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About my educational background, I must say that I am an MBA student with a lot of exposure and experience in management fields such as Marketing, Human Resource Management, and so on. To fulfill my passion for teaching, I am now moving to academics. The reason for such a move is my affection and love of interacting with the children. There is no doubt that demand for early childhood education educators is advocated by a constant emphasis on early childhood outcomes (Haslip and Gullo 2018). The demand for preschool professionals who manage early learners is predicted to remain robust (Lipscomb et al. 2021). I, being an MBA graduate, would like to assist the kids in learning organizational competencies that will help them become disciplined individuals. Also, I will advocate a kid's individual, academic, and social achievement during a vital phase of brain development. With my acquired skills and knowledge, I would like to support preschool kids in developmental areas such as mathematical thinking; physical development; social studies, emotional development, arts, scientific thinking, and so on. This will certify they are ready and prepared for forthcoming academic experiences. Last but not least, I want to enable relation-building activities that assist kids in bridging social gaps to make new connections and develop social abilities. As per Olaniyi (2020), the threshold concept is deemed as demonstrating vital phases of learning, the acquisition of which facilitates the students or learners to change from one level of success to another. It indicates essential concepts in a subject wherein comprehending such concepts is vital to converting the manner learners understand an entire subject, enabling them to move on in their learning. I decided to choose data handling as my threshold concept or subject to be taught in school which comes from mathematics or statistics. I chose this subject since data handling is deemed the base for all subjects and entire fields revolve around data. It is a crucial topic in the mathematics preschool curriculum since it brings forth the real-world of observing data to kids. This threshold concept will be transformative for the students with its fundamental areas such as tally marks, graphs, and so on. The preschool students will be capable of comprehending and applying the know-how of average, comprehending the vocab associated with data organization in graphs, and organizing and interpreting the data from charts and tables. Henceforth, it became essential for me to certify that students comprehend the concept of data handling during early childhood (Abdullah et al., 2020).

“Data is defined as the gathering of facts and figures which can be in any form numerical or non-numerical”. It is the information collected by us about the world. It is said that to make such information helpful, individuals are required to be capable of categorizing, sorting, organizing, demonstrating, and interpreting it (Ben-Zvi 2020). It can be said that kids are required to start at an early age to become data-proficient, whether functioning with smaller datasets or large ones, conventional data, or non-conventional data like images (Martinez and LaLonde 2020. Teaching data to early learners enables them to be capable of recognizing variations. The instances might entail activities that change as per who participates and what is completed; objects that change by color, weight, appeal, and so on. Further, the use of data enables them to categorize information about colors, functions, forms, tastes, shapes, and more. They will further be capable of sorting the information like animals segmented into wild and domestic by making a list of each (Meng et al. 2023).

“Data handling is defined as gathering and recording of a set of information and showing it in a form which is meaningful to others”. Besides, it indicates the procedure to gather, record, and present information in a manner that is useful to assess, make forecasts, and choices. It is typically demonstrated in the form of bar charts, pie charts, line graphs, and more (Osakunor et al. 2020). It is noteworthy that data handling in statistics has formed an important part of the mathematics curriculum in primary or elementary schools. It is stated that the data handling knowledge of early learners can help them master the usage of data from numerous contexts to make informed judgments. Data handling has been playing a crucial role in mathematics education as it entails real-world situations and helps in establishing critical thinking competencies in early learners (Naidoo and Mkhabela 2017). It is considered an element of mathematics and statistics that utilizes mathematical techniques to gather, organize, demonstrate, and understand quantitative data to resolve real-time issues (Chevallard and Bosch 2020).
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According to the EYP (Early Years Programme), early learners are considered intelligent, resourceful, and innovative people who develop, grow, and learn at diverse levels. It is found that these young learners explore their settings and learn about their world via play and relations with peers, educators, family, and community members (Bores-García et al. 2023). According to the IGCSE curriculum, early learners are curious individuals who are hoping to explore newer ideas and endure through stages when they become more proactive in their learning and require more direction from educators. In the IGCSE curriculum for early years, math is integrated into it for early learners. It states that at an early age, it is vital to assist kids in identifying how math influences routine life (Motsa et al. 2022). This curriculum introduces kids to the mathematical language, concepts, and thinking via activities and games that they might require when they initiate their primary education (Pritchard 2020). For the primary curriculum, primary math is integrated into the curriculum which inspires long-life enthusiasm for analytical and practical thinking. Three major areas will be covered namely number; geometry, and measure; and statistics and probability (Cambridge Assessment International Education 2023).

