Periodic Reporting for period 1 - EARLYMATH (Pathways to math difficulties -A longitudinal study from birth to school-age)
Reporting period: 2021-09-01 to 2023-02-28
The EarlyMath project (2021-2026) studies children’s early development of mathematical skills, motivation and emotions in interaction with learning environments. We want to understand better why the learning of basic mathematical skills is challenging for ten to twenty percent of children. This knowledge is needed for developing the means of early identification of children who need more support to learn the essential mathematical skills today, as well as for developing more efficient forms of support for childcare clinics, for early childhood education and care (ECEC), and for parents.
EarlyMath seeks answers to the following questions:
-What mathematical capacities and skills do small children have?
-What kind of developmental paths can be identified in children’s mathematical skills as well as in the related motivation and emotions?
-Why is learning mathematical skills more difficult for some than it is for others?
-How is mathematics present at home, in early childhood education and care, and at school?
-To what degree do parents’ skills predict their children’s skills?
EarlyMath seeks answers to the following questions:
-What mathematical capacities and skills do small children have?
-What kind of developmental paths can be identified in children’s mathematical skills as well as in the related motivation and emotions?
-Why is learning mathematical skills more difficult for some than it is for others?
-How is mathematics present at home, in early childhood education and care, and at school?
-To what degree do parents’ skills predict their children’s skills?
Summary of activities
EARLYMATH work began by writing of the ethical documents for the JYU Human Sciences Ethics Committee. Positive statement (#1518/13.00.04.00/2021) was received on November 29th 2021. During 2021, along with writing the ethical documents, we further refined the research design, as well as participant recruitment and measurement plans. Two of the post docs and a project researcher were recruited in 2021.
During the Spring of 2022 we started data collection in schools and prepared for the upcoming Toddler and Baby data collections. The School data collection went as planned. School sample is the pilot sample for the younger samples and these assessments were very informative for the finalizing of the data collection tools in the Toddler and Baby samples during 2022. During the Fall 2022, we started recruitment and data collection among the Toddler sample and Baby sample. A postdoc and a project researcher were recruited. Researcher assistants have been hired and trained for data collection.
Currently the data collection in all three samples is ongoing as planned.
From the beginning of the project we have started a careful metadata documentation. University of Jyväskylä has an active Open Science Center that supports the publication of the EARLYMATH metadata documentation in the JYU Converis system. We aim to publish the first version spring 2023. This documentation describes all the details of the data collection methodology.
Throughout the 18 months, we have utilized different dissemination opportunities, e.g. Researcher Night 2022. For the recruitment and other communication purposes, we prepared visuals and dissemination platforms (flyers, website, Facebook). We have also disseminated the idea and importance of the project to researchers, third sector actors, maternity clinics, city/town officials deciding on the access to schools and daycare centers, and general public to support the upcoming recruitment of participants. First papers have been submitted, AB meetings and internal seminars have been held, and we have participated in conferences (e.g. MCLS 2021). Also the first MA student thesis has been finished and published openly.
EARLYMATH work began by writing of the ethical documents for the JYU Human Sciences Ethics Committee. Positive statement (#1518/13.00.04.00/2021) was received on November 29th 2021. During 2021, along with writing the ethical documents, we further refined the research design, as well as participant recruitment and measurement plans. Two of the post docs and a project researcher were recruited in 2021.
During the Spring of 2022 we started data collection in schools and prepared for the upcoming Toddler and Baby data collections. The School data collection went as planned. School sample is the pilot sample for the younger samples and these assessments were very informative for the finalizing of the data collection tools in the Toddler and Baby samples during 2022. During the Fall 2022, we started recruitment and data collection among the Toddler sample and Baby sample. A postdoc and a project researcher were recruited. Researcher assistants have been hired and trained for data collection.
Currently the data collection in all three samples is ongoing as planned.
From the beginning of the project we have started a careful metadata documentation. University of Jyväskylä has an active Open Science Center that supports the publication of the EARLYMATH metadata documentation in the JYU Converis system. We aim to publish the first version spring 2023. This documentation describes all the details of the data collection methodology.
Throughout the 18 months, we have utilized different dissemination opportunities, e.g. Researcher Night 2022. For the recruitment and other communication purposes, we prepared visuals and dissemination platforms (flyers, website, Facebook). We have also disseminated the idea and importance of the project to researchers, third sector actors, maternity clinics, city/town officials deciding on the access to schools and daycare centers, and general public to support the upcoming recruitment of participants. First papers have been submitted, AB meetings and internal seminars have been held, and we have participated in conferences (e.g. MCLS 2021). Also the first MA student thesis has been finished and published openly.
The project aims to gather three unique datasets regarding the early years of child development in numerical cognition. The datasets will allow us to provide novel information on the research questions. With these information we aim to develop new methods for early identification and support for those in need and in this way improve mathematical skills and motivation development from early years onward.