OUseful.Info, the blog…

Over the weekend, I noticed that the Guardian was offering readers a chance to win the chance to study for an OU degree for free. Today, via a tweet, I see a link to a piece of editorial coverage from Friday – Live and learn with distance learning – on some of the motivations for studying for an OU degree – as well as a look at the commitment that’s involved in taking a distance learning degree.

The competition is prominently linked to:

I suspect we are going to see more of this…

I was also interested to see this tweet from @barnstormed on Sunday: Nice to see the @openuniversity on one of the electronic pitch-side advertising boards at Murrayfield :) #rugby #6nations [Anyone got a screenshot?]

See also a previous campaign: OU Course Discounts with the Tesco Clubcard, although I note this is about to come to an end?

Hmmm…

A couple of days ago, I ran a sort of repeated, 3 hour, Digital Sandbox workshop session to students on the Goldsmiths’ MA/MSc in Creating Social Media (thanks to @danmcquillan for the invite and the #castlondon students for being so tolerant and engaged ;-)

I guess the main theme was how messy tinkering can be, and how simple ideas often don’t work as you expect them to, often requiring hacks, workarounds and alternative approaches to get things working at all, even if not reliably (which is to say: some of the demos borked;-)

Anyway… the topics covered were broadly:

1) getting data into a form where we can make it flow, as demonstrated by “my hit”, which shows how to screenscrape tabular data from a Wikipedia page using Google spreadsheets, republish it as CSV (eventually!), pull it into a Yahoo pipe and geocode it, then publish it as a KML feed that can be rendered in a Google map and embedded in an arbitrary web page.

2) getting started with Gephi as a tool for visualising and interactively having a conversation with a network represented data set.

To support post hoc activities, I had a play with a Delicious stack as a way of aggregating a set of tutorial like blog posts I had laying around that were related to each of the activities:

I’d been quite dismissive of Delicious stacks when they first launched (see, for example, Rediscovering playlists), but I’m starting to see how they might actually be quite handy as a way of bootstrapping my way into a set of uncourses and/or ebooks around particular apps and technologies. There’s nothing particularly new about being able to build ordered sets of resources, of course, but the interesting thing for me is that even if I don’t get as far as editing a set of posts into a coherent mini-guide, a well ordered stack may itself provide a useful guide to a particular application, tool, set of techniques or topic.

As to why a literal repackaging of blog posts around a particular tool or technology as an ebook may not be such a good idea in and of itself, see Martin Belam’s post describing his experiences editing a couple of Guardian Shorts*: “Who’s Who: The Resurrection of the Doctor”: Doctor Who ebook confidential and Editing the Guardian’s Facebook ebook…

* One of the things I’ve been tracking lately is engagement by the news media in alternative ways of trying to sell their content. A good example of this is the Guardian, who have been repackaging edited collections of (medium and long form) articles on a particular theme as “Guardian Shorts“. So for example, there are e-book article collection wrappers around the breaking of the phone hacking story, or investigating last year’s UK riots. If you want a quick guide to jazz or an overview of the Guardian datastore approach to data journalism, they have those too. (Did I get enough affiliate links in there, do you think?!;-)

This rethinking of how to aggregate, reorder and repackage content into saleable items is something that may benefit content producing universities. This is particularly true in the case of the OU, of course, where we have been producing content for years, and recently making it publicly available through a variety of channels, such as OpenLearn, or, err, the other OpenLearn, via iTunesU, or YouTube, OU/BBC co-productions and so on. It’s also interesting to note how the OU is also providing content (under some sort of commercial agreement…?) to other publishers/publications, such as the New Scientist:

There are other opportunities too, of course, such as Martin Weller’s suggestion that it’s time for the rebirth of the university press, or, from another of Martin’s posts, the creation of “special issue open access journal collections” (Launching Meta EdTech Journal), as well as things like The University Expert Press Room which provides a channel for thematic content around a news area and which complements very well, in legacy terms, the sort of model being pursued via Guardian Shorts?

I think I may have confused Stephen Downes yesterday with my notes around consultation based courses, so here are some more loosely connected thoughts that will probably only serve to muddle the situation further, at least for now…;-)

Take the forthcoming UK Parliamentary Communications Green Paper that will lead to a revision of the legislation surrounding communications in the UK. In part, this will draw on the DCMS Communications review carried out earlier this year according to the following process: “An open letter was published on 16 May 2011 asking a broad range of questions about the communications sector. All non-confidential responses to the letter were published on 7 December 2011. Submissions received will be used to inform the Green Paper.” (The public submissions are available as a individual documents in either RTF or PDF format.)

The open letter [PDF] included a series a questions relating to communications policy. For example:

…
Q6. What are the competing demands for spectrum, how is the market changing and how can a regulatory framework best accommodate any rapidly changing demands on spectrum and market development?
…
Q12. What barriers are there to innovation in new digital media sectors, including video games, telemedicine, local television and education?

In a consultation-framed course, the consultation questions may be thought of as part of the assessment model. One of the aims of the course is to provide “students” taking the course with the knowledge, skills and understanding required to provide a considered response to some or all of these questions.

Note that we may wish to qualify the reading of a question, or wrap it with additional criteria; for example, we might tune Q6 above along the lines of: “What particular issues are likely to arise in the 300MHz to 3GHz band?”, or something like that!