For early learners, the data handling concepts to be taught as per the IGCSE curriculum entail chapters such as data and graphs; measurement; patterns; probability; sorting, ordering, and classifying. The teaching of data handling to early learners facilitates them to develop competencies to collate, organize, show, interpret, assess, and report data by posing questions for examination; and gathering and critically assessing data to understand reports and make forecasts about conditions. Moreover, the learning of probability concepts by early learners will assist them in developing competencies to make informed forecasts and define randomness and uncertainties (Adu and Gosa 2014).

It is found that elementary children have restrictions in thinking about abstract things. Concerning international curriculum, early learners have four levels of cognitive thinking abilities namely applying, assessing, evaluating, and creating (Oljayevna and Shavkatovna 2020). A scholar, SOHa et al. (2019) asserted that on the applying level, early learners are required to utilize learned resources in newer and concrete conditions. This entails implementing regulations, techniques, concepts, theories, and more. Subsequently, the assessing level focuses on the procedure of examining and dividing information into numerous parts by recognizing the causes to form a corporate structure that can be simply understood. At the evaluating level, the kids are required to defend and demonstrate notions by making judgments about information, and the validity of notions. At the creating level, the kids need to compile information from diverse components by providing alternative solutions. The main focus is provided on the formation of structures, developing stresses on an individual's innovation actions. Therefore, it is said that the cognitive development of early learners can influence the development of critical thinking abilities and comprehension of mathematical concepts (Oktaviani et al. 2023).

For kids to be capable of understanding vital statistics concepts better and to start to develop statistical thinking skills, initial development of the competencies of investigating and learning from the data is fruitful for Kindergarten kids (Campos 2019). It has been found by DEMIR and DEMIR (2022) that data handling education during elementary education is vital to enable a child’s future academic achievement to demonstrate their innovative, critical, and analytical abilities in school. It is argued further by Lin and Powell (2022) that one of the vital determinants of the success of children is early statistics and data handling abilities and mathematical literacy. Attaining such competencies at an initial age can surge the level of school achievement and improve career prospects in adulthood.

Primary learners are chosen by me since they are the ones who demonstrate a natural interest in and rejoicement in mathematics. Furthermore, long before entering school, these learners spontaneously investigate and utilize mathematics. In their routine play activities, they usually explore mathematical notions and procedures. For instance, they sort and categorize, compare quantities, and observe shapes and patterns. Since primary learners' experiences essentially form their outlook on mathematics, I want to provide them with an engaging and inspiring climate for their early encounters with mathematics (Cesarone 2008). To teach young kids about data handling, I would like to choose a few topics in this area namely sorting, grouping, classifying, data analysis, and more. Sorting is defined as the procedure to arrange a collection of data components in a definite order, typically in descending or ascending order based on a definite characteristic of the data components”. It further indicates the computational procedure to rearrange a provided set of items from a certain total order into descending or ascending order. This concept typically entails data encompassing records in one or various files. This practice aims to rearrange the records so the keys are arranged in numerical order (Nielsen et al. 2019). Sorting is deemed a vital cognitive ability in elementary school. This practice can establish reasoning and thinking competencies in early learners, even when they might not be capable of verbalizing why they put some objects together. An early learner who develops robust sorting skills might be able to make matches; recognize sets; identify and create patterns; compare sets for variances and likelinesses; comprehend how rules apply to sets; and categorize items by multiple attributes (Boone and Demanet 2020).

“Classification concept is defined as the practice of categorizing and organizing data for superior assessment and decision-making” (Allen and Cervo 2015). “Grouping of data is defined as the procedure of organizing data into related sets”. can be performed using a bar graph or pictograph. In this method, data is formulated by arranging individual observations of a variable into sets so a frequency distribution table of such sets offers a convenient manner to summarize or analyze the data. “Data analysis is defined as the practice of gathering information quantitatively and then organizing it in a certain manner which makes comparisons and generalizations possible”. “Data interpretation is defined as the process of attempting to explain the trends which were discovered from the data analysis” (Leavy 2015).
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In elementary school through grade 5, early learners emphasize particularly on categorical data. They usually classify objects in categories in the 1st grade and organize and demonstrate categorical data in the 2nd grade. It has been found that 3rd stage is deemed vital in the development of categorical data in that kids draw graphs with every picture showing more than an object, and bar charts wherein the height of every bar is multiplied by a scalar factor to know the number of objects in every category ((Leavy 2015).

