Web-Based Surveys Questions, Answers, and Designs Kent L. Norman Department of Psychology Human/Computer Interaction Lab Laboratory for Automation Psychology.

Slides:

Advertisements

Similar presentations

Course: Organizational Research Unit: 3 Collecting DataID: Christy 1 ORG101: Unit 3 – Collecting Data PQ AR QuestionsPresentation ActivityResources Instructions.

Advertisements

IT Works so Uwork(s): Letting Technology work for You!!!

IMPLEMENTING YOUR SURVEY. By the end of this lesson you will be able to: Conduct a survey questionnaire. Recruit and train enumerators and encoders to.

The Movement to EDR and the Impact on Editing: Electronic Approaches: Usage and Growth.

Copyright 2010, The World Bank Group. All Rights Reserved. Agricultural Data Collection Procedures Section A 1.

COLLECTING DATA ON A SAMPLE OF RESPONDENTS Designing survey instruments.

RESEARCH METHODS Lecture 24

Designing the Questionnaire

Chapter 8 Designing the Survey Questionnaire Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.

Topics: Interviewing Question Type Interviewing techniques

Surveys Questionnaires & Interviews Electronic Methods.

Screen guidelines For data entry. Screen Layout for Data Entry Identify screen (name and purpose). Keep number of screens to a minimum. Ensure that all.

Developing a Questionnaire. Goals Discuss asking the right questions in the right way as part of an epidemiologic study. Review the steps for creating.

Company LOGO B2C E-commerce Web Site Quality: an Empirical Examination (Cao, et al) Article overview presented by: Karen Bray Emilie Martin Trung (John)

Survey Research Questionnaire construction Types of surveys

© 2005 by Prentice Hall Chapter 3c Designing Interfaces and Dialogues.

Questionnaire Designing Developing the best instrument to collect data for your research.

1 Developing A Quality Assurance Program For The US Census Bureau’s Business Register David. D. Chapman US CENSUS BUREAU 1.

Web-Based Surveys: Questions, Answers, and Designs Kent L. Norman Department of Psychology Laboratory for Automation Psychology and Decision Processes.

Preparing for 5S All departments should be audited prior to 5S activity to establish baseline data. Prior to conducting 5S activities, all affected employees.

WRITING EFFECTIVE S. Before writing the Make a plan! Think about the purpose of the Think about the person who will read the and.

Sue Lowry Biostatistical Design and Analysis Center (BDAC) Clinical and Translational Science Institute Academic Health Center University of Minnesota.

Name: Abdullah Mohammed Alhatmi ID:86497 Course: Quality &Assurance Name: Abdullah Mohammed Alhatmi ID:86497 Course: Quality &Assurance Start.

Evaluation and analysis of the application of interactive digital resources in a blended-learning methodology for a computer networks subject F.A. Candelas,

Geneva, 30 October 2009 Giuseppe Sindoni, Istat, Italy An online system for multi-channel, register-based census data collection.

Chemistry B.S. Degree Program Assessment Plan Dr. Glenn Cunningham Professor and Chair University of Central Florida April 21, 2004.

Market Survey. “ Who are the potential clients? What do they want and prefer? ”

Questionnaire Design (Source: W.G Zikmund, B.J Babin, J.C Carr and M. Griffin, Business Research Methods, 8th Edition, U.S, South-Western Cengage Learning,

Talent Management System Mike Rounds and Ola Faucher Human Resource Management November 6,

Questionnaire administration EHES Training material.

Data management in the field Ari Haukijärvi 2nd EHES training seminar.

SurplusSurplus Surplus Forum January 8, SurplusSurplus Changes at Surplus Presented by Margaret Chambers, Director.

Old.libqual.org What will ARL do for you? What will you do? January 2005 Shrivenham, UK.

Qualtrics Data collection with Qualtrics Some Tips and Tricks Prof. Dr. Allard van Riel Marketing Department 3 March 2015.

Project 3 Cookie Cutters Kevin Huynh Sean Tsusaki Jordaniel Wolk.

Heuristic evaluation Functionality: Visual Design: Efficiency:

Multirater.com. SIOP ‘99 Slide - 2 multirater.com Behind the Scenes of a Web-Based 360 Feedback Process Keith Rettig.

European Conference on Quality in Official Statistics Session 26: Quality Issues in Census « Rome, 10 July 2008 « Quality Assurance and Control Programme.

Computerized Testing System in Science Based on Clickit platform Michal Biran Moshinsky R&D and Training Center - Ort Israel Wingate Seminar - May 2005.

Laboratory for Automation Psychology and Decision Processes Kent L. Norman, University of Maryland, USA (Catherine Plaisant, University of Maryland, USA)

Dr D.K. Nyahunzvi Midlands State University 2012.

Chapter 9 Survey Research. Chapter Outline Topics Appropriate to Survey Research Guidelines for Asking Questions Questionnaire Construction Self-administered.

The 2010 Population and Housing Census of Mongolia: Census PES 1 A.Amarbal Director of Population and Housing Census Bureau, National Statistical Office.

02/22/1999UT Austin: GSLIS LIS Information Management LIS /22/99 Martha Richardson.

Copyright 2010, The World Bank Group. All Rights Reserved. Managing Data Collection Section A 1.

Usability for Adults Over 50 Amy Lee Director of Customer Experience for Web AARP Services, Inc.

