Technological Innovations in Data Usefulness
This post is provided by guest blogger, Gerald Edwards Jr., graduate student University of St. Francis, MS Training and Development program
There is a massive amount of digital data available on any number of subjects. AI has pushed the boundaries of big data. Gleaning useful information from endless search parameters is an infinite challenge, especially in the e-learning setting. The use of AI and big data mining makes it nearly impossible for students, in the time frame of semester course work, to make meaningful connections between various subject matters. There is an emerging tool that is indispensable to students and researchers at all levels of education, but specifically in the e-learning setting.
An article published in the journal Heliyon, analyzes the available peer reviewed published research literature on the use of data graphs as an effective search technology which is highly adaptable and suited for the digital learning environment. The authors provide a systematic appraisal of user usefulness and successful research outcomes in the digital learning environment when searching topics using institutionally compiled data graphs. Data graphs allow seemingly independent information variables to interconnect and return more meaningful data to the user through AI and human compiled related data. This information is useful when students and institutions are interested in a comprehensive understanding of a specific topic. Data graphs have been developed in other areas but are emerging as a invaluable tool for higher education students and instructors participating in the e-learning environment.
Abu-Salih, B. & Alotaibi, S. (2024). A systematic literature review of knowledge graph construction and application in education. Heliyon, (10)3. https://doi.org/10.1016/jheliyon.2024.e25383
e-learning
