Tag Archives: JISCPress

Approaches to Soliciting Opinions for Institutional Responses to Formal Consultations

One of the things we didn’t put into the original JISCPress bid – though in hindsight we might have – was a use case for commentable documents in the context of government consultations soliciting formal responses from higher education institutions (for example, Universities UK: Review of External Examining Arrangements in the UK).

From a chat with Alison Nash in the OU’s recently reorganised Strategy Unit (I think?), it seems that candidate consultations are fielded by a member of that unit who then emails likely suspects (identified quite how, I’m not sure?) with either a link to, or copy of, the consultation document; (these are typically Word or PDF documents). As with many of the consultations we have looked at in the context of Write To Reply, the consultations typically have a set of questions associated with them that are distributed throughout the consultation document as a whole. Comments and responses to questions are then returned by email (I didn’t ask whether this is typically in the body of an email message, in a Word document, or as comments or highlighted changes on a copy of the orginal consultation), collated (again, I’m not sure how? One way would be to use a spreasheet, with rows for respondent and columns for each question (or vice versa)), and used to frame the institutional response. (I’m not sure if a draft of the institutional response was then circulated to the orginal commenters for final comment…?) The question that was then asked was: would a WriteToReply style approach be appropriate for managing returns of comments and answers to consultation questions in a rather more organised way than is currently the case?

(If anyone from the OU, or other HEIs who engage in producing formal instituional responses to consultations would like to provide further detail about the workflow for soliciting internal comments, producing drft and final versions of instituional responses, and then tracking the impact of comments made in the response, please post a comment to this post…)

Here are some thoughts/matters arising relating to how the WriteToReply/JISCPress/digress.it approach might apply:

– comments may need to be private; this could be achieved by hosting WordPress within the firewall, limiting who can view comments to members of the institution, or not making comments public (e.g. by moderating them, meaning that only the blog owner could see them). Limiting who can make comments can be achieved by requiring users to log in to the blog, and only providing certain users with log in accounts.

– it may not be appropriate to allowing commenting on all paragraphs, instead requiring users to only comment on actual questions. This might be achieved by disabling comments on all pages except a single summary page that contains one paragraph per question, maybe with links back to the actual posts that contain the question in context.

– if comments are solicited throughout the document, a dashboard tool such as Netvibes can be used to aggregate comments from different sections of the document; tools like Yahoo Pipes can also be used to aggregate comments from separate areas of the document and display them in a single view. Views over comments by individual commenters are also available and may be collated together on dashboard pages (for example, with separate pages aggregating comments from different sorts of commenter – e.g. allowing views over responses by Faculty, for example).

– once a formal response has been produced, it may be appropriate it post it on the consultation site to allow commenters to see how their comments were o weren’t integrated in to the official response (maybe leaving it open to them to submit a personal response to the consultation if they feel their views were not appropriately reflected, if at all. (The more I think about the process of these document based consultations, the more I feel a feedback loop is required that allows folk to see what sort of impact, if any, their comments may have had. I also briefly touched on this in On the Different Roles Documents and Comments May Take in a Commentable Document.) The consultation document site then becomes an important part of institutional memory, archiving as it does the original consultation, individual comments from members of the institution, and the institution’s formal response. It might also be the case that a draft of the institutional response is placed on the same site and comments on it solicited. (The site would then be hosting documents in two modes – the original consultation mode document, and then a draft mode document (again, this distinction appears in the Different Roles blog post.)

In many cases, it might be that the paragraph level commenting approach is not appropriate – unless comments are limited to just the consultation questions themselves, each as a separate commentable item. Where it is appropriate to isolate consultation questions from the surrounding text, a simple form may provide the best way of capturing comments.

In the OU, where I believe we are about to start rolling out Google Apps for Education to at least some of our students over the next month or two, it might be appropriate to look at using a Google form as platfrom for capturing comments. As well as satisfying the immediate goal (capture comments in a centralised way), this approach would also provide a legitimate and low risk use case for exloring how we might make use of the Google Apps environment as part of internal business processes.

