The use of electronic books (eBooks) in social science research

Richard Parker*Danius Michaelides†

Huanji Yang†Alex Frazer†Luc Moreau†

Camille Szmaragd*ZhengZheng Zhang*

Christopher Charlton*William Browne*

*Centre for Multilevel Modelling,University of Bristol, UK

†School of Electronics & Computer Science,University of Southampton, UK

Template

Dataset

Stat-JR: to re-cap…

Stat-JR writes commands, etc.,

to perform requested function

Template

Dataset

Stat-JR prompts user

for input Function performed

(If applicable) external software

opened, run, then closed, with results returned to Stat-JR. E.g…

Results of function

produced

(If applicable) results outputted as dataset to be fed back in…

myModel<- glm(normexam~Summary(myModel)plot(myModel,1) Select Open Worksheet

Select datafile.dtaSelect Equations from Fi

EquationsMacrosScripts Point & click instructions

ResultsModel:DIC: 9766.506Parameters:Beta1: 0.594

ChartsResults tables

Stat-JR’s eBook interface: DEEP

Documents withEmbeddedExecution andProvenance

Embeds Stat-JR’s statistical functionality within a ‘traditional’ notebook…

…so we first import one…

No eBooks loaded yet…

Navigate through pages of eBook

Hierarchical table of contents (can be expanded / collapsed at each node)

Behind the scenes…

• The eBook author (me) has specified which Stat-JR template to associate with this region of the eBook…

• …and has chosen one which creates plots via (“PlotsViaR”).

• Templates require input, from a user, before they can go ahead & perform the function appropriately…

• …the eBook author can pre-specify inputs (by writing them into the eBook code); any that are not pre-specified are then left to the eBook reader to complete.

Stat-JR writes commands, etc.,

to perform requested function

Template

Dataset

Stat-JR prompts user

for input Function performed

(If applicable) external software

opened, run, then closed, with results returned to

Stat-JR.

Results of function

produced

(If applicable) results outputted as dataset to be fed back in…

myModel<- glm(normexam~Summary(myModel)plot(myModel,1) Select Open Worksheet

Select datafile.dtaSelect Equations from Fi

EquationsMacrosScripts Point & click instructions

ResultsModel:DIC: 9766.506Parameters:Beta1: 0.594

ChartsResults tables

Stat-JR: to re-cap…

Behind the scenes…

• …the eBook author has associated relevant model-fitting Stat-JR templates with this region of the eBook…

• …and has pre-specified all of the inputs, bar the explanatory variables, which are therefore the only ones left to eBook reader to specify.

• Author has also specified what / where / when the output resulting from a template’s execution will be presented in the eBook…

Stat-JR writes commands, etc.,

to perform requested function

Template

Dataset

Stat-JR prompts user

for input Function performed

(If applicable) external software

opened, run, then closed, with results returned to

Stat-JR.

Results of function

produced

(If applicable) results outputted as dataset to be fed back in…

myModel<- glm(normexam~Summary(myModel)plot(myModel,1) Select Open Worksheet

Select datafile.dtaSelect Equations from Fi

EquationsMacrosScripts Point & click instructions

ResultsModel:DIC: 9766.506Parameters:Beta1: 0.594

ChartsResults tables

Stat-JR: to re-cap…

Content of text returned is conditional on value of results

Stat-JR’s DEEP system:Summary of features

• Built on Stat-JR’s powerful & flexible data-analytical engine.

• Embeds inputs and outputs of Stat-JR’s executable statistical functions within contextual information.

• Tailoring & specificity: e.g. associating carefully-chosen templates; pre-specifying inputs.

• Log / recording tool: behind-the-scenes, a comprehensive record is kept of each execution.

Stat-JR’s DEEP system:

• Teaching of quantitative social science research methods (including inter-operating software).

• Communicating principles / theories / inviting exploration of quantitative social science topics.

• Reports: transparency (e.g. access to embedded dataset / analytical methods, etc); facilitates multi-authored preparation.

• Tailored analytical techniques: pre-specifications allow user to ‘cut to the chase’ and/or circumvent software-specific learning curve.

Benefits for the social science researcher?

…so how do I use them?See http://www.bristol.ac.uk/cmm/research/estat/downloads/index.html …

…so how do I use them?See http://www.bristol.ac.uk/cmm/research/estat/downloads/index.html …for: Software download & installation instructions; eBook reading & authoring guidance; Example eBooks.

eBook authoring: is it easy? Depends what you want to do!…eBook-writing tool can help set-up basic eBook structure…although more sophisticated functionality will take time to implement. User Guides, and the example eBooks (which can open & look ‘under the bonnet’), are there to help.

Any questions?

richard.parker@bristol.ac.uk