It’s no longer enough simply to produce high-quality instruction. Today, you’re expected to engineer engaging, trackable learning solutions delivered at the speed of need. The aims stretch beyond learning to enhancing the employee experience and directly contributing to organizational goals. The means: an evidence-based, data-enabled approach to learning design and delivery. Join Trish Uhl in this 1-day workshop to learn how using advanced analytics can help you support this modern design approach.
Preview what Trish will be covering during the workshop, read her recent article: "Are you ready to start the workplace learning analytics journey?"
Training, talent, instructional design and other experienced learning professionals early in their workplace learning analytics journey. No experience with data science, analytics, statistics or algorithms necessary! Bring your learning practitioner skills, business acumen, organizational knowledge, curiosity and unique talents - -- and have a laptop handy!
TAKE-AWAYS:
Five principles of applying advanced analytics to learning experience design Data mining methods for enhancing the employee experience with a data-enabled approach Using analytics to link learning to organizational goals The skills needed to start developing analytical savvy Future proofing career strategies for staying ahead of the Skills Gap
Workplace Learning Analytics Strategic Planning Framework Tools & Technology Assessment Cheat Sheet Personal Development Plan for Developing Analytical Capabilities
Trish Uhl, PMP, CPLP
Trish is a creator of the Learning Systems Engineering Framework™, engineers learning solutions and leads project teams in design and development of data-enabled, results-driven learning experiences. As co-founder of the Talent & Learning Analytics Leadership Forum, Trish works with heads of Talent & Learning Development globally on setting and executing strategy for learning transformation and data-enablement projects. In addition, Trish works with talent and learning leaders on the professional development of their L&D teams, expanding the team’s focus from instructional products, to engineering dynamic learning systems leveraging data science, AI & machine learning, advanced analytics and predictive modeling to promote positive people impact and drive organizational outcomes.
For sister chapter members special rates, please contact admin@atdchi.org
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Cancellation Policy: All event registration fee refund requests must be submitted in writing to admin@atdchi.org prior to any event. Requests must be submitted at least three (3) business days prior to the event to receive a full refund. No refund will be provided for cancellations received within three (3) business days or for event attendee no-shows.