The method I can utilize to teach data handling to Kindergarten kids is that I can discuss the probability of routine events, utilizing suitable language such as sometimes, always, and so on. Besides, there can be a discussion of the likelihood of events in stories and there can be the use of modeling by educators of language which defines the probability of events. Further, I can prepare kids to participate in simpler probability events such as putting cards with kids’ names in a hat, and forecasting whose name will be drawn. Also, kids can be engaged in playing simpler games with dice and discuss if the games are fair or unfair.

Sorting is deemed a skill that can be taught to elementary students via simple play activities. There can be the use of hands-on learning to make kids learn about sorting activities. It can be said that sorting blocks according to their attributes is deemed an effective means to teach the concept of sorting rather than providing a worksheet with images. The activities that can be used by teachers to make kids learn about sorting include tidying up songs; dollhouse rooms; household objects; blocks; and so on. The kids can be taught to pack items away in sets that make sense like construction toys in an area, crayons in the containers, books on a shelf, and more. Further, there is a sorting button activity for kids wherein they can sort the buttons as per the colors into the diverse cups. For example, the kids will put a couple of the same color buttons (e.g. green) in a cup and other color buttons (e.g. blue) in other cups. This activity will enhance the fine motor skills, problem-solving skills, concentration power, social skills, and cognitive skills of the child (Steinhauer et al. 2015).

Another activity can be the use of animal cards with cut-outs of animals and kids can then be asked to sort them according to groups. Furthermore, dollhouse room activities can be used to teach children about sorting. Besides, children can be asked to sort out the block collection by shape, color, and more. I will teach the kids via the activity of sorting family members. In this activity, I will build an "Our family tree" with relocatable pictures that will lead to sorting the family members. This will enable the kids to learn about how individuals are the same and different. This activity will enable the children to think about how family relations work like who is married to whom, who their kids are, how spouses join the family, and more (Silinskas et al. 2020).

The first challenge in teaching preschool learners can be insufficient instructional resources. This is because the majority of the data-handling lessons taught at preschool levels need some teaching and learning resources to facilitate kids enjoying and completely benefit from the entire learning activity (Cagiltay et al. 2019). However, when such resources are not available, kids learn the concepts in abstracts. Another major challenge found is learning disorders like dysgraphia and dyslexia. Dyslexia is associated with a kid's incompetency to read accurately and dysgraphia reflects in the kid's capability to write suitably. Henceforth, the teachers who teach preschoolers reading, writing, and other major skills confront a significant challenge due to this (Hadhrami et al. 2022).

Regarding lesson design for young learners, I prefer collaborative and personalized learning practices. It is noteworthy that the vocabulary of math such as denominator, greater than, and more, and symbols such as =, and others should be comprehended to work issues since there are no contextual clues to help understanding. Therefore, collaborative learning activities are suitable while designing lessons since in those activities, symbolic and vocabulary understanding might be stimulated with peer modeling and cooperation. The activities which can be used here entail round the table and numbered heads. In round the table activity, kids can work on issues collectively bypassing the issues around the table for every reaction of members. Further, in the numbered head activity, kids discuss the answer to a question after every team member numbers off. Afterwards, the educator can call a specific number and group to respond to the questions (Reinhardt and Elwood 2019).

Concerning prospects, STEM learning is deemed an effective concept for learning data handling in elementary schools. The STEM (science, technology, engineering, and mathematics) education seems to be a strategy that refines preschool learners' know-how and experience and inclines them to resolve issues by making integrative associations for conditions they face in their routine lives and improves their innovativeness (Kastriti et al. 2022). It has been found by Barenthien et al. (2020). that it is essential and fruitful to apply an imaginative teaching approach such as STEM to acquire the essential competencies at the elementary level in school. Another scholar found that preplanned practices in mathematics education assist kids in acquiring essential abilities like observation, asking questions, experimenting, grouping, problem-solving, and communicating. Particular abilities like scientific perception, producing hypotheses, assessing data, and interpreting data can be attained at a very young age, and early learners can demonstrate an interest in statistical data and even understand such data for their hypotheses. Besides, it is vital to note that kids' inquiry and reasoning abilities must be cultivated by STEM practices in the early years so the existing know-how of statistics and data handling becomes more precise and preschoolers are introduced to such a culture. Nevertheless, at the point of an effective adoption of STEM education in elementary school, it is vital to consider designing developmentally suitable activities (Türk and Akcanca 2021).

