The Experts below are selected from a list of 155055 Experts worldwide ranked by ideXlab platform

Joan Garfield - One of the best experts on this subject based on the ideXlab platform.

Arthur Bakker - One of the best experts on this subject based on the ideXlab platform.

  • The nature and use of theories in Statistics Education
    International Handbook of Research in Statistics Education, 2017
    Co-Authors: Per Nilsson, Maike Schindler, Arthur Bakker
    Abstract:

    This chapter presents a literature review of theories used to frame and underpin Statistics Education Research. The aim is to describe, characterize and arrange the nature and use of theories in SER and hint at some potential trends and required directions for further theorizing the SER discipline. The review includes empirical research papers, published from 2004 to 2015, and focuses on students’ learning of Statistics or probability at the primary and secondary school level. The number of papers that fulfilled our inclusion criteria was 35.

  • Applying Contemporary Philosophy in Mathematics and Statistics Education: The Perspective of Inferentialism
    Proceedings of the 13th International Congress on Mathematical Education, 2017
    Co-Authors: Maike Schindler, Kate Mackrell, Dave Pratt, Arthur Bakker
    Abstract:

    Schindler, M., Mackrell, K., Pratt, D., & Bakker, A. (2017). Applying contemporary philosophy in mathematics and Statistics Education: The perspective of inferentialism. In G. Kaiser (Ed.). Proceedings of the 13th International Congress on Mathematical Education, ICME-13

  • An Introduction to Design-Based Research with an Example From Statistics Education
    Advances in Mathematics Education, 2014
    Co-Authors: Arthur Bakker, Dolly Van Eerde
    Abstract:

    This chapter arose from the need to introduce researchers, including Master and PhD students, to design-based research (DBR). In Sect. 16.1 we address key features of DBR and differences from other research approaches. We also describe the meaning of validity and reliability in DBR and discuss how they can be improved. Section 16.2 illustrates DBR with an example from Statistics Education.

  • Lessons from Inferentialism for Statistics Education
    Mathematical Thinking and Learning, 2011
    Co-Authors: Arthur Bakker, Jan Derry
    Abstract:

    This theoretical paper relates recent interest in informal statistical inference (ISI) to the semantic theory termed inferentialism, a significant development in contemporary philosophy, which places inference at the heart of human knowing. This theory assists epistemological reflection on challenges in Statistics Education encountered when designing for the teaching or learning of ISI. We suggest that inferentialism can serve as a valuable theoretical resource for reform efforts that advocate ISI. To illustrate what it means to privilege an inferentialist approach to teaching Statistics, we give examples from two sixth-grade classes (age 11) learning to draw informal statistical inferences while developing key concepts such as center, variation, distribution, and sample without losing sight of problem contexts.

  • Diagrammatic reasoning and hypostatic abstraction in Statistics Education
    Semiotica, 2007
    Co-Authors: Arthur Bakker
    Abstract:

    Peirce’s notions of diagrammatic reasoning and hypostatic abstraction are relevant to Educational research in areas where diagrams and abstraction play an important role. In this paper, I analyze an example from Statistics Education in which diagrammatic reasoning created opportunities for hypostatic abstraction. For instance, where students initially characterized data points as being ‘spread out,’ they later said, ‘the spread is large.’ This is a prototypical example of hypostatic abstraction — taking a predicate as a new object that can have predicates itself. More generally, the notion of diagrammatic reasoning proved helpful to identify the key learning processes involved in learning to reason about statistical concepts.

Audbjorg Bjornsdottir - One of the best experts on this subject based on the ideXlab platform.

Randall E. Groth - One of the best experts on this subject based on the ideXlab platform.

  • Working at the boundaries of mathematics Education and Statistics Education communities of practice
    Journal for Research in Mathematics Education, 2015
    Co-Authors: Randall E. Groth
    Abstract:

    Statistics Education has begun to mature as a discipline distinct from mathematics Education, creating new perspectives on the teaching and learning of Statistics. This commentary emphasizes the importance of coordinating perspectives from Statistics Education and mathematics Education through boundary interactions between the two communities of practice. I argue that such interactions are particularly vital in shared problem spaces related to the teaching and learning of measurement, variability, and contextualized problems. Collaborative work within these shared problem spaces can contribute to the vitality of each discipline. Neglect of the shared problem spaces may contribute to insularity and have negative consequences for research and school curricula. Challenges of working at the boundaries are considered, and strategies for overcoming the challenges are proposed.

  • Situating Qualitative Modes of Inquiry within the Discipline of Statistics Education Research.
    Statistics Education Research Journal, 2010
    Co-Authors: Randall E. Groth
    Abstract:

    Qualitative methods have become common in Statistics Education research, but questions linger about their role in scholarship. Currently, influential policy documents lend credence to the notion that qualitative methods are inherently inferior to quantitative ones. In this paper, several of the questions about qualitative research raised in recent policy documents in the U.S. are examined. Each question is addressed by drawing upon examples from existing Statistics Education research. The examples illustrate that qualitative methods can be used profitably to study statistical teaching and learning, and that in some cases qualitative methods are preferable to quantitative ones. By using the examples presented, qualitative researchers in Statistics Education can begin to more strongly situate their work within scholarly discourse about empirical research.

Peter Petocz - One of the best experts on this subject based on the ideXlab platform.

