Can Quantified Self Influence Your L&D Program?
The term “quantified self” refers to the use of technology to collect data about our lives, such as health and exercise metrics. If you need an example, look at your smartwatch. These devices collect data such as fitness habits, health patterns, sleep patterns and even data such as blood pressure and oxygen. This way of tracking can be beneficial despite overexposing our data, as it encourages us to keep up with positive habits or change those 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 behavior. More specifically, gathering information about a student through their own tracking device can reveal a lot about their training performance. It also allows you to design learning and development programs that are more focused on personal growth and self-improvement. In this article, you will learn how data monitoring can help you optimize your L&D strategy.
4 ways the quantified self can fit into your L&D strategy
1. Personalization
A quantified self can help people understand their strengths and weaknesses. By tracking their physical and mental state, students can determine which parts 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 based on individual needs and preferences. For example, if a student feels their productivity increases in the morning, they may want to schedule their online classes earlier in the day. If they realize they cannot concentrate for more than half an hour, shorter sessions may be in order.
2. Time Management
There are several time tracking apps that you can pair with your L&D programs. By tracking their daily routines, students can identify where they spend more time than they should and adjust their habits to leave more time for coursework. For example, someone who spends most of their time on their phone may decide to cut back on screen time and focus more on training.
3. Gamification
Use your learners’ self-monitoring metrics to gamify eLearning. They can set goals and track their progress, or even try to earn points in a reward system. For example, challenge your students to complete three microlearning lessons per week. The system will track their progress and allow them to collect points or move around the progress map. Gamification also improves motivation as students can see how far they have come and track individual milestones.
4. Improving mental and physical health
Students can measure their physical activity, sleep schedule, food intake and other metrics to see where changes need to be made. This will help them optimize their habits, making them healthier both physically and mentally. So it’s a great idea to incorporate a break reminder into your L&D program to encourage them to mentally refresh and avoid burnout.
The Challenges of the Quantified Self in eLearning
Data security
One of the biggest issues with data collection in general is privacy and security. It is important to ensure that student data is protected from hackers, data breaches and unauthorized access. This requires encryption methods and secure data storage systems combined with strict access controls. It is also important to have a clear policy regarding the use of data. For example, your eLearning platform or L&D program should clearly explain what data is collected, what the program does with it, and who can view it.
Technical issues
Collecting data from wearable devices such as smart watches or fitness bands requires compatibility with your learning management system. This can be a problem, especially if students use different types of devices, as the data may not be consistent and easily comparable.
Access to devices
Not every student has a wearable gadget to monitor their habits and help L&D teams tailor learning. If you want to track daily metrics, you may need to provide these devices to students. Otherwise, you risk creating a training program that excludes those who don’t have the necessary technology, or you won’t be able to offer them personalized learning paths because you lack analytics.
Privacy
On the other hand, some students who already own wearable devices may not be comfortable with sharing their data, even if it is beneficial to their learning process. Therefore, you should give them the option 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 frequency of logging into the software.
Conclusion
Quantified custom practices have the potential to improve your L&D strategy because they can optimize the learning experience as a whole. However, it is vital to secure the collection and analysis of student data as well as to consider all the above challenges and limitations. Your quantified data management practices must be ethical and fully transparent to build trust with your students and maximize metrics.
