Access the full text.
Sign up today, get DeepDyve free for 14 days.
WM Stroup, U Wilensky (2000)
Handbook of methods for research in learning and teaching science and mathematics
A. Bandura (1986)
Social Foundations of Thought and Action
E. Duckworth (1987)
The Having of Wonderful Ideas
(2004)
Cognitive exploration and search behavior in the development of endogenous representations
(1994)
What the development of non-universal understanding looks like: An investigation
(1996)
Embodying a nominalist constructivism: Making graphical sense of learning
(1987)
The objectification of observation : Measurement and statistical methods in the nineteenth century
(1987)
Fechner’s indeterminism: From freedom to laws of chance
Charles Murray (1995)
The Bell Curve: Intelligence and Class Structure in American Life.Social Forces, 74
JD Novak, DB Gowin (1984)
Learning how to learn
(2008)
Exploring the central limit theorem further. http://generative.edb
Ibrahim Halloun, D. Hestenes (1985)
The initial knowledge state of college physics studentsAmerican Journal of Physics, 53
(1999)
NetLogo. http://ccl.northwestern.edu/netlogo. Center for connected learning and computer-based modeling
A. Olding (2008)
Biology and knowledgeTheoria, 49
H. Stuart (1985)
Should concept maps be scored numerically, 7
W. Stroup, U. Wilensky (2000)
Assessing Learning as Emergent Phenomena: Moving Constructivist Statistics Beyond the Bell Curve
G. Posner, K. Strike, P. Hewson, William Gertzog (1982)
Accommodation of a scientific conception: Toward a theory of conceptual changeScience Education, 66
M. Engelmann (2013)
The Philosophical Investigations
Joan Garfield (2002)
The Challenge of Developing Statistical ReasoningJournal of Statistics Education, 10
Ella Jacobs (1898)
Ants.Journal of Education, 48
M. Morgan, L. Krüger, G. Gigerenzer (1987)
The Probabilistic revolution
E. Jablonka (2008)
International group for the psychology of mathematics education
D. Laplane (1992)
Thought and language.Behavioural neurology, 5 1
J. Piaget (1970)
Child's Conception of Movement and Speed
U. Wilensky (1993)
Connected mathematics : builiding concrete relationships with mathematical knowledge
(2003)
Central limit theorem simulation. http://generative.edb.utexas.edu/projects/esmi
J. Bransford (2000)
How people learn
J. Michell (2009)
The psychometricians' fallacy: too clever by half?The British journal of mathematical and statistical psychology, 62 Pt 1
A. Reid, P. Petocz (2002)
Students' Conceptions of Statistics: A Phenomenographic StudyJournal of Statistics Education, 10
William Smith, J. Bruner, J. Goodnow, G. Austin (1956)
A Study of ThinkingAmerican Journal of Psychology, 71
U. Wilensky (1995)
Paradox, programming, and learning probability: A case study in a connected mathematics frameworkThe Journal of Mathematical Behavior, 14
G. Nicoll (2001)
A three-tier system for assessing concept map links: a methodological studyInternational Journal of Science Education, 23
Marilyn Pelosi, T. Sandifer (2003)
Elementary Statistics: From Discovery to Decision
Vinh Pham (2009)
Computer Modeling of the Instructionally Insensitive Nature of the Texas Assessment of Knowledge and Skills (TAKS) Exam.
A. diSessa (2000)
Changing Minds: Computers, Learning, and Literacy
A. diSessa (1993)
Toward an Epistemology of PhysicsCognition and Instruction, 10
(2009)
What Bernie Madoff can teach us about accountability in education
This paper summarizes an approach to helping future educators to engage with key issues related to the application of measurement-related statistics to learning and teaching, especially in the contexts of science, mathematics, technology and engineering (STEM) education. The approach we outline has two major elements. First, students are asked to compute an “average square.” Second, students work with an agent-based simulation that helps them to understand how aspects of the central limit theorem might be integrated into a much larger conversation about the appropriateness, or validity, of current psychometric practices. We are particularly interested in how such practices and interpretive frameworks inform the construction of high-stakes tests. In nearly all current high-stakes test development, tests are thought of as being built-up from individual items, each of which has known statistical properties. The activity sequence outlined in this paper helps future educators to understand the implications of this practice, and the sometimes problematic assumptions it entails. This instructional sequence has been used extensively as part of a core course in a university-based certification program in the United States (UTeach) recognized for its innovative approaches to developing a new generation of secondary STEM educators.
"Technology, Knowledge and Learning" – Springer Journals
Published: Jan 7, 2012
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.