EARCOS Sponsored Weekend Workshop (2014)


With Jennifer Sparrow

October 17-18, 2014


Understanding by Design.  Developing and using rubrics.  Balanced assessment systems. Using data results.  Differentiation. Professional Learning Communities.  These are all buzz words in education today for a good reason – each one has been shown to have a positive impact on learning.  Unfortunately in practice they are often seen as “one more thing to do,” resulting in initiative fatigue. One approach that helps all of these areas develop is to integrate the implementation of these initiatives under one umbrella goal: Common Assessments.


As a result of this workshop, participants will deepen understanding of how to:

  • use Common Assessments to integrate unit planning, balanced assessment approaches, quality rubrics, using data results to inform instructional decisions, and professional learning communities;
  • develop quality assessment tasks and associated rubrics/scoring guides (or refine ones that already exist);
  • explore protocols for calibrating scoring of common assessments;
  • become familiar with a data-driven decision-making protocol that can be used to inform instructional decisions; and
  • support common assessments through Professional Learning Communities (PLCs).

Date:  October 17-18, 2014
Time:  Friday, 8:00 to 4:00
Saturday, 8:30 to 3:30

Venue:  Morrison Academy, Taichung, Taiwan
136-1 Shui Nan Road, Taichung, Taiwan

Workshop  Fee: USD $50
Registration Deadline:  October 10, 2014
Graduate Credit:  1 hour SUNY (Additional cost)

Contact:  Matt Strange (strangem@ma.org.tw )


Jennifer Sparrow, Executive Director of Teaching & Learning at Singapore American School, has thirteen years of middle school teaching and eight years of school-wide administrator focused assessment and data use.  She has experience with theory and practical implementation of quality formative and summative assessments. Jennifer gives real-world advice for engaging teams of teachers, teacher leaders, and administrators in analyzing data at many levels and for different purposes.