Sentino Personality API – Psychology NLP

Personality API, Big Five

Sentino Personality API – Psychology NLP

Personality API, Big Five

AI in Education – Personalized Learning Paths

Problem

AI in Education – Personalized Learning Paths

Traditionally, governments of the relevant federal states manage educational institutions in Germany, including secondary schools. In average, there are above 3,000 of schools in each federal state.

The local government is quite autonomous in dealing with educational issues. Among other things, it determines the academic content of pre-university training in senior secondary schools. At that, special attention is paid to students’ preferences, on the one hand, and development of a future-oriented and economically feasible educational model, on the other hand.

It is desirable to implement an unbiased scientific approach to examination of students’ preferences in senior secondary schools. The aim is to implement a standardized procedure for selection of a majoring field and academic content (compulsory and elective courses) for three years of pre-university training. However, the authorities often face a challenge – they are forced to take into consideration three equally important aspects: preferences of students, vocational interests and workload of teachers, current and future demand for certain professions and specializations.

Solution

Students' personality testing and intelligent data scoring with Sentino API

Our team can propose a comprehensive solution that includes students’ personality testing and subsequent intelligent data scoring with Sentino API. It allows both to increase the satisfaction level of students, teachers, and parents and optimise high-quality subject-oriented education based on a cost-saving approach. The whole process includes the following steps.

1. Personality Testing

Each student passes a small personality survey: completes a questionnaire of 10 questions and writes a short text self-description (“My Major Strengths and Weaknesses”).

2. Result Scoring

After, Sentino API processes test results and text data according to the RIASEC scale. The analysis helps to define the relevant spheres of vocational interests of each student. They are the following: Natural Resources, Health Services, Industrial and Engineering Technology, Arts and Communication, Business, Public and Human Services. Based on this information, it is possible to group students with due account of similarity of their vocational interests, representing different majoring fields. Thus, majoring fields, which are not popular with students, are included in the curriculum just in their minimum compulsory volume. The resources saved are re-directed into popular spheres.

3. Personalized Academic Content Selection

During the next step, young persons choose academic content of their pre-university training (i.e. individual compulsory and elective courses). Academic courses are proposed by teachers and school management with regard to future university training of students and demand for various specialists in German, European and global labour market. Moreover, it becomes possible to systemize and optimize the workload of teachers.

Benefits

Advantages
  • Standardized scientific approach to majoring field selection for students of senior secondary schools across the federal state
  • Unbiased and transparent procedure
  • Careful consideration of individual vocational interests
  • Future-oriented approach to education
  • Economically feasible and cost-effective organization of senior secondary education
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