One of the critical issues which has emerged from the debate about #blockchain is the distinction between documents and transactions. Blockchain technology is a technology for storing transactions - something for which MIT have recently released some software for credentialing (see https://medium.com/mit-media-lab/what-we-learned-from-designing-an-academic-certificates-system-on-the-blockchain-34ba5874f196#.t3r9eiimo). Transactions themselves are effectively references to documents, or hashes of documents. This has led to some spin-offs from blockchain to explore ways in which the web - which is effectively a set of relations between servers and filesystems - might be instead a list of hashed documents. This is the approach of IPFS (see http://ipfs.io) - which offers a serverless way of addressing and storing documents.
The distinction between transactions and documents has also become more prominent with the rising importance of analytics. Learning analytics counts transactions on a web server (for example, one running a VLE). It can also count words in the documents which comprise those transactions - for example, the words in an essay. Various forms of combinatoric algorithms (like, for example, Shannon entropy calculations) produce automatically-generated descriptions of user activity. The level of sophistication of the algorithms and the amount of data to process has led to a belief that such automatic analysis can identify causal explanations for things that happen. The analysis combines documents with transactions where sometimes there are many transactions and very short documents (for example, forum posts - on social media, Twitter), and other times there are very few transactions and a very long document (an essay).
In education the production of a long document (on time) with few transactions is unreliable. Students who have few transactions with the institution - whether it is not attending lectures (and signing the register) or not logging on to the VLE - are unlikely to produce the 3000 word essay assignment at the end of it. A lack of transaction data is usually a sign that the student has dropped off the course. Few transactions in most walks of life is usually a sign of a system about a break down - whether it is a company or a marriage. Some sociologists (e.g. Coase's New Institutionalism, Luhmann's social systems theory) have gone so far as to say that social institutions only exist because of the transactions that are made with them. If the transactions stop, the institution dies.
On social media, the drive of the company strategies of Facebook, Twitter, Google and Microsoft have been to increase the number of transactions users have with the services. If fewer people tweet, or send fewer tweets, Twitter has less data to exploit, whilst it is threatened by the possibility of a shrinking body of users to keep it going. So it has to find ways of getting people to interact in small transactions more: 'likes', 'retweets', 'pokes' and other minimal transactions are one strategy. Much more important however is the exploitation of mobile technology. Users staring at their screens endlessly on trains or even at the dinner table are sending transactions regularly - even when they aren't consciously aware of it: simply scrolling down the timeline now returns data to the service operators: these are tiny transactions which can be aggregated and analysed.
The latest technologies only increase the trend of more rapid transactions and more detailed documents contained in those transactions. Facebook's acquisition of Oculus Rift has enabled it to potentially exploit every head (and maybe every eyeball) movement at users immerse themselves in virtual worlds. At the same time, the rise of Bots is also focused on increasing transactions through the creation of conversation agents which are designed to prompt responses from users (these too are documents). Whilst most of the world will be fascinated by the Bot's 'intelligence', the whole purpose of the Bot from the service provider's point of view is to maintain engagement: it's not a Turing test where an end user cannot distinguish a human from a machine; it's a game aimed at maintaining the engagement of the user. Finally, games themselves are also transaction generating.
When it comes to education, there has also been a rise in importance of mobile, and this too has been focused on increasing the regularity of transactions. Mobile-based e-portfolio systems for example, have tools for capturing information in as lightweight a way as possible. Games-based learning, when done well, has also had this effect. But one of the critical things is the importance and potential of the documents which are produced by machines in response to user input.
The process of engagement and increasing transactions depends on the machine producing a document which constrains user behaviour in such a way that they continue to submit transactions. Seen this way, Bots are automatic document-producing machines. In fact, so is Google search: a user query is a short document, to which the machine responds with another document.
If teaching and learning is seen as a 'viable system' between a teacher and their learners, the principal way in which this system is viable can be measured in the transactions which are exchanged. If the teacher wants to increase the number of transactions (and therefore make the relationship more viable) they need to find ways in which learner interactions are 'rewarded' with documents which constrain future behaviours to continue to submit transactions.
Recently, I've been experimenting with automatically-produced documents to do just this. Effectively these are analytic reports which are sent to learners summarising their recent activity. The reports are all sent out at the same time, so learners tend to talk about them when they arrive (this is using time as an additional constraint). The reports indicate in a simple way where learners might need to increase their activity - and very often, it seems, this gentle 'nudge' has the effect of changing their behaviour (reported in the following week's report). There are many kinds of automatically-produced documents which are possible - many kinds of creative analysis which can serve to get learners talking to each other. And there are reports that can be created of learners' interactions with each other in the light of the reports.
The interactive web confuses the distinction between documents and transactions: a dashboard, for example, is a document which invites transactions to produce a new variety of document. Yet the distinction between the two is simple: documents constrain transactions; transactions produce documents. E-learning is about manipulating these constraints in such a way as to encourage conversation between learners and teachers.