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Reporting & Analysis of Mobile Learning: Is It Worth It?

“Mobile learning is here to stay. There doesn’t appear to be an end in sight as smartphones and tablet devices become more and more pervasive. Through continual evaluation and analysis, mobile learning strategies will become an effective component of any learning strategy.”

Technology allows us to do some amazing things with learning. Today, everyone wants to mobilize his or her content. It’s almost impossible to attend a learning and performance event without feeling inundated with presentations on mobile strategy, or the latest in mobile authoring solutions.

The challenge remains … is the effort worth it? Most stakeholders can’t explain (at least in concrete terms) why they need to create mobile learning for their audience, let alone why they need a plan to track and report on those efforts. In order to get the most out of your mobile learning strategy, here are some questions to get you started on reporting and analyzing this content.

What are you tracking?

To begin with, you have to determine what information you will need to track. As with all training, there are standard components you want to track. Those may include course attempts, completions, scores, etc. However, mobile learning opens up a number of other opportunities. For example, how do you account for level of interaction, reuse as performance support, and social learning?

Informal and/or social-based learning is rapidly becoming a mainstay of all learning activities. Some research suggests informal learning may account for as much as 70 percent of all corporate learning. Given the nature of mobile device integration with social media (including both smartphones and tablets), informal learning will continue to take on a larger role in corporate training. It’s important to identify the specific touch points within social learning that we need to track and report on. In addition to traditional learning, we need to give focus to frequency of interactions, type of interactions, and level of contribution.

How do you track it?

Tracking learning events has long been measured around AICC and SCORM standards. Most major learning platforms and authoring tools tout their support for these standards. However when it comes to mobile learning, you need to make sure your chosen platform supports these standards within a mobile context.

The first step is to review your authoring solution. If you’re creating your own content, there are a number of solutions that claim to author for mobile consumption. Test several out and pilot them with a variety of end users. Keep in mind that tools leveraging plugins are problematic for mobile devices, particularly as pertaining to tracking and reporting. The key is to focus on native HTML- and JavaScript-based authoring tools.

Next, confirm that your method of deploying content supports tracking of mobile assets. As with the content tools, make sure the system avoids the use of plug-in-based architectures for their SCORM or AICC packages. For example, it’s common for a LMS to leverage a Java-based SCORM player. HTML- and JavaScript-based content players are generally the best solution as they are available as standard browser features without the need for a plugin.

As previously mentioned, mobile devices naturally facilitate the use of social and informal learning. You will want to track these events on a different level than you do traditional classroom or online learning as learners access blogs, wikis, Twitter, YouTube, etc. from their mobile devices. Assuming these resources are part of your learning strategy (and they should be), you will want to track and evaluate how people are using them. It’s common to find authoring and talent platform solutions integrated with these informal resources. Just make sure you include tracking and reporting on the use of those resources and that mobile devices support them.

How are you evaluating it?

You need to prepare in advance for how you’re going to evaluate your mobile learning outcomes. It’s a little too late once you start collecting the information. You must start by clearly defining the objectives and intended outcomes.

Some groups find it challenging to nail down their exact intent for mobile learning. Determining if it will be a primary method for delivering training, or whether you let it focus on training and performance reinforcement provides the bulk of the needed direction. Evaluating the impact of performance support materials is very different from evaluating that of a complete training program. With clearly defined objectives, stakeholders are able to better evaluate the effectiveness.

From an overall evaluation perspective, mobile learning remains very similar to that of classroom or eLearning. You can leverage Kirkpatrick’s Model of training evaluation as the analysis basis for your mobile content. Of course, the focus still remains on the ability to impact behavior (Level 3) and business results (Level 4). Ultimately, senior stakeholders may even ask what the ROI is.

ROI within the learning space results in a mixed response. Kirkpatrick suggests you should instead focus on Return on Expectations (ROE). This is easy to do if those expectations are set from the outset. You’re then able to match the collected metrics with the defined expectations and determine to what extent they are met.

Is it worth it?

In the end, you must ask this one question: Is the effort required to create and deliver mobile learning worth it? Mobile learning is here to stay. There doesn’t appear to be an end in sight as smartphones and tablet devices become more and more pervasive. Through continual evaluation and analysis, mobile learning strategies will become an effective component of any learning strategy. It won’t be long before informal mobile learning becomes the main element of a holistic learning and performance strategy.