In the Related Information section of the Communication Review, links were provided to a Research report [on] the Contribution of the digital communications sector to economic growth and productivity in the UK and the Government’s broadband strategy among other things. In a sense, we have been gifted some “course readings”. There are also opportunities to dip into research that maybe doesn’t get read (or scrutinised) as widely as it might, in the form of Parliamentary Library Research Briefing papers.

So that’s part of the jigsaw: reviews, consultations, calls for evidence all involve policy makers soliciting evidence and opinion around a topic area that may include technical considerations. Where questions are asked, these may form part of the reflection/self-assessment/course assessment framework. The original call may itself be viewed as a high level syllabus of the topics to be addressed in the course. The course can then address these issues with reference to teaching material (for example, if we’re considering innovation, we met call out some introductory OpenLearn materials on “Characteristics of consumers and the market”.

Whilst the aim of the review, consultation or piece of proposed legislation may not in itself go too deeply into technical areas, it can be used to provide the SPEL (social, political, ethical, legal) context around a technology area and provide a jumping point off for a technical lesson in that subject area (for example, we may want to consider the similarities and differences between wired networks and wireless networks; or we may need to get up to speed on what optical fibre networks are good for.

Part of the story then, is to try to take the lazy route to curriculum development, and reuse someone else’s, which in this case also amounts to a repurposing of a document or process that wasn’t intended as a course to provide some of the content, topic, cohort discovering and pacing components of a course.

This repurposing lends an element of authenticity and relevance to the course of study (though as mentioned in my previous post, we must be wary that the course is not used as a vehicle for delivering propaganda).

What the approach may also do is increase the amount of scrutiny around a review or route to legislation. In the post No Minister: Any chance for the Communications Act?, Guardian Professional writer Dick Vinegar notes:

Last time around, in 2003, Lord Puttnam, a film director with the right blend of artistic and technical expertise, carried out a pre-legislative scrutiny. I believe that this knocked the heads of broadcasters (fluffies) and comms engineers (techies) together to produce a good bill. From what I have heard so far, I am not sure whether this time around we will get such a mature, ‘two cultures’ approach.

By providing a view over a consultation, or review that is course-like, we can maybe increase the amount of scrutiny involved in the process and also (maybe) deepen people’s understanding of the issues.

The course view thus provides a structured pathway through the relevant issues at a deeper level than provide by the typical supporting documentation, or perhaps just in a more reflective way. The course also provides a way in to citizen engagement from individuals who just want to explore the topic.

The consultation-framed course also provides a way of straddling news and academia, an area that has also interested me in a lifelong learning context for some time.

This could manifest itself in a couple of ways. For example, long form news articles could feature “academic” breakout boxes using OERs sourced from the course, or course discussions could be positioned around issues raised in recent news articles; in a wider context, entry routes to the course may be provided through the news media, from readers who want to know a little more about the issues involved within a particular consultation area (c.f. News, Analysis, Academia and Demand Education or Educative Media?).

Another interesting feature that arises out the consultation based course learning journey is that “authentic assessment opportunities” present themselves: for example, a student may submit an actual response to the consultation, or, if they entered via the news route, write a letter to the editor. Writing responses in the form of research briefing papers also provides another format for producing work that may be used to demonstrate understanding and knowledge in a meaningful and potentially useful way, as well as an assessable way.

The tone with which reviews or consultations are presented is also interesting from an educational perspective, in that the questions that are asked may be open and may not have a single right answer. (On the other hand, in calls for technical expert evidence, there may well be “correct” answers which the evidentiary call is intended to discover.) This frames the learning activity in the context of “we don’t know what the right answer is, but we need to find out/learn more. That is, the consultation is in some sense modeling part of the lifelong learning behaviour we want to inculcate in our students (learning is not just for school or university, right?!;-)

Is there a demand for such an exercise though? Again referring to the Guardian Professional article:

In the run up to the green paper, Westminster has been awash with conferences and seminars with titles like ‘What should be in the new Communications Bill?’ and ‘Dear Jeremy…’ (Hunt). Most of the speakers at these portentous events have been full of patriotic hyperbole and statements of the obvious. “The next Comms Act should focus on ensuring that the UK’s communications sector remained one of the most competitive in the world.” “A level playing field is needed in the internet ecosystem with global issues considered carefully.” “Regulation must not chill innovation.” “The limits of online privacy must be defined.” “Children must be protected.”

PS I mentioned in the previous post how at least one of the forums around the forthcoming Communications Green Paper was “CPD certified”. A little digging turned up The CPD Certification Service, which is presumably what that referred to. Anyway, I’ve added it to my watchlist to see if Pearson, or other companies of that ilk, start sniffing around it as a gateway to one possible new credentials market…

PPS Are there any emerging leaders in the qualification verification arena yet?

One of the really useful things about publishing documents in a structured way is that we can treat the document as a database, or generate an outline view of it automatically.

Whilst looking through the OU Structured Authoring XML docs looking for things I could reliably extract from them in order to configure a course custom search engine (Notes on Custom Course Search Engines Derived from OU Structured Authoring Documents), I put together a quick script to generate a course mind map based around the course structure.

It struck me that as structured document/XML views of OpenLearn material is available, I could do the same for OpenLearn docs. So here’s an example. If you visit the OpenLearn site, you should be able to find several modules derived from the old OU course T175. Going to the first page proper for each of the derived modules (URLs have the form http://openlearn.open.ac.uk/mod/oucontent/view.php?id=398868&direct=1), it is possible to grab a copy of the source XML document for the unit by rewriting the URL to include the setting&content=1: for example, http://openlearn.open.ac.uk/mod/oucontent/view.php?id=398868&content=1

Downloading the XML files for each of the T175 derived modules on OpenLearn into a single folder, I put together a quick script to mine the structure of the document and pull out the learning objectives for each unit, as well as the headings of each section and subsection. The resulting mindmap provides an outline of the course as a whole, something that can be used to provide a macroscopic view over the whole course, as well as providing a document that could be made available to people following the unit as a resource they could use to organise their notes or annotations around the unit.

