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The Department of Education's (ED) Office of Educational Technology today released a draft issue brief - Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics - representing the results of a months-long discourse among 8 academic and 15 industrial data mining and learning analytics experts conducted by SRI International. The brief, inspired by ED's 2010 National Educational Technology Plan (NETP), articulates the challenges and opportunities of Big Data in improving student outcomes and overall productivity of K-2 education systems. It focuses on three key research areas - educational data mining, learning analytics, and visual data analytics - and offers a set of corresponding recommendations, categorized by various stakeholders. ED is now seeking public comment on the draft.

Analytics and Recommendations block uses charts and tables which are colour coded so students can quickly see they participation. Students can see single analytics about their participation in the course. Teachers can see single, comparative analytics and global analytics (all students together) too. Morover, the block shows recommendations for students about what activities they should work to improve their final grade. It shows too a estimate final grade according with a reference course.

"Some might argue that the analytics tools at our disposal are currently mainly used for boring purposes, such as improving processes and making money. In this paper we will try to define learning analytics and their purpose for learning and education. We will ponder on the best possible fit of particular types of research methods and their analysis. Methodological concerns related to the analysis of Big Data collected on online networks as well as ethical and privacy concerns will also be highlighted and a case study of the use of learning analytics in a Massive Open Online Course explored."

"The Society for Learning Analytics Research (SoLAR) is an inter-disciplinary network of leading international researchers who are exploring the role and impact of analytics on teaching, learning, training and development. SoLAR has published a concept paper on Open Learning Analytics"

This study is an exploratory case study aimed at analysing one academic's teaching in terms of conceptions of teaching and its effect on student involvement or engagement. The research has been done by drawing on Gonzalez' dimensions of online teaching and data generated by the LMS and data analytics in general. There is growing interest in the use of academic analytics. However, most of the reported work is being done at the level of institutions/groupings of courses. Improving teaching can only be done through changing the conceptions of teaching/learning held by the academics. Can individual teaching staff, reflecting on their courses, learn anything important from examining their courses through analytics? How can this be done effectively? What do they find? This study uses an academic's approach to teaching + use as an indicator of involvement, therefore, an improvement of teaching.

Learning analytics and more listed on Educause site.

Set of links from Martin Hawksey about learner analytics, particularly using Google Analytics.

Suggested by Martin Hawksey as an easier way for non IT folks to get into analytics (or how to use analytics without asking IT!)

A 30 hour self paced free course on website analytics specifically targeted to education and open education.

George Siemens on proposal for society of learning analytics research

project led by University of Sussex to develop advanced analytics in Mahara

paper on a 3rd part tool for Moodle based on analytics of enhanced rubrics.

Learning Analytics for Moodle

The mythology of more data = more knowledge.

The core proposition is that with the unprecedented amounts of digital data now becoming  available about learners' activities and interests, from educational institutions and elsewhere online, there is significant potential to make better use of this data to improve learning  outcomes.

Interesting and easy to read piece on why predictive analytics can be beaten by knowledge on the ground and what we can learn from data and measurement error.

Education analytics news article about Sherpa