Suchergebnisse

"The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large-scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student's learning and guide teacher's instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices"--

Rationale of C-OAR-SE -- Validity and reliability -- Object classification and measures -- Attribute classification and measures -- Rater entity classifications -- Selection of item-type and answer scale -- Enumeration and scoring rule -- Qualitative research from a C-OAR-SE perspective -- DROAVR application checklist

Preface -- About the authors -- Foundations of design and analysis -- The scientific method -- Ethical research -- Research designs and variables -- Learning about a population from a sample -- Categorical variables and simple frequency -- One variable with frequency data -- Two variables with frequency data -- Research without grouping -- Examining relationships -- Scale development -- Prediction -- Grouped designs with independent samples -- One variable with two independent groups -- One variable with more than two independent groups -- Grouped designs with related samples -- One variable with two related groups -- Variable with repeated measures : more than two groups -- Advanced design -- Variables with independent samples -- Appendices -- Index