Avoid These Top Mistakes In Digital Learning Development

Avoid These Top Mistakes in Digital Learning
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    As you may be experiencing firsthand, the COVID 19 crisis has pushed students out of the classroom and into the world of online learning. Experts predict that online and remote learning isn’t going anywhere and that most schools will continue with an eLearning hybrid approach. If digital is our future, how do we provide the best education for our learners?

    In the age of technology, data, analytics, and AI can be incredible tools for supporting learners, but it’s important to understand the common pitfalls of eDesign before embarking on your own learning experience. This post will help you avoid the top five eLearning design mistakes, and help you better envision the future of work. 

    Data Content Is King

    Mistake 1: The theoretical approach. Many ed-tech developers begin with the “bigger picture” as opposed to thinking of students on a smaller scale. Instead of getting caught up in grand theoretical schemes, look to methods that have been statistically proven to help learners, such as active learning and self-regulated learning

    Try Including learning scientists on your team. This will help you narrow down the best strategies for students and provide insight into the details of effective education. 

    Mistake 2: Letting dashboards do all the talking. Data dashboards remain a common resource for instructors. Unfortunately, the designs of many analytics dashboards are not intuitive and require instructors to work very hard to find the information they are looking for. 

    Consider conducting a masterclass in dashboard reading for instructors or providing them with clearer guidance before taking on a new design system in the classroom. 

    Stay Constantly Connected With Learners 

    Mistake 3: Looking at limited data sources. Learning analytics often focus on data from the cognitive or behavioral domains. The cognitive domain is represented by student performance on activities and assessments, while the behavioral data is represented by data like student interactions with technology. 

    What gets overlooked, unfortunately, is the needs of the students themselves. Ask yourself how learners feel about their courses and their learning. Discover what is motivating or demotivating them. Once you find out how they feel about the new eLearning system, you can make changes accordingly. 

    Mistake 4: Ignoring the greater impact. Many data science teams focus on looking at key trends in the data to see what insights pop out without investigating whether specific interventions lead to desired learner outcomes.  

    Bridging the gap between trends and outcomes requires you to establish your goals for learners early on. What exactly is the desired outcome of this eLearning design? Consider using top Innovations in assessment development, such as natural language processing, which might help illuminate the connections between humans, computers and impact. 

    A Design System for Students

    Mistake 5: Forgetting to develop learners. Digital learning tool analytics often occur outside of the classroom, which leaves learners clueless about how their cognitive, behavioral, and affective data is being used to support their education. 

    Make sure to incorporate disclosure statements or metacognitive advice in your plan. This way, students are given the chance to reflect on and improve their learning. 

    It will take some time before all data is available to the learners who provided it, and students are equipped with the tools for understanding this data. Regardless, practicing honesty with your clients is a good business practice, and will build trust between you and your audience. 

    Building Better Digital Habits 

    Embracing data-driven learning is challenging, and will take time for both tech teams and learners. With the right expertise in learning and data science, paired with the desire to help students, this kind of learning could easily be our future. 

    What are some of the challenges you have faced either as a tech company, an educator, or a student coming to terms with data-driven learning? Don’t be afraid to share your hopes and fears with us here at WeLearn. Together, we can make the future of education brighter and better.

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