis of functional abilities and their development in early childhood (0-6 years old) are fundamental aspects among young children with certain ...

These protocol was performing compliance with the procedural regulations of the Bioethical Committee of the university of Burgos Spain prior to their participation, both the students and their parents, in some cases, legal tutors had all provided their informed consent and I'd been fully made aware of the objectives of the study. No financial compensation was offered for their participation. The protocol analyze the use of the software for recording and interpretation of results in a scale for the measurement of functional abilities, In 30 to 60 households.These scales analyze functional abilities, That are distributed in 11 areas. The server allows the recording interpretation of the functional development of users comparing the evolutionary development in each ability. It is measured in a lighter scale from one to five, from nothing to everything.This tool facilitates the detection of problems in the development of functional skills guides in implementation of training programs, and in turn facilitates the monitoring of user within such programs. Before using this server the teacher therapies cannot serve different abilities in a drug context. Also, it can compare these results with parents'information, Participant recruitment.Recruit children between zero to six years of development age with a history of special educational needs related to alteration in the area of motor development, cognitive, personal autonomy, and socialization, and with moderate to severe intellectual disabilities. A total of 11 participants, seven boys and four girls were recruited for the present study. Include children who show confirmed diagnosis of either moderate or severe intellectual disability in accordance with the diagnostic and statistical manual of mental disorders and attend a special education center for their schooling.The diagnosis should, in each case, have been confirmed by a Pediatric Neurologist at a hospital or a Psychologist on behalf of a multidisciplinary team in accordance with DSM-5. Ideally there should be no fewer than 15 participants. Exclude children with normal development in functional areas, motor cognitive, personal autonomy, and socialization development and children with an intellectual functioning limitation.Data collection. Collect data on the development of the children in different functional areas, food autonomy, personal care and hygiene, dressing and undressing independently, sphincter Control, functional mobility, communication and language, daily life routine, adapted behavior and attention. For the observation using the scale for the measurement of functional abilities in children between zero to six years old and conduct deo observation in a natural context.For example, schooling settings. Record observation throughout the week in different natural environment that reflect the daily life of the students at the center. For example, while playing, et cetera.let the teacher and the therapist who directly attend the child at the educational institution, record the observations and then put the results into the software. Experiment Procedures. Assigning a student to a teacher in the software.This step is unusually performed by the study director, who generally as the coordinator of the program. Login the software package with a username and password and select language, either English or Spanish. Enter on the information relating to student data from the register's help by the director of the center.Fill in the following field for each student. Name, sir name, code, sex, date of birth, developmental age, primary diagnosis, secondary diagnosis where appropriate and observation that are relevant to mediation, data, allergies and other information or interest to the management of the center. Enter the information relating to the teacher or therapist from the records held at the center.Assign the teachers to a group with a teacher or therapist by clicking on classroom, then go to the column Students, then choose the student to be assigned to the classroom and then click on teachers and select one Allocate each group of students and their teacher or therapist to a classroom by clicking in teachers'input dates, name, surname, identification code, mail, password, and observation. Then click accept Director can then devolve responsibility for student assessments to each teacher. The director can consult the assessments that the teacher will input into the software at any time throughout the academic year.Use of the software by the Teacher. The teacher or therapist performing the assessment can then select an academic year, and or a term. The scale offers the possibility of selecting different functional areas for each term, Login to the software with a username and password that the director can previously assigned.Enter the result of the assessments completed in natural environments for each participant assigned to a classroom. Choose a student in the software by clicking on his name and then start the assessment of a different functional area. Perform the comparative analysis between the development of each user and the expected development at that chronological age.Do this by following the steps. Once the data is registered select the column evaluation by right clicking select the year, and then the trimester select the column students and select the students of the class of whom you want to make the evaluation. Then select the column areas, clicking on the area and sub area that needs to be evaluated.Then click on the maximum tab. It gets the development of the students and the comparison in the development expected for their age Compare the different functional areas of each user from the classroom An analysis of the functional areas of each user can be performed with the software. Exporting data from the software.Select the user data and functional areas, then export the database. Select the column Excel, then get the database, then export database in the statistics program or library of your choice. Import the data into statistical packages and libraries such as SPSS, Weaker, Python, et cetera, and perform clustering analysis.Here, analysis with SPSS is detailed as below. Clustering or cluster analysis in an unsupervised machine learning technique N within K means it is a grouping method, which aims to partition a set of N observation into K groups in which N observation belongs to a group with a closer mean value. In this experiment K means clustering was used to check the clusters of children and their functional development measured with SFA Select the option analyze, and then classify followed by the option.K means cluster in the statistical package. Select cross tabs under descriptive statistics, and then the following two variables. Select the descriptive statistics option and then select cross tabs, and then the Cohen Kappa coefficient option.Use a spreadsheet to generate the spider chat and specific bar graphs for the groups of children with moderate and severe intellectual disabilities.Results. In this study, we present some example of data analysis with the observational protocol, coupled with the use of the software application. We first perform a cluster analysis in order to check whether both the diagnosis of medium and severe intellectual disabilities of the children with special educational needs corresponded to their actual development.Using the K means method, we found two clusters of belonging to either group. Cluster one and cluster two integrated 55%and 45%of the sample respectively. A cross table was then generated to study the relationship between the belonging cluster and the variable degree of disability cluster.It was found that all the subject grouped in cluster one belong to a group A, moderate intellectual disabilities, and cluster two included all the students belonging to a group B, severe intellectual disabilities. and there was only one with moderate intellectual disabilities. See table three, A Cohen Kappa coefficient 820, p=006 was obtained.Progressing with this analysis of study can be performed of the capabilities of the participant in each functional group, disability moderate versus disability severe. Spider chart and specific bar graphs were used for this purpose.Conclusions. The server improves the study of Austro Vascular Disorder In natural environments, because if a law record on professing of the data or filling the tissue therapist and analyze practically in real time.also the software facilitates the export of data from the center on classroom to file in excel a specific format, quit facilitate the insertion in a statical page Which is possible to perform other more complex analysis, such as the cluster analysis different of means with paramic or no paramic studies Analyze of the reliability of the server for that sample etc.

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JoVE Journal

Behavior

8.8K Views.  Universidad de Burgos. These protocol was performing compliance with the procedural regulations of the Bioethical Committee of the university of Burgos Spain prior to their participation, both the students and their parents, in some cases, legal tutors had all provided their informed consent and I'd been fully made aware of the objectives of the study. No financial compensation was offered for their participation. The protocol analyze the use of the software for recording and interpretation of results in a scale fo...