Download a copy of the T175 on OpenLearn Outline Freemind/.mm mindmap

If we could find a way of getting the OpenLearn page URLs for each section, we could add them in as links within the mindmap, thus allowing it to be used as a navigation surface. (See also MindMap Navigation for Online Courses in this regard.)

Here’s a copy of the Python script I ran over the folder to generate the Freemind mindmap definition file (filetype .mm) based on the section and subsection elements used to structure the document.

# DEPENDENCIES
## We're going to load files in from a course related directory
import os
## Quick hack approach - use lxml parser to parse SA XML files
from lxml import etree
# We may find it handy to generate timestamps...
import time


# CONFIGURATION

## The directory the course XML files are in (separate directory for each course for now) 
SA_XMLfiledir='data'
## We can get copies of the XML versions of Structured Authoring documents
## that are rendered in the VLE by adding &content=1 to the end of the URL
## [via Colin Chambers]
## eg http://learn.open.ac.uk/mod/oucontent/view.php?id=526433&content=1


# UTILITIES

#lxml flatten routine - grab text from across subelements
#via http://stackoverflow.com/questions/5757201/help-or-advice-me-get-started-with-lxml/5899005#5899005
def flatten(el):           
    result = [ (el.text or "") ]
    for sel in el:
        result.append(flatten(sel))
        result.append(sel.tail or "")
    return "".join(result)

#Quick and dirty handler for saving XML trees as files
def xmlFileSave(fn,xml):
	# Output
	txt = etree.tostring(xml, pretty_print=True)
	#print txt
	fout=open(fn,'wb+')
	#fout.write('<?xml version="1.0" encoding="UTF-8" ?>\n')
	fout.write(txt)
	fout.close()


#GENERATE A FREEMIND MINDMAP FROM A SINGLE T151 SA DOCUMENT
## The structure of the T151 course lends itself to a mindmap/tree style visualisation
## Essentially what we are doing here is recreating an outline view of the course that was originally used in the course design phase
def freemindRoot(page):
	tree = etree.parse('/'.join([SA_XMLfiledir,page]))
	courseRoot = tree.getroot()
	mm=etree.Element("map")
	mm.set("version", "0.9.0")
	root=etree.SubElement(mm,"node")
	root.set("CREATED",str(int(time.time())))
	root.set("STYLE","fork")
	#We probably need to bear in mind escaping the text strings?
	#courseRoot: The course title is not represented consistently in the T151 SA docs, so we need to flatten it
	title=flatten(courseRoot.find('CourseTitle'))
	root.set("TEXT",title)
	
	## Grab a listing of the SA files in the target directory
	listing = os.listdir(SA_XMLfiledir)

	#For each SA doc, we need to handle it separately
	for page in listing:
		print 'Page',page
		#Week 0 and Week 10 are special cases and don't follow the standard teaching week layout
		if page!='week0.xml' and page!='week10.xml':
			tree = etree.parse('/'.join([SA_XMLfiledir,page]))
			courseRoot = tree.getroot()
			parsePage(courseRoot,root)
	return mm

def learningOutcomes(courseRoot,root):
	mmlos=etree.SubElement(root,"node")
	mmlos.set("TEXT","Learning Outcomes")
	mmlos.set("FOLDED","true")
	
	los=courseRoot.findall('.//FrontMatter/LearningOutcomes/LearningOutcome')
	for lo in los:
		mmsession=etree.SubElement(mmlos,"node")
		mmsession.set("TEXT",flatten(lo))

def parsePage(courseRoot,root):
	unitTitle=courseRoot.find('.//Unit/UnitTitle')

	mmweek=etree.SubElement(root,"node")
	mmweek.set("TEXT",flatten(unitTitle))
	mmweek.set("FOLDED","true")

	learningOutcomes(courseRoot,mmweek)
	
	sessions=courseRoot.findall('.//Unit/Session')
	for session in sessions:
		title=flatten(session.find('.//Title'))
		mmsession=etree.SubElement(mmweek,"node")
		mmsession.set("TEXT",title)
		mmsession.set("FOLDED","true")
		subsessions=session.findall('.//Section')
		for subsession in subsessions:
			heading=subsession.find('.//Title')
			if heading !=None:
				title=flatten(heading)
				mmsubsession=etree.SubElement(mmsession,"node")
				mmsubsession.set("TEXT",title)
				mmsubsession.set("FOLDED","true")


mm=freemindRoot('t175_1.xml')
print etree.tostring(mm, pretty_print=True)
xmlFileSave('reports/test_t175_full.mm',mm)

If you try to run it over other OpenLearn materials, you may need to tweak the parser slightly. For example, some documents may make use of InnerSection elements, or Header rather than Title elements.

If youdo try using the above script to generate mindmaps/outlines of other OpenLearn courses, please let me know how you got on in the comments below (eg whether you needed to tweak the script, or whether you found other structural elements that could be pulled into the mindmap.)

