Entscheidungsbäume do it yourself (DIY) – Datenbasiertes Entscheiden
Overview
In the project "BaeumeDIY," we are developing an online self-learning course that will be published on the KI-Campus platform. This course is specifically designed for prospective teachers and active educators in secondary levels who wish to engage in a detailed and interactive exploration of the AI method Decision Trees. The focal point of the self-learning course is the understanding and creation of decision trees as a data-based AI model. To achieve this, real data as well as the interactive Data Science platform CODAP are utilized, providing learners with the opportunity to independently create and comprehend decision trees. The integration of CODAP enables a practical and illustrative approach. Additionally, the self-learning course will offer suitable, already tested materials for classroom instruction, which will be provided and reflected upon. This allows participants not only to acquire theoretical knowledge but also to deepen their understanding through practical application in the educational context. The goal of the "BaeumeDIY" project is to create a high-quality learning environment that offers prospective teachers, educators, and all interested individuals the opportunity to engage in a well-founded and practical exploration of decision trees as an AI model.
Key Facts
- Keywords:
- Data Science Education, AI Education
- Grant Number:
- 16DHBQP044
- Research profile area:
- Transformation and Education
- Project type:
- Knowledge transfer
- Project duration:
- 07/2021 - 02/2022
- Contribution to sustainability:
- Quality Education
- Funded by:
- BMBF
- Websites:
-
Homepage
Link zum Selbstlernkurs
