| | MAY 20209IT IS EQUALLY IMPORTANT TO COMMUNICATE WITH PARENTS ON HOW THE DATA IS BEING COLLECTED AND WILL BE USEDotherwise all that data is useless until institutions unlock its poten-tial. To effectively harness the po-tential of learning analytics, data that often sits unused on servers and databases must be mined to a state where it speaks volumes. Learning analytics is gaining momentum and will continue to evolve and innovate quite rapidly, remem-ber the whole point is from data mining to find positive actions that can be taken to spur improvement.Learning Analytics (LA) fo-cuses on applying tools and tech-niques at larger scales in instruc-tional systems while Educational Data Mining (EDM) focuses on de-veloping new tools and algorithms for discovering data patterns. If used properly, it can provide learn-ers with a personalized eLearning experience, help schools increase retention rate, guide on how to improve the course structure and fuel the modern education system and pedagogy in particular.How does all this work? It all starts with the learning sys-tem where a student learns online and the system captures detailed data about the student's experienc-es. This Big Data then can be used to make predictions about future performance. Students can then receive personalized material to fuel the performance growth and teachers can intervene and help as necessary. As with most techno-logical advancements, there are costs and challenges which can yield a high return on investments by developing a culture that uses data in making instructional de-cisions, involve IT departments in data collection roadmap, start with focused areas where data will help and build from there. It is equally important to commu-nicate with parents on how the data is being collected and will be used. There are a wide variety of current methods popular within educational data min-ing. These methods fall into the following general categories: prediction, clustering, relationship mining, a discovery with models, and distillation of data for human judgment. The first three catego-ries are largely acknowledged to be universal across types of data mining whilst the fourth and fifth categories achieve particular prominence within educational data mining.What is the goal? Predicting learner's behavior by improving student models, im-proving knowledge domain struc-ture models, studying the most effective pedagogical support for student learning and finally estab-lishing empirical evidence. These can be achieved by adapting psy-chometrics, employing statistical techniques, mining log data, face-to-face contacts, studying the psy-chology of how humans learn and using Intelligent Tutoring System (ITS). When working towards these goals it is important to think about all the stakeholders and not just the students. Consider the ed-ucators, researchers/ developers, and institutions.How to keep the data "un-polluted" for effective data mining?Data management for analytics is not the same thing as data man-agement for an enterprise data warehouse as it adds value along the way by completing summari-sations and adding metadata to variables. The process to keep the data clean is to simplify ac-cess to traditional and emerging data (try to minimise data move-ment between data sources and focus on improving governanc-es), strengthen the data scien-tists' arsenal with advanced an-alytics techniques, scrub data to build quality into existing data capture processes, shape data us-ing flexible manipulation tech-niques and finally share metada-ta across data management and analytics domains. ConclusionLA and EDM ride on high expec-tations even though they are rela-tively new fields of research and prone to several issues that need to be addressed. Big Data with technological progress represents an important paradigm shift and offers multiple opportunities. Despite the promise and high ex-pectations, their application in ed-ucational environments is faced with barriers, such as lack of a da-ta-driven culture and comprehen-sive easy-to-use integrated tools for LMS. Jimit Dattani
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