Over the last few days, I’ve been tinkering with OU Structured Authoring documents, XML docs from which OU course materials – both print and HTML – are generated (you can get an idea about what they look like from OpenLearn: find a course page with a URL of the form http://openlearn.open.ac.uk/mod/oucontent/view.php?id=397337&direct=1 and change direct to content: http://openlearn.open.ac.uk/mod/oucontent/view.php?id=397337&content=1; h/t to Colin Chambers for that one;-). I’ve been focussing in particular on the documents used to describe T151, an entry level online course I developed around all things gaming (culture, business, design and development), and the way in which we can automatically generate custom search engines based on these documents.

The course had a very particular structure – weekly topic explorations framed as a preamble, set of guiding questions, suggested resources (organised by type) and a commentary, along with a weekly practical session.

One XML doc was used per week, and was used to generate the separate HTML pages for each week’s study.

One of the experimental components of the course has been a Google Custom Search Engine, that supports searches over external resources that are linked to from the blog. The course also draws heavily on the Digital Worlds Uncourse blog, a site used to scope out the design of the course, as well as draft some of the materials used within it, and the CSE indexes both that site and the sites that are linked from it. (See eSTEeM Project: Custom Course Search Engines and Integrating Course Related Search and Bookmarking? for a little more context around this.)

Through using the course custom search engine myself, I have found several issues with it:

1) with a small index, it’s not really very satisfactory. If you only index exact pages that are linked to from the site, it can be quite hard getting any hits at all. A more relaxed approach might be to index the domains associated with resources, and also include the exact references explicitly with a boosted search rank. At the current time, I have code that scrapes external links from across the T151 course materials and dumps them into a single annotations file (the file that identifies which resources are included in the CSE) without further embellishment. I also have code that identifies the unique domains that are linked to from the course materials and which can also be added to the annotations file. On the to do list is to annotate the resources with labels that identify which topic they are associated with so we can filter results by topic.

2) the Google Custom Search Engines seem to behave very oddly indeed. In several of my experiments, one word queries often returned few results, more specific queries building on the original search term delivered more and different results. This gives a really odd search experience, and one that I suspect would put many users off.

3) I’ve been coming round more and more to the idea that the best way of highlighting course resources in a search context is through the use of Subscribed Links, that a user can subscribe to and that then appear in their Google search results if there is an exact query match. Unfortunately, Google pulled the Subscribed Links service in September (A fall spring-clean; for example of what’s been lost, see e.g. Stone Temple Consulting: Google Co-Op Subscribed Links).

4) The ability to feed promotions into the top of the CSE results listing is attractive (up to 3 promoted links can be displayed for any given query), but the automatic generation of query terms is problematic. Promotion definitions take the form:

<Promotion image_url="http://kmi.open.ac.uk/images/ou-logo.gif"
  	title="Week 4"
  	id="T151_Week4"
  	queries="week 4,T151 week 4,t151 week 4"
  	url="http://www.open.ac.uk"
  	description="Topic Exploration 4A - An animated experience Topic exploration 4B - Flow in games "/>

There are several components we need to consider here:

1. queries: these are the phrases that are used to trigger the display of the particular promotions links. Informal testing suggests that where multiple promotions are triggered by the same query, the order in which they are defined in the Promotions file determines the order in which they appear in the results. Note that the at most three (3) promotions can be displayed for any query. Queries may be based at least around either structural components (such as study week, topic number), subject matter terms (e.g. tags, keywords, or headings) and resource type (eg audio/video material, academic readings etc), although we might argue the resource type is not such a meaningful distinction (just because we can make it doesn’t mean we should!). In the T51 materials, presentation conventions provide us with a way of extracting structural components and using these to seed the promotions file. Identifying keywords or phrases is more challenging: students are unlikely to enter search phrases that exactly match section or subsection headings, so some element of term extraction would be required in order to generate query terms that are likely to be used.
2. title: this is what catches the attention, so we need to put something sensible in here. There is a limit of 160 characters on the length of the title.
3. description: the description allows us to elaborate on the title. There is a limit of 200 characters on the length of the description.
4. url: the URL is required but not necessarily ‘used’ by our promotion. That is, if we are using the promotion for informational reasons, and not necessarily wanting to offer a click through, the link may be redundant. (However, the CSE still requires it to be defined.) Alternatively, we might argue that the a click through action should always be generated, in which case it might be worth considering whether we can generate a click through to a more refined query on the CSE itself?

Where multiple promotions are provided, we need to think about:
a) how they are ordered;
b) what other queries they are associated with (i.e. their specificity);
c) where they link to.

In picking apart the T151 structured authoring documents, I have started by focussing on the low hanging fruit when it comes to generating promotion links. Looking through the document format, it is possible to identify topics associated with separate weeks and questions associated with particular topics. This allows us to build up a set of informational promotions that allow the search engine to respond to queries of what we might term a navigational flavour. So for example, we can ask what topics are covered in a particular week (I also added the topic query as a query for questions related to a particular topic):

Or what a particular question is within a particular topic:

The promotion definitions are generated automatically and are all very procedural. For example, here’s a fragment from the definition of the promotion from question 4 in topic 4A:

<Promotion 
  	title="Topic Exploration 4A Question 4"
  	queries="topic 4a q4,T151 topic 4a q4,t151 topic 4a q4,topic 4a,T151 topic 4a,t151 topic 4a"
  	... />

The queries this promotion will be displayed for are all based around navigational structural elements. This requires some knowledge of the navigational query syntax, and also provides an odd user experience, because the promotions only display on the main CSE tab, and the organic results from indexed sites turn up all manner of odd results for queries like “week 3″ and “topic 1a q4″… (You can try out the CSE here.)

