Big Data in Psychological Assessment Erasmus Project

Project Title

Big Data in Psychological Assessment

Project Key Action

This project related with these key action: Cooperation for innovation and the exchange of good practices

Project Action Type

This project related with this action type : Strategic Partnerships for higher education

Project Call Year

This project’s Call Year is 2017

Project Topics

This project is related with these Project Topics: New innovative curricula/educational methods/development of training courses; ICT – new technologies – digital competences

Project Summary

Big data has become crucial for the success of organizations in every sector. Governmental, cultural, medical, and business organizations use newly available data and analytical tools to understand and to deal with challenges. In the field of occupational psychology, methods for recruitment and selection by means of algorithms and artificial intelligence are being developed. The entrance of algorithms in the area of recruitment and selection urges professionals in the field to fundamentally rethink the role of assessing ‘classical knowledge’, traits and skills typically used for this process. In addition, the role of the assessor, the psychologist, the consultant, or, stated more generally, the human expert, needs to be redefined in all phases of the recruitment and selection procedure. Psychologists have to explore the ways in which the development of a more data-driven society should be integrated in their education to make sure that students and professionals possess the right skills and knowledge: knowledge and skills in data and ICT requirements, in addition to ‘classic’ knowledge and skills, are becoming more and more valuable. Graduates need new adaptive knowledge and skills in order to be fully prepared for the rapidly changing field of occupational psychology. Therefore students need to have:

• Data skills: have an understanding of the vast developments in data and computer science and their relevance to psychological knowledge and skills in recruitment and selection issues, which is accompanied by a critical attitude towards the possibilities and limitations of computer and data science;
• Interpretational skills: have to be able to interpret findings from big data and computer science research in terms of their relevance to the area of recruitment and selection.

This combination of data skills and interpretational skills relating big data to the recruitment and selection domain completely lacks in the existing master programmes in the field of occupational psychology. Therefore this project aims to incorporate data science in the master programs by developing and implementing state-of-the-art education through the development of a set of different modules on the integration of data science in the field of occupational psychology. The main objectives of this Strategic Partnership on Big Data in Psychological Assessment are:

1. To start up and intensify the network of organizations with valuable knowledge and expertise in the field of occupational psychology and data science;
2. To encourage the contribution of non-academic stakeholders to education;
3. To develop international state-of-the art master modules, addressing current educational and labour-market needs.

Students (at Saarland University and Erasmus University Rotterdam) will gain understanding in the vast developments of the use of big data in psychological assessment, based on a well-informed and critical attitude towards the possibilities and limitations of computer and data science. They will acquire in-depth knowledge on big data and will learn basic skills in data analysis and in collecting big data information (social networking sites etc.) from the internet. Students at TU Delft will learn that the underlying assumptions of big data have to be valid and non-discriminatory seen from an applicants’ and psychological perspective. To this means, students will learn about the basic concepts of recruitment and personnel selection. Students will also learn to incorporate this knowledge when building algorithms.

To guarantee a high-quality and impact/cost effective project, the partners have set up an adaptive monitoring and evaluation model, which builds on the Partnership Effectiveness Model (PEM). PEM is a monitoring and evaluation approach, developed by EUR that helps practitioners to get access to relevant knowledge on partnerships. It is composed by two dimensions: descriptive and analytical.

The activities and contribution of EPSO, as Associated Partner, are not funded by this project. This means that this Strategic Partnership offers real value for money as the contribution of EPSO has not to be paid out of the budget.

This project contributes to a long term and systemic transformation of higher education and of business. The project’s aim is to build synergies between theory and practice, between data science and psychology and between business and universities. This project will educate a new generation of psychologists and data scientists with a different, more balanced mind-set linking the business operations to the universities. Being aware of these interdependencies will benefit partners, associated partners and stakeholders in a variety of ways and will have impact on a local, regional, national, EU and global level.

EU Grant (Eur)

Funding of the project from EU: 273517 Eur

Project Coordinator

UNIVERSITAT DES SAARLANDES & Country: DE

Project Partners

• Owiwi
• TECHNISCHE UNIVERSITEIT DELFT
• PRECIRE Technologies GmbH
• ERASMUS UNIVERSITEIT ROTTERDAM
• D&D Consultants Grup