Learn how to take Classes Online with New Book on the Moodle Learning Management System
Moodle Course Conversion: Beginner’s Guide is a new book from Packt that provides the quickest way for teachers and trainers to turn their familiar teaching materials into a Moodle e-learning course. Written by Ian Wild, this book helps to add multimedia, and incorporate existing sounds and videos to improve a course by converting the existing handouts, worksheets, and other resources into Moodle courses.
This book begins by showing educators how to turn their teaching schedule into an engaging and attractive Moodle course, with the correct number of topics and in a fixed timeframe. Lecturers will learn how to format resources such as documents, slideshows, worksheets etc. in a way that will be effective for students, and will make it easier for them to read and follow.
Using the Moodle course, students will be able to submit their assignments for lecturers to mark or assess on the computer, thereby reducing boxes of assignments to carry to and from school. Instead of having students call into the office during breaks or preparation time, teachers can use forums and messaging to deliver quizzes, tests, and videos, and keep in contact with students whenever convenient.
Teachers, tutors, and lecturers who want to use Moodle to enhance their courses will find this book useful. The book is out now and is available from Packt. For more information, please visit http://www.packtpub.com/moodle-course-conversion/book
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Sponsored by AMD
Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
Learn more about catching the bad guy in this free white paper.
Sponsored by DLT Solutions
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Enter to Win an Adafruit Pi Cobbler Breakout Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- 5-21-13, Prototyping Pi Plate Kit: Philip Kirby
- Next winner announced on 5-27-13!
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Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?



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