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Predictive analytics–using massive amounts of historical data to predict future events–is a practice that’s making it easier and faster for colleges to decide which students to enroll and how to get them to graduation. But using data in this way may make decision-making processes harder, not easier. That’s because predictive analytics can aid in discriminatory […]
The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the copyright permissions of resources allow for remixing, […]
Recent critiques of both the uses of and discourse surrounding big data have raised important questions as to the extent to which big data and big data techniques should be embraced. However, while the context-dependence of data has been recognized, there remains a tendency among social theorists and other commentators to treat certain aspects of […]
A new research initiative from McGraw-Hill Education and Colorado State University is exploring the use of learning analytics to boost retention. The collaboration represents the first academic research project undertaken by the recently created McGraw-Hill Education Learning Science Council, a group of education experts and McGraw-Hill researchers focused on learning analytics, learning algorithms, learning quality […]
Learning analytics is a phenomenon emerging throughout Europe and they have a great potential to help educational institutions provide better learning. The ABLE project believes learning analytics is ultimately only as useful as the action it generates. OEE interviewed project partners Rebecca Edwards, Ed Foster and Tinne De Laet to learn more about the ABLE […]
New America releases framework to help colleges use predictive analytics to benefit students. Inside Higher Ed
Findings from two research studies at scale reveal the implications of learning analytics research for designing courses in learning management systems. Data-driven interventions shine light on our institutional conceptions of learning, who our students are, and our responsibility — or perhaps our willingness — to support students. By focusing the lens of analytics on course design, we may be able to define success in […]
In this paper we present an example of a Social Learning Analytics Tool to visualize real-time discussion activities in a MOOC environment. Practitioners and researchers can read how to implement and use such a SLA tool as a plugin in practice. Open Education Europa
Code-Dependent: Pros and Cons of the Algorithm Age Algorithms are aimed at optimizing everything. They can save lives, make things easier and conquer chaos. Still, experts worry they can also put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in […]
Learning analytics are often formatted as visualisations developed from traced data collected as students study in online learning environments. Optimal analytics inform and motivate students’ decisions about adaptations that improve their learning. We observe that designs for learning often neglect theories and empirical findings in learning science that explain how students learn. We present six […]