The promotions I have specified so far also lack several things:

1) queries based on the actual question description, so that a query related to the question might pull the corresponding promotion into the search results (would that be useful?)

2) a sensible link. At the moment, there is no obvious way in the SA document of identifying one or more resources that particularly relate to a specific question. If there was such a link, then we could use that information to automatically associate a link with a question in the corresponding promotions element. (The original design of the course imagined the Structured Authoring document itself being constructed automatically from component parts. In particular, it was envisioned that suggested links would be tagged on a social bookmarking service and then automatically pulled into the appropriate area of the Structured Authoring document. Resources could then be tagged in a way that associates them with one or more questions (or topics), either directly though a question ID, or indirectly through matching subject tags on a question and on a resource. The original model also considered the use of “suggested search queries” that would be used to populate suggested resources lists with results pulled in live from a (custom) search engine…)

At the moment, it is possible to exploit the T151 document structure to generate these canned navigational queries. The question now is: are promotional links a useful feature, and how might we go about automatically identifying subject meaningful queries?

At the limit, we might imagine the course custom search engine interface being akin to the command line in a text based adventure game, with the adventure itself being the learning journey, and the possible next step a combination of Promotions based guidance and actual search results…

[Code for the link scraping/CSE file generation and mindmap generator built around the T151 SA docs can be found at Github: Course Custom Search Engines]

PS as ever, I tend to focus on tinkering around a rapid prototype/demonstration at the technical systems overview level, with a passing nod to the usefulness of the service (which, as noted above, is a bit patchy where the searchengine index is sparse). What I haven’t done is spend much time thinking about the pedagogical aspects relating to how we might make most effective use of custom search engines in the course context. From a scoping point of view, I think there are a several things we need to unpick that relate to this: what is it that students are searching for, what context are they searching in, and what are they expecting to discover?

My original thinking around custom course search engines was that they would augment a search across course materials by providing a way of searching across the full text of resources* linked to from the course materials, and maybe also provide a context for searching over student suggested resources.

It strikes me that the course search engine is most likely to be relevant where there is active curation of the search engine that provides a search view over a reasonably sized set of resources discovered by folk taking the course and sharing resources related to it. “MOOCs” might be interesting in this respect, particularly where: 1) it is possible to include MOOC blog tag feeds in the CSE as a source of relevant content (both the course blog content and resources linked to from that content – the CSE can be configured to include resources that are linked to from a specified resource); 2) we can grab links that are tagged and shared with the MOOC code on social media and add those to the CSE annotations file. (Note that in this case, it would make sense to resolve shortened links to their ultimate destination URL before adding them to the CSE.) I’m not sure what role promotions might play in a MOOC though, or the extent to which they could be automatically generated?

*Full text search across linked to resources is actually quite problematic. Consider the following classes of online resources that we might expect to be linked to from course materials:

• academic papers, often behind a paywall: links are likely to be redirected through a library proxy service allowing for direct click-thru to the resource using institutional credentials (I assume the user is logged in to the VLE to see the link, and single sign on support allows direct access to any subscribed to resources via appropriate proxies. That is, the link to the resource leads directly to the full text, subscribed to version of the resource if the user is signed on to the institutional system and has appropriate credentials). There are several issues here: the link that is supplied to the CSE should be be the public link to the article homepage; the article homepage is likely to reveal little more than the paper abstract to the search engine. I’m not sure if Google Scholar does full-text indexing of articles, but even if it does, Scholar results are not available to the CSE. (There is also the issue of how we would limit the Scholar search to the articles we are linking to from the course materials.)
• news and magazine articles: again, these may be behind a paywall, but even if they are, they may have been indexed by Google. So they may be full text discoverable via a CSE, even if they aren’t accessible once you click through…
• video and audio resources: discovery in a large part will depend on the text on the web page the resources are hosted on. If the link is directly to an audio or video file, discoverability via the CSE may well be very limited!
• books: Google book search provides full text search, but this is not available via a CSE. Full text searchable collections of books are achievable using Google Books Library Shelves; there’s also an API available.

I guess the workaround to all this is not to use a Google Custom Search Engine as the basis for a course search engine. Instead, construct a repository that contains full text copies of all resources linked to from the course, and index that using a local search engine, providing aliased links to the original sources if required?

However, that wasn’t what this experiment was about!;-)

Course Resources as part of a larger connected graph

Another way of thinking about linked to course resources is that they are a gateway into a set of connected resources. Most obviously, for an academic paper it is part of a graph structure that includes:
- links to papers referenced in the article;
- links to papers that cite the article;
- links to other papers written by the same author;
- links to other papers in collections containing the article on services such as Mendeley;
- links into the social graph, such as the social connections of the author, or the discovery of people who have shared a link to the resource on a public social network.
For an informal resource such as a blog post, it might be other posts linked to from the post of interest, or other posts that link to it.

Thinking about resources as being part of one or more connected graphs may influence our thinking about the pedagogy. If the intention is that a learner is directed to a resource as a terminal, atomic resource, from which they are expected to satisfy a particular learning requirement, then we aren’t necessarily interested in the context surrounding the resource. If the intention is that the resource is gateway to a networked context around one or more ideas or concepts, then we need to select our resources so that they provide a springboard to other resources. This can be done directly (eg though following references contained within the work, or tracking down resources that cite it), or indirectly, for example by suggesting keywords or search phrases that might be used to discover related resources by independent means. Alternatively, we might link to a resource as an exemplar of the sort of resource students are expected to work with on a given activity, and then expect them to find similar sorts of, but alternative, resources for themselves.

