The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a rigorous and fast-emerging discipline that synthesizes the learning sciences, instructional design, engineering design, and other methodologies to support learners. As learning engineering becomes an increasingly formalized discipline and practice, new insights and tools are needed to help education, training, design, and data analytics professionals iteratively develop, test, and improve complex systems for engaging and effective learning. Written in a colloquial style and full of collaborative, actionable strategies, this book explores the essential foundations, approaches, and real-world challenges inherent to ensuring participatory, data-driven, learning experiences across populations and contexts.

Learning Engineering for Online Education is a comprehensive overview of the emerging field of learning engineering, a form of educational optimization driven by analytics, design-based research, and fast-paced, large-scale experimentation. Chapters written by instructional design and distance learning innovators explore the theoretical context of learning engineering and provide design-based examples from top educational institutions. Concluding with an agenda for future research, this volume is essential for those interested in using data and high-quality outcome evidence to improve student engagement, instructional efficacy, and results in online and blended settings.

The Design Recommendations for Intelligent Tutoring Systems series has covered many different topics over the past ten years. Those topics have ranged from general components of intelligent tutoring systems (ITSs) (Learner Modeling, Instructional Management, Authoring Tools, Domain Modeling) to advanced elements (Assessment Methods, Team Tutoring, Self-Improving Systems, Data Visualization, Competency Based-Scenario Design). Our most recent previous volume included a series of Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analyses on all the initial topics as well as overviews of ITSs in general and the Generalized Intelligent Framework for Tutoring (GIFT) software (Sottilare et al., 2012; Sottilare et al., 2017; Goldberg & Sinatra, 2023). Each book in the Design Recommendations for Intelligent Tutoring Systems series has been associated with an Expert Workshop on the same topic. These workshops are part of a cooperative agreement (W911NF18-2-0039) between US Army Combat Capabilities Development Command (DEVCOM) Soldier Center and University of Memphis. One of the goals of the expert workshops is to learn more about ITS capabilities that are being developed, and how these approaches, as well as lessons learned, could enhance the GIFT software (GIFT is freely available at https://www.GIFTtutoring.org). Invited experts in industry, academia, and government discuss the expert workshop topic, their applicable work, and suggestions for improving GIFT in what is usually a two day event. Both the University of Memphis and GIFT Teams participate in the workshop, help to guide discussion, and ask questions that will provide insight into current challenges in GIFT. The expert workshop associated with this current book was held virtually in October 2022, and included presentations about both general approaches and specific applications to professional education in ITSs. Additionally, the University of Memphis team that participated in the workshop included Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Jody Cockroft. The US Army DEVCOM Soldier Center team who participated in the workshop included Benjamin Goldberg, Gregory Goodwin, Anne M. Sinatra, Randall Spain, and Lisa N. Townsend. The current volume and the expert workshop that was associated with it, branched out in a new direction and rather than addressing specific components of an ITS or types of features/approaches that could be included in ITSs, it focused on how to apply an ITS for specific types of training. The specific focus was on ITSs for Professional Career Education. This topic area was selected, as in general, ITS research tends to be focused on K-12 or college education, and in many cases on domains such as algebra or physics. However, for the military, and for industry, trainees are adult learners and domains tend to be more active, applied, and experiential. This workshop provided an opportunity for discussion of specific examples of applied training that occurs with ITSs, as well as discussion of general approaches and considerations for applied professional education in ITSs.

Improve information security by learning Social Engineering. Key Features Learn to implement information security using social engineering Get hands-on experience of using different tools such as Kali Linux, the Social Engineering toolkit and so on Practical approach towards learning social engineering, for IT security Book Description This book will provide you with a holistic understanding of social engineering. It will help you to avoid and combat social engineering attacks by giving you a detailed insight into how a social engineer operates. Learn Social Engineering starts by giving you a grounding in the different types of social engineering attacks,and the damages they cause. It then sets up the lab environment to use different toolS and then perform social engineering steps such as information gathering. The book covers topics from baiting, phishing, and spear phishing, to pretexting and scareware. By the end of the book, you will be in a position to protect yourself and your systems from social engineering threats and attacks. All in all, the book covers social engineering from A to Z , along with excerpts from many world wide known security experts. What you will learn Learn to implement information security using social engineering Learn social engineering for IT security Understand the role of social media in social engineering Get acquainted with Practical Human hacking skills Learn to think like a social engineer Learn to beat a social engineer Who this book is for This book targets security professionals, security analysts, penetration testers, or any stakeholder working with information security who wants to learn how to use social engineering techniques. Prior knowledge of Kali Linux is an added advantage

Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you’ll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You’ll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You’ll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author’s extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer. Table of Contents PART 1 AN INTRODUCTION TO MACHINE LEARNING ENGINEERING 1 What is a machine learning engineer? 2 Your data science could use some engineering 3 Before you model: Planning and scoping a project 4 Before you model: Communication and logistics of projects 5 Experimentation in action: Planning and researching an ML project 6 Experimentation in action: Testing and evaluating a project 7 Experimentation in action: Moving from prototype to MVP 8 Experimentation in action: Finalizing an MVP with MLflow and runtime optimization PART 2 PREPARING FOR PRODUCTION: CREATING MAINTAINABLE ML 9 Modularity for ML: Writing testable and legible code 10 Standards of coding and creating maintainable ML code 11 Model measurement and why it’s so important 12 Holding on to your gains by watching for drift 13 ML development hubris PART 3 DEVELOPING PRODUCTION MACHINE LEARNING CODE 14 Writing production code 15 Quality and acceptance testing 16 Production infrastructure

This book describes an approach to engineering education that integrates a comprehensive set of personal, interpersonal, and professional engineering skills with engineering disciplinary knowledge in order to prepare innovative and entrepreneurial engineers. The education of engineers is set in the context of engineering practice, that is, Conceiving, Designing, Implementing, and Operating (CDIO) through the entire lifecycle of engineering processes, products, and systems. The book is both a description of the development and implementation of the CDIO model and a guide to engineering programs worldwide that seek to improve the education of young engineers.

Engineering Effective Learning Engineering Effective Learning Toolkit offers a systematic, step-by-step approach for designing, managing, and evaluating successful training, learning, and performance projects. Harold D. Stolovitch and Erica J. Keeps–international leaders in the field of workplace learning and performance and coeditors of both editions of the Handbook of Human Performance Technology–have designed this toolkit based on their popular course that has been conducted and tested with hundreds of leading organizations worldwide. A hands-on resource, Engineering Effective Learning Toolkit is filled with illustrative, real-world examples and includes on CD-ROM easily reproducible and customizable information charts and job aids to help you accomplish each step in the instructional design process. This indispensable toolkit is a personal "coach" you can refer to on an "as-needed" basis or use to complete a training project from start to finish. Engineering Effective Learning Toolkit is the first book in the Learning and Performance Toolkit Series. Praise for Engineering Effective Learning Toolkit "Watching great instructional design is like observing great ice skating. The audience is wowed by the flow and beauty and usually has no inkling about all it took to get there. Erica and Harold know how to make the magic happen. They also know how to make it easy for their readers. They offer us all the ingredients for their special choreography." –Beverly Kaye, CEO and founder, Career Systems International and author, Up Is Not The Only Way; coauthor, Love ‘Em or Lose ‘Em: Getting Good People to Stay "All instructional designers with varying degrees of experience interested in improving performance through systematically designed training programs can benefit from the Toolkit. This book provides an organization with a solid foundation to make significant performance improvements quickly. We know because we use Harold’s and Erica’s process and tools with great success." –Michel Roy, human resources manager, Alcan Primary Metal "This book, written by two of the world’s most experienced instructional designers, is filled with ready-to-use and proven-to-work job aids, tools, checklists and charts. If you develop learning programs of any type, this is the book to use!" –Dana and Jim Robinson, principals, Partners in Change and coauthors, Performance Consulting and Zap the Gaps! "As a training manager for the last 20 years, I have used and implemented the Stolovitch and Keeps Engineering Effective Learning process. It has proven to be very efficient in designing, developing, and implementing instructional interventions. I am thrilled to see that this process will now be available to all!" –Daniel Dupont, chief learning officer, Société des Alcools du Québec "In a very clear and easily executable fashion, the authors have managed to provide a roadmap for success. It is as applicable for seasoned veterans as it is for individuals new to the instructional design process." –Lisa Cavallaro, manager, learning & development, WW Talent Resourcing & Development, Cisco Systems "Clear, concise, practical, proven, and useful–this provides all one has to know to design successful learning." –Roger Kaufman, professor, office for needs assessment & planning, Florida State University, and director, Roger Kaufman & Associates "If you’re involved with the design of learning, then this book has something to offer you. From beginner to the most advanced instructional designer, there are tools and tips that you can immediately and effectively put to use!" –Frank S. Wilmoth, Director for Learning Excellence, Prudential Real Estate and Relocation Services