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This is a session of Topic 6: Research in Statistics education             Full topic list


(Tuesday 4th, 10:30-12:30)

Research methodologies in Statistics education


Organiser


Abstract

This session will address methodological problems and their suggested solutions in statistics education research. Authors are invited to write and submit paper presentations about the following subtopics:

  • Paradigms and research programs in Statistics Education Research
The main question to be addressed here is whether general guiding principals or models can be discerned in Statistics Education Research between the first ICOTS and the one that is being organized now. Knowledge of teaching and learning processes does not grow naturally or inexorably. It is produced through the inquiries of scholars, theorists and practitioners and it is a function of the questions being asked and the problems being posed. Most of us are working within scientific communities, people who share a conceptions of questions, methods and techniques. A goal of this sub topic will be to describe diverse communities that comprise the activities and universe of Research on Statistics Education.

  • Philosophy of Statistics Education Research
What is the meaning of the basic concepts in the field of Statistics Education? Authors interested in this sub domain are invited to analyze these concepts in order to operationalize them in measurement procedures. Basic concepts in the domain of Statistics Education are: teaching, learning, knowledge and knowledge construction. The main focus of this sub theme is analysis of the meaning of key concepts.

  • Measurement of teaching and learning in Statistics Education Research
The measurement of effectiveness of teaching and learning statistics are welcomed in this topic. Authors are invited to analyze current measurement practice and to propose more sensitive and sensible measurement models. What are the recent psychometric advances and which lessons can be learned from it?
Contributions to the measurement, the reliability and interpretation of verbal processing data are especially welcomed. Which models can be used to measure process-tracing. A comparison of different approaches are of interest in the domain covered by this topic.

  • Quantitative methods in Statistics Education Research
The basic assumption of innovative teaching and learning in the domain of Statistics Education is the comparison of at least two treatments: the old method with some innovative new one. Papers considering the design, interpretation and analysis of teaching and learning treatments are most welcome. Themes of interest are: randomized experiments; sample selection and assignment; measures of the implementation of the treatments; variation in implementation; enhancing power; the use of difference scores, gain scores and residual scores; analysis of covariance; structural equation models; regression-discontinuity models; multiple regression models and methods for meta-analysis of teaching and learning effect sizes.

  • Qualitative methods in Statistics Education Research
Under this title contributions which can be characterized as ethnographic, qualitative, participant observational, case study, symbolic interactionist, phenomenological, constructivist or interpretive are welcome. These approaches are relatively new in the field of Statistics Education Research. They nevertheless need attention as attempts to enhance measurement methods for concepts that are difficult to measure. Examples of such concepts might be: Thinking and reasoning, knowledge structures and understanding and comprehension.

Papers

PaperTitlePresenter(s) / Author(s)
6G1An example of individualizing learning and assessment through computerized testingPaul Fields (United States)
Edward Paul Johnson
6G2Learning goals: the primacy of statistical knowledgeNick J Broers (Netherlands)
6G3Assessing students’ understanding of statisticsLuc Bude (Netherlands)
6G4Individual curricula — beliefs behind teachers’ beliefsAndreas Eichler (Germany)