Gifted Students’ Understanding of Statistics: Analysis of Data Arising from a Small Group Teaching Experiment

Aisling M. Leavy

Gifted and Talented International, 2003, vol. 18, issue 1, 17-26

Abstract: The principal objective of the study was to gain insight into cognitive processes related to three gifted students understanding of data. A small group teaching experiment was used to uncover students understanding of the notion of distribution and consisted of a clinical interview phase, teaching phase, and analysis phase. Fifteen teaching episodes followed the initial clinical interview and involved students working together on a variety of mathematical activities. The study examined how students organized data, described and indexed distributions of data, in addition to investigating their conceptualization of the mean. Results suggest that (a) modes and ranges were the most salient features of distributions, (b) typical values were generally located in clusters of data, (c) the mean was not utilized in the constructed measures of typicality, and (d) students had a relatively sophisticated understanding of samples and populations. Implications for curricular treatment of statistics for gifted students are discussed.

Date: 2003
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/15332276.2003.11673004 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:ugtixx:v:18:y:2003:i:1:p:17-26

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/ugti20

DOI: 10.1080/15332276.2003.11673004

Access Statistics for this article

Gifted and Talented International is currently edited by Sheyla Blumen

More articles in Gifted and Talented International from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().