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Using Learning Analytics to Improve Learning Techniques COMP 683 F12 David Cachia 3050444.

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Presentation on theme: "Using Learning Analytics to Improve Learning Techniques COMP 683 F12 David Cachia 3050444."— Presentation transcript:

1 Using Learning Analytics to Improve Learning Techniques COMP 683 F12 David Cachia 3050444

2  Improving the overall learning experience of students and teachers.  Personalize learning strategy by learning about the student and how they react to different learning styles.  Once style(s) are realized, tailor testing and learning material to cater to student needs. Objective

3  Student Testing  Time elapsed per second  Incorrect vs. Correct  Environmental  When is the student doing their tests?  Student demographics Where is the data coming from?

4  Student Learning  Learning Technique  Visual, Auditory, Kinesthetic/Tactile(if possible)  Cognitive Approaches (efficiency)  Participative  Competitive  Collaborative  Independent/Dependent  Environmental  When is the student doing their learning?  Student demographics Where is the data coming from?

5  Harness analytics technology to develop trends, forecasts, and strategies for each learner.  Various analytics tools (e.g. Google Analytics)  Data Correlation (e.g. Google Correlation)  Educational Data Mining (Romero, C., & Ventura, 2007)  KPIs (Key Performance Indicators)  Student Success / Failure  Time Stamps (user activity)  All whilst ensuring data quality! How will we analyze the data?

6  By personalizing the educational experience the student will go through various tests so we can learn about the person.  Since our LMS is adaptive to the learner, it will adjust as we gather and analyze data about the student  Strategies discussed by knewton (constantly assess learning methods that work most efficiently)  http://www.youtube.com/watch?v=LldxxVRj4FU http://www.youtube.com/watch?v=LldxxVRj4FU How we can improve learning

7  Determine what is most efficiently challenges the student  Use strengths to build confidence while encouraging student to excel in weaker areas  Provide teachers/teaching assistants vital information to assist in learning  Unique assignments, apply learning profile to student  By personalizing student learning strategy it will empower the student  “Intelligent Curriculum” How we can improve learning

8  Ultimately the universal measurement of knowledge is testing (or deliverables in the form of assignments, essays, etc.)  If the teaching material is not delivered efficiently, effectively, or personally (tailored to student) we can have mixed/negative response.  Content Management Systems / Learning Management Systems must provide student with enriched content delivery methods. CMS / LMS

9 Student Profile Data Mining Data Analysis & Reporting Learning Profile Refinement Analytics Model

10  Depending on purpose and study stream  Learner Demographics  Student Race / Age / Time Zone / Language  Perceived Strengths / Weaknesses (asked via questionnaire) – also known as ‘self-identified’ info  Interests (Social Media integration will provide great insight)  Character Building (use of Social Media, online behavior to build digital understanding of individual) Student Profile

11  Information from Student Profile  Social Media connection(Social Media integration will provide great insight)  Character Building (use of browser content [cookies] online behavior to build digital understanding of individual)*  YouTube Search  Google Search  Email conversations  * Privacy Concerns could be difficult here, in theory would be excellent  Student Testing and Learning Metrics (see slide ¾) Data Mining

12  Use of analytics technology to develop trends, forecasts, and strategies for each learner.  Various analytics tools (e.g. Google Analytics)  Data Correlation (e.g. Google Correlation)  Educational Data Mining (Romero, C., & Ventura, 2007)  Develop and use KPIs (Key Performance Indicators)  Student Success / Failure  Inform responsible person(s) of student progress via report. Data Analysis and Reporting

13  Based on reports and data analysis a learner profile is created (and is constantly adjusted with new information)  Learner profile identifies learner strengths and weaknesses and leverages them for optimal learning and testing skill.  E.g. student ‘Sally’ is taking a advanced history course at the college level.  Sally is consistently has difficulties memorizing dates of historical events, but has no issue recalling the significance of the event.  Sally’s was learning strategy is traditional – text and pictures.  Sally is introduced to auditory learning combined with visual, and emphasizes or repeats portions that discuss dates. Learning Profile

14  The student learning profile is continually refined to determine what works for the student.  Learning strategies may vary subject to subject, and learner profile efficiency will become increasingly effective with more data mining and analysis. Refinement

15  Thank you for your time – I hope you enjoyed this presentation  David Cachia – 3050444 – M.Sc student, Athasbasca University Thank you for your time


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