Open AccessThe use of a hierarchical construct to investigate students’ learning of inferential statistics
Author(s) -
Saras Krishnan,
Norisma Idris
Publication year - 2013
Language(s) - English
Resource type - Conference proceedings
DOI - 10.52041/srap.13202
Subject(s) - construct (python library) , statistical inference , mathematics education , multilevel model , statistics , computer science , statistics education , psychology , mathematics , programming language
At present, there is still a need for more research in the teaching and learning of inferential statistics because of the limitedness of literature in this area of statistics education. Moreover, there is continuing evidence of students’ partial or unsuccessful learning of many aspects of inferential statistics. This is one of the concerns brought to attention in my postgraduate research whereby part of my work involved the development of a hierarchical construct to identify the different levels of students’ learning of inferential statistics. This paper particularly discusses the use of this hierarchical construct to investigate the learning of inferential statistics among students.