Jupyter notebooks offer multiple pedagogical scenarios for teaching computational competences in sciences and engineering courses.In this workshop, we want to help teachers design educational Jupyter notebooks so that their students go beyond “just playing” with code and a graph or animation.This workshop centers on a set of criteria, in the form of a rubric, which can be used to ensure that Jupyter notebooks are designed to effectively reach the intended students' learning goals.Participants will work with two different educational Jupyter notebook examples to gain familiarity with pedagogical scenarios for using Jupyter notebooks, learn to identify quality criteria, evaluate instructional quality using the rubric, and propose improvements.The session will foster collaboration and reflection and enable educators to design didactically powerful instructional notebooks that teach disciplinary and computational thinking in the most efficient ways.Overall, the rubric offers a systematic approach to enhance the effectiveness of instructional Jupyter notebooks, contributing to improved teaching and learning outcomes in computational thinking skills embedded in disciplinary education.