The way to integrate STEM learning in data handling is via the use of IBL (inquiry-based learning) which includes asking kids open-ended questions that inspire them to investigate, experiment, and discover. Moreover, this will assist them in developing their scientific learning, data-handling reasoning, and technical fluency. The kids of elementary school can ask and respond to questions about the patterns of data, effects of variables, and more (Deák et al. 2021).

The above analysis of the essay concludes that mathematics and statistics are deemed a vital part of each kid's daily life, it assists them to comprehend the world around them. It is further inferred that early learners' mathematical capability foresees forthcoming mathematical attainment and such abilities generalize to other subjects in the preschool that need math applications.

It is also concluded that an ideal means for preschool kids to integrate data handling education explicitly with a minimum of one of the STEM learning so that knowledge can become associated, emphasized, meaningful, and pertinent to kids. It has offered manners to place data handling learning in meaningful settings and endorse the usage of hands-on practices associated with real-time issues. Therefore, it can be said that STEM learning can increase kids' interest in learning and has a vital realistic value in refining kids' all-inclusive capability in data handling (He et al. 2021).


Abdullah, A.H., Mun, S.H., Mokhtar, M., Ashari, Z.M., Jumaat, N.F., Ali, D.F., Samah, N.A. and Abdurrahman, M.S., 2020. Using active learning with smart board to enhance primary school students' higher-order thinking skills in data handling. Universal Journal of Educational Research, 8(10), pp.4421-4432.

Adu, E.O. and Gosa, L.J., 2014. The teaching and learning of data-handling in primary schools: South African Experience. Mediterranean Journal of Social Sciences, 5(23), p.814.

Allen, M. and Cervo, D., 2015. Data quality management. In Multi-Domain Master Data Management (pp. 131-160). Elsevier.

Barenthien, J., Oppermann, E., Anders, Y. and Steffensky, M., 2020. Preschool teachers’ learning opportunities in their initial teacher education and in-service professional development–do they have an influence on preschool teachers’ science-specific professional knowledge and motivation?. International Journal of Science Education, 42(5), pp.744-763.

Ben-Zvi, D., 2020. Data handling and statistics teaching and learning. In Encyclopedia of mathematics education (pp. 177-181). Cham: Springer International Publishing.

Boone, S. and Demanet, J., 2020. Track choice, school engagement and feelings of perceived control at the transition from primary to secondary school. British Educational Research Journal, 46(5), pp.929-948.

Bores-García, D., González-Calvo, G., Barba-Martín, R.A., García-Monge, A. and Hortigüela-Alcalá, D., 2023. International Baccalaureate Primary Years Programme: a systematic review. Journal of Research in International Education, 22(2), pp.149-163.

Cagiltay, K., Cakir, H., Karasu, N., Islim, O.F. and Cicek, F., 2019. Use of educational technology in special education: Perceptions of teachers. Participatory Educational Research, 6(2), pp.189-205.

Cambridge Assessment International Education 2023. Cambridge primary mathematics (0096). [Online] Available at Accessed on 26 September 2023

Campos, P., 2019. Data Literacy is no longer optional. Newsletter of the International Statistical Literacy Project, 1, p.11.

Cesarone, B., 2008. Early childhood mathematics: Promoting good beginnings. Childhood Education, 84(3), p.189.

Chevallard, Y. and Bosch, M., 2020. Didactic transposition in mathematics education. Encyclopedia of mathematics education, pp.214-218.

Deák, C., Kumar, B., Szabó, I., Nagy, G. and Szentesi, S., 2021. Evolution of new approaches in pedagogy and STEM with inquiry-based learning and post-pandemic scenarios. Education Sciences, 11(7), p.319.

DEMIR, M. and DEMIR, M., 2022. Mathematics in Early Childhood Education: Awareness, Perspectives, Knowledge. [Online] Available at Accessed on 22 September 2023

Hadhrami, A.S.A.L., Al-Amrat, M.R., Khasawneh, M.A.S. and Darawsheh, S.R., 2022. Approach to Improve Reading Skill of Students with Dyslexia. Information Sciences Letters, 11(6), pp.2333-2338.

Haslip, M.J. and Gullo, D.F., 2018. The changing landscape of early childhood education: Implications for policy and practice. Early Childhood Education Journal, 46, pp.249-264.

He, X., Li, T., Turel, O., Kuang, Y., Zhao, H. and He, Q., 2021. The impact of STEM education on mathematical development in children aged 5-6 years. International Journal of Educational Research, 109, p.101795.

