The SQELT project intends to develop a refined, comprehensive model of PIs or integrative core dataset in the field of L&T, including data definition, data formats and software-adequacy. The integrative core dataset in L&T shall be prepared for its use in per-formance data analytics. It is a background assumption of the project that it still is a desideratum – for teachers and students, universities’ strategies and governance, quality assurance agencies, employers, higher education research, and higher education politics – to look deeper into the ‘big black box’ of competence-oriented quality and quality development in L&T. It is particularly im-portant to undertake such investigations within the framework of integrative, non-reductionist approaches to teaching-and-learning-and-assessment, because of the multiplicity of universi-ties’ performance areas and stakeholder interests, and the interconnectedness of the processes within L&T (and with research and institutional management).


Duration 01/09/2017 - 30/11/2020
Funding EU
Program ERASMUS+

Department for Continuing Education Research and Educational Technologies

Center for Educational Management and Higher Education Development

Department for Higher Education Research

Principle investigator for the project (University for Continuing Education Krems) Univ.-Prof. Dkfm. Dr. habil Attila Pausits
Project members


Barbato, G.; Bugaj, J.; Campbell, D.F.J.; Cerbino, R.; Ciesielski, P.; Feliks-Dlugosz, A.; Milani, M.; Pausits, A. (2022). Performance indicators in higher education quality management of learning and teaching: lessons from a benchlearning exercise of six European universities. Quality in Higher Education, 28/1: 82-105

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