The simplest case, then, would be for the internal staff member responsible for gathering comments to create a Google form. I don’t know if internal staff members have yet been issued with login details for how to access Google Apps on the open.ac.uk domain, but in the interim they can either create a personal Google account (or I could let them have an account on one of my Google apps domains!). Creating a form can be done either from the main docs menu, or within a Google spreadsheet (the posted form results are collated within a spreadsheet).

Google docs - create new form

For most consultations based around a set of specific questions, the format of the form would look something like this:

Creating a google form to field consultation question replies

That is, a copy and pasted copy of each consultation question (with minor tweaks so the question makes sense in a standalone questionnaire) as a separate form item, with a Paragraph text element for the response.

If additional commentary is required, the section head (which includes a description component) can be used to display it:

Google form - section head

It might also be worth capturing “any other comments” in a final paragraph text comment at the end of the questionnaire.

Although the form, once published, would be open to anyone on the apps domain, (if they knew the URL), a further “security” measure would be to prompt the user for a consultation “pass phrase” emailed to them as part of the request for comments (“please enter this keyphrase when you complete the form so we can put your responses into the class of ‘high priority’ responses”;-) This might even be a required element.

Alternatively, a keyphrase element could be used to sort the responses in the results spreadsheet, or as suggested above in the context of digress.it, used to sort responses for example by Faculty, (Alternatively, an optional unique key code be be generated for each invited response to identify their responses. Or we could request an OU identifier, name, email address etc to track who made what comment (though these approaches are gameable and don’t necessarily imply that the person with a given identifier is the person who submitted the form…)). If users are logged in to the Google Apps environment, it may be that their identity is recorded anyway…? Hmm….

Google form responses

For just collecting responses, pretty much anyone could just set up the form and then email the link to the form to the potential commenters. With the availability of Google Apps script, and a little bit of developer time, it would also be possible to provide alerts to the internal consultation organiser whenever a form submission is made, provide automated collation of responses by question and pop these into a Google wordprocessor doc (I think…?!) and even manage a circulation list – so for example, a list of respondents could be created in a spreadsheet, used to mail out invitations for them to complete the form, and then track their response. In the advent of them not responding within a certain period, an automated reminder could be sent out. (I’m guessing it would take about a day to build and test such a workflow, which once created would be reusable.)

Another advantage of using the Google Apps approach would be that the response spreadsheet (or an automagically maintained Google wordprocessor doc version of it) could be shared to other members of the team providing the formal institutional response as an online shared document appearing in each individual’s Google docs “inbox”.

PS it seems that within a Google Apps for Edu environment, it may now also be possible for users to edit their form responses if they want to revise their answers…

PPS it’s also worth noting here a couple of practical considerations about how to write a consultation document bearing in mind that someone might put together a form to collate the responses. Firstly, the question should make sense as a standalone item (i.e. out of context) or very clearly identify what it is referring to rather than just “the above”. Secondly, if the questions are collated together in a single appendix, it makes it easier to just check off that each question has been included in the form. (It’s also handy as a one page item for someone who is putting together the response.) Links to the original context also help; (in a sense, this sort of Appendix is like “List of Tables” or “List of Figures” that acts as contents page for locating questions within the document). Reading over the questions in an Appendix will also make it obvious whether or not the question was written in such a way that it implicitly refers to content surrounding it in the original embedded context (“see the above” again…) Note that I’m not saying questions shouldn’t be embedded, just that when they are taken out of context, they still make sense and read well. In the example I give above about external examiners, the questions had to be tweaked so that they made sense as standalone items.

