scholarly journals Workbook for e-Education: Children’s Online Handwriting Quality Analysis.

Author(s):  
Hanen Akouaydi ◽  
Yahia Hamdi ◽  
Houcine Boubaker ◽  
Faouzi Alaya Cheikh ◽  
Adel M. Alimi

<div>This paper describes an innovative e-learning project which is the development of a digital workbook that helps teaching handwriting at school. In this work, we propose a new qualitative and quantitative analysis process of cursive handwriting. This process detects automatically mistakes, gives a real-time feedback and helps teachers evaluate children’s writing skills. The main aim of this digital workbook is to help children learn how to write correctly. The proposed process is composed of five main criteria: shape,direction, stroke order, position respect to the reference lines and kinematics of the trace. It analyzes the handwriting quality and gives automatically feedback based on the Beta-Elliptic Model using similarity detection (SD) and dissimilarity distance (DD) measure. Our work apprehends dynamic and visual representation of the acquired traces and selects efficient features adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbols drawing. It demonstrates that beta-elliptic is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Our application offers two interactive interfaces respectively dedicated to learners, and experts or teachers who can adapt it easily to the specificity of each child. The validation of the proposed system is done on a database collected in Tunisia primary schools with 400 children. Experimental results show that the efficiency and robustness of our suggested framework that do help teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.</div>

2021 ◽  
Author(s):  
Hanen Akouaydi ◽  
Yahia Hamdi ◽  
Houcine Boubaker ◽  
Faouzi Alaya Cheikh ◽  
Adel M. Alimi

<div>This paper describes an innovative e-learning project which is the development of a digital workbook that helps teaching handwriting at school. In this work, we propose a new qualitative and quantitative analysis process of cursive handwriting. This process detects automatically mistakes, gives a real-time feedback and helps teachers evaluate children’s writing skills. The main aim of this digital workbook is to help children learn how to write correctly. The proposed process is composed of five main criteria: shape,direction, stroke order, position respect to the reference lines and kinematics of the trace. It analyzes the handwriting quality and gives automatically feedback based on the Beta-Elliptic Model using similarity detection (SD) and dissimilarity distance (DD) measure. Our work apprehends dynamic and visual representation of the acquired traces and selects efficient features adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbols drawing. It demonstrates that beta-elliptic is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Our application offers two interactive interfaces respectively dedicated to learners, and experts or teachers who can adapt it easily to the specificity of each child. The validation of the proposed system is done on a database collected in Tunisia primary schools with 400 children. Experimental results show that the efficiency and robustness of our suggested framework that do help teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.</div>


2020 ◽  
Author(s):  
Yahia Hamdi ◽  
Hanen Akouaydi ◽  
Adel Alimi

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, gives real-time on-line feedback for children’s writing, and helps teachers comprehend and evaluate children’s writing skills. The proposed method adjudges five main criteria: shape, direction, stroke order, position respect to the reference lines, and kinematics of the trace. It analyzes the handwriting quality and automatically gives feedback based on the combination of three extracted models: Beta-Elliptic Model (BEM) using similarity detection (SD) and dissimilarity distance (DD) measure, Fourier<br>Descriptor Model (FDM), and perceptive Convolutional Neural Network (CNN) with Support Vector Machine (SVM) comparison engine. The originality of our work lies partly in the system architecture which apprehends complementary dynamic, geometric, and visual representation of the examined handwritten scripts and in the efficient selected features<br>adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbol drawing. The application offers two interactive interfaces respectively dedicated to learners, educators, experts or teachers and allows them to adapt it easily to the specificity of their disciples. The evaluation of our framework is enhanced by a database collected in Tunisia primary school with 400 children. Experimental results show the efficiency and robustness of our suggested framework that helps teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.<br>


2020 ◽  
Author(s):  
Yahia Hamdi ◽  
Hanen Akouaydi ◽  
Houcine Boubaker ◽  
Adel Alimi

