The Next Step for Learning Analytics
Jinan Fiaidhi
Abstract
Open-access reader
Jinan Fiaidhi
Abstract
Open-access reader
Use of learning analytics in real-world educational applications is growing as academic institutions realize its potential, especially in dealing with the exponential growth of unstructured data. Adding text analytics to learning analytics applications is particularly appealing, because most of the unstructured data dealt with in academia involves text. This article discusses the importance of using textual analytics within the paradigm of learning analytics.
OpenAlex reports 38 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Use of learning analytics in real-world educational applications is growing as academic institutions realize its potential, especially in dealing with the exponential growth of unstructured data. Adding text analytics to learning analytics applications is particularly appealing, because most of the unstructured data dealt with in academia involves text. This article discusses the importance of using textual analytics within the paradigm of learning analytics.
Key concepts: Learning analytics, Analytics, Computer science, Data science, Software analytics, Data analysis, Cultural analytics, Big data