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A Learning Progression for Constructing and Interpreting Data Display. Research Report. ETS RR-20-03
Kim, Eun Mi; Oláh, Leslie Nabors; Peters, Stephanie – ETS Research Report Series, 2020
K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…
Descriptors: Mathematics Education, Statistics Education, Teaching Methods, Data Analysis
Graf, Edith Aurora; Peters, Stephanie; Fife, James H.; van Rijn, Peter W.; Arieli-Attali, Meirav; Marquez, Elizabeth – ETS Research Report Series, 2019
Learning progressions (LPs) describe the development of domain-specific knowledge, skills, and understanding. Each level of an LP characterizes a phase of student thinking en route to a target performance. The rationale behind LP development is to provide road maps that can be used to guide student thinking from one level to the next. The validity…
Descriptors: Mathematical Concepts, Learning Processes, Sequential Approach, Student Development
Fife, James H.; James, Kofi; Peters, Stephanie – ETS Research Report Series, 2020
The concept of variability is central to statistics. In this research report, we review mathematics education research on variability and, based on that review and on feedback from an expert panel, propose a learning progression (LP) for variability. The structure of the proposed LP consists of 5 levels of sophistication in understanding…
Descriptors: Mathematics Education, Statistics Education, Feedback (Response), Research Reports
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection