Text components of digital lessons and problems are often static: they are written once and too often not improved over time. This is true for both large text components like webpages and documents as well as the small components that form the building blocks of courses: explanations, hints, examples, discussion questions/answers, emails, study tips, motivational messages. This represents a missed opportunity, since it should be technologically straightforward to enhance learning by improving text, as instructors get new ideas and data is collected about what helps learning. We describe how instructors can use recent work (Williams, Kim, Rafferty, Maldonado, Gajos, Lasecki, & Heffernan, 2016a) to make text components into adaptive resources that semiautomatically improve over time, by combining crowdsourcing methods from human computer interaction (HCI) with algorithms from statistical machine learning that use data for optimization.
Changes in the world economy, specifically toward information industries, have changed the skillset demand of many jobs (Organization for Economic Development [OECD], 2012a). Information is created, acquired, transmitted, and used—rather than simply learned—by individuals, enterprises, organizations, and communities to promote economic and social development. Major employers and policy makers are increasingly asking teachers and educators to help students develop so-called real-world skills (Gallup, 2013). While learning basic numeracy and literacy skills still is crucial to success in the job market, developing real-world skills also is essential to success in the job market and worldwide economic development.
Real-world skills, or “21st century skills,” include critical thinking, collaborative problem solving, creativity, and global competency. These skills that facilitate mastery and application of science, mathematics, language arts, and other school subjects will grow in importance over the coming decade (National Research Council, 2012; OECD, 2012a, 2012b). A wide range of initiatives and programs in education promote learning and assessment of real-world skills. These include, for example, the Common Core State Standards (National Governors Association Center for Best Practices and Council of Chief State School Officers, 2010a, 2010b), Next Generation Science Standards (National Research Council, 2013), Common European Framework of Reference (Council of Europe, 2011), Partnership for 21st Century Skills (Partnership for 21st Century Skills, 2009), Education for Life and Work (National Research Council, 2012), and assessment frameworks in the Programme for International Student Assessment (PISA) (OECD, 2013).
Because of the importance of promoting these skills, we have embarked on a journey to create a Handbook of Research on Technology Tools for Real-World Skill Development. Because conceptions and educational applications of real-world skills are evolving rapidly, we have welcomed a wide range of skills in the Handbook. The following four strands of skills are represented in the chapters: Thinking skills refer to higher-order cognition and dispositions such as critical thinking, complex problem solving, metacognition, and learning to learn. Social skills refer to attitudes and behaviors that enable successful communication and collaboration. Global skills refer to attitudes and behaviors that emphasize the individual’s role in, and awareness of, the local as well as the global and multicultural environment. Digital skills emphasize information and digital literacies needed in the technology-rich world in which we live. Similarly, the chapters in this Handbook describe a range of technology tools to support teaching, learning, assessment for learning (e.g., Stiggins, 2005; Wiliam, 2011), feedback for learning (e.g., Hattie, & Timperley, 2007; Shute, 2008), and scoring of student responses.
As technology-rich environments for teaching, learning, assessment, and feedback are being integrated into educational processes, there is much to be learned about how to leverage advances in technology, learning sciences, and assessment to develop real-world skills for the 21st century. Research findings on what works best are just emerging, possibly due to the strong multi-disciplinary approaches required to extract the greatest value. This Handbook is intended to serve as a first body of research in the expanding area of technology tools for teaching, learning, assessment, and feedback on real-world skills that educators can turn to in the coming years as a reference. Our aim is to bring together top researchers to summarize concepts and findings. The Handbook contains contributions of leading researchers in learning science, educational psychology, psychometrics, and educational technology. Assuming that many readers will have little grounding in those topics, each chapter outlines theory and basic concepts and connects them to technology tools for real-world skill development. We see this as one of the most crucial contributions of the Handbook, seeking to establish strong theoretical principles that can inform educational research and practice and future research and development.
Nesterko, S. O., Seaton, D., Reich, J., McIntyre, J., Han, Q., Chuang, I., & Ho, A. (2014). Due dates in MOOCs. Proceedings of the First (2014) ACM Conference on Learning @ Scale , 193–194. Publisher's Version