A CODING CURRICULUM FOR K-12 EDUCATION: THE EVIDENCE-BASED APPROACH

In recent years, public and private educational systems are making efforts to update their programmes as to integrate computational thinking and computer programming in K-12 grades. Despite the expertise of the academic world in teaching CS, and the vast amount of knowledge and tools available to evaluate programming skills in industry, there are no clear clues on how children do learn CS concepts, or what is the best strategy to develop coding skills in the school, and how to implement it with limited resources (hardware and trained personnel). The reason for these difficulties has to do with the variety of environments in the market, as well as the complexity to perform controlled multicenter experimentation with children that are exposed differently to computer programming (from no contact at all, to gaining skills at home, or in academies). We propose a curriculum to teach the most relevant concepts of CS, ranging from the very basic command execution, to problem-solving with Artificial Intelligence heuristics, covering the whole K-12 school grades. Instead of being based on computational thinking studies, this curriculum is the result of four years of field work, testing the ToolboX Academy programming environment on site, from a direct scrutiny of children interaction with the interface and tasks definition, to a controlled experiment where more than a thousand students became involved, from 30 different centers. The result is a detailed description of how the fundamental concepts of computer programming can be presented to primary-school students in order to reach a high level of coding proficiency, as well as acquiring the AI bases.

 

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CODING SKILLS ARE ACQUIRED GENDER-INDEPENDENTLY IN THE K-12 SYSTEM: THE TOOLBOX.ACADEMY EXPERIENCE

Gender inequality in accessing STEM studies is a serious problem that higher education needs to solve. But the reasons for this are not clear yet. Among the arguments considered, a prevalent one has to do with a supposed innate male competence for science and engineering. In a controlled experiment involving 356 female and 394 male participants, of ages ranging from 6 to 18 years, subjects were asked to solve tasks by writing computer programs, and performance was measured as the number of tasks solved in a given time. Statistical analysis of the learning curves showed that female participants performed as well as male participants in acquiring coding skills and problem-solving. This result contradicts this innate bias, showing that both genders qualify at the same level for computer programming, and suggests policies to gender-balance affiliation to STEM careers, since an early exposure to the computer sciences might combat stereotypes like «coding is only for boys». In the paper we analyze in detail the main results of this experiment, as well as direct feedback from female and male subjects in solving the tasks.

 

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MANAGING E-LEARNING METADATA WITHIN TOOLBOX.ACADEMY: KNOWLEDGE ACQUISITION WITH BIG DATA ALGORITHMS AT THE STUDENT AND GROUP LEVELS

E-learning is not only providing new means to access knowledge, and changing the way teaching takes place at the school and at home, it is also paving the way to learn more and know better about the students’ skills, competences, attitude or disorders. Statistics and AI-based big data are the methods to acquire this knowledge, that is of great value for educators and managing teams. Indeed, what looks like a simple interaction between the student and yet another application interface, actually generates a considerable amount of metadata which holds the clues of how the student’s cognitive processes deal with the task in question. This metadata, when treated properly, reveals useful knowledge to improve education, as a recent experience with the ToolboX Academy environment has shown. While atypical slopes in learning curves might point toward ADHD or intellectual giftedness, recurrent typing errors might reveal dyslexia, or discalculia might be detected by numeric errors over the average. What is more, tasks in this environment are specially designed for detecting other disorders, like daltonism. These are but examples of what coding environments can reveal with basic big data analysis, but the fine-grain interaction does actually store even more data, and group-level processing can also disclose deficiencies in the teaching process, in general or particular subjects, mainly in the STEM area. In this paper, we describe the approach followed by ToolboX Academy to disclose this information.

 

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Validación de la herramienta de programación ToolboX

El día 5 de abril, tendrá lugar en el CEP de Antequera la presentación de la » Herramienta didáctica Toolbox» .
A esta jornada asistirá profesorado de 27 centros andaluces, que participarán en el experimento de validación de dicha herramienta.
Esta investigación se realiza en el marco del Convenio de cooperación entre la Consejería de Educación de la Junta de Andalucía y la Universidad de Málaga para el desarrollo de intervenciones, en el ámbito de la innovación y la investigación, en centros docentes públicos no universitarios de la Consejería de Educación.
El objetivo de esta experimentación será estudiar la conveniencia de  implantar ToolboX como herramienta didáctica en la comunidad educativa andaluza.
Este experimento de validación,  abarca dos aspectos:   la integración técnica de la aplicación en la plataforma informática dependiente de la Consejería de Educación, y la evaluación de la eficacia docente de la herramienta para la enseñanza de competencias en determinadas asignaturas y transversal en la programación de ordenadores.
ToolboX es un entorno de desarrollo que permite introducir la programación de ordenadores en asignaturas sin competencias informáticas. Parte de la premisa de que el alumnado, al resolver un problema, realiza cálculos en una secuencia determinada (es decir, procede algorítmicamente) y puede expresarlos en un lenguaje informático sencillo, del mismo modo que lo hace en estilo libre sobre un cuaderno o pizarra.
Fecha: 05/04/2018
Fuente/Autor: Consejería de Educación. Servicio de Innovacíon Educativa.
Información adicional:

Centros participantes en la validación:

IES AVERROES de Córdoba

IES STA ROSA DE LIMA  de Córdoba
CEIP NTRA SRA DEL CARMEN de Lucena
IES POLITÉCNICO HERMENEGILDO LANZ  de Granada
IES LA ZAFRA de Motril
CEIP ARDIRA de Málaga
CEIP LOS PRADOS de Málaga
IES MEDITERRÁNEO de Salobreña
IES SAN ANTONIO de Bollullos Par del Condado
CEIP LA LEALA de Arroyo de la Miel
IES CAMPANILLAS de Campanillas
IES LAS SALINAS de Fuengirola
CEIP INTELHORCE de Málaga
CEIP LA BIZNAGA de Málaga
CEIP SAN MIGUEL de Nerja
IES ALVAREDA de Dos Hermanas
IES VIRGEN DE VALME de Dos Hermanas
IES HERMANOS MACHADO de Dos Hermanas
IES NICOLÁS COPÉRNICO de Écija
IES ANTONIO DE ULLOA de La Rinconada
CEIP HUERTA DEL RETIRO de Mairena del Alcor
CEIP MAESTRO PEPE GONZÁLEZ de San José de la Rinconada
IES SEVERO OCHOA de San Juan de Aznalfarache
IES SAN JUAN de San Juan de Aznalfarache
IES VICENTE ALEIXANDRE de Sevilla
IES MIGUEL DE SERVET de Sevilla
IES MURILLO de Sevilla