UTA Launches Online Graduate Degree in Learning Analytics

In response to the accelerating impact of digital technologies on learning, The University of Texas at Arlington will launch an online Master of Science in learning analytics in fall 2021.

Wednesday, May 19, 2021 • Linsey Retcofsky :

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More Info on UTA's MSLA Program

George Siemens, professor of psychology, said the new degree will prepare students to meet the growing demand for learning analytics professionals across a variety of industries.

Learning analytics is the measurement, collection, analysis and reporting of data regarding learners and their contexts to understand and optimize learning and the environments in which it occurs. The discipline combines data science techniques, psychology, education and technological innovation.

Job opportunities for learning analytics are more abundant than workers who can perform them. The lack of a learning analytics workforce motivated Siemens and colleague Justin Dellinger, learning analytics program coordinator, to establish the graduate degree at UTA.

“Graduates of this program will have wide-ranging opportunities, from positions in government agencies to academic settings to large corporations,” Siemens said. “Any organization that deals with an abundance of data to try to understand social and knowledge processes needs employees with this expertise. There is a huge gap between demand for employees and supply.”

Dellinger said the degree will prepare students to develop an integrated and nuanced understanding of how to use data to improve learning and organizational performance and how social systems solve problems and evolve.

“As a global program, we anticipate participation from students representing diverse backgrounds,” Dellinger said. “They will bring different experiences and skill sets to the classroom while collaborating to solve real-world problems.”

A pivotal goal of learning analytics is to discover methods of education that are more effective than traditional curriculum-centered techniques that often neglect learner experiences.

“In many ways, the teaching and learning models we have now are problematic since the focus is on teaching rigid curriculum rather than developing students’ abilities to respond effectively to complex changes,” Siemens said. “Learning analytics has the potential to play an orienting role in helping society transition to a more collaborative model of learning—one that accounts for learner knowledge as well as curriculum content.”

Following those ideals, Siemens and Dellinger designed learner-centered courses that employ engaging and responsive teaching and learning methods.

“We call it computed curriculum,” Siemens said. “We will build learner profiles to chart a student’s progress through their courses. As one demonstrates mastery in an area, a different type of learning resource will be provided to them. We will use the profiles to gain insight into how we can restructure student experiences to target the depth of their learning, rather than simply targeting the curriculum.”

Morteza Khaledi, dean of the College of Science, said the program substantiates UTA’s reputation as a world-leading research university.

“UTA’s program will be an example for learning analytics degrees across the world,” Khaledi said. “Drs. Siemens and Dellinger will utilize unique pedagogy and create a leading model for building effective learner profiles to assess students’ learning pathways.”

The Master of Science in learning analytics is intended for individuals who want to pursue a career in fields that are impacted by the digitization of learning and knowledge processes in complex information environments. With the rapid rise of digital technologies for work and learning, this program is ideal for anyone interested in learning how to use data to gain insight into how people and systems produce knowledge. The program will benefit faculty, teachers, corporate learning specialists, sociologists or others interested in using data as a research instrument to understand human social and cognitive processes.