Challenge 11. Develop longitudinal graduate tracking system: conducting effective joint data collection and analysis (e.g. market needs, unemployment rates, completion and placement rates)
With reference to Quality Assurance systems and particularly to Check phase, the graduate tracking system represents a priority in Europe (New Agenda for Skills, 2016) as the collection of several data can support the improvement of the Higher Education system itself. However, not only do HEIs face difficulties in collecting and comparing very different data, but in some cases, they also do not apply appropriate tools and evaluation methodologies for collecting and interpreting relevant data.
Moreover, the collected data are not always used for strategic planning and improving HEIs educational offer.
The development of a longitudinal tracking system could instead enhance Universities’ capacity of guaranteeing the quality and relevance of the training programmes, in line with students’ and Knowledge Triangle actors’ actual needs and challenges.
As a consequence, such a system would ensure joint cooperation of key Knowledge Triangle actors and increase data comparability among countries.
Guideline 22. Evaluate the learning method and tools’ effectiveness against the labour and research needs
HEIs should engage business and research organizations within the FRAMELOG for gathering and analysing relevant data in order to be able to assess the level of quality of the educational programmes. This data should refer in particular to: completion of the education programmes, impact of the method and tools implemented on the learning process and results, placement rates, student readiness for further learning, level of employability skills, etc.
- Based on specific performance indicators set-up in the planning phase, asses the quality of the methodological approach and tools used within the educational programme
- Involve business and research organizations, as well as students and other stakeholders that participated at the educational programme in the assessment
- Collect and analyse the input received and make the necessary revisions in order to ensure the quality and relevance of the education programme and to strengthen the FRAMELOG implementation.
- Use demand forecasting techniques for planning and decision making; use historical data to identify patterns which are likely to continue and use mathematical models to predict future demand
- Use advanced analytics to turn information into action to identify optimal courses of action.
Guideline 23. Assess training effectiveness (use of acquired competencies in work-field context – through survey/interviews with companies and research organizations)
The employability opportunities and the economic growth of the logistic and supply chain management area depend both on the capacity of students to put into practice the skills and competences build within the education programme. Therefore, the assessment phase should refer not only to knowledge, skills and competences acquired, but mainly on the capacity of the student to use them in a work-field environment (e.g. in case of internships, stages, work-based learning programmes, etc.).
The implementation of FRAMELOG facilitates sustainable cooperation among the key players (HEI, companies and research institutions) and therefore, allows HEIs to measure periodically the effective application of the learning outcomes in a work-field context.
Through the various cooperation activities indicated in Framework it is necessary to collect also information about which competences students can really use in the work-field activities and with which results.
- Apply assessment instruments that can provide relevant data regarding not only the competences built, but in particular the students’ ability to use them in work-field environments
- When organizing cooperation activities, in particular face to face meetings, interviews, roundtables, focus groups, ask questions regarding: e.g. which competences students actually use in accomplishing their tasks in the work-field context, with which results they use these competences, which are the missing competences if any, etc.
- In addition to these cooperation activities, it is necessary to conduct also structured surveys/interviews that will allow more relevant and comparable data on this issue.
UNWE (University of National and World Economy) work with a consortium of stakeholders including non-profit sectoral and professional organisations, manufacturing and commercial companies with well-developed logistics departments, logistics service providers, and suppliers of logistics equipment and software to develop a competency-based approach to curriculum design, taking into account the opinion of the students and the business (https://www.unwe.bg/en).
Challenge 12. Apply feedback loops mechanisms among the three sides of the ‘Knowledge Triangle’ (University, Research and Business)
As the Knowledge Triangle is mainly based on the cooperation between HEIs, Business and Research, such a collaboration should be applied not only for developing new programmes, contents and activities, but also to customize and correctly implement cooperation procedures and trends throughout all the education phases and beyond.
In particular, organizations (HEIs, Research institutions and business sector) register difficulties in maintaining active their collaboration also after the end of the education/training activities. During this phase they could have the opportunity to communicate information about the relevance of education/training, the actual implementation of competences built during the education/training activities, future needs and trends. Although all these organizations are aware of the relevance this stage has on the Knowledge Triangle implementation and on the overall quality of the education and training, they are still facing difficulties in improving their cooperation and communication in this regard.
Guideline 24. Develop and continuous update of a ‘feedback loop’ mechanism within the FRAMELOG, involving key actors from the logistic and supply chain management area
In order to guarantee not only the sustainability of FRAMELOG, but also its improvement over time, the key players should stay in permanent connection based on specific agreements and established working mechanisms that allow for smooth flow of data and communication.
This permanent exchange of data and experiences, based on specific conventions (that make clear statements regarding cooperation objectives, methods, performance indicators, tools, etc.) and having precise goals is the fundamental condition for ensuring the quality of the educational programmes and the sustainability of the FRAMELOG application.
- Based on the cooperation agreements, conduct permanent communication of data among the three key players in order to ensure that the educational programmes are always up to date for the industry and for the research environments (e.g. use common online platforms, regular emails and/or meetings, formative assessments, etc.)
- Organize Peer-Review activities among the key players in order to collect qualitative feedback and data, and for enhancing the cooperation
- Implement appropriate data management activities (that provide scientifically relevant data analysis, that provide accurate and integrated data from the key stakeholders, that provide data relevant and customized for HEIs, research and business, etc.) that allow for effective data analysis benefitting all main players: HEI, business and research organizations, students, the logistic and supply management area in general at all levels.
The Politecnico di Milano School of Management ‘ Observatory on Contract Logistics’ is part of the Observatories on Digital Innovation system by Politecnico di Milano School of Management with a group of 20 companies acting as partners of the Observatory . Workshops are organized to transfer outcomes of the Observatories to Business School students (https://www.mip.polimi.it/en/).