GECKO

(Graph-based Environment for Competency and Knowledge item Organization)

This project aims at developing a technique, framework and platform to comprehensibly evaluate different curricula, standards and competency models for computer science education in primary and lower secondary schools. The idea behind this new methodology is to represented knowledge items of different curricula, educational standards or competency models for computer science as single vertices of a graph and connect them with relations. During the project a web-based platform to display, evaluate and develop curricula for computer science related topics, is build.

Project team

Project coordinator

Mag.Dr. Stefan Pasterk

+43 463 2700 3585
Stefan [dot] Pasterk [at] aau [dot] at

Software Development

Philipp Mödritscher, MSc

Quality assurance

Univ.-Prof. Dipl.-Ing. Dr. Andreas Bollin

+43 463 2700 3516
andreas [dot] bollin [at] aau [dot] at

Mag. DI Dr. Max Kesselbacher, B.Sc.

Project description

The curricula are mapped to a graph database (neo4J) and represented as directed dependency graphs. We call the elements within a curriculum competencies and they display the vertices/nodes of the graph. These are connected by two different relations: ‘requires’-relation and ‘expands’-relations. So, if a competency is related to another competency by a ‘requires’-relation, the first competency should be already known by students before they start to work on the second competency.

The relations between the competencies are added from scratch and are evaluated by experts, using spreadsheets. For the purpose of a user friendly tool, our platform provides a comfortable, fast and motivating user interface for experts’ evaluations. The results from these evaluations are stored and displayed within the tool. Researchers and developers with a valid account are able to retrieve these results in different statistical forms. To improve administration researchers and developers need a comfortable and fast way, to upload new curricula or edit existing curricula in the graph database and represent them as graphs.

The main aim of this project is it to provide teachers or curriculum developers the possibility to develop a new curriculum, following several criteria. So, teachers who are developing a curriculum for their class are able to filter the competencies they can reach, for example by a specific age-group, and receive suggestions, which competencies the students should already have. They can dd or delete suggested competencies to design their individual curriculum.

GECKO is an important component in the larger project DigiFit4All. It is used to collect competencies for computer science and digital education and to develop new competency models. National and international curricula, educational standards, and competency models build the basis for the competency collection. With the help of the models created in GECKO, learning paths can be calculated and competency profiles of learners can be stored to support the creation of personalized open online courses (POOCs).

Funding: Institute
Duration: 2016 –

Downloads:

Technical Report: Basic Digital Education in Austria (created February 20, 2017) (PDF Download)
Handout: A Graph-based Approach to Analyze and Compare Computer Science Curricula for Primary and Lower Secondary Education (PDF Download)

Publications

Stefan Pasterk, Andreas Bollin: Digital Literacy or Computer Science: Where do Information Technology Related Primary Education Models Focus on?. 2017 15th International Conference on Emerging eLearning Technologies and Applications (ICETA) , IEEE, Piscataway (NJ), 2017,

Stefan Pasterk, Andreas Bollin: A Graph-based Approach to Analyze and Compare Computer Science Curricula for Primary and Lower Secondary Education. Proceedings of th 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITICSE), ACM Press, New York (NY), 2017,
Stefan Pasterk, Andreas Bollin: Graph-based Analysis of Computer Science Curricula for Primary Education. 2017 IEEE Frontiers in Education Conference Proceedings, IEEE, 2017,