This book provides a systematic study of the Programme for International Student Assessment (PISA) based on big data analysis, aiming to examine the contextual factors relevant to students’ digital reading performance. The author first introduces the research landscape of educational data mining (EDM) and reviews the PISA framework since its launch and how it has become an important metric to assess the knowledge and skills of students from across the globe. With a focus on methodology and its applications, the book explores extant scholarship on the dynamic model of educational effectiveness, multi-level factors of digital reading performance, and the application of EDM approaches. The core chapter on the methodology examines machine learning algorithms, hierarchical linear modeling, mediation analysis, and data extraction and processing for the PISA dataset. The findings give insights into the influencing factors of students’ digital reading performance, allowing for further investigations on improving students’ digital reading literacy and more attention to the advancement of education effectiveness. The book will appeal to scholars, professionals, and policymakers interested in reading education, educational data mining, educational technology, and PISA, as well as students learning how to utilize machine learning algorithms in examining the mass global database.

This book provides a systematic study of the Programme for International Student Assessment (PISA) based on big data analysis, aiming to examine the contextual factors relevant to students’ digital reading performance. The author first introduces the research landscape of educational data mining (EDM) and reviews the PISA framework since its launch and how it has become an important metric to assess the knowledge and skills of students from across the globe. With a focus on methodology and its applications, the book explores extant scholarship on the dynamic model of educational effectiveness, multi-level factors of digital reading performance, and the application of EDM approaches. The core chapter on the methodology examines machine learning algorithms, hierarchical linear modeling, mediation analysis, and data extraction and processing for the PISA dataset. The findings give insights into the influencing factors of students’ digital reading performance, allowing for further investigations on improving students’ digital reading literacy and more attention to the advancement of education effectiveness. The book will appeal to scholars, professionals, and policymakers interested in reading education, educational data mining, educational technology, and PISA, as well as students learning how to utilize machine learning algorithms in examining the mass global database.

This sixth volume of PISA 2009 results explores students’ use of information technologies to learn.

Assessment is messy. Day-to-day, in-the-moment assessments not only reveal information that drives future instruction but also offer a comprehensive picture of students’ abilities and dispositions toward learning. As teachers, we might know what this looks and feels like, yet it can be hard to put into action—hence the messiness. Say hello to digital student portfolios—dynamic, digital collections of authentic information from different media, in many forms, and with multiple purposes. Using digital portfolios to capture student thinking and progress allows us to better see our students as readers, writers, and learners—and help students see themselves in the same way! Matt Renwick’s Digital Portfolios in the Classroom is a guide to help teachers sort through, capture, and make sense of the messiness associated with assessment. By shining a spotlight on three types of student portfolios—performance, process, and progress—and how they can be used to assess student work, Renwick helps educators navigate the maze of digital tools and implement the results to drive instruction.

"Programme for International Student Assessment"--Cover.

With this updated document, IRA and NCTE reaffirm their position that the primary purpose of assessment must be to improve teaching and learning for all students. Eleven core standards are presented and explained, and a helpful glossary makes this document suitable not only for educators but for parents, policymakers, school board members, and other stakeholders. Case studies of large-scale national tests and smaller scale classroom assessments (particularly in the context of RTI, or Response to Intervention) are used to highlight how assessments in use today do or do not meet the standards.

Literacy in the 21st century is about constructing and validating knowledge. Digital technologies have enabled the spread of all kinds of information, displacing traditional formats of usually more carefully curated information such as encyclopaedias and newspapers.