Knowing how much energy a building uses is often the first step towards reducing it’s energy footprint, so here’s a quick round up of the university open data initiatives I know of that are based around energy data. (If you know of more, please let me know via the comments.)

First up, via @lncd, here’s a heatmap showing change in energy building usage compared aross the last two days:

This visulisation (built on top of Lincoln U’s open data feeds (http://data.lincoln.ac.uk/)) charts energy usage over a calendar month:

Read more about Lincoln’s energy data hacks here: University of Lincoln Energy Data …. an update!.

Over in Oxford, there’s a tool called OpenMeters that displays charts of energy usage by building:

The Oxford data is available as Linked Data from http://data.ox.ac.uk/datasets/, err, I think… As ever, it’d probably take me an hour or two to find out how to make my first query that returns anything meaningful to me in a form I could actually do anything with!;-) I also wonder whether the Oxford project feeds into another Oxford initiative: iMeasure?

(By the by, I misread the title of this place from the other place to Oxford as “A Linked Data Model Of Building Energy Consumption”: A Limited-Data Model Of Building Energy Consumption, which explores a model “targeted at practical, wide-scale deployment which produces an ongoing breakdown of building energy consumption”.)

Whilst I don’t think Warwick University’s energy monitoring page is based on exposed open data, it does have some dials/gauges on it:

(By the by – that page doesn’t have a Warwick favicon associated with it in my browser; should it?)

So – a quick round up (and huuuuuuge displacement activity from what I should have been doing this afternoon), but I think it’s worth tracking and reporting on these early demonstrations…

See also: JISC Green ICT projects (which I note don’t seem to return popular Google results for queries relating to university energy data, even when searches are limited to the .ac.uk domain…) and the Greening ICT Programme Community Site; Govspark, which compares energy usage across government departments; Innovations in Campus Mapping for a review of how open data is being used to support enhanced interactive campus maps; and Open Data Powered Location Based Services in UK Higher Education.

PS given Lincoln are publishing all manner of open data, I wonder whether there is enough there to do an ad hoc version of the Heat and light by timetable project using data they’re producing just anyway?!

What does it take for a digital scholar’s blog to become academically credible?

At a time when we know that folk go to Google for a lot of their search needs, the academic library argues it’s case, in part, as a place where you can go to get access to “good quality” (academically credible) and comprehensive information through what we might term academic search engines.

The library’s search offerings are presumably subscription based (?) and their results often link through to subscription content; but the academic life is a privileged one, and our institutions cover the access costs on our behalf. (I guess this could almost be considered one of the “+ benefits” you might imagine an enthusiastic copywriter assuming for an academic job ad!)

The library and information access privilege extends to students too, so we might imagine a well-intentioned, but perhaps naive, student thinking that if they run a search using the Library’s “academically certified” search engine, they will get the sort of result they can happily cite in an essay, without fear of criticism about the academic credibility of the source publication.

We might imagine, too, that academics and researchers also place an element of trust in the credibility of sources returned as results to search queries raised using library discovery services.

So here’s a claim (which is untested and may or may not be true): if you want your work to stand a chance of being referenced in a piece of scholarly work, you need it to be discoverable in the places that the scholar goes to discover supporting claims or related material for the work they’re doing. The assumption is that the scholar will use a library provided discovery service because it is less noisy than a general web search engine and is likely to return to resources from credible sources. The curation of sources – and what is not included in the index – is in part what the subscription discovery service offers.

What this means is that if digital scholars want their blogging activity to be discoverable in the academic context, they need to find some way of getting some of their blogposts at least into academic discovery service indices.

But this is not likely to happen, right? Wrong… Here’s what I noticed when I ran a search using the OU Library’s “one-stop” search earlier today:

A top two reference to a Mashable article (albeit identified as a news item) via the Newsbank database and a top ranked periodical article from Fast Company (via the UK/EIRE Reference Centre database). (Hmmm, I wonder how quickly this content is indexed? That is, how soon after posting on Mashable does an article become discoverable here?)

So maybe I need to start writing for Mashable?!

Or maybe not…?

One of the attractive features of WordPress as a publishing platform is that it provides feeds for everything, including category and tag level feeds. A handful of my category feeds are syndicated, for example to R-Bloggers, the Guardian Datablog blogroll and (I’m not sure if this still works?) the Online Journalism blog. Only posts tagged in a particular way are sent to the syndicated feeds.

So I’m wondering this: how much mileage would there be in setting up aggregation blogs around particular academic areas that not only syndicate content from publisher members, but also act as a focus for indexing by a service such as Newsbank? The content would be publisher-moderated (I don’t post content on non-R related matters to my R-bloggers syndication feed) and hopefully responsive to the norms of the aggregation community itself.

Precendents already exist of course; for example, Nature.com blogs aggregates blogs from a variety of working scientists. Is this content discoverable via the OU Library’s one stop/Ebsco search?

For an academic’s work to count in RAE terms, it needs to be cited. In order to be cited, it needs to be discoverable. Even if it isn’t citeable as a formal article, it can still make a contribution if it’s discoverable. To be academically discoverable, content needs to be discoverable via academic search engines. So why should Mashable count, but not personal academic blogs that are respected within their own communities?

PS I’m a bit out of touch with referencing converntions; I remember that pers. comm. used to be an acceptable way of crediting someone’s ideas they had personally communicated to you; is there a pub. comm. (that’s pub. comm. not just pub comm. ;-) equivalent that might be used to refer to online or offline public communications that might not otherwise be citeable?

