Browsing by Author "Lampen, Erna"
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- ItemCase Study of Prospective Teachers Engaged in Professional Noticing of their Students’ Mathematical Thinking(MDPI, 2022-09-28) Selmer, Sarah; Lindstrom, Denise; Lampen, ErnaAbstract: In this study, prospective teachers engaged in professional noticing of their students’ mathematical thinking captured in pieces of written work. Researchers then worked to characterize the prospective teachers’ professional noticing using a lens of responsive teaching. Results indicate that prospective teacher decisions about how to respond to their students’ mathematical thinking fall on a responsiveness continuum, often shifting in responsiveness across pieces of student written work. The findings of this study provide guidance for teacher educators who work to develop K–12 educators’ responsive teaching practices.
- ItemTeacher narratives in making sense of the statistical mean algorithm(AOSIS Publishing, 2015-06-24) Lampen, ErnaTeaching statistics meaningfully at school level requires that mathematics teachers conduct classroom discussions in ways that give statistical meaning to mathematical concepts and enable learners to develop integrated statistical thinking. Key to statistical discourse are narratives about variation within and between distributions of measurements and comparison of varying measurements to a central anchoring value. Teachers who understand the concepts and tools of statistics in an isolated and processual way cannot teach in such a connected way. Teachers’ discourses about the mean tend to be particularly processual and lead to limited understanding of the statistical mean as measure of centre in order to compare variation within data sets. In this article I report on findings from an analysis of discussions about the statistical mean by a group of teachers. The findings suggest that discourses for instruction in statistics should explicitly differentiate between the everyday ‘average’ and the statistical mean, and explain the meaning of the arithmetic algorithm for the mean. I propose a narrative that logically explains the mean algorithm in order to establish the mean as an origin in a measurement of variation discourse.