Data & Analytics for Instructional Designers

2023-04-11
Data & Analytics for Instructional Designers

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  • Author: Megan Torrance
  • Publisher: Association for Talent Development
  • ISBN: 1953946453
  • Category : Business & Economics
  • Languages : en
  • Pages : 286

Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data—from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you’ll need to get going. So set aside any math anxiety! Through a “If I can see it, I can be it” approach to learning data and analytics, the book blends practical what-is and how-to content with real-world examples and longer case studies from practitioners. Chapters conclude with opportunities for you to put these techniques to work right away, whether you are in a data-rich environment already, or whether you are just getting started and working on hypotheticals.

Agile for Instructional Designers

2019-08-27
Agile for Instructional Designers

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  • Author: Megan Torrance
  • Publisher: Association for Talent Development
  • ISBN: 1949036510
  • Category : Business & Economics
  • Languages : en
  • Pages : 236

Discover Agile for Better Instructional Design To serve business needs amid greater volatility and uncertainty in the workplace, learning and development professionals need project management methods that can keep up. Enter Agile. Popular in the software development space as an approach to project management, Agile when applied to instructional design provides a framework for adapting to change as it happens and for delivering the content most needed by learners. Agile for Instructional Designers proposes using Agile methodology to manage training projects and highlights where traditional linear processes have failed the business and the end users. Recognizing that software development and instructional design have different needs and outcomes, author Megan Torrance developed the LLAMATM methodology. Her approach adapts the common phases of ADDIE to incorporate the incremental, iterative nature of Agile projects. It allows learners to test and evaluate which features or design functions work before they’re finalized. It also offers a way to accommodate inevitable mid-project modifications pushed by stakeholders, subject matter experts, or organizational leaders. With templates for goal alignment, learner personas, scope definition, estimating, planning, and iterative development, Agile for Instructional Designers is the resource you need to embrace change in learning and development.

Educational Data Analytics for Teachers and School Leaders

2022-10-28
Educational Data Analytics for Teachers and School Leaders

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  • Author: Sofia Mougiakou
  • Publisher: Springer Nature
  • ISBN: 3031152662
  • Category : Education
  • Languages : en
  • Pages : 249

Educational Data Analytics (EDA) have been attributed with significant benefits for enhancing on-demand personalized educational support of individual learners as well as reflective course (re)design for achieving more authentic teaching, learning and assessment experiences integrated into real work-oriented tasks. This open access textbook is a tutorial for developing, practicing and self-assessing core competences on educational data analytics for digital teaching and learning. It combines theoretical knowledge on core issues related to collecting, analyzing, interpreting and using educational data, including ethics and privacy concerns. The textbook provides questions and teaching materials/ learning activities as quiz tests of multiple types of questions, added after each section, related to the topic studied or the video(s) referenced. These activities reproduce real-life contexts by using a suitable use case scenario (storytelling), encouraging learners to link theory with practice; self-assessed assignments enabling learners to apply their attained knowledge and acquired competences on EDL. By studying this book, you will know where to locate useful educational data in different sources and understand their limitations; know the basics for managing educational data to make them useful; understand relevant methods; and be able to use relevant tools; know the basics for organising, analysing, interpreting and presenting learner-generated data within their learning context, understand relevant learning analytics methods and be able to use relevant learning analytics tools; know the basics for analysing and interpreting educational data to facilitate educational decision making, including course and curricula design, understand relevant teaching analytics methods and be able to use relevant teaching analytics tools; understand issues related with educational data ethics and privacy. This book is intended for school leaders and teachers engaged in blended (using the flipped classroom model) and online (during COVID-19 crisis and beyond) teaching and learning; e-learning professionals (such as, instructional designers and e-tutors) of online and blended courses; instructional technologists; researchers as well as undergraduate and postgraduate university students studying education, educational technology and relevant fields.

Visualizations and Dashboards for Learning Analytics

2021-12-16
Visualizations and Dashboards for Learning Analytics

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  • Author: Muhittin Sahin
  • Publisher: Springer Nature
  • ISBN: 3030812227
  • Category : Education
  • Languages : en
  • Pages : 624

This edited volume fills the gaps in existing literature on visualization and dashboard design for learning analytics. To do so, it presents critical tips to stakeholders and acts as guide to efficient implementation. The book covers the following topics: visualization and dashboard design for learning analytics, visualization and dashboard preferences of stakeholders, learners’ patterns on the dashboard, usability of visualization techniques and the dashboard, dashboard and intervention design, learning and instructional design for learning analytics, privacy and security issues about the dashboard, and future directions of visualization and dashboard design. This book will be of interest to researchers with interest in learning analytics and data analytics, teachers and students in higher education institutions and instructional designers, as it includes contributions from a wide variety of educational and psychological researchers, engineers, instructional designers, learning scientists, and computer scientists interested in learning analytics.

