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|
Center for Educational Management and Higher Education Development
|Principle investigator for the project (University for Continuing Education Krems)||Univ.-Prof. Dkfm. Dr. habil Attila Pausits|
|Project members||Priv.-Doz David Friedrich James Campbell|
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