Session Session 15 FAFSA on the Web - Onward and Upward!

Library Questionnaire Colin Conway Camille Riviere.

Conference on Data Quality for International Organisations, Newport, April Assessment of statistical data quality: The example of the Occupational.

The Design of Electronic Educational Environments: Issues and Principles in Human/Computer Interaction Kent L. Norman Department of Psychology Laboratory.

Survey Methodology Survey Instruments (1) EPID 626 Lecture 7.

Designing Interactive Edits for U.S. Electronic Economic Surveys and Censuses: Issues and Guidelines Elizabeth M. Nichols, Elizabeth D. Murphy, Amy E.

Dr. Michael R. Hyman, NMSU Data Preparation. 2 File, Record, and Field.

Managed by UT-Battelle for the Department of Energy Weatherization Assistant: Ramp Up Support Mark Ternes Mike Gettings Oak Ridge National Laboratory 2009.

1 Cognitive Aspects Associated with Sample Selection Conducted by Respondents in Establishment Surveys La Toya Barnett Thomas Rebecca L. Morrison Grace.

Topic (i): Editing nearer the source Work Session on Statistical Data Editing Vienna, Austria April 2008.

University of Colorado at Denver and Health Sciences Center Department of Preventive Medicine and Biometrics Contact:

Durham County Non-Profit Funding Program Board of County Commissioners’ Worksession August 6, 2012.

CJA 474 Week 2 Individual Assignment Motivation and Control Thanks for Nothing Paper Review the Thanks for Nothing case study in Ch. 7 of Organizational.

PSYCH 570 Week 1 Individual What is Organizational Psychology Paper Check this A+ tutorial guideline at

Overview of E-Learning Authoring Software

TIM 58 Chapter 3, continued: Requirements Determination Ch

Homework 5 Hints.

Financial Affairs Training Webpage Redesign

Pair Programming Assistant

Financial Affairs Training Website

Data Preparation (Click icon for audio) Dr. Michael R. Hyman, NMSU.

Turkish Statistical Institute

Multi-Mode Data Collection

Turkish Statistical Institute Demographic Statistics Department

Presentation transcript:

Web-Based Surveys Questions, Answers, and Designs Kent L. Norman Department of Psychology Human/Computer Interaction Lab Laboratory for Automation Psychology

Reasons for Web-based Surveys: Cost-efficiency, Dissemination-collection, Central control Automation Hypermedia

Pitfalls of Bad Design: Good ideas don't always migrate directly to the Web. Bad design is easier to generate than good design. One bad design leads to another.

Interface Issues with Surveys Formatting and Navigation (Norman,Friedman, Norman & Stevenson, 2000) Organization of Items and Navigation (Norman, Slaughter, Freidman, Norman, Stevenson, 2000) Automatic Customization (Norman, Pleskac, & Norman, 2001 Edits and Corrections and Navigation Conditional Jumps and Navigation (Norman, 2001; Norman & Pleskac, 2002)

Experiment Our experiment compared three different designs: –Manual Scrolling, –Automatic Items –Automatic Scrolling Survey included successive jumps of one, two, and three items. Respondents were 36 undergraduate students in a within subjects factorial design.

Manual Scrolling

Automatic Items Automatically jumps to the next appropriate item when alternative is clicked.

Automatic Scrolling Automatically scrolls down to the next appropriate item when alternative is clicked.

Results Automatic Item was the fastest, especially for 3 follow-up questions.

Expanding Clicking on a triangle expands the survey to show follow-up or skipped questions.

Automatic Gray Out Automatically grays out items to be skipped when an alternative is clicked.

Guidelines Reduce the branching instructions to a minimum to reduce reading time, confusion, and perceived difficulty of the questionnaire. Automate conditional branching when possible, but allow the respondent to override branching if there is a need to do so on the part of the respondent.

Guidelines Hide follow-up questions to shorten the apparent length of the questionnaire. Make skipped questions available only if the respondent specifically wishes to view them. When the respondent is allowed to see and answer all questions, implement logic and consistency checks on conditional branches.

Guidelines Streamline forward movement through the questionnaire while allowing backtracking to view or change answers. Finally, although good design seems intuitive, it requires usability testing before final implementation.

Credits Support from the U.S. Census Bureau, Statistical Research Division. Thanks to students, Tim Pleskac, Kirk Norman, Nick Robb.

References Norman K. L. & Pleskac (January 2002). Conditional Branching in Computerized Self-Administered Questionnaires: An Empirical Study. LAP , HCIL , CS-TR-4323, UMIACS-TR Norman K. L. (November 2001). Implementation of Conditional Branching in Computerized Self-Administered Questionnaires. LAP , HCIL , CS-TR-4319, UMIACS-TR Norman K. L., Pleskac T.J., Norman K. (May 2001) Navigational Issues in the Design of On-Line Self-Administered Questionnaires: The Effect of Training and Familiarity. LAP , HCIL , CS-TR-4255, UMIACS-TR Norman K., Slaughter L. Friedman Z.,Norman K.,Stevenson R. (October 2000). Dual Navigation of Computerized Self-Administered Questionnaires and Organizational Records. LAP , HCIL , CS-TR-4192, UMIACS-TR Norman, K. L., Friedman, Z., Norman, K. D., & Stevenson, R. (2000). Navigational Issues in the Design of On-Line Self Administered Questionnaires (HCIL-TR , LAP-TR )