The availability of learning data provides great opportunities for learning professionals, but also provides its share of challenges. Evolving technologies make it easy to acquire vast amounts of data which can inform effective design and allow for meaningful assessment. Most L&D professionals, however, are not data scientists, and they may not have ready access to the IT and analytics resources needed to realize the benefits that carefully collected, effectively analyzed data can offer them. The feedback from a wide population of learning professionals indicates that there is a real need to develop foundational skills regarding the effective collection and meaningful application of learning data.
As the availability of data transforms the practice of instructional design as it is transforming other professions, there has been great enthusiasm about the potential use of data not just to evaluate learner progress, but also to improve learning design; what has been lacking is some basic principles and practices to streamline the process of using data in the learning professionals day to day tasks. The Experience API, or xAPI, is quickly becoming a significant factor in creating learning data. Understanding the basics of the xAPI specification is a key aspect to collecting usable data. We take on the specification from the point of view of the instructional designer to see it in a non-developer perspective. We also look at how xAPI is used to create the pieces needed across industries to gather meaningful, interoperable data. The first need is the understanding of data; moving the experience of data beyond mere completions and test scores into a powerful means to understand learning paths and improve course design.
This books walks readers through what data is, how to collect it and how to use it. This foundation will help them assess where they are now and where they’d like to go with their data capabilities. This book addresses how to view learning data within the larger organizational context, presenting tools to help practitioners identify data needs in terms of goals and strategies, as well as defining data required to track organizational performance goals, or to make recommendations and improvements to meet those goals. Investigating Performance uses both Quantitative and Qualitative data to take readers beyond the data L&D uses today and help them adapt tools from industries like UX design, Business Intelligence, and Competitive Intelligence to broaden their data toolset.