ASMT - 105 Data Informed Improvement  The ‘Data Informed Improvement’ micro-credential earners have a functional understanding of definitions of improvement science, continuous improvement, learning improvement, the Learning Improvement Process, and academic innovation. This micro-credential focuses on the importance of using assessment results to improve student learning.
This micro-credential is in the Academic Assessment Series, which consists of five modules focusing on foundational aspects of academic assessment and continuous improvement.
Upon completion of this micro-credential, learners will be able to:
- Articulate the difference between the concepts of improvement science, continuous improvement, and learning improvement as they apply to our work in higher education assessment.
- Determine the most effective way to present a set of assessment data for a learning improvement review.
- Analyze assessment data to identify learning improvement strategies.
- Explore how academic innovation is used in higher education to advance student success.
Earning Criteria: To earn this micro-credential, learners must:
- Complete an online learning material on using informed data of course or program assessments.
- Submit an assignment to identify specific strategies for implementation for their own program or course using theories and skills gained from the module.
- Attend a synchronous learning session to demonstrate skills in educational assessment and the continuous improvement process. The assessment team provides qualitative feedback on the learner’s prior assignment during the synchronous session. Following the session, participants are provided the opportunity to submit the final version and a rubric is used to share additional feedback.
- Submit a final quiz. If learners receive less than 80% on the quiz, they are prompted to retake the quiz.
Skill(s):
- Continuous Improvement Process
- Educational Assessment
Tags: #LearningImprovement, #ImprovementScience, #ContinuousImprovement, #AcademicInnovation Status: Active
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