Dear Readers,
Today’s post is about analytics in learning and education. I will provide you information and examples from an article “Penetrating the Fog: Analytics in Leaning and Education”.
Higher education is mostly connected with data collection and online education. As Google’s Marissa Mayer suggests, data usage and collection nowadays have been defined through three elements:
- Speed—The increasing availability of data in real time,
- Scale—Increase in computing power,
- Sensors—New types of data: the “Internet of Things”.
The Outcome of these three concepts are data-management and decision making approaches. When talking about data-analysis, we should consider the big data. The McKinsey Global Institute defines big data as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.” As mentioned in the article the key emphasis in big data is “that the data itself is a point of or a path to value generation in organizations. Data is a critical value layer for governments, corporations, and higher education institutions.”
Regarding the learning analytics and academic analytics, the following table illustrates the differences and the important information for each:
The important values of analytics for higher education can be defined as:
- They can develop administrative decision-making and organizational resource allocation.
- They can identify at-risk learners and the ways to assist them.
- They can improve leaders transition to holistic decision-making.
- They can provide up-to-date information in order to increase organizational productivity and effectiveness.
- They can promote learners’ self-assessment.
In general, learning analytics is essential for educators, students, and administrators in order to recognize and be aware of the learners’ performance, and identify at-risk students, so that they can revise and utilize more useful teaching plans to decrease such risks. As mentioned in the article “Learning analytics can penetrate the fog of uncertainty around how to allocate resources, develop competitive advantages, and most important, improve the quality and value of the learning experience.” Therefore, use of analytics and big data will advance pedagogical strategies for higher education in Armenia. Armenian educators and teachers should learn about this technology and its usage in order to identify their institutions’ strengths and weaknesses.
Teaching is fun! 