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On the Different Roles Documents and Comments May Take in a Commentable Document

Chatting over possible use cases for digress.it in a meeting at UKOLN yesterday, it struck me that there are at least three different roles we might expect a commentable document to play in a open discussion context:

  • draft document – in which comments are solicited on different parts of a document, with a view to producing a revised version of the document that takes into account the various comments made on the commentable version of it. For example, the publication of draft standards (e.g. British Standards – commentable drafts) or draft policy documents (e.g. Leicester University social media policy). Users may be able to see the consequences of comments by comparing final versions of the document with the orginal commentable version, and the comments associated with it.
  • consultation document – in which issues are discussed and a series of consultation questions asked, often embedded within the various sections of the body of the document. For example, HEFCE REF Consultation. If a summary of responses is provided around the consultation, along with a review of what actions were taken that relate back to the consulation questions, commenters will be able to judge whether or not their comments appeared to influence the direction of post consultation outcomes.
  • guidance document – in which comments may be round around guidance either requesting or providing clarification of particular points, or collecting examples of how others have practically implemented guidance. For example, COI Guidance on open source software. This sort of document can act as a hub for aggregating practical advice implementing guidance. In contrast to the previous two document/comments, the comments thermselves can become a means of sharing practical advice around the guidelines, and may effectively deliver practical guidance themselves. The outcomes of requests for clarification may also be trackable, if for example they result in revisions to the original guidance, or indeed if they result in a futher comment that clarifies the matter; (in this case, we might see clarifying comments as providing a similar role as do comments on a draft document?).

Combining elements of all three types listed above, we might also consider an amplification, or discussion, document, such as documents published in support of a meeting (“meetings without borders”, or “semi-permeable meetings”; for example Using WriteToReply to Publish Committee Papers. Is an Active Role for WTR in Meetings Also Possible?). [Added: I guess that educational materials might also be regarded as discussion documents?] Rather than being the focus of a conversation, these documents are part of an ongoing process, or conversation, where comments raised may either be seen to be a continuation of a discussion held in a meeting, or as part of a conversation that may be continued in a folow on meeting. Feedback to commenters about how comments are received may be realised through mentions to matters raised in comments appearing in the minutes of later meetings (which may even reference back to the orginal comment).

Looking at these various document types, it seems to me that it is possible for commenters to look for evidence in later/follow-on documents about the extent to which their comments may or may not have directly influenced the content of those follow-on documents, as well as providing opportunities for direct links back to comments that influenced later documents from those later documents themselves.

If a consultation platform can start to highlight the impact comments may have on practice or policy development through appropriate feedback, such as “follow-on feedback” (i.e. the demonstration of how a comment on one document influenced the content of another), then it feels right to me that it is more likely that people will start to see it as a tool that supports “real” involvement in a process?

PS Seems like I’m too late to add this distinction in as feedback to the COI draft guidance on commentable docs.

Measuring Website Usage With Google Analytics, Part I

Knowing where to get started with reporting website statistics can often provide new webmasters with something of a challenge. In this post, I’ll quickly review the guidance provided by the Central Office of Information on Measuring Website Usage which:

describes a common approach to measuring website traffic [for central government]. This enables departments to answer Parliamentary Questions and Freedom of Information Requests about website usage consistently and reliably

I’ll also start to explore how to generate reports that satisfy those guidelines using Google Analytics.

The proposed metrics “are defined according to industry standards set by the Joint Industry Committee for Web Standards (JICWEBS)” and specify the following minimal level of reporting (Measuring Website Usage – Reporting requirements):