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I think it's important to firstly differentiate between mobile "learning" and mobile "support" (as in performance support).

Mobile "learning" suggests formal structured learning with an design approach no different to that for any other structeured learning activity - objectives, assessment, teaching strategy. As such the Kirkpatrick approach for evaluation works.

For me, un-structured (informal learning) under which mobile "support" falls is, from an evaluation perspective, at Level 3 (Application) and that's where we need to demonstrate value.

Overall I have found that there are some basic things often not considered well enough these days.

The first is agreeing at the outset and with all stakeholders what constitutes success - "how will we know when this (intervention) has been successful?"

The second is about a communication strategy with a focus on managing expectations - for example if an intervention is being built that is clearly about supporting performance just-in-time then don't try and convince anyone it's a formal training program, and don't try and evaluate it as such.

Thirdly, consider evaluation form the outset as integral to the quality control planning and its execution throught the development process.
I partly agree with Spence that learning is something structured while by m-learning we often mean some kind of performance support or instant knowledge pill.

Evaluation is always necessary by educational projects and there is no difference with m-learning. The stakeholders want to know if the invested time and resources bring any value, and the designers want to see if there is anything that needs upgrade.

The technical issue is not the case. There are at least a few ways to monitor m-learning: special LMS that allow "playing" with the content offline and sychronizing when user is online, monitoring of social activity (which is often part od m-learning solution) or specially designed SCORM courses that you have mentioned.
First of all, thank you Skip for the though provoking article. Also I got as much out of the comments as I did the article it's self. All in all, has left me wondering should our educators be putting so much effort in trying to make mobile learning fit the traditional educational cookie cutter, or should they be focusing on a totally new ... "what is learning now that mobile devices will be used more that PCs themselves? I have often felt and stated scorm and aicc will be a thing of the past, smart devices take over the world and the world becomes more global. Those two platforms will be to education as DOS is to computers now days. We all need to start thinking of how learning will change its self, before developing the tracking and assessment aspects. Else you are wasting your time. For example as appliances adapt technology that evolved from the mobile evolution, less will be delivered via the traditional classroom, as say your kitchen appliances teach and monitor your home economics skills, your car monitors your driving skills all tied to your phone with your personal IA instructor, interacting and teaching you throughout your daily routine. (using mobile technologies such as your location, real time news and media, virtual classroom attendees from around the world, motion sensors, Google's Gogggles to see and identify what is around you, physical activities using wii technology, apps and technology not yet on the market but will be next year... next month,etc. )

Just saying all the data, and data types will never fit within traditional monitoring techniques and frameworks like scorm, and the words evaluation and assessment, even score are taking on a whole new meaning. Just like today, I would never see text book learning being used in place of the highly interactive software 'Training" we currently develop for the skilled trades industry. In our industry, our maintenance and engineering simulation training software is so complex, scorm can not camper to the level or reporting and evaluation we currently get from custom LMS built to handle the simulations. Mobile is going to be so much more than that. So if while thinking mobile learning, you are also thinking of scorm implementation, you has missed the picture of what exactly mobile technology is.
The previous comment on mobile devices interacting with tools and equipment along with AI "instructors" is an interesting one. I have designed a program for training commercial truck drivers on a simulator along these lines. In order to implement a design that would provide appropriate feedback on task performance (in this case, shifting) we faced some complex tasks:

1. We had to create simulator hardware and software built from the ground up to support the training objectives, not just emulate equipment operation. For example, pressure exerted on the shift lever is a behavior that differentiates expert from novice drivers and existing driving simulators did not have the hardware or software capability to measure this.

2. The parameters of the behaviors we wanted to train had to be clearly defined and validated. For example, a single shift for a commercial truck takes less than 2 seconds to complete and yet there are over 12 discrete sub-tasks that must be executed with precision in that time frame. SMEs did not agree on the precise sequence of events. We had to create a software program that would allow us to capture and document expert performance before we could begin to write training. An interesting side note - the actual performance of the SMEs was virtually identical, it was just their individual perceptions of what they were doing that differed.

3. The instructional software had to be designed to interactively access, process, and respond to performance data. Both drill and practice exercises and freeplay driving simulations had to be designed that included progressively decreasing levels of remediation and increasing levels of difficulty.

Bottom line, mobile monitoring of performance and just-in-time AI tutoring is a wonderful ideal and works remarkably well when it's done properly. However, it's difficult, time consuming, and expensive to develop.

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