Learning analytics

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs . A related field is educational data mining.

History

Work in progress: sociologists like Wellman and Watts...and mathematicians like Barabasi and Strogatz. The work of these individuals has provided us with a good sense of the patterns that networks exhibit (small world, power laws), the attributes of connections (in early 70's, Granovetter explored connections from a perspective of tie strength and impact on new information), and the social dimensions of networks (for example, geography still matters in a digital networked world).

Criticism

An earlier definition discussed by the community:

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning.

and its criticism:

1. "I somewhat disagree with this definition - it serves well as an introductory concept if we use analytics as a support structure for existing education models. I think learning analytics - at an advanced and integrated implementation - can do away with pre-fab curriculum models". George Siemens, 2010.
2. "In the descriptions of learning analytics we talk about using data to "predict success". I've struggled with that as I pore over our databases. I've come to realize there are different views/levels of success." Mike Sharkey 2010.

Methods

Methods for learning analytics include:

• Social network analysis (SNA) - "the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA]."

• Behavioral trust analysis - using instances of conversation and propagation (people communicating and using information to generate new information) as an indicator of trust.

• Influence and passivity measure - assessing the influence of people and information by measuring the number of times it is passed on, cited, or retweeted.

• Content analysis

• Impact of interaction

• Prediction

• Personalization & Adaptation

• Intervention

• Information visualization, typically in the form of so-called learning dashboards

Software

Much of the software that is currently used for learning analytics duplicates functionality of web analytics software, but applies it to learner interactions with content. Social network analysis tools are commonly used to map social connections and discussions (see Social network analysis software). Some examples of learning analytics software tools:

• SNAPP - a learning analytics tool that visualizes the network of interactions resulting from discussion forum posts and replies.
• LOCO-Analyst - a context-aware learning tool for analytics of learning processes taking place in a web-based learning environment
• SAM - a Student Activity Monitor intended for Personal Learning Environments

See also

• Text analytics
• Academic analytics
• Pattern recognition
• Educational data mining
• Odds algorithm
• Predictive analytics

External links

• Learning Analytics Google Group with discussions from researchers and individuals interested in the topic.
• 1st International Conference Learning Analytics & Knowledge
• 2nd International Conference Learning Analytics & Knowledge
• Next Gen Learning definition
• Microsoft Education Analytics with information on how to use data to support improved educational outcomes.
• Goldstein, P. J., & Katz, R. N. Academic analytics: The uses of management information and technology in higher education. 2005
• Educational Data mining
• IBM Business Analytics
• Campbell, J. & Oblinger, D. Academic analytics. Educause 2007.
• Educause resources on learning analytics
• Norris, D., Baer, L., & Offerman, M. A National Agenda for Action Analytics. National Symposium on Action Analytics 2009.
• Adali, S., et al. Measuring Behavioral Trust in Social Networks. IEEE International Conference 2010.
• Romero, D., et al. Influence and Passivity in Social Media. Social Science Research Network, 2010.
• Graber, C. Behavior Influenced More In Denser Networks. Scientific American, 2010 (Includes audio recording).
• Carmean, C. & Mizzi, P. The Case for Nudge Analytics Educause 2010.
• Jovanović, et al. Using Semantic Web Technologies for the Analysis of Learning Content IEEE Internet Computing, Vol. 11, No. 5, 2007, pp. 45-53
• Ali, L., Hatala, M. Gašević, D., Jovanović, J., A Qualitative Evaluation of Evolution of a Learning Analytics Tool, Computers & Education, Vol. 58, No. 1, 2012, pp. 470-489
• Duval, E. Attention please! Learning analytics for visualization and recommendation, Proceedings of LAK11: 1st International Conference on Learning Analytics and Knowledge, Banff, Canada, 27 February - 1 March 2011