Laura Sauli MIMOD Final workshop 12 April 2019

Slides:



Advertisements
Similar presentations
Mixed-Mode Experiments Rachel Vis, Statistics Netherlands QUEST Ottawa, April 2007.
Advertisements

Responding to the Challenge Alison Wride 1. Why we are talking about it Higher fees Economic downturn and concerns about rates of return Higher than anticipated.
American Community Survey ACS Content Review Webinar State Data Centers and Census Information Centers James Treat, ACSO Division Chief December 4, 2013.
Final Thoughts. Health Communication Process Pre-work Formative Research Strategy Development Pre-testing Implementation Evaluation.
>> EU-ISRAEL TWINNING PROJECT Activity D.3 Design of web-based survey and questionnaire (CAWI) Jerusalem, 29 April – 1 May 2014.
Instrument Development and Psychometric Evaluation: Scientific Standards May 2012 Dynamic Tools to Measure Health Outcomes from the Patient Perspective.
Session topic (i) – Editing Administrative and Census data Discussants Orietta Luzi and Heather Wagstaff UNECE Worksession on Statistical Data Editing.
Census Transformation: progress in New Zealand ONS Beyond 2011 Research Conference, May 2014.
Miami, Florida, 9 – 12 November 2016
Modernisation Story of Statistics Slovenia
Rachel Vis-Visschers & Vivian Meertens QDET2, 11 November 2016
Investment Intentions Survey 2016
NEW WELSH BACCALAUREATE AND RE
NI14: The Cabinet Office Perspective
How can spatial information be obtained, managed, maintained and delivered within Arctic Council ? Ole Kristian Bjerkemo EPPR Executive Secretary.
Merja Kallio-Peltoniemi QDET2/12th November 2016
Kozlu Anadolu Lisesi, Turkey
Analysis of the Reporting Forms for the Structural Business Survey
Science Behind Cross-device Conversion Tracking
Margin of Error: We’re Only Human…
Acting Section Head, Regulatory Activities Section, NSNI, IAEA
Flexibility = Accessibility:
‘On Your Marks’ Student Learning Exam Strategies
What is OCACCESS Online?
National quality guidelines in Denmark
Building a Real World Semantics for MODAF
Jakub Hrkal ESTAT Unit F-4
Addison, Joanne, Katherine, SunMi
New ways to get the data Multiple mode and big data
Multi-Mode Data Collection Approach
GBV survey: progress EUROSTAT 20 March 2018.
Item 6.2 ISCED Fields of education and training 2013 (ISCED-F 2013)
Education and Training Statistics Working Group – June 2014
Marina Signore Director of Research Data Collection Directorate, Istat
Go Mobile with MX! Enhanced Responsiveness in MX 8.2
Create – Performance Task
CEF e-Invoicing Readiness Checker
Structure of the final report
Draft Methodology for impact analysis of ESS.VIP Projects
INVESTORSCOPE Hi-Fi Prototype.
Protech’s Short and Long Term Roadmap
OPTIONS FOR FUTURE MANAGEMENT OF ROUPELL PARK
Item 7 - Roadmap and mandate for the Task Force on UOE Education Expenditure Data Eurostat Education and Training Statistics Working Group - Luxembourg,
The Hub Innovation Program Evaluation Plan
Chapter 5: Water management and adaptation
Education and Training Statistics Working Group – 2-3 June 2016
Evaluation of the pilots for the EU Victimisation Survey Module
The change of data sources in the Spanish SILC
Modernising the system of micro-data collections in social statistics
Implementing mixed mode questionnaire in FI-SILC
Conducting Marketing Research
Vlasta Zucha, STATISTICS AUSTRIA,
ROME April 11th | 12th MIMOD Mixed-Mode Designs for Social Surveys
Elizabeth Liner Lab of Things.
WP1 Conclusions and a look ahead MIMOD
MIMOD – Project overview
Mode effects in mixed-mode data collection WP2
Multi-Mode Data Collection
Overview of objectives
What is Planning? Planning as a Basic Human Activity
Deciding the mixed-mode design WP1
Mobile device sensor data in ESS surveys WP5
MIMOD – A look ahead MIMOD Mixed-Mode Designs for Social Surveys
WP3 Case Management Systems
GISCO working group meeting 2015
Overview of objectives WP5
Adaptive mixed-mode design WP1
Social Science Curriculum Roll Out
Item 5 Modernisation of the EU-SILC Production
ESS conceptual standards for quality reporting
Presentation transcript:

Laura Sauli MIMOD Final workshop 12 April 2019 WP5: Discussion Laura Sauli MIMOD Final workshop 12 April 2019

Mobile first as a strategy: should we do it? Short answer: YES! We cannot choose the device for the respondent We cannot afford to lose the respondents whose only device is mobile Allows effective contact strategies Mobile first = respondent first Developing mobile friendly questionnaires benefits questionnaires in general 15 June 2019 Laura Sauli

Assessing fitness for mobile devices Criteria presented are relevant But are they too difficult to implement? Is it dangerous to talk about ”assessing the fitness”? What happens if a questionnaire gets a low score? Is the conclusion to stop all development work on the questionnaire? The current mode can also cause response burden and measurement error  doing nothing is not a good option Identifying some surveys as more challenging (SILC) Can be misleading, as the surveys are conducted in country-specific ways Maybe the evaluation should start from a clean page? 15 June 2019 Laura Sauli

Mobile friendly questionnaires: how to do it? Transformation of the questionnaire (not translation from CATI but also redesigning CATI and web-questionnaire) Shorter surveys: Removing questions is often possible even if at first seems impossible Eurostat: reconsider the number of variables and mandatory questions? Questionnaire layout: Invest in developing and testing a common mobile friendly layout for all questionnaires Shorter and simpler questions: Possible, but requires a lot of iterations and testing Eurostat: Re-evaluate the model questionnaires and variables from this perspective? 15 June 2019 Laura Sauli

https://youtu.be/t5i6Gt0R2bw Conclusions Brakes in time series will happen  this is the place to make bold improvements and simplifications into the questionnaire and improve the questionnaire Everything has to be redesigned to make to questionnaire/survey to fit for smartphones Design boldly – tailored design gives better respondent experience and makes the questions easier to understand. Make long questionnaire shorter with questionnaire changes and design solutions (fewer clicks, checkbox questions, dynamic answering buttons). Make respondent friendly questionnaire: pretest – redesign – pretest – redesign. Iterative approach is recommended. merja.kallio-peltoniemi@stat.fi DEMO (SILC): https://youtu.be/t5i6Gt0R2bw QUEST - October 2018 Merja Kallio-Peltoniemi

Sensor data: early days We know what is or should be possible to do, but do not (yet) have the means to do it  frustrating! Criteria presented and assessment of ESS surveys gives interesting insight and food for thought Does it help in practice? Do we need to start from what is doable / available? Further concerns: Can we invest enough in the development work? Common apps are not enough, they need to be integrated in the IT-infrastructure What happens to harmonization and comparability? Fast development: how do we know what solutions work in 5 years? 15 June 2019 Laura Sauli