Given a company or personal name, what’s a quick way of generating meaningful tags around what it’s publicly known for, or associated with?

Over the last couple of weeks or so, I’ve been doodling around a few ideas with Miguel Andres-Clavera from the JWT (London) Innovation Lab looking for novel ways of working out how brands and companies seem to be positioned by virtue of their social media followers, as well as their press mentions.

Here’s a quick review of one of those doodles: looking up tags associated with Guardian news articles that mention a particular search term (such as a company, or personal name) as a way of getting a crude snapshot of how the Guardian ‘positions’ that referent in its news articles.

It’s been some time since I played with the Guardian Platform API, but the API explorer makes it pretty easy to automatically generate some (the Python library for the Guardian Platform API appears to have rotted somewhat with various updates made to the API after its initial public testing period).

Here’s a snapshot over recent articles mentioning “The Open University” (bipartite article-tag graph):

Here’s a view of the co-occurrence tag graph:

The code is available as a Gist: Guardian Platform API Tag Grapher

As with many of my OUseful tools and techniques, this view over the data is intended to be used as a sensemaking tool as much as anything. In this case, the aim is to help folk get an idea of how, for example, “The Open University” is emergently positioned in the context of Guardian articles. As with the other ‘discovering social media positioning’ techniques I’m working on, I see the approach useful not so much for reporting, but more as a way of helping us understand how communities position brands/companies etc relative to each other, or relative to particular ideas/concepts.

It’s maybe also worth noting that the Guardian Platform article tag positioning view described above makes use of curated metadata published by the Guardian as the basis of the map. (I also tried running full text articles through the Reuters OpenCalais service, and extracting entity data (‘implicit metadata’) that way, but the results were generally a bit cluttered. (I think I’d need to clean the article text a little first before passing it to the OpenCalais service.)) That is, we draw on the ‘expert’ tagging applied to the articles, and whatever sense is made of the article during the tagging process, to construct our own sensemaking view over a wider set of articles that all refer to the topic of interest.

PS would anyone from the Guardian care to comment on the process by which tags are applied to articles?

PPS a couple more… here’s how the Guardian position JISC recently…

And here’s how “student fees” has recently been positioned:

Hmmm…

Over the last week or two, I’ve been playing around with a few ideas relating to where Twitter accounts are located in the social landscape. There are several components to this: who does a particular Twitter account follow, and who follows it; do the friends, or followers cluster in any ways that we can easily and automatically identify (for example, by term analysis applied to the biographies of folk in an individual cluster); who’s notable amongst the friends or followers of an individual that aren’t also a friend or follower of the individual, and so on…

Just to place a stepping stone in my thinking so far, here’s a handful of examples, showing who’s notable amongst the followers of a couple of official HE Twitter accounts but who doesn’t follow the corresponding followed_by account.

Firstly, here’s a snapshot of who followers of @OU_Community follow in significant numbers:

Hmmm – seems the audience are into their satire… Should the OU be making some humorous videos to tap into that interest?

Here’s how a random sample (I think!) of 250 of @UCLnews’ followers seem to follow at the 4% or more level (that is, at least 0.04 * 250 = 10 of @UCLnews followers follow them…)

Seems to be quite a clustering of other university accounts being followed in there, but also “notable” figures and some evidence of a passing interest in serious affairs/commentators? That other UCL accounts are also being followed might suggest evidence that the @UCLnews account is being followed by current students?

How about the followers of @boltonuni? (Again, using a sample of 250 followers, though from a much smaller total follower population when compared to @UCLnews):

The dominance of other university accounts is noticeable here. A couple of possible reasons for this suggesting are that the sampled accounts skew towards other “professional” accounts from within the sector (or that otherwise follow it), or that the student and potential students have a less coherent (in the nicest possible sense of the word!) world view… Or that maybe there are lots of potential students out there following several university twitter accounts trying to get a feel for what the universities are offering.

If we actually look at friend connections between the @boltonuni 250 follower sample, 40% or so are not connected to other followers (either because they are private accounts or because they don’t follow any of the other followers – as we might expect from potential students, for example?)

The connected followers split into two camps:

A gut reaction reading of these communities that they represent sector and locale camps.

Finally, let’s take a look at 250 random followers of @buckssu (Buckinghamshire University student union); this time we get about 75% of followers in the giant connected component:

Again, we get a locale and ‘sector’ cluster. If we look at folk followed by 4% or more of the follower sample, we get this:

My reading of this is that the student union accounts are pretty tightly connected (I’m guessing we’d find some quite sizeable SU account cliques), there’s a cluster of “other student society” type accounts top left, and then a bunch of celebs…

So what does this tell us? Who knows…?! I’m working on that…;-)

How can we use customised search engines to support uncourses, or the course models used to support MOOC style offerings?

To set the scene, here’s what Stephen Downes wrote recently on the topic of How to partcipate in a MOOC:

You will notice quickly that there is far too much information being posted in the course for any one person to consume. We tried to start slowly with just a few resources, but it quickly turns into a deluge.

You will be provided with summaries and links to dozens, maybe hundreds, maybe even thousands of web posts, articles from journals and magazines, videos and lectures, audio recordings, live online sessions, discussion groups, and more. Very quickly, you may feel overwhelmed.

Don’t let it intimidate you. Think of it as being like a grocery store or marketplace. Nobody is expected to sample and try everything. Rather, the purpose is to provide a wide selection to allow you to pick and choose what’s of interest to you.

