Products & Services

As Senior Director of Product Management for Learn Course Delivery, Jim Chalex conducts research & guides the development of new capabilities to help instructors, learners, and staff get the most out of their online learning environment.  He specializes in assessment, data visualization, and analytics.

 

Data is in, but you don’t us need to tell you that. It’s evident by the number of infographics that pop up every day presenting data in a compelling way on any number of topics; these past few weeks, it’s been all about which Olympic athletes are getting the most social buzz and how the winningest Olympic nations fare when it comes to education.

But, regardless of the topic, it’s what we do with data that really matters. The same can be said for integrating EdTech into the classroom.

We know that students are already grabbing their education by the reins and looking for ways to personalize every part of their learning process – from where they get content to the tools they use in the classroom – they are in control.

So why shouldn’t we give them the opportunity to evaluate themselves?

The BbWorld 2012 Conference will focus on five key themes that matter to you: Social Learning, Digital Content, Technology Adoption, Mobility and now Analytics in Action. I am pleased to say that Ellen Wagner, Partner and Sr. Analyst, Sage Road Solutions LLC, and Executive Director, WCET will be speaking on the topic of Analytics in Action.

Your institution collects data from learners to some degree. But, how do you turn that data into actionable grounds to improve learning? Join Ellen Wagner Ph.D. at her Feature Session “Making Learning Analytics Matter in the Educational Enterprise” and discover how analytics can be used to promote personalization, convenience and consistency in all facets of the online lives of your students.

This session will take a deep dive into applying statistics analyses to help you make better, more informed decisions on teaching and learning.  You will also look at the student road-map and see how analytics techniques can be used in the classroom to improve engagement and motivation.

Please join me in welcoming to the Blackboard Analytics solution set our latest innovative contribution to the use of data across educational institutions, Blackboard Analytics for Learn. This new solution provides rich, easily accessible data to measure and explore student LMS activity, course design and usage, and student educational outcomes, on demand and over-time, by integrating Blackboard Learn and student information system data. At the recent Southern California Technology in Education Conference, I was asked to respond to several questions concerning analytics and the LMS: What are the barriers to better analytics around the LMS? And, what can we do across the higher education community to encourage better progress in developing LMS analytics tools? One of the primary barriers I cited was the traditional difficulty with which institutions are able to gain user friendly, attributionally rich, longitudinal data from their mission critical systems such as the student information and learning management systems. Our efforts and solutions within Blackboard Analytics are targeted exclusively at overcoming this barrier. To contribute to the educational community of practice for how LMS analytics can develop, we are pleased to make today’s announcements regarding Blackboard Analytics for Learn. As my colleague Dr. Deb Everhart blogged earlier this week, analytics from the rich activity and performance data within the LMS highlights great formative promise toward improving student academic performance and the management of the LMS. Advised by our client development partners, we’ve made specific design choices to contribute to this promise. For example, we’ve pre-built integration with the leading student information systems to ensure dimensional analysis associated with student grades, demographic attributes, and institutional departments. As with other Blackboard Analytics solutions, Blackboard Analytics for Learn extends our core approaches to both pre-built and rich data analyses and dashboards, as well as highly extensible analytics data model customization. Finally, implementation and end-user access to the Blackboard Analytics for Learn data model remains rapid and easily achievable. Last year at BbWorld, Ray Henderson announced our goal of introducing Blackboard Analytics for Learn. In reaching this goal, we are fortunate to have been advised by a group of clients whose teaching and learning through Blackboard Learn contributes greatly to their institutional objectives. In mid-2011, we launched a Product Development Partnership, a critical component of Blackboard’s development and design methodology, to work with clients who advised us on the overall set of questions we sought to answer with our analytics solution. Then, in late 2011, we partnered with three institutions which deployed our software, live, on campus, in our pre-release field trial, to utilize our Analytics for Learn solution to examine real questions on their campuses regarding student performance, course design and Blackboard Learn usage. For these partnership efforts, we are considerably thankful to Montgomery County Community College, University of Maryland Baltimore County, and Grand Rapids Community College. In the coming weeks, we look forward to exploring further with our client community how Blackboard Analytics for Learn can improve student success, optimize online instruction, and contribute to the overall management of Blackboard Learn. We’ve begun actively implementing now with our next set of institutions. We look forward to exploring these initial successes and findings at the upcoming BbWorld in New Orleans in July. We’ll look forward to seeing you and continuing the conversation with you there.

Everyone is talking about analytics applied to education and how “big data” can (will?) transform many aspects of our educational institutions. And for those of us passionate about improving opportunities for learning, the phrase “learning analytics” is particularly intriguing. So what do we mean by “learning analytics”? In short, it’s “the use of data and models to predict student progress and performance, and the ability to act on that information,” as defined in the Next Generation Learning Challenges (see the useful Educause Learning Initiative brief). Learning analytics overlaps with the somewhat broader phrase “academic analytics,” which encompasses other institutional bodies of data such as enrollments, graduation rates, and institutional outcomes tracking. A combination of learning analytics and academic analytics can provide an environment where administrators, advisors, faculty, and the students themselves have the data visualization tools they need for learner success. For example, what happens when students can see their own course participation & grade data and compare it to that of others (anonymously) in the same course, while the course is in progress, allowing them to change their behavior mid-course? This type of exposure to learning analytics can be a powerful motivator. Students become more aware of their activities and time on task in their courses. And while the technology is not comprehensive (some courses have more online activities than others), the balance between online and offline activities can be understood by the student despite the lack of data on the offline activities, once the student has crossed that important threshold of self-awareness.