Learner Analytics, Benefits And Practices

Initially, learners will explore factors that affect learning, then plan and monitor their personal and professional

When working in a school environment certain information has to be gathered about pupils, for the system to work effectively.

The data gathered may likewise assist the parents to create a learning environment and to motivate their child to the learning/interest that they have not achieved.

This section discuss about the common traits or ideas observed in the three research topics. Although, each of the three articles discuss a unique idea, all of them are aimed at utilizing the web data to produce better results. Web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilization of the valuable user generated data from the social media or the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by an individual. All the three articles propose an idea to solution the problem stated, compared their results to the existing models and showed significant improvement.

Here we discuss about the common traits or ideas observed in the three research topics. Although, these three papers discuss about different ideas, they all fall under the web data mining domain. web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilisation of the valuable user generated data from the social media or the the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by the individual.

Plotting my exam scores on a graph to see my performance on a subject was an activity back in my school. The ups and downs on the graph helped me identify my positives and negatives. As a kid, this kindled my passion towards analytics. While studying engineering at Kumaraguru College of Technology, I had to carry out various analyses for my experiments and projects. This further developed my interest in analytics. Being a part of the League for Entrepreneurial Empowerment and Development (LEED), gave me an opportunity to start a business at college.

My experiences in learning over the years were very negative in K-12. When I returned to academics several years later, I assumed that school would be just as hard and boring as it was the first time I suffered through it. This time around I had a goal and a drive to succeed, so I pushed myself harder in school than I ever had to in my entire life and now I have a career that I love. I finished nursing school in May and graduated with an associate’s degree and now that I’m working as a Nurse it has sharpened my time management skills, which will come in very handy as an independent learner. The main thing that might be a challenge for me as a FlexPath learner is now I won’t have as much time between assignments, so I will have to approach my

As a student that values the ability to make my own choices and opportunities to conduct research, UChicago appeals to my sense of learning. Unlike other universities, UChicago’s Department of Computer Science provides some of the best education in the world and allows students to build strength in an additional field due to the program’s flexibility. Not only that, UChicago’s Center for Scholarly Advancement encourages undergraduate research and would allow me to continue the scientific research that I am currently conducting, as well as allowing me to be mentored by great professors who are researching similar topics. In particular, Professor Ben Zhao and Professor Heather Zheng’s research on data-driven models of user behavior appeals to

Jennifer Schnidman Medbery, the founder and CEO of Kickboard, graduated from Columbia University in the City of New York with a B.A. in Computer Science in 2006 (Medbery, n.d.). During her stint at Teach for America (2006-2008), Jennifer Medbery taught math in Helena-West Helena, AR (Medbery, n.d.). In 2008, Medbery accepted the position of a founding teacher at New Orleans Charter Science and Mathematics Academy (Medbery, n.d.). What astonished her was that the most challenging facet of the work was keeping track of student performance (Fenn, 2011). She came to the decision to make software that can help teachers analyze and track students’ progress and behavior (Fenn, 2011). In 2009, Jennifer Medbery presented a prototype for Kickboard, a web-based application for tracking school analytics (Larino, 2013). Medbery’s company, Drop the Chalk, has expanded nationally (Kickboard was launched across 20 states by 2013) (Empson, 2013).

The way I learn is depending on the style of learning.I am mostly a visual and a tactile learner.As a visual learner I like mostly to read or see how its done.If I need anything explained I like to see a picture or imagine it how its suppose to be.When I want to take notes I need to see the board as notes written on it or a presntation explaning either steps or diractions or notes this will give me a better understanding.As a visual learner I like my things very organized and marked by any color or labeled or else it will make me feel very confused and irritated.An example of a visual learner if i need to get directions to a place i need things to be explained and descriped to me this way I can make it to the place i need to go to. On

Receiving an education via an online course is one that has begun with many challenges. I have come from having no knowledge of researching information to feel like I have journeyed a long way finding the confidence to research pertinent and quality resources. Through this particular unit I have been given the implements to develop a sound knowledge of online group collaborations and the programs to allow the communication to take place.

Early one morning, I typed the final semicolon, signaling CompareClass’s completion. Throughout the next day I explained the site to my friends and hinted at its capabilities during class. Finally, school ended, and our schedules were released. I rushed home, opened my laptop, and navigated to the site’s database. The first hour rolled by as I witnessed new users slowly trickle in. It grew to an influx. Within two months, more than eighty percent of the students from my high school had accounts, while users reported from eight distinct schools. My passion came to

We then transform this data into actionable information and share it with our partners so that they can determine the factors that will positively impact our students' educational journey.

In order to personalize learning for each user we seek to first determine their indi-vidual learning interest by determining the tag class where their interest lies and there-after determining the tag distributions represented in their learner model to determine their specific learning interest. In eliciting the learning interest of individual learner, we inferred their long term and their short term learning interest. Questions asked from January 2009 to December 2011 were used to infer their long term learning needs while questions asked within January 2014 to July 2014 were used to depict the short term learning needs of the user. The specific learning interest of the learner in both long and short term was determined by mining all tags employed in questions asked by the user in the long and short term time period. In determining

Ferguson Rebecca [1] provides a review of learning analytics. The paper examines various factors like technological, educational and political factors that drive learning analytics such as Big data, Online learning, political and economic concerns. The authors have described how data driven analytics developed and how learning analytics emerged, and the relationships between LA and educational data mining and academic analytics. Whereas educational data mining focuses on how to extract useful data from a large learning dataset, learning analytics focuses on optimizing opportunities in online learning environment. Academic analytics, on the other hand, focuses on improving learning opportunities and educational results across national and international levels. The authors also identify a future set of challenges to be addressed by learning analytics like establishing clear set of ethical guidelines, coupling with recent and emerging learning technologies, understanding learner perspectives and working with wide range of learning datasets.