Learning Analytics

2020
Learning Analytics

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  • Author: Cristina Hall
  • Publisher:
  • ISBN: 9781789663006
  • Category : BUSINESS & ECONOMICS
  • Languages : en
  • Pages : 0

Utilize organizational data and analytics to make better decisions about managing the learning and development of your workforce.

Learning Science for Instructional Designers

2021-04-13
Learning Science for Instructional Designers

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  • Author: Clark N. Quinn
  • Publisher: Association for Talent Development
  • ISBN: 1952157463
  • Category : Business & Economics
  • Languages : en
  • Pages : 187

Ensure Your Instructional Design Stands Up to Learning Science Learning science is a professional imperative for instructional designers. In fact, instructional design is applied learning science. To create effective learning experiences that engage, we need to know how learning works and what facilitates and hinders it. We need to track the underlying research and articulate how our designs reflect what is known. Otherwise, how can we claim to be scrutable in our approaches? Learning Science for Instructional Designers: From Cognition to Application distills the current scope of learning science into an easy-to-read primer. Good instructional design makes learning as simple as possible by removing distractions, minimizing the cognitive load, and chunking necessary information into digestible bits. But our aim must go beyond enabling learners to recite facts to empowering them to make better decisions—decisions about what to do, when, and how. This book prepares you to design learning experiences that ensure retention over time and transfer to the appropriate situations. Gain insights into: Providing spaced practice and reflection Tapping into motivation and challenge to build learner confidence Using performance-support tools, social learning, and humor appropriately Prompts at the end of each chapter will spark your thinking about how to use these concepts and more in your daily work. Written by Clark N. Quinn, author of Millennials, Goldfish & Other Training Misconceptions: Debunking Learning Myths and Superstitions, this book is perfect for anyone who strives for their instruction to stand up to learning science.

Learning Analytics

2014-07-04
Learning Analytics

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  • Author: Johann Ari Larusson
  • Publisher: Springer
  • ISBN: 1461433053
  • Category : Education
  • Languages : en
  • Pages : 195

In education today, technology alone doesn't always lead to immediate success for students or institutions. In order to gauge the efficacy of educational technology, we need ways to measure the efficacy of educational practices in their own right. Through a better understanding of how learning takes place, we may work toward establishing best practices for students, educators, and institutions. These goals can be accomplished with learning analytics. Learning Analytics: From Research to Practice updates this emerging field with the latest in theories, findings, strategies, and tools from across education and technological disciplines. Guiding readers through preparation, design, and examples of implementation, this pioneering reference clarifies LA methods as not mere data collection but sophisticated, systems-based analysis with practical applicability inside the classroom and in the larger world. Case studies illustrate applications of LA throughout academic settings (e.g., intervention, advisement, technology design), and their resulting impact on pedagogy and learning. The goal is to bring greater efficiency and deeper engagement to individual students, learning communities, and educators, as chapters show diverse uses of learning analytics to: Enhance student and faculty performance. Improve student understanding of course material. Assess and attend to the needs of struggling learners. Improve accuracy in grading. Allow instructors to assess and develop their own strengths. Encourage more efficient use of resources at the institutional level. Researchers and practitioners in educational technology, IT, and the learning sciences will hail the information in Learning Analytics: From Research to Practice as a springboard to new levels of student, instructor, and institutional success.

Innovative Learning Analytics for Evaluating Instruction

2021-07-19
Innovative Learning Analytics for Evaluating Instruction

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  • Author: Theodore W. Frick
  • Publisher: Routledge
  • ISBN: 1000454770
  • Category : Education
  • Languages : en
  • Pages : 136

Innovative Learning Analytics for Evaluating Instruction covers the application of a forward-thinking research methodology that uses big data to evaluate the effectiveness of online instruction. Analysis of Patterns in Time (APT) is a practical analytic approach that finds meaningful patterns in massive data sets, capturing temporal maps of students’ learning journeys by combining qualitative and quantitative methods. Offering conceptual and research overviews, design principles, historical examples, and more, this book demonstrates how APT can yield strong, easily generalizable empirical evidence through big data; help students succeed in their learning journeys; and document the extraordinary effectiveness of First Principles of Instruction. It is an ideal resource for faculty and professionals in instructional design, learning engineering, online learning, program evaluation, and research methods.

Learning Analytics: Fundaments, Applications, and Trends

2017-02-17
Learning Analytics: Fundaments, Applications, and Trends

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  • Author: Alejandro Peña-Ayala
  • Publisher: Springer
  • ISBN: 3319529773
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 303

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.

Big Data Analytics

2013-08-23
Big Data Analytics

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  • Author: David Loshin
  • Publisher: Elsevier
  • ISBN: 0124186645
  • Category : Computers
  • Languages : en
  • Pages : 142

Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem