By Lance Eaton
That’s always the first question I get when I tell people that I am an instructional designer (an ID for those of us “in the know”).
It all started when I was 6 years old, and my dad asked me what I wanted to be when I grew up. I peered up into his face and said with an earnest seriousness that no child should muster, “I want to be an instructional designer.”
Data is increasing with the use of learning technologies, and data is being produced at virtually every learning footprint. The next step in the process is to take the data and analyze the connections to improve the entire learning experience.
Learning analytics is the measurement, collection, analysis, and reporting of data about the learners and their contexts for the purpose of understanding and optimizing learning and the environment in which it occurs. [1]
Learning analytics has been around for some time. Its origin can be traced to business intelligence and to predicting consumer behavior. Learning analytics in education has emerged in the last few
decades, and it follows similar analysis and predictive relationships. Learning analytics is growing to keep pace with deciphering patterns from huge data sets to further support and personalize the learning experience.
My interest in learning analytics stems from my research on learning style preferences. The hypothesis was that, if you could determine a user’s learning style preference, then you could optimally display content in a form to best suit the way a learner could interpret it; you could support their success. At that time, most analysis had to be completed prior to the learning, and then you could track users accordingly. Real-time data analysis was in its infancy. The vision then was that, in the future, this could be done via machine learning, with data analysis and dynamically serving up content in a format that learners best understood. Today, those capabilities exist in some learning management systems in the form of learning analytics and adaptive learning.
Currently, most learning management systems are able to track a student’s footprint throughout a course. It can document when a user logs in and logs out, and they can determine the type of content they viewed and for how long. They can also alert students to assignments, assessments and most course requirements, including their status within each course. Some learning systems have dashboards that indicate the students’ progress compared to their expectations and compared to their cohorts’ performance.
In my opinion, most learning management systems are good at data reporting, but they fall short in data analysis and in relationships. The challenge is to harness the data and to make reasonable connections, so that meaningful, positive and proactive interventions can be made; ultimately, we hope to improve the instructional process and student success.
Learning analytics has relevance and usefulness across various groups, including instructors, students, instructional designers and institutions.
Instructors can use learner analytics to gain insight into student progress:
Analytics can also be used as an early warning system for at-risk students; they can trigger appropriate messaging.
Students:
Students can use learner analytics to gain insight into their progress:
As computer technologies develop and more learning components are online, it is essential for learning specialists to evaluate the impact of each emerging technology and to investigate the strengths, weaknesses and appropriate applications for the learners. Sometimes, this is in the form of a retrospective analysis, but increasingly this analysis can be done closer to the time of the event for more agile course adjustments.
Learning analytics can also be used for continuous improvement of the learning design, such as increasing learner engagement, expanding knowledge retention and improving course and program
outcomes.
Learning analytics can be applied at the institutional level for reporting usage trends. In the future, courses could have personality profiles based on course metadata. These items could include tags, such as “projects-based learning,” “discussions,” “hybrid” and “synchronous.” Each metadata tag could also have an associated strength. Each student would also have his or her own evolving learning personality profile.
This data matching would be similar to how Amazon recommends products based on a customer’s purchasing history and behavior. To optimize student success, the recommendation engine architecture could suggest courses that best match the profiles and that mesh with individual learning styles.
It would be short sighted to think that the landscape of learning analytics is only within the confines of an online learning management system. It is increasingly apparent that the majority of learning
occurs outside of the learning management system; it is only the tip of the iceberg. Learning also occurs informally, such as through social media, experiences and discussions. Learning analytics should be inclusive, capturing all learning opportunities. The Experience API (xAPI) has been developed as a mechanism to record and track all types of learning experiences. Ultimately, inclusion of this learning data will broaden analysis and connections. However, in my experience in piloting the xAPI, it is more elusive than reality. It will take time for the experiential footprints to be folded into the mix of the learning data.
Learning analytics is not a one-time, one-size-fits-all approach. It is dynamic, as the parts of the system change and grow. Learning analytics is an emerging field that can benefit many; it has the potential of being a significant factor in improving the overall learning experience in educational institutions or in corporate training.
[1] Society for Learning Analytics Research, 2011.
[2] Low, G. (1995). A study of the effects of learning style preference on achievement in a medical computer simulation (Doctoral dissertation). Retrieved from UMI Dissertation Database (Accession No. ALMA BOSU1 21625699380001161)
Not subscribed to our blog?
The Americas Society and Council of the Americas invited me to discuss scalable innovative practices for education with experts and leaders dedicated to advancing and shaping the political, economic, social and cultural agendas of the Western Hemisphere. The purpose was to take what works in New York City and bring it to other education systems.
Here are some ideas I shared that global leaders can bring back to their countries.
1) Online Learning Communities for Education Resources
It is no longer okay for companies to provide teachers with just a product. Today we ask companies whose products we use, like Google, PBS, and Common Sense Media to develop online learning networks comprised of their staff and NYCDOE educators who use the product. Communities on sites like Google, Facebook, and Edmodo allow educators to connect with one another to share ideas, best practices, troubleshoot issues, and more. A member from the NYCDOE and from the company participate in the group to provide appropriate support as needed.
Teachers love it.
Alone, exhausted, and unseen become connected, energized, and recognized.
2) Partnering with Companies to Develop Expertise within The System
Have you ever been to a classroom and seen a SMARTboard serving as a bulletin board or known that teachers were barely scratching the surface when it comes to using certain technologies? Technology without pedagogy is a waste of money.
Today companies must be held accountable to do more than just sell tools and resources to schools. They must come with an important additional component to grow capacity across the district. That component is a no-cost program that creates and connects teachers across the district who are power-users of the same resources so they can become area experts supporting others back in their school and districts.
Participants become experts and share their skills and knowledge by:
Products are no longer stand alone. They come with training and support that helps ensure their successful use. You can learn more about this program here.
3) Technology Single Point of Contacts (Tech SPOC)
Every school designates a single point of contact for technology who can participate in professional learning opportunities, receive information about technology (i.e. via a newsletter and website), and join an online community for anytime/anywhere support.
4) One Stop for Technology Professional Learning Opportunities
Sounds simple, but until recently we didn’t have a central place on our website where all learning opportunities were placed. Now there is one online place to find both internal and external opportunities such as workshops, institutes, conferences, meet ups, and webinars.
5) Incorporate Student, Educator and Parent Voice
One of the most important scalable practices that can be effectively implemented in any school system is to incorporate the voice of students, staff, and parents. Do this not only by speaking with all stakeholders, but also asking them to be a part of the rules, policies, guidelines, curriculum, and learning that takes place in your school or district. For example, our professional learning opportunities are created with and reviewed by a professional development team of educators who test the work and materials with their students then provide us with feedback.
Our Social Media Guidelines for students were created by interviewing more than one hundred students and numerous educators and parents. We then reached out to the stakeholders to help us create the guidelines in a format they choose. In this case infographics. Once created, we go back to the stakeholders and get feedback then update. We created guides for parents and teachers and professional development. You can see them at schools.nyc.gov/socialmedia.
6) Partner with Students for Learning
While educators are expected to be experts in pedagogy, it is smart to tap into the intelligence of students when it comes to technology. Invite students to be creative with technology. Make a chart of favorite tech tools and indicate who your class experts are. If educators want to be in the know, there is a great free site from Common Sense Media called Graphite.org that rates and reviews digital resources.
7) Embrace Social Media for Students
If we want to run for office, run a business, or change how things are run where we work, live, or play we must be savvy in the use of social media. It is crucial for college, career, and life success. Stay tuned for my next post, to learn some ways to do this right.
So, what do you think? Could some of these practices be put into place where you work? Are there challenges or concerns that are in the way of you implementing these practices? What are some scalable practices that are successful where you work?
Click here to subscribe to our blog!
Brandeis University’s Graduate Professional Studies division (GPS) will launch a fully-online graduate certificate program in Learning Analytics in September 2015, the university announced today.
Designed to be completed in 1.5 years or less, the program is for professionals with strong backgrounds in education, instructional design, or institutional research. Cross-disciplinary in nature, the certificate will provide students with the foundational tool sets and theory of business intelligence and data analysis. These skillsets are necessary for evaluating the effectiveness of courses, programs and instruction, and prepare students to fill a highly in-demand skills gap in a burgeoning job market.
