Hic sunt dracones: There be dragons!
•
1 like•459 views
This document summarizes research on mapping the demand and supply of social work placements in New Zealand. It discusses conducting a survey of institutions providing social work education and analyzing data from the Social Workers Registration Board. The research aims to quantify placement demand, clarify quality issues, and innovate new placement models. So far, the survey found that over half of placements are with non-government agencies, and government placements are more likely to have on-site and registered social work supervision. The research faces challenges in analyzing the Registration Board's data and suggests an alternative data collection format. Open questions consider how to improve the balance and quality of placement opportunities.
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Similar to Hic sunt dracones: There be dragons!
Similar to Hic sunt dracones: There be dragons! (20)
Recently uploaded
Recently uploaded (20)
Hic sunt dracones: There be dragons!
- 1. Hic sunt dracones: there be dragons! Mapping the demand & supply of social work placements in Aotearoa New Zealand Dr Kathryn Hay (Massey University) Neil Ballantyne (Learning Designs) Karin Brown (Open Polytechnic)
- 2. Outline • • • • • Why map demand and supply? The research programme What have we discovered so far? Questions The next steps
- 3. Why map demand and supply?
- 4. The research programme • Quantifying demand: Survey & SWRB dataset • Clarifying quality: Interviewing practice educators • Innovating practice learning: Piloting new models
- 5. The survey participants Institutions Population Participants Universities 5 3 Polytechnics 8 4 Wānanga 2 0 Total 15 7 Note: two polytechnics excluded from population as they have not yet placed students.
- 6. Government & NGO placements Survey data: Placement types NonGovernment 55% SWRB dataset: Placement agencies used Government 30% Government 45% NonGovernment 70%
- 7. Government & NGO placements Survey data: Placement types NonGovernment 55% SWRB dataset: Supervisors Government 34% Government 45% NonGovernment 66%
- 8. Survey data: RSW supervisors Proportion of placement supervisors who were RSWs by placement agency type in 2012 RSW Non-RSW NGO Government 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
- 9. SWRB data: RSW supervisors Proportion of placement supervisors who were RSWs by placement agency type in 2012 RSW Non-RSW NGO Government 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
- 10. SWRB data: Placements Proportion of government and NGO placement agencies used for each placement 3rd Placement 2nd Placement Government Non-Government 1st Placement 0% 20% 40% 60% 80% 100%
- 11. Survey data: On-site supervsion Proportion of placement supervisors who were onsite by placement agency type in 2012 NGO Onsite Offsite Government 0% 20% 40% 60% 80% 100%
- 12. SWRB data: On-site supervision Proportion of placement supervisors who were onsite by placement agency type in 2012 NGO Onsite Offsite Government 0% 20% 40% 60% 80% 100%
- 13. SWRB data: On-site RSW supervisors Proportion of placement supervisors who were RSW & onsite by placement agency type in 2012 NGO Onsite RSWs Others Government 0% 20% 40% 60% 80% 100%
- 14. Challenges with the SWRB dataset • Official documents designed for audit rather than research purposes • Resources required to clean the data • Questions may be interpreted in different ways • Many missing values and altered table layouts • Possible input errors related to table design • Regulatory function may influence responses • The real world is messier than forms
- 15. Suggested alternative data collection format
- 16. Questions • What would you want to include in a national placement dataset? • Is the balance between governmental & non-governmental placement opportunities an issue? • Should we require at least one governmental and one NGO placement? • How do we improve the number of RSW onsite supervisors? • Could local consortia of teaching institutions and agencies improve the match between supply and demand?
- 17. What would be the value of a national social work placement data set? • • • • • Enables placement planning Support workforce planning Identifies placement demand hot spots Monitors progress towards onsite RSW supervision Useful for leveraging and targetting resources to improve supply and manage demand
- 18. Dragon tamers Kath Hay K.S.Hay@massey.ac.nz Karin Brown Karin.Brown@openpolytechnic.ac.nz Neil Ballantyne neil@learningdesigns.co.nz
Editor's Notes
- Refer to hic sunt dracones- the unknown. There are frequent anecdotal comments across the tertiary sector about limited placement options. pressure on agencies and tertiary providers etc. We wanted to map some facst about student placements in NZHow many placements are required each year? In what types of agencies are students placed?Given the SWRBs stated preference that: ‘all placements will have supervision provided by fully registered social workers’, AND ‘at least one placement will be supervised on site by a fully registered social worker’What proportion of students are supervised by RSWs, and what proportion of supervision is onsite or offsite?What proportion of students are supervised by an onsite RSW?
- The work we’ll discuss today is about quantifying placement data: especially placement demand. However, this is part of larger practice learning research agenda.Obtaining good, accurate quantitative data is important for placement planning, but so is finding out what make for a high quality practice placement. So another part of our research will clarify what counts as quality.We are also interested in developing new models of practice learning, and evaluating their use in practiceToday however we want to discuss issues around mapping placement demand, and to share with you our encounters with various data dragons. We’ll end with some recommendations about how the data dragons might be tamed– but this is a tricky business. Never underestimate a fire-breathing data dragon.The data we draw on for this paper is derived from two sources: 1) a survey conducted by the research team, 2) the SWRB annual reports submitted for every approved programme and each programme delivery site.We invited all TEIs to participate in a survey – offered online or in hard copy. The survey commencedin November 2012 and was followed up in January 2013. Questions related to numbers of students placed; projections for 2013; types of agencies, supervision of students, i.e. RSW, external; geographical locations of; students who couldn’t be placed or whose placements were terminated and reasons for this.We SWRB annual reports include similar data about placement provision.
