AI-supported profile analysis according to Griesshaber for German at the vocational school in Uster
Summary
Evoya AI has developed a modern web application for the Uster Vocational School that automates the entire Griesshaber profile analysis process. This solution uses several AI-supported steps to digitize handwritten texts from students, divide them into minimum sentence equivalent (MSE) units, perform the analysis and output the results in an Excel file. The application enables continuous optimization through centrally managed, easily customizable AI instructions and offers teachers the ability to test and use the process directly via chat agent.
Time saving
per profile analysis
30 - 60 min
Project duration
2 weeks
Process automation
Initial situation and challenge
The previous process for profile analysis according to Griesshaber was time-consuming and manual. Pupils wrote handwritten texts that were manually transferred to an Excel file by teachers. These texts were then divided into minimum sentence equivalent (MSE) units and categorized according to the Griesshaber method. Finally, an evaluation and profile classification was carried out based on the results. The purpose of the profile analysis is to determine the grammatical complexity of the pupils' utterances and their language level. This enables targeted support for the pupils' language skills.
Manually capturing and analyzing handwritten texts from students was error-prone and time-consuming. The different qualities of the handwriting and the students' varying command of the language made it impossible to use conventional optical character recognition (OCR) technologies effectively. In addition, the interpretation of the texts required a high degree of sensitivity on the part of the teachers.
Manually capturing and analyzing handwritten texts from students was error-prone and time-consuming. The different qualities of the handwriting and the students' varying command of the language made it impossible to use conventional optical character recognition (OCR) technologies effectively. In addition, the interpretation of the texts required a high degree of sensitivity on the part of the teachers.
Solution and functions
Evoya AI developed a modern web application that automates the entire Griesshaber profile analysis process. The solution comprises several AI-supported steps:
- Digitization of handwriting: Using advanced AI models to recognize and interpret handwritten texts.
- Division into MSEs: Automatic segmentation of texts into minimum sentence-value units.
- Preparation of the analysis: Categorization and analysis of the subsets according to the Griesshaber method.
- Output to Excel file: Automatic generation and export of the analysis results to an Excel file.
- Continuous optimization: Centrally managed AI instructions that can be easily adapted by teachers, as well as a chat agent for direct use and testing of the application.
Step 1: Digitization of the manuscript (page 1 of 2)
Step 2: Division into minimum set-valued units (MSE)
Step 3: Creating the analysis
Step 4: Output to an Excel file
Step 5: Continuous optimization
Centrally managed AI instructions that can be easily customized by teachers, as well as a chat agent for direct use and testing of the application.
Added value
The automation of the Griesshaber profile analysis offers the Uster vocational school considerable advantages:
- Time saving: Reduction of the manual workload for teachers, leaving more time for individual support for pupils.
Between 30 and 60 minutes can be saved per test. - Accuracy: Increasing the accuracy and consistency of analyses through the use of advanced AI technologies.
- Scalability: Possibility to apply the process to a larger number of students without additional personnel costs.
- Flexibility: Easy adaptation and optimization of AI instructions by teachers to meet individual student needs.
- Future-proofing: Preparation for future enhancements, such as the creation of support plans, personalized exercises and the integration of an interactive tutor for students.
Outlook
The process does not end with the analysis. The next steps include:
- Develop a support plan: Development of individual support plans based on the results of the analysis.
- Personalized exercises: Creation and implementation of personalized exercises related to the students.
- Interactive tutor: Integration of an interactive tutor who works with students based on the support plan and answers their questions.
- Further processes: Additional processes to further support pupils are already being considered.
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