Early childhood education plays a key role in the development, health, and well-being of a child.

Magrid comes with a wide range of training tasks (>2500) targeting different aspects of mathematical abilities.

Training activities are focused on the major building blocks of early mathematical development and can be categorised into two main classes: visual-spatial and numerical tasks.
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Early childhood education plays a key role in the development, health, and well-being of a child.

MaGrid comes with a wide range of training tasks (>2500) targeting different aspects of mathematical abilities.

Training activities are focused on the major building blocks of early mathematical development and can be categorized into two main classes: visual-spatial and numerical tasks.
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Visual-spatial tasks

Training activities in this category are focused on different tasks of visual perception and visuo-motor integration. These types of tasks require visual processing of information, a motor output, and the coordination between the two. Figure completion and drawing a copy are examples of visual spatial tasks that can improve children’s visual-perceptual abilities and fine motor skills.

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Numerical tasks

The number-specific tasks target different aspects of basic math competencies. The theoretical framework for designing and developing these tasks has been set by the four-step developmental model of numerical cognition (Von Aster & Shalev, 2007). In this developmental model,  four different forms of number knowledge are distinguished: quantitative knowledge, verbal number knowledge, Arabic number knowledge, and sequential knowledge. The numerical tasks in Magrid focus on these four components and the mapping between different representations of numbers (mapping between the first three steps in a developmental model).

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Visual-spatial tasks

Training activities in this category are focused on different tasks of visual perception and visuo-motor integration. These types of tasks require visual processing of information, a motor output, and the coordination between the two. Figure completion and drawing a copy are examples of visual spatial tasks that can improve children’s visual-perceptual abilities and fine motor skills.

https://magrid.lu/wp-content/uploads/2020/10/illustration-01.png

Numerical tasks

The number-specific tasks target different aspects of basic math competencies. The theoretical framework for designing and developing these tasks has been set by the four-step developmental model of numerical cognition (Von Aster & Shalev, 2007). In this developmental model,  four different forms of number knowledge are distinguished: quantitative knowledge, verbal number knowledge, Arabic number knowledge and sequential knowledge. The numerical tasks in Magrid focus on these four components and the mapping between different representations of numbers (mapping between the first three steps in a developmental model).

Empirical Evidence on the Effectiveness of the Magrid Learning Solution

Magrid comes with a wide range of training tasks (>2500) targeting different aspects of mathematical abilities.

Magrid application has been used in several research studies to survey its scientific effectiveness Research studies have been conducted in Luxembourg (Lucet, University of Luxembourg), Germany (IWM, Tuebingen), and France (University of Lille 2) on ~500 preschoolers.

The results of the studies revealed that children who used the application over the training period made significant gains in different aspects of early visual special and numerical abilities:

  • Spatial perception (Cornu, Schiltz, Pazouki, & Martin2019 Cornu, Pazouki, Schiltz, Fischbach, & Martin2018)
  • Visuomotor integration (Cornu, Schiltz, Pazouki, & Martin2019 Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Counting (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Number naming (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Number sequence knowledge (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 

The outcomes of the studies are the empirical evidence, not only for the effectiveness of the training application but also for the feasibility of implementing this application in an authentic school setting. 

The interested reader may refer to the published research papers for a detailed description of the studies’ designs and the results.

Empirical Evidence on the Effectiveness of the Magrid Learning Solution

Magrid comes with a wide range of training tasks (>2500) targeting different aspects of mathematical abilities.

Magrid application has been used in several research studies to survey its scientific effectiveness Research studies have been conducted in Luxembourg (Lucet, University of Luxembourg), Germany (IWM, Tuebingen), and France (University of Lille 2) on ~500 preschoolers.

The results of the studies revealed that children who used the application over the training period made significant gains in different aspects of early visual-spatial and numerical abilities:

  • Spatial perception (Cornu, Schiltz, Pazouki, & Martin2019 Cornu, Pazouki, Schiltz, Fischbach, & Martin2018)
  • Visuomotor integration (Cornu, Schiltz, Pazouki, & Martin2019 Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Counting (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Number naming (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 
  • Number sequence knowledge (Cornu, Pazouki, Schiltz, Fischbach, & Martin2018) 

The outcomes of the studies are the empirical evidence, not only for the effectiveness of the training application but also for the feasibility of implementing this application in an authentic school setting. 

The interested reader may refer to the following published research papers for a detailed description of the studies’ designs and the results.

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Cornu, V., Schiltz, C., Pazouki, T., & Martin, R. (2019). Training early visuo-spatial abilities: A controlled classroom-based intervention study. Applied developmental science, 23(1), 1-21.

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Pazouki, T., Cornu, V., Sonnleitner, P., Schiltz, C., Fischbach, A., & Martin, R. (2018). MaGrid: a language-neutral early mathematical training and learning application. International Journal of Emerging Technologies in Learning (iJET), 13(08), 4-18.

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Cornu, V., Pazouki, T., Schiltz, C., Fischbach, A., & Martin, R. (2018). Overcoming language barriers in early mathematics instruction with “MaGrid”-a language-neutral training tool for multilingual school settings.

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Pazouki, T., Cornu, V., & Martin, R. (2016, June). Visual Spatial Math Training Tool: An iPad Application for Training Visual-Spatial Abilities in Preschoolers. In EdMedia+ Innovate Learning (pp. 1594-1602). Association for the Advancement of Computing in Education (AACE).

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Jung, S., Meinhardt, A., Braeuning, D., Roesch, S., Cornu, V., Pazouki, T., … & Moeller, K. (2020). Hierarchical Development of Early Visual-Spatial Abilities–A Taxonomy Based Assessment Using the MaGrid App. Frontiers in Psychology, 11.

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Cornu, V., Schiltz, C., Pazouki, T., & Martin, R. (2019). Training early visuo-spatial abilities: A controlled classroom-based intervention study. Applied developmental science, 23(1), 1-21.

https://magrid.lu/wp-content/uploads/2020/10/N-1-01-640x360.png

Pazouki, T., Cornu, V., Sonnleitner, P., Schiltz, C., Fischbach, A., & Martin, R. (2018). MaGrid: a language-neutral early mathematical training and learning application. International Journal of Emerging Technologies in Learning (iJET), 13(08), 4-18.

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Cornu, V., Pazouki, T., Schiltz, C., Fischbach, A., & Martin, R. (2018). Overcoming language barriers in early mathematics instruction with “MaGrid”-a language-neutral training tool for multilingual school settings.

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Pazouki, T., Cornu, V., & Martin, R. (2016, June). Visual Spatial Math Training Tool: An iPad Application for Training Visual-Spatial Abilities in Preschoolers. In EdMedia+ Innovate Learning (pp. 1594-1602). Association for the Advancement of Computing in Education (AACE).

https://magrid.lu/wp-content/uploads/2020/10/N-1-04.png

Jung, S., Meinhardt, A., Braeuning, D., Roesch, S., Cornu, V., Pazouki, T., … & Moeller, K. (2020). Hierarchical Development of Early Visual-Spatial Abilities–A Taxonomy Based Assessment Using the MaGrid App. Frontiers in Psychology, 11.

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