Digitalization in Swiss schools

Cooperation partners

DigiPrim cooperates with other research groups:

The PANDA project is a cooperation between researchers from the Interfaculty Centre for Educational Research (ICER), the Swiss Distance University of Applied Sciences (FFHS) and the Pädagogische Hochschule Bern (PHBern). It is funded by the initiative BeLEARN and collaborates with the DigiPrim and ÜGK project teams.

PANDA uses process data from the digital-based assessment within the framework of the ÜGK 2024 pilot to inform the development and administration of future assessments. The data will be used to cluster students into groups with different usage behaviour and to gain insights about suspicious test items.

Unlike traditional assessments, digital-based assessments (DBAs, also called computer-based assessments) collect process data, such as student choices and interactions with the assessment environment. These process data provide information about the actions taken by students while solving test items. The BeLEARN project PANDA investigates usage patterns (e.g., response and reaction times, number of clicks, skipping patterns) generated by students’ actions during the DBA. Students’ usage patterns can be utilised to better understand the assessment development and administration processes in schools, during lessons, and for teaching.

Using process data from the Überprüfung der Grundkompetenzen (Assessments of Basic Skills, further referred to as UGK), the project’s main goal is the discovery of usage patterns in solving items across different school languages in the UGK trial data collected in 2022 (grade 2). This strand of research will contribute to a better understanding of how the UGK and assessments for 8-year-olds should be developed and administered and inform assessment developers, practitioners, researchers, and policy makers. For example, the insights from the trial data can inform the development of future main studies. 

PANDA currently encodes the information provided in log files and runs a retrospective analysis of the log files to find suspicious test items based on the usage behaviour of students. In the next step, the data will be used to cluster students into groups with different usage behaviour. We think that these clusters can describe the patterns and give further insights about the suspicious items. The next steps will include the inspection of the patterns from the didactical perspective to establish potential theoretical and didactical implications.

Project team:

Dr. Andrea Erzinger, Dr. Jessica Herzing, Dr. Simon Seiler (ICER), Dr. Martin Hlosta, Dr. Sukanya Nath, Prof. Dr. Per Bergamin (FFHS), Dr. Florian Keller Zai (PHBern)

Duration:

02/2023 - 06/2023