3.3.1 Targeted data collection

Quality management means that developing quality is pursued systematically and is based on facts and figures. Thus, collection of data for assessing achievement of quality objectives is an inevitable practice in all VET institutions that have adopted an internal QMS.

Experience shows, however, that quality-oriented VET institutions often collect too many data and these data are neither analysed nor used, simply because it is impossible to cope with the magnitude of the task. But uncontrolled data collection not only creates unnecessary work; in the long run, it also discourages respondents from giving feedback. Stakeholders flooded with feedback questionnaires, possibly with incoherent questions, will not provide valid answers.

Hence the importance to strictly concentrate data collection on predefined quality objectives of your own VET institution and its core process of teaching and learning, and from the outset to keep collection of feedback from stakeholders within tolerable bounds.

 

Box 13. A piece of advice

Scope of data to be collected should be strictly limited and clearly focused to assess achievement of your quality objectives as defined in the planning stage.

 

Further, the quality manager should ensure that a suitable system for data collection and processing is available and that it requires minimal effort. Nowadays, many inquiries can be performed online and by linking them with an appropriate data processing programme it should be possible to process and analyse the information automatically. It is highly recommended therefore, not to use homemade tools for data collection and data processing, but to take advantage of professional support from outside the VET institution, and in fact in several Member States such systems are provided by relevant public authorities.

In some countries, data processing and analysis of results are undertaken externally by the education authorities, which provide VET institutions with their individual results, together with reference data, by placing their results in a context of average ratio of all institutions, thus allowing for benchmarking and common learning among VET providers.

 

Box 14. Proposals of the EQAVET recommendation

The quality criteria in Annex I of the EQAVET recommendation stipulate that ‘evaluation of outcomes and processes is regularly carried out and supported by measurement’. The descriptors suggest that:

  1. self-assessment/self-evaluation is periodically carried out;

  2. evaluation and review cover processes and results/outcomes of education, including assessment of learner satisfaction as well as staff performance and satisfaction;

  3. evaluation and review include adequate and effective mechanisms to involve internal and external stakeholders.

 

Some basic data, especially for running VET programmes, should be extracted immediately from the organisation’s business management system without involving stakeholders. This includes information on participation rates in individual VET programmes as well as students’ graduation rates. The business management system should allow capture of these data broken down by individual characteristics of students such as gender and age, or according to affinities to vulnerable groups.

With these data, generated from your business management system, you may already evaluate some of the indicators included in the EQAVET framework, presented in Box 15.

 

Box 15. EQAVET indicators

Annex II of the EQAVET recommendation proposes a comprehensive set of quality indicators, which can be used to support evaluation and quality improvement of VET providers.

European quality indicators propose:

  1. application of an internal QMS;

  2. investment in further training of teachers and trainers;

  3. establishment of participation rates in VET programmes, according to type of programme and individual/social characteristics (gender, age, vulnerable groups);

  4. establishment of completion rates in VET programmes, according to type of programme and individual/social characteristics;

  5. establishment of placement rates after graduation from VET programmes, according to type of programme and individual/social characteristics:

    1. destination of graduates after completion of VET programmes;

    2. share of employed graduates;

  6. use of acquired skills at the workplace:

    1. occupation obtained by graduates according to type of training and individual/social characteristics;

    2. satisfaction rate of graduates and employers with acquired skills/competences;

  7. use of unemployment rate according to individual/social characteristics (context indicator);

  8. prevalence of vulnerable groups (context indicator);

  9. mechanisms to identify (changing) training needs in the labour market;

  10. schemes used to promote better access to VET.

 

It is important to note that some European quality indicators are arranged in a chain of indicators, which are interrelated and build on one another and thus can provide information of additional value. For instance, having collected information on participation rates (indicator 5) and completion rates (indicator 6) it is possible to calculate drop-out rates by comparing the two. The more detailed and disaggregated the information gathered is (for example according to gender, age, ethnic background, educational background) the more reliable the evidence they provide. If information on participation, completion and destination is analysed by VET programme and individual/social characteristics of students, it will be possible to identify the effects on students with different social characteristics and thus to evaluate suitability and adequacy of the various VET programmes they have gone through.

However, information available from the business management system is insufficient to evaluate all these basic indicators, not to mention individual quality objectives of your own organisation. Additional methods for data collection must be used to get deeper insights into quality of a VET institution.