Assessment Analytics In Education
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Assessment Analytics in Education
This book is about the current state of research in online assessment. The growth of this field is set to accelerate exponentially with emerging opportunities for automatic data collection and analysis. Yet, the future of online assessment faces major challenges including, perhaps most importantly, the extent to which assessments, when enabled by technology, can serve simultaneously the needs of learners, teachers and those of the enterprise of education. This book details, specifically, the multiple ways in which online assessment can be utilized, such as: Providing virtual coaching or tutoring Offering appropriate scaffolding Allowing analysis of student decision-making Providing the mechanism for students to review and comment on each others digital creations Creating a space for online discussion Providing expert coaching for modeling and animation work With the increased availability of vast and highly varied amounts of data from learners, teachers, learning environments, and administrative systems within educational settings, further opportunities arise for advancing pedagogical assessment practice (Ifenthaler et al., 2018). This book fully details these opportunities, as well as privileges and constraints of analytics-enhanced assessment, harnessing formative as well as summative data from learners and their contexts in order to facilitate learning processes in near real-time and help decisionmakers to improve learning environments.
OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots
How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems.
Learning Analytics: Fundaments, Applications, and Trends
This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.