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, gives real-time on-line feedback for children’s writing, and helps teachers comprehend and evaluate children’s writing skills. The proposed method adjudges five main criteria: shape, direction, stroke order, position respect to the reference lines, and kinematics of the trace. It analyzes the handwriting quality and automatically gives feedback based on the combination of three extracted models: Beta-Elliptic Model (BEM) using similarity detection (SD) and dissimilarity distance (DD) measure, Fourier<br>Descriptor Model (FDM), and perceptive Convolutional Neural Network (CNN) with Support Vector Machine (SVM) comparison engine. The originality of our work lies partly in the system architecture which apprehends complementary dynamic, geometric, and visual representation of the examined handwritten scripts and in the efficient selected features<br>adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbol drawing. The application offers two interactive interfaces respectively dedicated to learners, educators, experts or teachers and allows them to adapt it easily to the specificity of their disciples. The evaluation of our framework is enhanced by a database collected in Tunisia primary school with 400 children. Experimental results show the efficiency and robustness of our suggested framework that helps teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.<br>


2021 ◽  
Author(s):  
Yahia Hamdi ◽  
Hanen Akouaydi ◽  
Houcine Boubaker ◽  
Adel Alimi

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, gives real-time on-line feedback for children’s writing, and helps teachers comprehend and evaluate children’s writing skills. The proposed method adjudges five main criteria: shape, direction, stroke order, position respect to the reference lines, and kinematics of the trace. It analyzes the handwriting quality and automatically gives feedback based on the combination of three extracted models: Beta-Elliptic Model (BEM) using similarity detection (SD) and dissimilarity distance (DD) measure, Fourier<br>Descriptor Model (FDM), and perceptive Convolutional Neural Network (CNN) with Support Vector Machine (SVM) comparison engine. The originality of our work lies partly in the system architecture which apprehends complementary dynamic, geometric, and visual representation of the examined handwritten scripts and in the efficient selected features<br>adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbol drawing. The application offers two interactive interfaces respectively dedicated to learners, educators, experts or teachers and allows them to adapt it easily to the specificity of their disciples. The evaluation of our framework is enhanced by a database collected in Tunisia primary school with 400 children. Experimental results show the efficiency and robustness of our suggested framework that helps teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.<br>


2020 ◽  
Author(s):  
Yahia Hamdi ◽  
Hanen Akouaydi ◽  
Houcine Boubaker ◽  
Adel Alimi

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, gives real-time on-line feedback for children’s writing, and helps teachers comprehend and evaluate children’s writing skills. The proposed method adjudges five main criteria: shape, direction, stroke order, position respect to the reference lines, and kinematics of the trace. It analyzes the handwriting quality and automatically gives feedback based on the combination of three extracted models: Beta-Elliptic Model (BEM) using similarity detection (SD) and dissimilarity distance (DD) measure, Fourier<br>Descriptor Model (FDM), and perceptive Convolutional Neural Network (CNN) with Support Vector Machine (SVM) comparison engine. The originality of our work lies partly in the system architecture which apprehends complementary dynamic, geometric, and visual representation of the examined handwritten scripts and in the efficient selected features<br>adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbol drawing. The application offers two interactive interfaces respectively dedicated to learners, educators, experts or teachers and allows them to adapt it easily to the specificity of their disciples. The evaluation of our framework is enhanced by a database collected in Tunisia primary school with 400 children. Experimental results show the efficiency and robustness of our suggested framework that helps teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.<br>


2021 ◽  
Author(s):  
Hanen Akouaydi ◽  
Yahia Hamdi ◽  
Houcine Boubaker ◽  
Mourad Zaied ◽  
Faouzi Alaya Cheikh ◽  
...  

<div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The main aim of this notebook is to aid kids learn how to write correctly. We analyze handwriting according to major criteria like shape, kinematics of the trace, position respect to the reference lines,</div><div>stroke order and direction.</div>


2021 ◽  
Author(s):  
Hanen Akouaydi ◽  
Yahia Hamdi ◽  
Houcine Boubaker ◽  
Mourad Zaied ◽  
Faouzi Alaya Cheikh ◽  
...  

