This book is about practicable learning analytics, that is able to become a successful part of practice, ultimately leading to improved learning and teaching. The aim of the book is to shift our perspective on learning analytics creation and implementation from that of “designing of” technology to that of “designing for” a system of practice. That is, any successful implementation of learning analytics requires a systematic approach, which the book explains through the lens of the Information Systems Artefact, constituting of the three interdependent artefacts: “technical”, “information” and “social”. The contributions of this book go beyond a consideration of particular humans such as teachers and students, and their individual activities to consider the larger systems of activity of which analytics become part of. The chapters included in this book present different cases of learning analytics implementation across countries, and the related opportunities and challenges related to generalizability of the results. The book is written for designers, students and educators of learning analytics who aim to improve learning and teaching through learning analytics.

In the world of education, technology has revolutionized teaching and learning practices globally. However, the widespread adoption of technology, especially in response to Covid-19, has led to a deluge of data from students' digital footprints. The challenge lies in effectively using this data through learning analytics (LA) to optimize K-12 classroom practices. Emergent Practices of Learning Analytics in K-12 Classrooms, edited by Dr. Nurdan Kavakl? Uluta? and Dr. Devrim Höl offers a comprehensive solution to these challenges. This book gathers academic scholars to explore practical perspectives on applying learning analytics in K-12 classrooms, combining qualitative and quantitative methodologies. Addressing topics such as predictive analytics, ethical considerations, and future directions, it empowers educators to make data-driven decisions, creating engaging learning experiences for improved student outcomes. By embracing the insights and recommendations presented in this book, academic scholars can confidently navigate the realm of learning analytics and shape the future of K-12 education.

Due to rapid technological advancements, evolving workplace structures, and a shift towards remote work, the nature of work is undergoing transformations influencing communication, work dynamics, and learning processes. Improving the skills of future workforces is now a necessity as the growth of work-skill misalignment and employability skills gaps becomes prevalent. Educational institutions must prepare students for the digital world by providing them with advanced knowledge and essential skills in modern technology. To positively shape the future workforce, effective solutions for skill revitalization should be explored. Revitalizing Student Skills for Workforce Preparation explores the intricacies of evolving and complex professional landscapes, including the challenges and opportunities of student skill development. The pivotal role of skill development in education is emphasized while delving into how effective skill education will shape the future workforce. This book covers topics such as digital technology, professional development, and emotional intelligence, and is a useful resource for educators, business professionals, and policymakers, academicians, researchers, and administrators.

Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.

Master the Fundamentals of Modern Visual Analytics--and Craft Compelling Visual Narratives in Tableau! Do you need to persuade or inform people? Do you have data? Then you need to master visual analytics and visual storytelling. Today, the #1 tool for telling visual stories with data is Tableau, and demand for Tableau skills is soaring. In Visual Analytics Fundamentals, renowned visual storyteller and analytics professor Lindy Ryan introduces all the fundamental visual analytics knowledge, cognitive and perceptual concepts, and hands-on Tableau techniques you'll need. Ryan puts core analytics and visual concepts upfront, so you'll always know exactly what you're trying to accomplish and can apply this knowledge with any tool. Building on this foundation, she presents classroom-proven guided exercises for translating ideas into reality with Tableau 2022. You'll learn how to organize data and structure analysis with stories in mind, embrace exploration and visual discovery, and articulate your findings with rich data, well-curated visualizations, and skillfully crafted narrative frameworks. Ryan's insider tips take you far beyond the basics--and you'll rely on her expert checklists for years to come. Communicate more powerfully by applying scientific knowledge of the human brain Get started with the Tableau platform and Tableau Desktop 2022 Connect data and quickly prepare it for analysis Ask questions that help you keep data firmly in context Choose the right charts, graphs, and maps for each project--and avoid the wrong ones Craft storyboards that reflect your message and audience Direct attention to what matters most Build data dashboards that guide people towards meaningful outcomes Master advanced visualizations, including timelines, Likert scales, and lollipop charts This book has only one prerequisite: your desire to communicate insights from data in ways that are memorable and actionable. It's for executives and professionals sharing important results, students writing reports or presentations, teachers cultivating data literacy, journalists making sense of complex trends. . . . practically everyone! Don't even have Tableau? Download your free trial of Tableau Desktop and let's get started!

The quality of students’ learning experiences is a critical concern for all higher education institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Developing Effective Educational Experiences through Learning Analytics is a pivotal reference source that focuses on the adoption of data mining and analysis techniques in academic institutions, examining how this collected information is utilized to improve the outcome of student learning. Highlighting the relevance of data analytics to current educational practices, this book is ideally designed for researchers, practitioners, and professionals actively involved in higher education settings.

This book shares the collective experience of integrating electronic portfolios as assessment tools and as instruments for life-long learning in courses across various disciplines in higher education. It enables readers to trace the evolution of e-portfolios over the last ten years and to deal with the challenges faced by instructors and students when implementing e-portfolios in their respective courses. Further, the book suggests flexible ways of dealing with those challenges. It also highlights the relevance of electronic portfolios for the needs and demands of contemporary societies. As such, it speaks to a large target audience from a range of disciplines, roles and geographical contexts within the wider context of higher education in Asia and around the globe.

Inventory Analytics provides a comprehensive and accessible introduction to the theory and practice of inventory control – a significant research area central to supply chain planning. The book outlines the foundations of inventory systems and surveys prescriptive analytics models for deterministic inventory control. It further discusses predictive analytics techniques for demand forecasting in inventory control and also examines prescriptive analytics models for stochastic inventory control. Inventory Analytics is the first book of its kind to adopt a practicable, Python-driven approach to illustrating theories and concepts via computational examples, with each model covered in the book accompanied by its Python code. Originating as a collection of self-contained lectures, Inventory Analytics will be an indispensable resource for practitioners, researchers, teachers, and students alike.

This practical book in instrumental analytics conveys an overview of important methods of analysis and enables the reader to realistically learn the (principally technology-independent) working techniques the analytical chemist uses to develop methods and conduct validation. What is to be conveyed to the student is the fact that analysts in their capacity as problem-solvers perform services for certain groups of customers, i.e., the solution to the problem should in any case be processed in such a way as to be "fit for purpose". The book presents sixteen experiments in analytical chemistry laboratory courses. They consist of the classical curriculum used at universities and universities of applied sciences with chromatographic procedures, atom spectrometric methods, sensors and special methods (e.g. field flow fractionation, flow injection analysis and N-determination according to Kjeldahl). The carefully chosen combination of theoretical description of the methods of analysis and the detailed instructions given are what characterizes this book. The instructions to the experiments are so detailed that the measurements can, for the most part, be taken without the help of additional literature. The book is complemented with tips for effective literature and database research on the topics of organization and the practical workflow of experiments in analytical laboratory, on the topic of the use of laboratory logs as well as on writing technical reports and grading them (Evaluation Guidelines for Laboratory Experiments). A small introduction to Quality Management, a brief glance at the history of analytical chemistry as well as a detailed appendix on the topic of safety in analytical laboratories and a short introduction to the new system of grading and marking chemicals using the "Globally Harmonized System of Classification and Labelling of Chemicals (GHS)", round off this book. This book is therefore an indispensable workbook for students, internship assistants and lecturers (in the area of chemistry, biotechnology, food technology and environmental technology) in the basic training program of analytics at universities and universities of applied sciences.