  1. The following web metrics, as defined by the Joint Industry Committee for Web Standards (JICWEBS), must be measured for each and every publicly accessible website operated by an organisation:
    • Unique User/Browsers
    • Page Impressions
    • Visits
    • Visit Duration
  2. Central government departments must measure Unique User/Browsers, Page Impressions, Visits and Visit Duration starting from 1 April 2009 for every website open on 1 April 2010.
  3. Executive agencies and non-departmental public bodies (NDPBs) must measure Unique User/Browsers, Page Impressions, Visits and Visit Duration starting from 1 April 2010 for every website open on 1 April 2011.
  4. The following information must be provided to COI at the end of each quarter:
    • Number of monthly Unique User/Browsers
    • Number of monthly Page Impressions
    • Number of monthly Visits
    • Number of Visits of at least two Page Impressions
    • Total time in seconds for all Visits of at least two Page Impressions
  5. Each report should contain figures for each of the previous three months. This information should be provided in the format shown in the reporting template in Appendix A.COI Website usage reporting template http://coi.gov.uk/guidance.php?page=237
  6. All figures should exclude internal web development activity, performance monitoring, automated broken link detection and other types of non-human activity (e.g. robots and spiders). Further details on what to exclude are found in the Page Impressions section.

So what does Google Analytics offer “out of the box”?

Headline report - Google Analytics

The Visitors Overview repeats these figures and additionally provides an indication of the number of ‘unique’ visitors:

Visitors Overview

At face value then, it would appear that the Google Analytics are providing at least some of the required stats (though we need to clarify that the numbers as recorded by Google Analytics conform to what the COI has in mind for those reports as described in their guidance on the Minimum standard for web metrics!) But what does that guidance relating to “at least two web pages” mean?

To understand the emphasis on “at least two pages”, it’s worth reflecting on the notion of bounces and the bounce rate. Bounce rate refers to the proportion of visitors to a site who only visit one page on a website before leaving that site, and as such tend to leave no meaningful analytics behind.

According to the ClickTale blog (What Google Analytics Can’t Tell You – Part 1), Google Analytics “has no way of knowing how long a bounced visitor, who only visits one page, spent on your website”. That is, it appears that the time spent looking at a page appears not to be based on the difference between the time when a page has fully loaded (and generated a trackable onload event) and its unload event; instead, it is calculated as the time between two loading one page and clicking through to and loading a second page on the sam site.

Which is why the emphasis on collecting stats from at last two pages: given the current crop of analytics tools that struggle to do anything meaningful with single page visits, specifying a two page visit means that not only visits to the site that are likely to be meaningful are reported, but also that the reports are more likely to contain meaningful data too. (There is an obvious problem here: if visitors visit two pages, and quickly click to the second from the first before exiting the site from the second page, the time spent on the second page won’t be captured? See for example Time on Site & Time on Page – Google Analytics metric mystery)

One of the nice things about Google Analytics is that it lets you create custom views, or “segments” of the data in which you can specify things such as the minimum number of pages visited when generating a particular report. In order to do this, you specify an “Advanced Segment”. Here’s what an Advanced Segment for a “minimum of two pages visited report” might look like:

GA Advancd segment - visited at last two pages

Applying this segment to the same data charted above gives these results:

Segmented goog stats

GA segmented view

So for example, in this version of the report we see that the average number of page views and the average time on site has gone up.

Something I don’t think Google Analytics report is the total time on site. Bearing in mind the lack of data regarding the time spent on exit pages, the best we can do is multiply the number of visits by the average time on site to get an estimate of the total time on site.

With just this single advanced segment, a simple calculation, and the out of the can reports from Google Analytics, I think we can deliver on the suggested stats based on a literal reading of the headings, though in a follow up post I’ll check to see if the more detailed spec on the metrics matches the way that Google ANalytics defines its metrics.

PS Unfortunately, the segmented report appears to have lost the number of absolute unique visitors (although I think the recommended report wanted the number of uniques, including bounces, to the site?) Anyway, let’s play: the number of visits gives the upper bound on the number of unique visitors, but can we also estimate the lower bound? One heuristic might be to look at the number of visits and uniques in the original report (176 uniques, 245 visits), see how many visits were lost in discounting the bounces (245-104 = 141), assume these were all unique and subtract these from the original number of uniques (176-141=35). I think this gives the lower bound on uniques as recorded by Google Analytics for non-bouncing visitors?

