At the beginning of the school stage, the children's abilities are transcendental, particularly those related to mathematics because they are the most significant predictor of their future school success (Duncan et al., 2007). In this context, it is essential to know the mathematical contents that can be reliably learned during the early years, especially those that mean success at later stages.

Several authors explore this question. A significant result in this regard is the one published by Sarama & Clements (2009). They synthesize relevant research on what children can learn from birth to primary education, highlighting a broad spectrum of skills and knowledge in mathematics. Their work was a milestone for the Common Core State Standards (CCSS), the prevalent curriculum in the United States, therefore having a vital role in informing practice. Thirteen years later, it looks like there are no updates regarding this matter.

The purpose of this study is to fill this gap, answering which mathematical skills and knowledge, present in kindergarteners or children attending the first year of primary school, are predictors of greater mathematical achievement during their school career.

In Learning Psychology, Constructivism states that every new knowledge needs to fit with the previous one if significative learning is the goal (Bransford et al., 2000). Therefore, it is possible to infer that differences in early mathematical knowledge may explain differences in mathematical achievement and performance during late school years.

Early differences correlate to differences between students from different socioeconomic backgrounds in later years. Furthermore, those early differences appear to increase throughout the formal teaching path (Burchinal et al., 2011; Fryer & Levitt, 2004; Hanushek et al., 2019).

Several empirical academic studies are trying to find which knowledge or mathematical skills, present in children starting school age, are predictors of future mathematical academic performance. However, their results and conclusions have not been contrasted, and therefore nor critically analyzed the current curricula by differentiating the critical contents of those that are mere accessories.

If the skills or knowledge that are meaningful for future mathematical achievement are identifiable, then it's possible to improve results through early systemic interventions, by placing greater emphasis on them within classrooms. Even more, this could inform teachers and policymakers to effectively choose mathematical content on early childhood curricula, embracing the development of logical thinking.

As a consequence, this could significantly help students from low-income families or with learning disabilities by focusing their work more efficiently. This might also help reduce the existing gap between students coming from different socio-cultural realities and those who have different characteristics, improving equity through the mathematical education.

A systematic search was done in the Web of Knowledge database from the words "longitudinal" AND "study" AND "mathematics" AND "Achievement," reaching 851 results. Then, the results were refined using the words "skill*" OR "know*", obtaining 284 results. The documents that met the following criteria were selected: 1. Type of resource: journal article belonging to the main collection of Web of Science. 2. Variables: i. Articles whose design includes as an independent, control, or moderator variable some skill or mathematical knowledge, and ii. Those in which the dependent variable is knowledge, performance, or mathematical learning, which can be considered as a single knowledge or specific skill (arithmetic ability, for example) or as a set that refers to skills or mathematical contents (mathematical achievement, for example, measured as a standardized test score). 3. Type of study: As this work seeks to know skills or mathematical knowledge that predicts greater mathematical performance, they should be longitudinal empirical studies. 4. School stage: Investigations considering an initial measurement with children between five and six years old (K-1 levels). 5. Subjects of study: all articles whose focus was on students with learning difficulties were excluded because the focus of interest of this review is to detect the best mathematical predictors of future mathematical achievement for most of the population. These students are part of the samples that have considered the studies analyzed, but these samples are diverse and include all types of students who attend regular schools. 6. Years considered: only works published from 2000 to 2021. Analysis Plan To answer the question that guides this systematic review, the skills or knowledge predicting more outstanding mathematical outcomes were categorized according to the domains used by Sarama and Clements (2009) because they sought to synthesize relevant research regarding mathematical learning in primary education. These domains are consistent with the knowledge and skills that have been studied in the articles reviewed. Then a metanalysis will be performed on each domain.

The articles reviewed developed empirical research in the United Kingdom, the United States, Germany, Italy, Belgium, Finland, Austria, the Netherlands, Luxembourg, and Hong Kong. According to the PISA results in mathematics, most of these countries are above the average in the OECD, except for Italy, Luxembourg, and the United States (OCDE, 2016). In all of them, the variables that respond to the research question are independent, control, or moderating variables. The dependent variables are, in turn, some measure of knowledge or mathematical achievement. A surprising finding of this review is that no article included anything related to "data analysis", which is part of the category, level I, "Other domains." This review reaffirms the lack of research on this mathematical topic, one of the most used in daily life (when interpreting surveys or graphs). As Sarama and Clements (2009) point out, very little evidence has been gathered about this knowledge, mainly because it is considered that children as young (up to 6 years) would still not be able to understand it. Just the articles whose samples are more numerous and considering different types of control variables are those that -mainly- address the three less studied categories. This is relevant because their results show that knowledge and skills that belong to other domains – different than numbers- are transcendent for obtaining good results during the school experience. The lack of studies on these three categories may lead to a misinterpretation. Perhaps it could be a sign of the complexity to assess other domains within early years, suggesting a possible explanation for the performance gap of students from different backgrounds reflecting difficulties when teaching and assessing these domains.

Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., Feinstein, L., Engel, M., Brooks-Gunn, J., Sexton, H., Duckworth, K., & Japel, C. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428–1446. https://doi.org/10.1037/0012-1649.43.6.1428 OCDE. (2016). PISA 2015 Results (Volume I). OECD Publishing. https://doi.org/10.1787/9789264266490-en Sarama, J. A., & Clements, D. H. (2009). Early childhood mathematics education research: Learning trajectories for young children. In Early Childhood Mathematics Education Research: Learning Trajectories for Young Children. Routledge Taylor & Francis Group. https://doi.org/10.4324/9780203883785