Kastriti, E., Kalogiannakis, M., Psycharis, S. and Vavougios, D., 2022. The teaching of Natural Sciences in kindergarten based on the principles of STEM and STEAM approach. Advances in Mobile Learning Educational Research, 2(1), pp.268-277.

Leavy, A., 2015. Looking at practice: revealing the knowledge demands of teaching data handling in the primary classroom. Mathematics education research journal, 27, pp.283-309.

Lin, X. and Powell, S.R., 2022. The roles of initial mathematics, reading, and cognitive skills in subsequent mathematics performance: A meta-analytic structural equation modeling approach. Review of Educational Research, 92(2), pp.288-325.

Lipscomb, S.T., Chandler, K.D., Abshire, C., Jaramillo, J. and Kothari, B., 2021. Early childhood teachers’ self-efficacy and professional support predict work engagement. Early childhood education journal, pp.1-11.

Martinez, W. and LaLonde, D., 2020. Data science for everyone starts in kindergarten: Strategies and initiatives from the American Statistical Association. Harvard Data Science Review, 2(3).

Meng, X., Chen, N., Ishida, J., Watanabe, K. and Murakami, T., 2023. Crossmodal correspondences between visual features and tastes in preschoolers: an exploratory study. Frontiers in Psychology, 14.

Motsa, L., Bhebhe, S. and Nxumalo, Z., 2022. Instructional Strategies Used In Teaching Siswati Language In The Kingdom Of Eswatini Primary Schools. Journal homepage: www. ijrpr. com ISSN, 2582, p.7421.

Naidoo, J. and Mkhabela, N., 2017. Teaching data handling in foundation phase: Teachers’ experiences. Research in Education, 97(1), pp.95-111.

Nielsen, H., Tsirigos, K.D., Brunak, S. and von Heijne, G., 2019. A brief history of protein sorting prediction. The protein journal, 38, pp.200-216.

Oktaviani, M., Dwihapsari, K., Islami, M.N., Dewi, N.P., Fadhilah, R.N. and Palupi, Z.D., 2023. Cognitive Development of Elementary School Children in Developing Critical Thinking Ability and Understanding Mathematical Concepts. International Education Trend Issues, 1(3), pp.134-142.

Olaniyi, N.E., 2020. Threshold concepts: designing a format for the flipped classroom as an active learning technique for crossing the threshold. Research and Practice in Technology Enhanced Learning, 15(1), p.2.

Oljayevna, O. and Shavkatovna, S., 2020. The Development of Logical Thinking of Primary School Students in Mathematics. European Journal of Research and Reflection in Educational Sciences, 8(2), pp.235-239.

Osakunor, D.N., Munk, P., Mduluza, T., Petersen, T.N., Brinch, C., Ivens, A., Chimponda, T., Amanfo, S.A., Murray, J., Woolhouse, M.E. and Aarestrup, F.M., 2020. The gut microbiome but not the resistome is associated with urogenital schistosomiasis in preschool-aged children. Communications Biology, 3(1), p.155.

Pritchard, M., 2020. Empowering learning: The importance of being experiential. John Catt Educational.

Reinhardt, K.S. and Elwood, S., 2019. Promising practices in online training and support: Microlearning and personal learning environments to promote a growth mindset in learners. In Handbook of research on virtual training and mentoring of online instructors (pp. 298-310). IGI Global.

Silinskas, G., Sénéchal, M., Torppa, M. and Lerkkanen, M.K., 2020. Home literacy activities and children’s reading skills, independent reading, and interest in literacy activities from kindergarten to grade 2. Frontiers in Psychology, 11, p.1508.

SOHa, H.M., Abdullahb, A.H. and Mokhtarc, M., 2019. Enhancing Primary School Students' Higher Order Thinking Skills in Data Handling through Active Learning with Smart Board. Proceedings of the 27th International Conference on Computers in Education. Taiwan: Asia-Pacific Society for Computers in Education, 2, pp. 51-57.

Steinhauer, H.W., Aßmann, C., Zinn, S., Goßmann, S. and Rässler, S., 2015. Sampling and weighting cohort samples in institutional contexts: The National Educational Panel Study cohort samples of kindergarten children, students in grade 5 and in grade 9. AStA Wirtschafts-und Sozialstatistisches Archiv, 9, pp.131-157.

Türk, A. and Akcanca, N., 2021. Implementation of STEM in Preschool Education. Journal of Educational Leadership and Policy Studies.

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