{"id":113,"date":"2013-10-31T19:41:18","date_gmt":"2013-11-01T02:41:18","guid":{"rendered":"https:\/\/blogs.ubc.ca\/learninganalytics2013\/?page_id=113"},"modified":"2013-11-03T13:34:44","modified_gmt":"2013-11-03T20:34:44","slug":"best-practices","status":"publish","type":"page","link":"https:\/\/blogs.ubc.ca\/learninganalytics2013\/best-practices\/","title":{"rendered":"Best Practices"},"content":{"rendered":"

Learning Analytics: Student Achievement and Student Success<\/strong><\/p>\n

<\/strong>According to Elias (2011)<\/a>, when it comes to student achievement and student success, the following questions should be considered:<\/p>\n

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Learning analytics is learner-centred and learner-focused.
(http:\/\/www.condenaststore.com\/-sp\/But-sweetie-children-are-the-backbone-of-our-educational-system-New-Yorker-Cartoon-Prints_i8473848_.htm)<\/p><\/div>\n

– How effective is the course?<\/p>\n

– Is it meeting the needs of the students?<\/p>\n

– How can the needs of learners be better supported?<\/p>\n

– What interactions are effective?<\/p>\n

– How can they be further improved?<\/p>\n

Elias (2011) states that traditional approaches to teaching and to learning involve student evaluation, the analysis of grades and attrition rates, and instructor perceptions. In turn, the evaluation and the analysis of learning include only (a) a limited quantity of data that students and instructors are willing to share at the end of a course, (b) a limited quality of self-reported\/retrospective data, and (c) a delay between the events being reported and the implementation of an intervention.<\/p>\n

\"\"<\/a>

Best Practices in Learning Analytics for Education
(http:\/\/www.elearnspace.org\/blog\/2010\/08\/25\/what-are-learning-analytics\/)<\/p><\/div>\n

However, Elias (2011) also states that emerging approaches to teaching and to learning involve analytic tools that focus on the selection, the capture, and the processing of data that will be helpful for students and for instructors at the course or individual level. Moreover, learning analytics is focused on building systems able to adjust content, levels of support, and other personalized services by capturing, reporting, processing, and acting on data on an ongoing basis in a way that minimizes the time delay between the capture and the use of data. In brief, learning analytics seeks to combine historical and current user data in order to predict what services specific users may find useful now.<\/p>\n

Lastly, Elias (2011) explains that learning analytics works to make the most of the modeling capacity of analytics in order to predict behavior, act on predictions, and use the results in the process in order to improve the predictions over time as it relates to teaching and to learning practices. In all, the study and the advancement of learning analytics involves the development of new processes and tools aimed at improving learning and teaching for individual students and instructors, and the integration of these tools and processes into the practice of teaching and learning.<\/p>\n

Learning Analytics: US Education System<\/strong><\/p>\n

This video is about learning analytics pertaining to the US education system. The presentation touches on the need to capitalize on learning analytics in the US education system in order to really put students first. Certainly, the use of learning analytics in our education systems in Canada is already evident.<\/p>\n