This is an important part of the connectivist model being used in this course. The idea is that there is no one central curriculum that every person follows. The learning takes place through the interaction with resources and course participants, not through memorizing content. By selecting your own materials, you create your own unique perspective on the subject matter.

It is the interaction between these unique perspectives that makes a connectivist course interesting. Each person brings something new to the conversation. So you learn by interacting rather than by mertely consuming.

When I put together the the OU course T151, the original vision revolved around a couple of principles:

1) the course would be built in part around materials produced in public as part of the Digital Worlds uncourse;

2) each week’s offering would follow a similar model: one or two topic explorations, plus an activity and forum discussion time.

In addition, the topic explorations would have a standard format: scene setting, and maybe a teaser question with answer reveal or call to action in the forums; a set of topic exploration questions to frame the topic exploration; a set of resources related to the topic at hand, organised by type (academic readings (via a libezproxy link for subscription content so no downstream logins are required to access the content), Digital Worlds resources, weblinks (industry or well informed blogs, news sites etc), audio and video resources); and a reflective essay by the instructor exploring some of the themes raised in the questions and referring to some of the resources. The aim of the reflective essay was to model the sort of exploration or investigation the student might engage in.

(I’d probably just have a mixed bag of resources listed now, along with a faceting option to focus in on readings, videos, etc.)

The idea behind designing the course in this way was that it would be componentised as much as possible, to allow flexibility in swapping resources or even topics in and out, as well as (though we never managed this), allowing the freedom to study the topics in an arbitrary order. Note: I realised today that to make the materials more easily maintainable, a set of ‘Recent links’ might be identified that weren’t referred to in the ‘My Reflections’ response. That is, they could be completely free standing, and would have no side effects if replaced.

As far as the provision of linked resources went, the original model was that the links should be fed into the course materials from an instructor maintained bookmark collection (for an early take on this, see Managing Bookmarks, with a proof of concept demo at CourseLinks Demo (Hmmm, everything except the dynamic link injection appears to have rotted:-().

The design of the questions/resources page was intended to have the scoping questions at the top of the page, and then the suggested resources presented in a style reminiscent of a search engine results listing, the idea being that we would present the students with too many resources for them to comfortably read in the allocated time, so that they would have to explore the resources from their own perspective (eg given their current level of understanding/knowledge, their personal interests, and so on). In one of my more radical moments, I suggested that the resources would actually be pulled in from a curated/custom search engine ‘live’, according to search terms specially selected around the current topic and framing questions, but I was overruled on that. However, the course does have a Google custom search engine associated with it which searches over materials that are linked to from the course.

So that’s the context…

Where I’m at now is pondering how we can use an enhanced custom search engine as a delivery platform for a resource based uncourse. So here’s my first thought: using a Google Custom Search Engine populated with curated resources in a particular area, can we use Google CSE Promotions to help scaffold a topic exploration?

Here’s my first promotions file:

<Promotions>
   <Promotion id="t151_1a" 
        queries="topic 1a, Topic 1A, topic exploration 1a, topic exploration 1A, topic 1A, what is a game, game definition" 
        title="T151 Topic Exploration 1A - So what is a game?" 
        url="http://digitalworlds.wordpress.com/2008/03/05/so-what-is-a-game/"
        description="The aim of this topic is to think about what makes a game a game. Spend a minute or two to come up with your own definition. If you're stuck, read through the Digital Worlds post 'So what is a game?'"
        image_url="http://kmi.open.ac.uk/images/ou-logo.gif" />
</Promotions>

It’s running on the Digital Worlds Search Engine, so if you want to try it out, try entering the search phrase what is a game or game definition.

(This example suggests to me that it would also make sense to use result boosting to boost the key readings/suggested resources I proposed in the topic materials so that they appear nearer the top of the results (that’ll be the focus of a future post;-))

The promotion displays at the top of the results listing if the specified queries match the search terms the user enters. My initial feeling is that to bootstrap the process, we need to handle:

- queries that allow a user to call on a starting point for a topic exploration by specifically identifying that topic;
- “naive queries”: one reason for using the resource-search model is to try to help students develop effective information skills relating to search. Promotions (and result boosting) allow us to pick up on anticipated naive queries (or popular queries identified from search logs), and suggest a starting point for a sensible way in to the topic. Alternatively, they could be used to offer suggestions for improved or refined searches, or search strategy hints. (I’m reminded of Dave Pattern’s work with guided searches/keyword refinements in the University of Huddersfield Library catalogue in this context).

Here’s another example using the same promotion, but on a different search term:

Of course, we could also start to turn the search engine into something like an adventure game engine. So for example, if we type: start or about, we might get something like:

(The link I associated with start should really point to the course introduction page in the VLE…)

We can also use the search context to provide pastoral or study skills support:

These sort of promotions/enhancements might be produced centrally and rolled out across course search engines, leaving the course and discipline related customisations to the course team and associated subject librarians.

Just a final note: ignoring resource limitations on Google CSEs for a moment, we might imagine the following scenarios for their role out:

1) course wide: bespoke CSEs are commissioned for each course, although they may be supplemented by generic enhancements (eg relating to study skills);

2) qualification based: the CSE is defined at the qualification level, and students call on particular course enhancements by prefacing the search with the course code; it might be that students also see a personalised view of the qualification CSE that is tuned to their current year of study.

3) university wide: the CSE is defined at the university level, and students students call on particular course or qualification level enhancements by prefacing the search with the course or qualification code.