Statistik og almendannelse : statistisk ræsonneren gennem datamodellering som almendannende erfaringer i indskolingen

Publikation: Kandidat/diplom/masterKandidatspecialeForskning


Resumé/abstract: The aim of this master thesis is to provide new perspectives on the integration of concepts concern-ing statistical reasoning through data modeling with primary school students and concepts of Allge-meinbildung. The thesis and therefore the research question is subdivided into two parts. The first part is guided by the question, which potentials does data modeling in primary education according to research literature contain for developing student’s statistical reasoning and contribute to Allgemeinbild-ung? This part is a theoretical exploration of the potentials in primary education for students to de-velop their statistical reasoning through experiences with data modeling and how these experiences can be characterized with concepts of Allgemeinbildung. Research point to the possibilities for young children to develop their statistical reasoning in a co-herent and holistic way through data modeling (Doerr, delMas & Makar, 2017; English, 2010). If young children get the opportunity to make informal statistical inferences and informal statistical reasoning, it supports later conceptual understanding, but it also lays down the foundation for stu-dents to acknowledge the utility of data for making meaning of their own world (Makar, 2016; Makar & Rubin, 2009). The aim of Allgemeinbildung is to educate citizens for participation in a democratic society. This aim requires students’ self-development and the development of autonomy (Niss, 2000; Winter, 1995). In that light mathematics instruction should provide students with the opportunity to create key experiences according to Winter (1995). I’ve chosen to focus on the key experience where mathematics provides students with the opportunity to perceive and understand phenomena in the world around them (Winter, 1995). Mathematical modeling is a way to gain such experiences, but it is crucial to experience how the process works (Biehler, 2019). I discuss how the development of mathematical modeling competency combined with overview and judgment regarding applications of mathematics in other subject or practice areas (Niss & Jensen, 2002), can contribute to the devel-opment of Allgemeinbildung. Because data modeling with young children contain the opportunity to explore phenomena in their own world through informal statistical reasoning and inference, and because of the opportunity to 2 develop personal meaning from data in a holistic and coherent way, I characterize in a theoretical perspective young students’ statistical reasoning through data modeling as contributions to their Allgemeinbildung. The second part of this thesis is an empirical study of how the above-mentioned potentials can be put into practice and answer the research question how, to which extend and under which circum-stances can these potentials be put into practice in a Danish 3. grade (9-10 years old). To answer this question, I design and implement a lesson plan for 4 sessions, which frames the students’ par-ticipation in a whole data modeling process, where they pose questions from a meaningful context, identify attributes, design their own investigation, collect data, structure, visualize and represent data, analyze and interpret data and draw conclusions. A key process in the design is to move from an extra-mathematical domain to a mathematical domain, and letting the students struggle with this demanding process. In my analysis, I bring out three groups to explore their processes with the pur-pose to characterize their informal statistical reasoning and to trace these experiences as contributions to their Allgemeinbildung. [...].
StatusUdgivet - 2019


  • DPLI