“Campaign” Tracking With Google Analytics

Of the very many things that it’s possible to provide webstats reports about, such as tracking visitors arriving from organisational wbsites, one of the most useful is being able to track how much traffic has been driven back to your website from a particular link – such as a link included in a particular tweet, or in a particular email announcement, and so on.

If a link to a JISCPress document appears on a third party webpage, and somebody clicks on that link and then lands on the corresponding JISCPress page, Google Analytics will capture where that incoming visitor cam from via the Referring Sites report. At the top level this is organised by domain:

Google Analytics - Referring sites

We can then tunnel down to the page level:

More referrers

This is all well and good, but sometime we also might want to know where the person who posted the referring link on their web page got hold of it. Did they capture it from a tweet, for example, or via an email list? When we releas a URI into the wild via some sort of marketing campaign, what sort of life does that URI have, and where will it end up sending traffic back from?

In the Googe Analytics FAQ answer How do I tag my links?, a method is described for adding additional tags to a referral URL (that is, a URL that you publish and/or distribute more widely that refers back to your website) that Google Analytics can use to segment traffic referred from that URL. Five tags are available (as described in Understanding campaign variables: The five dimensions of campaign tracking):

Source: Every referral to a web site has an origin, or source. Examples of sources are the Google search engine, the AOL search engine, the name of a newsletter, or the name of a referring web site.
Medium: The medium helps to qualify the source; together, the source and medium provide specific information about the origin of a referral. For example, in the case of a Google search engine source, the medium might be “cost-per-click”, indicating a sponsored link for which the advertiser paid, or “organic”, indicating a link in the unpaid search engine results. In the case of a newsletter source, examples of medium include “email” and “print”.
Term: The term or keyword is the word or phrase that a user types into a search engine.
Content: The content dimension describes the version of an advertisement on which a visitor clicked. It is used in content-targeted advertising and Content (A/B) Testing to determine which version of an advertisement is most effective at attracting profitable leads.
Campaign: The campaign dimension differentiates product promotions such as “Spring Ski Sale” or slogan campaigns such as “Get Fit For Summer”.

(For an alternative description, see Google Analytics Campaign Tracking Pt. 1: Link Tagging.)

The recommendation is that campaign source, campaign medium, and campaign name should always be used.

Elsewhere, (Library Analytics (Part 7), from which elements of this post have been taken), I considered how these codes might be used to track course referrals to Library resources from a VLE (something I need to revisit, now I’ve had a little more time to consider the possible role(s) of these tracking codes). But it also seems to me to be reasonable to raise a few questions about how we might use these tracking codes in the context of a document on JISCPress or WriteToReply in order to track referrals back to the site from social media campaigns highlighting a particular document or section of a document.

So, what are sensible mappings/interpretations for the campaign variables? Remember, these tracking variables are parameters that we might add to a link that we have posted somewherethat is intended to drive traffic back to the site. The tracking variables are there to allow us to see how different links are performing. Thinking about how we might use these five tracking dimensions, whether or not we use them in the “intended” Google Analytics way, may also provide us with some ideas about how to use links to drive traffic back to our site.

To try and ground the exercise, consider this example: a new document is published on JISCPress and we want to compare how well links posted on Facebook compare with links posted on Twitter for driving traffic back. For tracking to be most effective, we hope that if a link is rebroadcast or shared, the tracking variables are carried along with it. This means that if a link is posted to Twitter, that gets shared onto Facebook and onto a blog, we can look at the traffic that comes back, and from where (via the Referral tracking described at the start of this post), for each of the separately released URIs. A second example might relate to a campaign intended to drive traffic back to a particular section or paragraph of a document. This campaign might involve publishing a link back to the same paragraph in a series of separate posts or status updates, each with a different slug or call to action message. That is, each link+message may be published in the same place (and hence have the same referrer information), but at different times and with different link text, or contextual information. A third example might be where there is more than on link back to the same document on a web page, and we want to track how effective each link is compared to the others?

