SUSTAINABLE QUALITY ENHANCEMENT IN HIGHER EDUCATION LEARNING AND TEACHING
evalag (Evaluation Agency Baden-Wuerttemberg, Mannheim, Germany) as a lead partner together with nine European higher education institutional partners has been granted a Strategic Partnership for Higher Education within the Erasmus+ Program under the key action Cooperation for Innovation and the Exchange of Good Practices. The project has a duration of 33 months (2017-2020) and is carried out by its ten partners from nine European countries, namely Austria, Belgium, Germany, Italy, The Netherlands, Norway, Poland, Portugal, and the United Kingdom.
SUSTAINABLE QUALITY ENHANCEMENT IN HIGHER EDUCATION LEARNING AND TEACHING. Integrative Core Dataset and Performance Data Analytics
Motivation and goals
Quality assurance (QA) and quality enhancement in higher education institutions (HEIs), particularly in learning and teaching (L&T), is more important than ever because of the requirements of knowledge societies and socioeconomic mobility in a globalized world. This immediately implies the need for systematic performance monitoring and strategic quality development in L&T, but not restricted to L&T.
Therefore the SQELT project aims at establishing a comprehensive set of performance indicators (PIs) and quality evaluation instruments for assessing HEIs’ performance quality in L&T. While the L&T dataset shall include generic core data relevant to any HEI, it is also intended that the L&T dataset will be part of a toolbox from which HEIs can select ‘individual’ PIs and evaluation instruments according to their specific strategic profile, mission and vision. This integrative L&T dataset shall also be prepared for its use in digital performance data management, particularly Learning Analytics, including an ethical code of practice.
The SQELT project intends to contribute to the ‘Research on Indicators of Teaching Quality’, which recently was also recommended to the European Parliament. The results of the SQELT project shall help to ensure HEIs and their stakeholders get maximum benefit from the L&T dataset and digital performance data management. To this end HEIs should use systems that are designed in consultation with stakeholders; supported by an ethical code of practice; driven by the improvement of performance processes and stakeholder engagement; and adjusted to the particular needs and strategic orientation of an institution.
The SQELT project builds on available models of digital performance data management in L&T, an analysis of contemporary literature, digital performance data management models and practice of the project participants, external experts’ knowledge, and surveys with the project’s HEI partners about their assessments of relevance and actual use of performance data and indicators. The L&T dataset will be developed by conceptual analysis and comparison of the various sources including benchmarking of the partner HEIs and an impact analysis to support inductive development of a reference framework for the L&T dataset.
The project has six Transnational Project Meetings and nine Multiplier Events, among them one International Evaluation Workshop, one International Conference and seven Euro-Region Dissemination Workshops. The main outputs will be a Benchlearning Report, an integrative L&T dataset, an Ethical Code of Practice for Learning Analytics, a Manual for the application of the L&T dataset, and, last but not least, peer-reviewed publications of the results.
The main target groups of the SQELT project are HEIs’ actors in L&T and stakeholders interested in L&T quality enhancement, such as students, parents, employers, HE politics, QA agencies. The SQELT project intends to include as many of these as possible. Since SQELT has the character of a pilot project with limited capacities, however, the focus will pre-eminently be on HEIs including students, teaching staff and internal QA, and secondarily on QA agencies and HE politics.
For SQELT project information see also: https://ec.europa.eu/...