In the past few years, online learning has come a long way from linear, static slides that the user clicks through. Modern systems engage learners with high-resolution video, audio, and interactive technologies that can ascertain learning, such as quizzes. In addition, companies are now making training accessible on mobile devices, so learners can train on their own terms and at a time that fits their workload and schedule.
These technologies and methods are helping make online training more equitable than high-touch (and high-cost) live training. Now we are entering the next phase of development for online learning. Platforms will incorporate analytics and sophisticated tracking and feedback tools to help close the gap on a distinct advantage of classroom instruction: emotions.
Feedback from learners
It’s pretty easy for a physical classroom instructor to determine whether her class is engaged or not. Body posture, body language, facial expressions, and eye contact are just a few of the available signals. The instructor also has the extra advantage of asking the class directly if they understand the content or if it is boring them to tears. With a perfectly timed raise of the eyebrow, the instructor can elicit laughter and make a meaningful connection with the audience.
The training software industry is beginning to deliver intuitive tools that allow trainers to understand how users are reacting to the content. This enables trainers to measure the effectiveness of the content and the likelihood that they are reaching educational objectives. This is important, particularly in fields such as law enforcement, armed forces, and healthcare, where missing information could result in dangerous consequences for users and patients.
Generally, trainers want to know when users are getting bored, or when the content is simply too complex. Electronic eye and facial tracking technologies embedded in training tools can give instructional designers and organizations an objective, more personal, and more relevant analysis of the training, through the collection and instant analysis of potentially thousands of data points captured about learners, their learning preferences, and their unique needs.
If 65 percent of users look away from the screen for 15 seconds or more during Section 3, that’s a pretty good sign that something is not clicking. Or what if 80 percent of users look confused during one segment? There’s another reason to reevaluate the content. Adaptive systems incorporating tracking technologies have the potential to make online training more effective for the larger audience and personalized for the individual learner.
Tracking technologies: a rich history
As you might expect, these technologies are not new. The AdELE framework was one of the earliest areas of research for eye tracking, although it references work done in the 1960s and 1970s. In the AdELE framework, the researchers state the goals as “to observe users’ learning behaviour in real time by monitoring characteristics such as objects and areas of focus, time spent on objects, frequency of visits, and sequences in which content is consumed. [They want] to gain an insight into the strategies which users apply when using an eLearning platform and to be able to detect patterns indicative of disorientation or other suboptimal learning strategies.”
More recent technology, based on a concept called Structure from Motion, is used in online maps and 3-D movies reconstructed from 2-D material. One use of this technology for expression tracking is to compute a full 3-D face shape and then track the center of the pupil to reconstruct a person's basic gaze. A company called Affdex uses video tracking to read facial expressions in order to measure the emotional connection consumers have with advertising and media. Emotion tracking is a nascent concept in the field of education and training, but it’s definitely coming.
Facial tracking is already having business implications. Some smartphones unlock the screen when the owner looks at the phone's camera, instead of requiring a code. In a recent episode of 60 Minutes about facial tracking, Professor Alessandro Acquisti of Carnegie Mellon University predicted that in the near future, smartphones would make facial searches as common as Google searches. As with any groundbreaking new technology, there are both positives and negatives for society.
The positives include better security for our devices; in eLearning, the benefits are specific, real-time, feedback mechanisms that help designers, instructors, and those receiving instruction. This has potentially enormous application not only for corporate training but even in higher education, where online learning is beginning to transition from experimentation and classroom supplementation to accredited, online degrees. The promise is that highly relevant, personalized, and dynamic online learning can be as effective—or even more so—than offline learning.
Practical use of tracking tech in training
Here’s how tracking technologies work in an online training session: After the user starts the training on a PC or mobile device, the software can not only analyze reactions for later analysis but respond to them in real time. For instance, if the program detects that the user has looked away for more than a few seconds, the training will pause that segment. If the program detects through expression analysis that the user is confused, it may offer a quiz or present the information in a different way. The designer has full control over how the software reacts to the user’s eye movements and facial expressions, so that, for instance, the user could opt out of the replay. Such tracking and assist technologies are merely another aid to the designer or the trainer—and not intended to “take over” the session like HAL, the computer gone mad in the epic film 2001: The Space Odyssey.
Concerns about tracking and feedback tools
However, we don’t want to make light of the valid concerns that people may have about digital tracking technologies:
First, there is the claim that such technologies are “Big Brother” tools, which help employers spy on their workers and catch them in the act of goofing off during a training session. This claim overlooks an important differentiator in how the technology is being incorporated within online learning. Developers of eLearning software are collecting and reporting on aggregate data from the audience. Trainers and managers do not receive individual reports or videos of users taking training, but instead, trends across their audience.
The goal is to improve the training, not penalize individuals. The payoff is that trainers and designers receive invaluable feedback on which course content is providing the highest or lowest amount of engagement. Instead of guessing, trainers and designers have a more precise idea of which materials need improvement—insights that they could combine with user surveys and quizzes to get a well-rounded analysis of the training program.
Another issue is the accuracy of the software’s analysis and feedback. If a learner is distracted by a colleague walking by and making a joke, and then laughs, it could be misinterpreted. Or, someone who looks at the ceiling for 30 seconds or even a minute may still be consuming and connecting with the information. Learning styles are not the same for everyone.
Of course, these situations happen in live trainings too, although the instructor can stop the discussion and check in with students if needed. During an online training session, obviously that’s not possible. Yet with some of the features mentioned above—pausing of the training program and presenting the user with options to continue, replay, or skip the content for later, the learner is still in control of his or her experience.
This brings up an important point, in that the quality of the science behind these tools is critical. Software providers will need to account for other variables in designing accurate facial and emotive tracking tools, such as gender and cultural differences. It’ll be easy to develop and publish faulty software; developers will need to incorporate specialized expertise on facial and body language, learning modalities, and more into their products.
We’re still at the early stages of this technology. In less than 12 months, though, it’s possible that some of these tools will be fully incorporated in the top eLearning platforms. The transition may not be easy, and adaptive learning software won’t be a great fit for all companies. Yet this is our future. Consider the days when there was a backlash against GPS technologies: people didn’t want to know that their movements and locations could be monitored by some device. Yet now, what would we do without tools like Google Maps and the GPS systems in our cars?
True, there will be some element of privacy lost in the incorporation of tracking technologies into learning, yet the upside might be bigger. Companies are constantly in demand of new skills, which can be exceedingly difficult and costly to find in the workforce. Retraining employees on any number of topics from new regulations to productivity skills to technical skills will be a continual requirement in maintaining a competitive, high-performing workforce. Employers won’t be able to afford to do this exclusively through live trainings; digital training is the only way that we can bridge the learning gap economically and effectively.