提升教師專業學習社群之可行策略探究：「資料導向決定」觀點   全文下載

The Study of Enhancement of Teachers' Professional Learning Communities by Using Data-driven Decision Making

提升教師專業學習社群，已成為當前主要教育政策推動之議題，而資料導向決定對於提升教師專業學習社群之發展，具有其重要性。本文旨在運用資料導向決定的觀點來探討教師專業學習社群之發展，首先介紹資料導向決定之發展背景、意義及內涵；其次，再論述教師專業學習社群的意義、內涵與實務困境；再者，探究資料導向決定對於教師專業學習社群之重要性；最後，以資料導向決定的觀點，探討促進教師專業學習社群的四大可行策略，其包括：一、提倡資料導向決定的知識領導，積極投入社群發展；二、形塑資料導向決定文化，營造合作夥伴關係；三、設立資料倉儲整合平臺，提升學習社群效能；四、有效蒐集各方資料觀點，凝聚社群共同願景。

Enhancement of teachers' professional learning communities is a primary issue in education. Data-driven decision making (DDDM) plays a very important role in teachers’ professional learning communities. We begin our discussion by explaining the nature and development of DDDM. Then, we discuss the meaning and practical difficulties of teachers' professional learning communities. Next, we analyze the importance of DDDM in teachers' professional learning communities. Finally, we present the following measures to enhance professional learning communities, including: 1. Promoting knowledge leadership related to DDDM and devotion to community development; 2. Shaping the culture of DDDM and creating relations between cooperative partners; 3. Building an integrated data warehouses platform and enhancing the effectiveness of the learning community; and 4. Collecting different opinions and concentrating on the common aspirations of the community.