- One of the perennial problems with survey data is, of course, response rates. We managed to secure a sample of almost 50% of TEIs who responded to a set of questions designed for the purposes of the research.For a large population this wouldn’t be a bad sample size, but in the context of an exercise to map placement demand across NZ, it’s far from ideal.The SWRB annual reports, on the other hand, are a requirement on all approved programme providers. Consequently they offer a complete dataset. However, this is an ‘official dataset’ designed for the purposes of audit and accountability rather than as a research instrument. In the slides that follow we’ll refer to both sets of data and conclude with a discussion of the data dragons hidden in the detail.
- Survey (N=493); SWRB data (N=1002)NB in the SWRB data, four forms did not include the number of different placement agencies usedand are excluded from this analysis.We’ll discuss the significance of the balance of placement types later but for now we want to highlight the differences in the data sources. Both the survey and SWRB data suggest engagement with more NGO than governmental agencies but there is a significant difference between the data sources.The differences might be accounted for in terms of a bias in the survey sample. However, there is another possible explanation. The SWRB report template asks respondents to give the number of ‘placement agencies used’ not the number of placements by agency type. Indeed since they number of supervisors identified (N=1613) is significantly greater than the number of placement agencies used, this seems to be how most respondents interpret the question.
- Survey (N=493); SWRB data (N=1613)This chart shows supervisors used which should more closely reflect the number of placements used (so long as only one supervisor is being identofied for each placement).
- Flick between this one and next slide to show differences (main notes on next slide).
- Survey data NGO (N=272 | RSW 53% | Non RSW 47%)Government (N=226 | RSW 85% | Non RSW 15 %)% difference in RSWs = 32%SWRB dataNGO (N=547 | RSW 42% | Non RSW 58%)Government (N=1066 | RSW 76% | Non RSW 24%)% difference in RSWs = 34%As you can see although there are similar differences between the proportions of RSW and Non-RSW supervisors in the two datasets (with government placements having significantly higher rates of RSWs in both sources) the SWRB data reports a lower proportion in both sectors.
- The survey data wasn’t broken down by placement sequence, but the SWRB data was.According to the SWRB data the proportion of students in a government placement by placement is as follows1st Placement: 21% Gov | 78% NGO2nd Placement: 40% Gov | 60% NGO3rd Placement: 29% Gov | 71% NGO
- Flick between this one and next slide to show differences (main notes on next slide).Survey data NGO (N=272 | On-site 59% | Off-site RSW 41%)Government (N=226 | On-site 75% | Off-site 25 %)% difference in Onsite = 16%
- Survey data NGO (N=272 | On-site 59% | Off-site 41%)Government (N=226 | On-site 75% | Off-site25 %)% difference in on-site = 16%SWRB dataNGO (N=547 | On-site 78% | Off-site 22%)Government (N=1066 | On-site 82% | Off-site 18%)% difference in on-site = 4%But the difference may be accounted for in the ways the questions are intepreted. It’s possible that the SWRB data are including more than one supervisor for each placement. The question could be read that way.
- Survey data SWRB dataNGO (N=272 | On-site RSW 23% | Others 77%)Government (N=226 | On-siteRSW 66% | Other 34%)% difference in on-site RSWs = 43%
- We must be clear that we do not intend to be critical of the SWRB or the TEIs in relation to the integrity of this data. The form wasn’t designed for the purposes of research and even the best designed form still requires time devoted to checking and cleaning the data.The fact that the SWRB collects this data is extremely helpful and it could be developed into a serious placement and worforce planning tool. IN fact it could be used as a national placement dataset.To improve the form:The format would need to be restructured (see following slide). Guidance on coding definitions need to be included (eg what is a primary supervisor?)Someone would need to check, clarify and clean the data.
- This logic diagram shows how the data entries should be related to each otherImprove clarity of form design (perhaps using an excel, pdf, or online format to prevent alterations to the structure of the form)Data might also include:Information on student progress (fails, withdrawals etc). The form collects this data now but providing instructions and definitions would improve data integrity.Use of more than one supervisor (eg for the purposes of cultural supervision)Type of government placement (eg CYF, DHB, Probation)Geographic location of placement. This would highlight localities where demand is high and perhaps help planning to improve supply.
- 1. What do you think (at a minimum) a national placemenent dataset should include?2. What do you think of the balance between Gov and NGO placement learning opportunities given that the majority of RSWs are employed by government organisations (nb not the majority of SWs)?“Child, Youth and Family (30%) and the District Health Boards (26%) are the largest single employers of registered social workers followed by the non-government sector organisations employing 21%” (from SWRB annual report 2011–2012)3. How can we improve the number of RSW onsite supervisors? Would the advent of mandatory registration be sufficient?4. We can tell that a large number of placements are required each year and teaching institutions assume the demand will increase. All of our survey all respondent agreed or strongly agreed with the statement that Finding student placements will become progressivley more difficult. What could be done to better coordinate supply and demand? Would local consortia of employers and agencies help to mange and unlock plaecment learning opportunities?