<div>An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The main aim of this notebook is to aid kids learn how to write correctly. We analyze handwriting according to major criteria like shape, kinematics of the trace, position respect to the reference lines,</div><div>stroke order and direction.</div>


2021 ◽  
Vol 26 ◽  
pp. 162-167
Author(s):  
Lisa Darragh

Internet access and the availability of digital devices in the classroom have grown exponentially. Correspondingly, we have online platforms for learning mathematics that are subscription-based and available for schools or individuals to purchase. Research in mathematics education tends to focus on the benefits to teaching and learning afforded by digital technology, while less attention is given to the implications of having commercial applications in our mathematics classrooms, and their considerable cost. This paper reports on a study of online mathematics instructional programmes in primary schools of New Zealand. Data sources include a survey sent to mathematics leaders of all primary schools, and a discursive analysis of the websites of the most commonly used instructional programmes. There was an obvious similarity found between the promises of the websites and the rationales expressed by school leaders for using the programmes, suggesting that schools are succumbing to the seductive promises of these commercial programmes. It is argued that we need to further examine the implications of using such programmes in our mathematics classrooms, especially in the context of profit-making inside public education.


Author(s):  
Rowaydah Faiq Hammad Al-Dmour

The study aimed at uncovering the physical and administrative obstacles faced by female teachers in their use of e-learning in the basic and secondary education stages in the governorate of Karak. In order to achieve the objectives of the study, the researcher used the descriptive method. The study tool consisted of a questionnaire that was distributed to a sample of 150 teachers representing 25% of the study population. Using the statistical program (spss) (3.96). At the level of the two axes, the axis of administrative obstacles obtained an average of 4.12 and the physical obstacles at an average of 3.79 and all of them were high. The results showed that there were no statistically significant differences between the basic school , And secondary school in physical constraints, while there are differences of statistical significance Primary schools, secondary schools in administrative and macro-level constraints, and for basic schools. In the light of the results, a number of recommendations and proposals were presented to overcome the obstacles facing the use of e-learning in Karak and all the Kingdom.


2019 ◽  
Vol 19 (61) ◽  
Author(s):  
Montse Castro Rodríguez ◽  
Diana Marín Suelves ◽  
Héctor Sáiz

La formación de la ciudadanía en competencia digital interesa a administraciones nacionales y supranacionales. En los últimos años se han invertido ingentes cantidades económicas en la dotación de infraestructura y en I+D+I para el desarrollo tecnológico en distintos sectores de la sociedad. La integración de dispositivos digitales en la sociedad ha impacto en las políticas educativas de muchos países, llevándolos a considerar la competencia digital como aspecto clave en la enseñanza obligatoria y esencial para la inclusión social. En este artículo, se presentan los resultados de una investigación realizada en cuatro centros de Educación Primaria de Valencia y Galicia, reconocidos por su trayectoria innovadora en el uso de las TIC. El objetivo es identificar y analizar las visiones que la comunidad educativa de cada escuela tiene sobre la competencia digital que está adquiriendo el alumnado participante en prácticas educativas mediadas por TIC. Para la recogida de información se empleó metodología cualitativa, específicamente entrevistas a profesorado, familias y alumnado. Los resultados reflejan modelos diferentes de trabajo y conceptualización de la competencia digital. Todos ellos reconocen su relevancia para la inclusión en la sociedad del futuro y desmitifican su rol hegemónico en el aprendizaje escolar.   The training of citizens in digital competence is of interest to national and supranational administration. In recent years enormous amounts of money have been put into the provision of facilities and I+D+I for technological development in different sectors of society. The integration of digital devices in the industry, communication and society has had a profound impact on educational policies in many countries, making them consider the digital competence as a key in the compulsory education and essential to the social inclusion. This article shows the results of a research conducted in four primary schools from Valencia and Galicia that are recognized because of their innovative trajectory in the use of ICTs. The aim is to identify and analyse the visions of the education community members from each school about the digital competence which is being acquired by the students involved in educational practices mediated by ICTs. To collect the information, it was used a qualitative method based on interviews with teachers, families and students. The results reflect different work models and concepts about the digital competence. It is recognized that the ICTs are relevant to the inclusion in the society of tomorrow and it has been demystified their hegemonic role on school learning.


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