University of Maryland, Baltimore County and a local government agency are working collaboratively to examine Competency-Based Education and identify opportunities to use learning analytics and adaptive learning techniques to both improve student learning outcomes and more effectively and efficiently train employees.
The demand for frequent training is stronger than ever for today's government and industry employee. Shrinking budgets, time constraints, and quickly changing trends have motivated employers to look for training solutions that are online, just-in-time, and customized in order to address the recurring need for education and training to remain competitive and thrive. Academia is attempting to address this challenge by offering more online programs, but these programs often exclude direct linkages to competencies required by employers, and fail to use the full power of learning analytics. Furthermore, employers are slow to adopt new, useful strategies incorporated by academia that could significantly improve job training processes, both for the employee and the employer.
The University of Maryland, Baltimore County (UMBC) has been involved in a University System of Maryland (USM) badging initiative called B.E.S.T - Badging Essential Skills for Transitions - which aims to help students demonstrate career-ready skills, or competencies, acquired through either curricular or co-curricular experiences. Like our local government agency partner, UMBC is looking beyond this system-wide initiative for strategies to leverage online tools that offer student-centered, flexible solutions that enable students to acquire the necessary skills and competencies.
During the 2018-2019 academic year, UMBC and a local government agency will combine their efforts in collaboration to address this problem.
In this session, the collaborating organizations will describe their plan and process for addressing the aforementioned issues. We will examine Competency-Based Education (CBE) with online instruction and identify opportunities to use learning analytics to influence student outcomes. We will then discuss the potential benefits of incorporating academic strategies using CBE, the use of predictive analytics and adaptive learning techniques into government and industry training programs to more effectively and efficiently train employees.
This session is ideal for both academic and industry leaders, faculty and staff interested in learning ways to collaborate with others in education and training domains, especially on the examination and identification of innovative teaching and learning strategies. Slides and web resources will be posted on the conference website and shared during the session. The speakers will use web-based response systems to poll the audience with multiple types of questions including open-ended feedback.