Here are the supported variables again:

  • source: the obvious thing to use this variable for is the domain or URI of the page where the link is published to. So if we tweet a link, twitter.com might be sensible. If we blog it, actually might be best?
  • medium: this is intended to refer to the sort of link that has generated the traffic, such as a banner ad. In our case, we might clarify the intent with which the link was posted, such as announcement, or question;
  • term: this is an optional parameter, and I’m not sure how it should be used or whether it conflicts with other Google services. If we post something with a hashtag on twitter, or a st of tags on delicious, might we use those tags are terms?
  • content The second optional variable, this is often usd to discern A/B test ads. If we tweet the same link with different call to action/prompting questions, maybe this differential content should be uniquely identified with the content field?
  • campaign: typically used for tracking a promotion or campaign, this field might be used to identify a different document when, for example, a link to the top level JISCPress is referred to in a announcement about a particular document?

So for example, we might have something like:
http://writetoreply.org/?utm_campaign=ukgovurisets &utm_medium=announcement&utm_source=actually
appearing as the link for WriteToReply in an announcment about the hosting of the UK Government URI Sets document.

Or maybe a call to action on twitter relating to a particular part of a document:
What benefits would you like to see from #JISCRI calls? http://writetoreply.org/jiscri/2009/03/11/rapid-innovation-projects/#3?utm_campaign=jiscri &utm_medium=question&term=JISCRI&utm_source=twitter.com&utm_content=slug3

To support the generation of tracking URIs, a URL Generator Tool (like the official Tool: URL Builder) that will accept a tweet, for example, along with a JISCPress/WriteToReply URL and then automatically create tracking variable values might be worth considering?

Thoughts on JISCPress

As we come to the final month of the JISCPress project, we had some great news over on WriteToReply last week where we were able to announce that Eduserv would be covering our hosting costs for the immediate future (Eduserv funds hosting for WriteToReply, eFoundations: Write To Reply).

So what exactly does the platform we’ve been working on have to offer? Here’s one of the ways I think of it…

A document publishing platform that automatically atomises documents to the paragraph level, allows aggregated commenting at the paragraph and ‘user’ level, and supports the republication and re-presentation of documents in a variety of standard formats at the document level.

The first part of the process is the (manual assisted) ingress stage, in which documents are imported into the WordPress environment such that each substantive document section ideally maps onto a single WordPress “blog post”:

An RSS for the document as a whole, with one item per section, is generated automatically by the WordPress platform. A single item RSS feed is also generated for each page (so the content of each page can be easily transported around the web).

The second part of the process is the atomisation of each post, carried out automatically by the Digress.It theme, in which each paragraph in the document is given its own unique URI, derived from the URI of the web page (“blog post”) the paragraph appears on:

Potentially, an RSS feed can also be produced for each page in which each paragraph is a separate feed item, thus allowing a page/section to be transported around the web via a single feed, but in atomised form.

The paragraph level chunks produced by the atomistation process can be transcluded as independent elements in independent web documents in other documents by a variety of means (as an embeddable object, via XML, txt, JSON, etc):

The default nature of the WordPress platform allows comments to be made at the level of each web page, with an RSS feed of comments for each page being published ‘for free’. JISCPress extends this functionality by allowing comments to be associated with discrete paragraphs. Views over the comments are also available at the user level, (that is, grouped according to the user who made the comments, wheresoever they are made in the document). An additional RSS fed of comments by user is also available, which means that a document on the platform can actually be used as a scaffold for a critical response to the document by a particular user.

A further level of innovation is based on the automated generation of ‘semantic tags’ at the page level. Once generated, tag based collections of posts can be syndicated in the normal way via WordPress generated tag based RSS feeds:

JISCPress also benefits from the Trackback mechanism implemented by WordPress. When a page or paragraph URI is linked to from a third party web page, a trackback to the originating page may be captured, which we interpret as the automated capture of links remote annotations or comments about the document.

