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Can Quantified Self Affect Your L&D Program?
The term “quantified self” refers to the use of technology to collect data about our life, like health and workout metrics. If you need an example, just look at your smartwatch. Those devices collect data like fitness habits, health patterns, sleep schedules, and even indications like blood pressure and oxygen. This method of tracking can be beneficial, despite the overexposure of our data, as it prompts us to keep up with positive habits or change the ones that don’t contribute to our overall well-being.
Quantified self and eLearning are based on the idea that data collection can help improve our learning behaviors. More specifically, gathering information about a learner via their own tracking device can reveal a great deal about their training performance. It also allows you to design Learning and Development programs that are more targeted for personal growth and self-improvement. In this article, you will read about how data monitoring can help you optimize your L&D strategy.
4 Ways Quantified Self Can Fit Into Your L&D Strategy
1. Personalization
The quantified self can help people understand their strengths and weaknesses. By tracking their physical and mental state, learners are able to see which times of the day they are most productive and when they need to take a break. This information can be used to create customized eLearning plans, taking individual needs and preferences into consideration. For instance, if a learner feels their productivity rise in the mornings, they might want to schedule their online courses earlier in the day. If they realize they can’t concentrate for more than half an hour, shorter sessions may be in order.
2. Time Management
There are multiple time-tracking apps that you can pair with your L&D programs. By tracking their daily routines, learners can identify where they are spending more time than they should and adjust their habits to leave more time for their courses. For example, someone who spends most of their time on their phone may decide to limit their screen time and focus more on their training.
3. Gamification
Use your learners’ self-tracking metrics to gamify the eLearning experience. They can set goals and track their progress, or even try to score points in a reward system. For example, encourage your learners to complete three microlearning sessions per week. The system will track their progress and allow them to accrue points or move along the progress map. Gamification also improves motivation since learners are able to see how far they’ve come and track individual milestones.
4. Mental And Physical Health Improvement
Learners can measure their physical activity, sleep schedule, food intake, and other metrics to identify where they need to make changes. This will help them optimize their habits, making them healthier both physically and mentally. So, it’s a great idea to incorporate break reminders in an L&D program to encourage them to take a mental refresher and avoid burnout.
Challenges Of Quantified Self In eLearning
Data Security
One of the biggest issues with collecting data, in general, is privacy and security. It’s crucial to ensure that learners’ data is protected from hacking, data breaches, and unauthorized access. This requires encryption methods and secure data storage systems combined with strict access controls. It’s also crucial to have clear policies regarding the data’s use. For example, your eLearning platform or L&D program should clearly explain what data is being collected, what the program is doing with it, and who can view it.
Technical Issues
The collection of data from wearable devices like smartwatches or fitness bands requires compatibility with your Learning Management System. This can be a challenge, especially if the learners are using different types of devices, as the data may not be consistent and not easily comparable.
Access To Devices
Not every learner has a wearable gadget to monitor their habits and help L&D teams customize the learning experience. As such, you may need to provide learners with these devices if you want to track daily metrics. Otherwise, you run the risk of creating a training program that excludes those who do not own the necessary tech or will be unable to offer them personalized learning paths because you lack the analytics.
Privacy
On the other hand, some learners who already own wearable devices may not be comfortable with their data being shared, even if it’s beneficial for their learning process. Thus, you should give them the ability to opt out if they have privacy concerns. Keep in mind that you can still use your training software to track certain aspects of their performance, such as completion rates and software login frequency.
Conclusion
Quantified self practices have the potential to enhance your L&D strategy, as they can optimize the learning experience as a whole. However, it’s vital to safeguard learners’ data collection and analysis, as well as consider all of the challenges and limitations mentioned above. Your quantified self data management practices must be ethical and fully transparent to build trust among your learners and maximize the metrics.
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