“As the learning analytics field continues to evolve, it is more important than ever before to use the technology and data we have available to us to understand and, ultimately, enhance the learning experience,” said Brian Salerno, director of Online Learning and Instructional Design at Brandeis GPS.
The five-course, 15-credit certificate program draws heavily from two existing Brandeis GPS master’s degrees: Instructional Design and Technology and Strategic Analytics. Applicants are expected to possess a post-graduate degree in a related field as well as three years of relevant work experience.
In addition to the new Learning Analytics certificate, Brandeis GPS offers eight fully online part-time master’s degrees, including Strategic Analytics, Bioinformatics, Health and Medical Informatics, Instructional Design & Technology, and Software Engineering. All Brandeis GPS programs are asynchronous, providing students with a flexible and convenient approach to completing their degree.
Students interested in applying to the Learning Analytics certificate program should complete their application by Aug. 11, 2015. Students also have the opportunity to take a course prior to applying for admission. Registration for the summer 2015 term opened on April 14, with courses beginning May 20. For more information about Brandeis GPS, please visit www.brandeis.edu/gps.
Click here to subscribe to our blog!
by Ariel Garber
The development of learning analytics will help shape a new model for teaching and learning, creating a system that provides insight and information to support student success. The field of learning analytics, defined by EDUCAUSE, is “deciphering trends and patterns from educational big data, or huge sets of student-related data, to further the advancement of a personalized, supportive system of higher education.” Learning analytics evaluates student behavior in order to determine learning efficiency, creating conversations with students about learning strategies and how well they feel learning has occurred. Technology allows us to study learning experiences through the capture and analysis of learning and performance data.
“Analytics provides a new model for college and university leaders to improve teaching, learning, organizational efficiency, and decision making and, as a consequence, serve as a foundation for systemic change,” said George Siemens and Phil Long in their article about learning analytics.
A key feature of learning analytics is its learning-centric focus, analyzing student performance outside of the classroom in order to gain a new understanding of the efficiency of students, teachers and the curriculum. Beyond basic retention and completion, learning analytics produces students with both inquiry and analysis focus and critical and creative thinking skills.
The implementation of learning analytics requires restructuring academic institutions, to include re-evaluating the flow of data between departments, increasing personal student support, reshaping course design, delivery and more. These changes will be felt by the faculty, students and the institution as a whole. Collaborative and creative leadership is essential in fostering an academic environment that can support and utilize learning analytics.
The Online Instructional Design & Technology program at Brandeis GPS offers foundational skills through the study of instructional design principles, educational technology, and adult learning theories. Students gain the experience needed to solve a variety of instructional challenges and, ultimately, create and deliver high-quality online programs and interactive courseware.
In large part because of the continuous growth in online programs, the Bureau of Labor Statistics data demonstrates that jobs in instructional design and technology have grown 20.8% since 2004, and project above average growth as high as 20% for instructional design jobs between 2010 and 2020. In the next four years alone, the bureau projects over 36,000 new jobs will become available in instructional design and technology.
This reveals the growing forum for learning analytics and Strategic Analytics, also offered at Brandeis Graduate Professional Studies. Brandeis GPS is hosting an Analytics 360 Symposium on Wednesday, April 8, 2015 from 9am-4:30pm at Hassenfeld Conference Center of Brandeis University in Waltham, Massachusetts.
The day-long symposium will focus on promoting a discussion of the growing field of analytics and how organizations can leverage big data to make more strategic decisions. Panelists will engage in a conversation that places analytics in the context of big data, education, health, marketing and business.
Register here for the Analytics 360 Symposium on April 8, 2015 at Brandeis University. The cost for NERCOMP members is $135 and the cost for non-members is $265. Submit this form to learn more about special pricing available to members of the Brandeis community. For more information, email analytics360@brandeis.edu or call 781-736-8786. You can also find us on Twitter using #GPSAnalytics.
Click here to subscribe to our blog!
© 2023 Brandeis GPS Blog
Theme by Anders Noren — Up ↑
Brandeis University | Blogs @ Brandeis | Write a Blog
Welcome Guest | Login (Brandeis Members Only)