When considered in these terms, the JISCPress/WriteToReply platform is seen to provide a powerful means of publishing documents in which individual sections may carry their own unique URI, and individual paragraphs within a section also contain their own unique URI (which in many situations may be rooted on the section URI).

The platform can also be regarded as republishing – or re-presenting – each section (i.e. page) and each paragraph as an independent entity. That is, whenever a document is published via the platform, each separate paragraph may also be thought of as being independently published “for free”, in the sense that:

– each paragraph is independently addressable,
– each paragraph is independently commentable, and
– each paragraph is independently republishable/syndicatable.

So, given that, can you think of any ways in which the JISCPress/WriteToReply platform can support your document publishing and comment gathering strategy?

Paragraph Embedding from JISCPress

One of the things I was keen to explore within the context of the JISCPress project was the potential for using WordPress as a platform for publishing paragraph level fragments that could be embedded in third party web pages.

As Joss announced on the JISCPress blog, We’ve got paragraph data output switches! that expose paragraph level content through a unique URI in a variety of formats (xml, txt, html, rss and json), as well as object embed codes for each paragraph, though I’m not sure if this is going to be maintained…? e..g at the moment, I think we’re trialling literal text blockquote embeds:

Blockquote embed

(If the object embed does disappear, similar functionality could be achieved using the JSON feed and a Javascript function, though I guess we need JSON-P (i.e. support for something like &callback=foo to make that really easy.)

See also: A Quick Update for a review of the latest feature releases within the digress.it theme we’re using.

To demonstrate one possible use case for object embedding, see the post Engaging With the Issues Raised By The Google Book Settlement which includes three embedded paragraphs from the JISC’s current consultation around the Google books settlement.

Embedding content from write to reply

Here’s the actual HTML:

Embedding content from WriteToReply

Note that currently there is an issue with sizing the embed container (can any CSS gurus out there give us a fix?

Object sizing issue with WTR embeds

Ideally we need to identify the container height and then size it automatically so there are no scrollbars? I’m guessing .scrollHeight might have a role to play in autodetecting this?)

One thing you might notice is that the URIs for the embedded consultation questions follow a similar pattern – only the paragraph number identifier changes:
http://writetoreply.org/googlebooks?p=8&digressit-embed=4

What this means is that we should be able to pull in a random paragraph by constructing a URI with a randomly generated paragraph number. So for example:

var n=2+Math.floor(Math.random()*5);
var o=document.createElement(‘object’);
o.setAttribute(‘style’,’width: 100%; height:70px;’);
o.setAttribute(‘id’,’61c197964762012d4819093ebeee4fcf’);
var p=’http://writetoreply.org/googlebooks?p=8&digressit-embed=’+n;
p=p.replace(/#038;/,”); //get round WordPress escaping everything…
o.setAttribute(‘data’,p);
document.getElementById(‘wtr_embed’).appendChild(o);

If you reload the page, you have an 80% chance of seeing a different question…

Here’s the Javascript snippet:

var n=2+Math.floor(Math.random()*5);
var o=document.createElement('object');
o.setAttribute('style','width: 100%; height:70px;');
o.setAttribute('id','61c197964762012d4819093ebeee4fcf');
var p='http://writetoreply.org/googlebooks?p=8&digressit-embed='+n;
p=p.replace(/#038;/,''); //get round WordPress escaping everything...
o.setAttribute('data',p);
document.getElementById('wtr_embed').appendChild(o);

//There’s a div with an appropriate id attribute (‘wtr_embed’) also added to the page…
//Note that the div needs to be placed before any inline Javascript in the page;-)

I’m not sure yet if we can track the use of embeds (certainly server logs should be able to track calls, but these probably can’t be captured using Google Analytics?), but it’s still early days…