Presentation at IASSIST 2006 – Ann Arbor, Michigan 05.22-26Atle Jåstad, Norwegian Social Science Data Services

ESS EduNet

http://essedunet.nsd.uib.no

Internet-based analysis training programme aiming to facilitate and enrich access to empirical data in the social sciences.

The resource is developed for use in higher education.

Containing: Theory Data Methodology

The ambition is to create a social science laboratory that combines the elements of social science to an integrated whole: theory, data and methodology.

What is ESS EduNet?

– Texts written by two distinguished researchers

ESS EduNet is designed to connect the two components, and to stimulate to empirical data analysis in higher education.

The main components

- Data of high quality: From the European Social Survey (1st round)

• Social and political trust Written by Professor Kenneth Newton, Department of Politics, University of Southampton. Two theories of the origin of social trust are presented and assessed, and the relationship between political and social trust is outlined.

Topics

• Human values Written by Professor Shalom Schwartz, Department of Psychology, Hebrew University, Jerusalem. Schwartz’ theory on human values is presented, and it is illustrated how values can be used both as dependent as well as independent variables.

• Statistical data For online analysis or download. Each topic refers to a very limited subset of ESS data (round 1), carefully selected to focus on a manageable set of dependent and independent variables, including contextual data. Some variables are original ESS-variables, others are recoded or computed especially for the topics.

• Run-time NSDstat The users may download a run-time version of the statistical software NSDstat for later use, making it easy for institutions without any statistical software to make use of the website.

• Methodological glossary Short description of some key concepts.

Data

In ESS EduNet it is possible to browse and analyse data and metadata online, and to download data in many formats.

The most important features for online analysis are:

Online analysis

• Frequency tables

• Descriptive statistics

• Multivariate cross tables

• Correlation

• Regression

• Thematic maps

User guide Contains: Text on technical requirements, about NSDstat and about weighting. In addition there is an introduction on how to analyse data online.

Other resources

Discussion Is a forum where the users can discuss theoretical or methodological questions.

About Short description of the ESS project and the ESS EduNet.

Just another online resource

As most web-sites, ESS EduNet aspires to be more than just another online resource. But it is difficult to ignite the enthusiasm of demanding students and teachers. It is not sufficient to offer relevant information, it is necessary to wrap the information in a design that makes it easy to find and utilise it.

When we were trying to figure out how we could minimise the threshold for using ESS EduNet, we had to seek inspiration outside the web-design community…

Design principles

1. Keep each page as screen-readable as possible

2. Keep navigation at a minimum

3. Offer relevant information where needed

Design example: Mouseover

Display information by pointing at elements in the text:

• references • footnotes• keywords• figures and tables

For example: When reference is made to a figure, it is not necessary to go back (troublesome navigation) or to insert the figure once more in the text (waste of space).

Point the mouse cursor at the highlighted word, for example “Figure 1.1”.

Design example: Mouseover

Design example: Show/hide

Display text only when needed:

• solutions to exercises• SPSS or NSDstat instructions • particularly important information (weighting)

For example: If you are using SPSS, it is not necessary to read the instructions for NSDstat users.

Design example: Show/hide

To work with ESS EduNet

• Each topic is divided into several chapters.

• One chapter equals, very roughly, one hour of work. • Each chapter contains exercises with varying degree of difficulty.

Run analyses

Theory

Interpretation of statistical result

Operationalization

To work with ESS EduNet: Research-like learning

The topics are designed to guide the users through the research process; from a theoretical problem to the interpretation of statistical results.

To work with ESS EduNet: Example

• Select a topic•Read the theoretical introduction to get a better understanding of the topic• Solve the exercises• Create tables• Get help if you need it

Advantages with this type of teaching package

Closeness to data

Research practice

Easy to use

http://essedunet.nsd.uib.no