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Quality Research in Literacy and Science Education

International Perspectives and Gold Standards

  • Book
  • © 2009

Overview

Editors:
  1. Mack C. Shelley

    1. Iowa State University, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Larry D. Yore

    1. University of Victoria, Canada

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    You can also search for this editor in PubMed   Google Scholar

  3. Brian Hand

    1. University of Iowa, USA

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    You can also search for this editor in PubMed   Google Scholar

  • Provides uniquely international perspectives on modern applications of research methods in education
  • Demonstrates how researchers and educators in science education and literacy can strengthen their findings and have more impact on teachers’ classroom practice and students’ learning
  • Shows how those who make education policy can be informed and their decisions affected by researchers
  • Deepens and broadens communications among the fields of education, statistics, political science, and public policy
  • Attempts to bring unity to the quantitative and qualitative research traditions

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Table of contents (28 chapters)

  1. Front Matter

    Pages i-xxix
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  3. Setting the Agenda: Science Education and Science-based Research

    1. Why “Gold Standard” Needs Another “s”: Results from the Gold Standard(s) in Science and Literacy Education Research Conference

      • Larry D. Yore, Pietro Boscolo
      Pages 19-39

    2. Research and Practice: A Complex Relationship?

      • Robin Millar, Jonathan Osborne
      Pages 41-61

    3. Moving Beyond the Gold Standard: Epistemological and Ontological Considerations of Research in Science Literacy

      • Donna E. Alvermann, Christine A. Mallozzi
      Pages 63-81

    4. Longitudinal Studies into Science Learning: Methodological Issues

      • Russell Tytler
      Pages 83-105

    5. An International Perspective of Monitoring Educational Research Quality: Commonalities and Differences

      • Richard K. Coll, Wen-Hua Chang, Justin Dillon, Rosária Justi, Eduardo Mortimer, Kim Chwee Daniel Tan et al.
      Pages 107-137

    6. Considering Research Quality and Applicability Through the Eyes of Stakeholders

      • Denyse V. Hayward, Linda M. Phillips
      Pages 139-148

  4. Curriculum and Pedagogy

    1. Researching Effective Pedagogies for Developing the Literacies of Science: Some Theoretical and Practical Considerations

      • Vaughan Prain
      Pages 151-168

    2. Pedagogy, Implementation, and Professional Development for Teaching Science Literacy: How Students and Teachers Know and Learn

      • Lori Norton-Meier, Brian Hand, Andy Cavagnetto, Recai Akkus, Murat Gunel
      Pages 169-187

    3. Approaching Classroom Realities: The Use of Mixed Methods and Structural Equation Modeling in Science Education Research

      • Martina Nieswandt, Elizabeth H. McEneaney
      Pages 189-211

    4. Mixed-methodology Research in Science Education: Opportunities and Challenges in Exploring and Enhancing Thinking Dispositions

      • Tamar Levin, Tili Wagner
      Pages 213-243

    5. New Directions in Science Literacy Education

      • E. Wendy Saul, Brian Hand
      Pages 245-260

  5. Statistics, Research Methods, and Science Literacy

    1. Multilevel Modeling with HLM: Taking a Second Look at PISA

      • John O. Anderson, Todd Milford, Shelley P. Ross
      Pages 263-286

    2. Methods from Item Response Theory: Going Beyond Traditional Validity and Reliability in Standardizing Assessments

      • Amy G. Froelich
      Pages 287-301

    3. Confounding in Observational Studies using Standardized Test Data: Careful Disentanglement of Statistical Interpretations and Explanations

      • Mary C. Meyer
      Pages 303-322

    4. Predicting Group Membership using National Assessment of Educational Progress (NAEP) Mathematics Data

      • David A. Walker, Shereeza F. Mohammed
      Pages 323-335

    5. Incorporating Exploratory Methods using Dynamic Graphics into Multivariate Statistics Classes: Curriculum Development

      • Dianne Cook
      Pages 337-355

    6. Approaches to Broadening the Statistics Curricula

      • Deborah Nolan, Duncan Temple Lang
      Pages 357-381

    7. Dr. Fox Rocks: Using Data-mining Techniques to Examine Student Ratings of Instruction

      • Morgan C. Wang, Charles D. Dziuban, Ida J. Cook, Patsy D. Moskal
      Pages 383-398
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Keywords

About this book

Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.

Reviews

The strength of this book, its inclusion of many perspectives that include political and policy pressures, budget priorities, task force reports, research complexities, curriculum complexities, and teaching-learning complexities, will be appreciated by many who see "No Childe Left Behing" and "high-stakes testing" as overly simplistic and potentially harmfull to education. It contains important information and valuable insight into the complexities of conducting quality sience literacy research in particular and education research in general. Also, the emphasis on producing research that can be understood and used properly by policy makers at local, state, and national levels is a strength of the book. I have been in the science education research field for over 40 years, including a stint as editor of the Journal of Research in Science Teaching, and I can say that I profited from reading this book.

Ron Good, Professor Emeritus, Louisiana State University and Florida State University, USA

Editors and Affiliations

  • Iowa State University, USA

    Mack C. Shelley

  • University of Victoria, Canada

    Larry D. Yore

  • University of Iowa, USA

    Brian Hand

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