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New developments in the UK Higher Education. Dr Inna Pomorina Bath Business school. Рамки профессиональных стандартов. Areas of Activity. A1 Design and plan learning activities and/or programmes of study A2 Teach and/or support learning A3 Assess and give feedback to learners
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New developments in the UK Higher Education Dr Inna Pomorina Bath Business school
Рамки профессиональных стандартов
Areas of Activity • A1 Design and plan learning activities and/or programmes of study • A2 Teach and/or support learning • A3 Assess and give feedback to learners • A4 Develop effective learning environments and approaches to student support and guidance • A5 Engage in continuing professional development in subjects/disciplines and their pedagogy, incorporating research, scholarship and the evaluation of professional practices
Core knowledge • K1 The subject material • K2 Appropriate methods for teaching, learning and assessing in the subject area and at the level of the academic programme • K3 How students learn, both generally and within their subject/ disciplinary area(s) • K4 The use and value of appropriate learning technologies • K5 Methods for evaluating the effectiveness of teaching • K6 The implications of quality assurance and quality enhancement for academic and professional practice with a particular focus on teaching
Professional values • V1 Respect individual learners and diverse learning communities • V2 Promote participation in higher education and equality of opportunity for learners • V3 Use evidence-informed approaches and the outcomes from research, scholarship and continuing professional development • V4 Acknowledge the wider context in which higher education operates recognising the implications for professional practice
TEF • What is TEF? • TEF is the Teaching Excellence Framework, introduced by the Government in 2016 ‘to recognise and reward excellent learning and teaching.’ • Learning and teaching will be recognised by Gold, Silver and Bronze awards to providers. A ‘statement of findings’ from the assessors will be published in conjunction with the award.
Implications of the Teaching Excellence Framework TEF aims to: • Provide an excellent (measurable) teaching experience • Ensure teaching has equal status with research - staff promotion • Provide students with the information they need to judge teaching quality • Social mobility - WP, better retention and progression to further study or a graduate job • Move to clearer outcome-focused criteria and metrics.
TEF • What does TEF mean for universities? • TEF will affect both reputation and finances: TEF outcomes will inevitably be used by prospective students deciding where and what to study; and a university’s ability to raise student fees (in line with inflation) will be directly linked to its TEF award
TEF • How does it work? • TEF is an annual exercise that will be implemented by the Higher Education Funding Council for England (HEFCE). Participating universities make submissions that are a combination of data and narrative themes. • What will be measured in 2017? • In 2016-17, TEF awards will be based on two bundles of information from each university: • i. an evidenced narrative of teaching and learning activities that either mark them out as distinctive, or exceed the established expectations for teaching quality as used by the QAA • ii. institution-wide data that is already collected, comprising teaching quality, learning environment (including student retention) and student outcomes (Destinations of Leavers from Higher Education (DLHE) survey). • Widening participation performance is woven throughout the submission.
Six ‘core’ metrics • Teaching on my course (NSS) • Assessment and feedback (NSS) • Academic support (NSS) • Non-continuation (HESA and ILR data) • Employment or further study (DLHE) • Highly skilled-employment or further study (DLHE) • As well as the headline core metrics there are ‘splits’, which look at variations in each of the core areas by (amongst others) gender, ethnicity, age and disability. The aim of the split metrics is to establish how students from different backgrounds fare on the various measures relative to their peers. • TEF is aiming to incentivise institutions to look seriously at – and address – inequity amongst different student groups; highlighting differences in this way will show where the work needs to be done, and where good practice can be celebrated.
Annual Provider Review by HEFCE • Replaces QAA Reviews • University Submission based on publically available data and Governing Body assurance on quality • The combination of intelligence, assurance and data considered by the HEFCE Quality Committee to make the final judgement. • Published outcomes (for 2016-17 in April/May 2017)– ‘quality judgments’: • Meets requirements • Meets requirements with conditions • Pending – further investigation/intervention and may lead to judgments that the provider does not meet Annual Provider Review requirements or does not meet baseline requirements
Based on data supplied to HEFCE • HESES; HEIFES; HESA; ILR; • Performance indicators on non continuation rates (UG and PG) and WP; • NSS; • TEF indicators; DLHE; degree outcomes. • It will consider: • Student recruitment patterns – actual and forecast • Sub contract arrangements • Student profile • Retention • DLHE • Participation of under represented groups • Student satisfaction and teaching quality (via NSS) • Degree profiles
NSS • The NSS is a key source of data about student experiences. It was designed to inform student choice and contribute to public accountability; it is also used by the media as a data source for university league tables. In examining the survey, there are certain issues around collection of the data which HEFCE should be aware of when considering the use of NSS data as part of quality indicators: • • under-reporting of certain groups and over-coverage of others is a matter of concern and could lead to bias in use of the data • • the lack of a voice from those who did not complete their course is a potential weakness in the planned quality indicators; neither DLHE nor NSS have this element. As for the previous point, this could result in bias. While the NSS response rates are good by modern standards, an understanding of the nonresponders would be of significant benefit