Victory’s spinoff metacog was just featured in a blog post by Databricks, a company founded by the team that created Apache Spark, a powerful open-source data processing engine. See the Databricks blog post below.
metacog has been hard at work releasing new capabilities of its learning analytics platform, while at the same time enhancing existing capabilities. If you offer subscription-based products, you know that your customers expect continuous improvement. With metacog, we partner with you to deliver new capabilities in deep learning analytics that you can easily integrate into your products to generate new data-driven business models and revenue streams.
Why data analytics for adaptive and competency-based learning is so challenging
You may have seen many companies offering data analytics applied to learning products. If you look closely, most of the time what is offered is “administrative-level” data and simple scoring data:
- Time-on-task data – How long did learners use the interactive?
- “Attendance” data – Did learners participate?
- SCORM-compliant scores reported to a learning management system (LMS) – How well are learners doing?
- Simple score reports – How many right, how many wrong?
It turns out that in order to improve anything, you have to be able to measure it, but so far in education we have been measuring the wrong thing – the final answer.
This explains why scoring is the key issue. In the past, most open-ended assessments had to be human-scored. And this greatly reduces the frequency with which teachers and professors assign open-ended assessments. Yet it is open-ended tasks that best assess the ability of a candidate to perform well in today’s job market.