Tools for teaching and learning
To really understand the relationship between technology and education we need to take a better look at the word ‘technology’. The word is often used synonymously with the phrase ‘modern technology’ (mostly in reference to computers, the internet and other digital breakthroughs of the previous decades). Modern technology, at least when still in its state of modernness, rarely sees a smooth journey to widespread adoption. More often than not it stumbles its way into the mainstream, with rapid gains and stalls coming frequently. ‘Technology’ simply refers to the application of scientific knowledge for practical purposes. When we speak of ‘educational technology’ we refer to the effective use of technological tools in learning. This included (and still includes) the abacus, writing slates, blackboards, books and slide projectors. The last 15 years have seen an onslaught of development in the IT and software industries, which has left many confused over the current and future direction of technology in an education context. It can be hard to delineate the significance of computers, the internet, specialised software and the uptake of mobile devices. Two terms exist to encompass all of these in regards to education – Computer-Based Instruction (CBI) and Computer-Based Training (CBT). For the most part, these two terms mean the same thing. From a media perspective it’s worth considering that all of these technologies serve a similar purpose, which is to transmit audio and video both to and from a learner. When viewed this way, it’s possible to further break down these tools into two broad roles – to enable learning to take place over large physical and time distances, and to augment learning with the power of technology. The concept of a Learning Management System (LMS) is largely based in the first of these roles, however two specific modern advancements look to be on the cusp of a radical shift in the structure of education – mobile learning and the Tin Can API.
M-learning
Mobile learning, sometimes called M-learning, has an equally lofty definition – learning across multiple contexts, through social and content interactions, using personal electronic devices. Marketers and technologists have long since learned that rapid incremental change often leads to outdated definitions when these sorts of industry terms are defined too specifically. This can lead to a too-narrow focus and missed opportunities. For that reason, M-Learning technologies include tablets and mobile phones, as well as notebooks. The most quantifiable benefit of M-Learning is the almost instantaneous nature of content sharing amongst learners and teachers. This breakthrough alone has shown to boost exam scores from the fiftieth to the seventieth percentile, though the mechanics of this are still being debated. Research by Aurion Learning has shown that successful M-learning requires a different pedagogical approach focused on access, less structured learning, short bursts of content, and the ability to learn-on-demand. This year’s boom in ‘wearable technology’ has a lot of industry-watchers excited. Verizon Wireless recently conducted interviews with CEOs to find out where they thought wearables fit into learning. The overwhelming response was that jobs requiring high levels of technical expertise or requiring remote feedback or support would most benefit from rapid-learning coupled with wearable technology. Another survey by PWC showed that 77% of workers believe an important benefit of wearable technology coupled with M-learning is in making people more efficient and productive at work.
While the most obvious benefit of M-learning is in its ability to bring learning to a large quantity of society, other technological advancements are more focused on improving the quality of learning for individuals.
The Tin Can API
For the past ten years, the default technology for capturing and distributing online learning has been the SCORM standard. The philosophy behind SCORM largely came from the same philosophy that guided offline education, namely that a learner could be judged by the quality and quantity of finished actions, whether these actions comprised parts or the whole of some form of accreditation. This was powered through SCORM’s use of metadata in handling web-based content and events. The thinking was to essentially categorise and sub-categorise formal learning depending on the level of granularity to be captured. Most educators now agree that at least 70% of all learning occurs informally – in what you could call the ‘experience zone’. The US Department of Defense (through its Advanced Distributive Learning standards body) recognised this shortcoming in 2010 and awarded a contract to Rustici Software to research and define a new standard, which they did a year later.
The Experience API (also known as Tin Can API) uses an Actor:Verb:Object-style statement written in simple code. This simplicity allows for all sorts of different ways of capturing learning events – for example, replace Actor:Verb:Object with John:Read:ATrainingManual, or Stacey:Created:CampaignArtwork. This is a radical advance towards truly understanding the learnt value of a person.
Implications
Think of mobile-learning as primarily increasing the spread of education and the Tin Can API increasing the depth of education. Like most things to do with education, this is not a tradeoff per-say, simply two improvements that are likely to mutually reinforce and strengthen each other. For example with traditional LMS content, rigid data models and in-browser JavaScript communication requirements make it difficult to support emerging mobile technologies. The way the Tin Can API captures learner data facilitates much richer learning experiences which can be made and measured. Essentially any action a user makes can be sent as a Tin Can statement to a Learning Record Store (LRS), which holds all of these statements and exists separately from an LMS. Because Tin Can frees up the collection of learner data from web-browsers (through its use of one more digital Learning Record Stores), activity creators can now use native applications on mobile for trackable learning. While this all sounds quite technical, the potential impact on learning is huge. For example, with each game of Sudoku you play in your time off, your reasoning and pattern-matching ability can be logged and measured (and used to create a more accurate ‘learning style’ for you). With the power of Tin Can and mobile phones, all of the wonders of the modern phone can be utilised for both learning and learning capture – such as the phone’s accelerometer, GPS, camera, compass, and gyroscope. The open and super-flexible architecture of the Tin Can API, at its core, removes some enormous hurdles that currently exist in online learning and frees the future of learning up to the creativity of tomorrow’s learning creators.