  • Statistics Education Research
    International Handbook of Research in Statistics Education, 2017
    Co-Authors: Peter Petocz, Anna Reid, Iddo Gal
    Abstract:

    This chapter sketches in broad strokes and critically examines several aspects of the world of research that pertain to the teaching, learning, understanding, and using of Statistics and probability in diverse contexts, both formal and informal. It reflects on the methods and conceptual schemes that underlie the research activity in this field (the how), the topics being researched (the what), and the people carrying out the research (the who). The chapter examines purposes and motivations for different types of studies in Statistics Education, distinguishing between large-R research that often aims for academic reporting and generalizability versus small-r types of research whose motivation is more on local problems set in a particular context. We illustrate some trends in the field by presenting empirical results from an exploratory qualitative analysis of the text of a body of papers and publications in the field. The chapter points out that the range of what qualifies as research in (or of relevance to) Statistics Education is much broader than what gets published in leading journals and conferences in our field. It highlights the multiplicity of philosophical foundations and methodologies in use. Some directions for future development and research are outlined, including aspects of statistical literacy, cultural dimensions of Statistics Education research, the role of practitioner inquiry, and the importance of broad interdisciplinary research in Statistics Education.

  • Representations of Internationalisation in Statistics Education
    Journal of Statistics Education, 2009
    Co-Authors: Narelle Smith, Anna Reid, Peter Petocz
    Abstract:

    Internationalisation is an important but contentious issue in higher Education. For some it means the facilitation of student mobility and an important source of funding for universities, while for others it forms a philosophy of teaching and student engagement, highlighting issues of global inequality. In this study, the papers from a recent Statistics Education conference, the 7th International Conference on Teaching Statistics, are subjected to a critical discourse analysis against a theoretical frame derived from research describing different ways of understanding and working with internationalisation. The analysis demonstrates how a specific discipline-based community — the Statistics Education community — involves itself with issues of internationalisation.

  • BEING CRITICAL ABOUT APPROACHES TO RESEARCH IN Statistics Education
    2006
    Co-Authors: Anna Reid, Peter Petocz
    Abstract:

    Teachers undertaking Educational research for the first time usually begin their explorations by evaluating some aspect of their practice. By contrast, experienced researchers will start from an argued research question supported by a defined theoretical framework. In this paper, we use a critical discourse approach to explore various interpretive research paradigms that are commonly used to investigate aspects of Statistics Education. By considering the underlying epistemological positions and critiquing the approaches and methods used to explore human action in social situations, we become more critical in the design, implementation and reporting of research in Statistics Education. INTRODUCTION Statistics Education research is represented through language that is situated in the world of Statistics teachers and lent an external credibility through the use of academic discourse (such as citations for authority, institutional affiliation and academic levels). How can we make sense of the different sorts of research that comprise Statistics Education research? What do these research orientations say about the focus and nature of research in Statistics pedagogy? What constitutes legitimacy in research practice of Statistics Education? A critical discourse approach enables us to treat language as a form of social practice. Texts - in this case, texts representing a sample of research in Statistics Education - are situated within the activity of the writers and readers: thus, the research writings can be interpreted as representative of those situations. In this paper, we will examine a sample of texts from ICOTS-6 (and elsewhere), including our own work using phenomenography, that represent the discourse of statistical Education researchers. We will look at the locus and focus of the studies, and the relationships between the central research questions, the methods used to explore those questions and their outcomes. We aim to establish a framework for reflective teachers and active researchers to examine their own research assumptions and evaluate the 'trustworthiness' of their findings. Much mainstream research in higher Education uses qualitative methods to examine learning situations, often represented through analysis of some sort of linguistic elements. For statisticians, who deal primarily with variation using numerical methods, qualitative approaches can seem arcane: within Statistics, rigour is represented by the use of statistical techniques. A recent talk by Shelley (2005) claims that rigour in Educational research in Statistics (and elsewhere) can only be established by the use of "proper scientific methods," and describes US Government legislation to "foster scientifically valid research." Here, Shelley legitimises quantitative experimental designs for the study of social situations through a careful elaboration of language common to the core of Statistics as a research method in its own right. The use of terms such as 'scientific,' 'experiment,' 'gold standard,' 'quantification,' 'random trials,' 'valid control groups' and even 'power' all seem consistent with the world inhabited by statisticians. However, those who are involved with pedagogical experiments find themselves questioning the lived experience of the participants and the implications for change in learning relationships. Researching pedagogical situations provides an opportunity to explore using 'improper' methods, and to acknowledge the qualitative variation found amongst people, their orientations to learning and their expectations for their futures. Indeed, statisticians have become aware of the benefits of including qualitative as well as quantitative aspects of research in Statistics Education (e.g., Batanero et al., 2001). Moss (2004) suggests that a critical discourse approach can bridge barriers created by the inter-subjective nature of Statistics and the social realities represented through hermeneutic approaches. Guba and Lincoln (1989) propose that the notion of trustworthiness as a qualitative equivalent of rigour demands that four criteria are met: the research must be credible, transferable, dependable and confirmable. These criteria lend authenticity to the research.

  • Completing the Circle: Researchers of Practice in Statistics Education
    Mathematics Education Research Journal, 2003
    Co-Authors: Anna Reid, Peter Petocz
    Abstract:

    Research in student learning can be based on a theoretical framework, observations of students’ learning, the products of this learning, and students’ own conceptions of the subject and of learning. In the final analysis, such investigations have a clear purpose—to improve student learning. We report on using the results of research into student learning in Statistics to improve the learning environment in a university class on regression analysis. We believe this is an effective method of becoming “researchers of practice” in Statistics Education.