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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.〔(【引用サイトリンク】 title=Call for Papers of the 1st International Conference on Learning Analytics & Knowledge (LAK 2011) )〕 A related field is educational data mining. For general audience introductions, see: * The Educause Learning Initiative Briefing * The Educause Review on Learning analytics * And the UNESCO "Learning Analytics Policy Brief" (2012) ==What is Learning Analytics?== The definition and aims of Learning Analytics are contested. One earlier definition discussed by the community suggested that "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." 〔Siemens, George. "What Are Learning Analytics?" Elearnspace, August 25, 2010. http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/〕 But this definition has been criticised: # ''"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.〔(George Siemens in the Learning Analytics Google Group discussion, August 2010 )〕 # ''"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.〔(Mike Sharkey - Director of Academic Analytics, University of Phoenix, in the Learning Analytics Google Group discussion, August 2010 )〕 A more holistic view than a mere definition is provided by the framework of learning analytics by Greller and Drachsler (2012). It uses a general morphological analysis (GMA) to divide the domain into six "critical dimensions". A systematic overview on learning analytics and its key concepts is provided by Chatti et al. (2012) 〔Mohamed Amine Chatti, Anna Lea Dyckhoff, Ulrik Schroeder and Hendrik Thüs (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning (IJTEL), 4(5/6), pp. 318-331.〕 and Chatti et al. (2014) 〔Chatti, M. A., Lukarov, V., Thüs, H., Muslim, A., Yousef, A. M. F., Wahid, U., Greven, C., Chakrabarti, A., Schroeder, U. (2014). Learning Analytics: Challenges and Future Research Directions. eleed, Iss. 10. http://eleed.campussource.de/archive/10/4035〕 through a reference model for learning analytics based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It has been pointed out that there is a broad awareness of analytics across educational institutions for various stakeholders, but that the way 'learning analytics' is defined and implemented may vary, including: # for individual learners to reflect on their achievements and patterns of behaviour in relation to others; # as predictors of students requiring extra support and attention; # to help teachers and support staff plan supporting interventions with individuals and groups; # for functional groups such as course team seeking to improve current courses or develop new curriculum offerings; and # for institutional administrators taking decisions on matters such as marketing and recruitment or efficiency and effectiveness measures." 〔Powell, Stephen, and Sheila MacNeil. Institutional Readiness for Analytics A Briefing Paper. CETIS Analytics Series. JISC CETIS, December 2012. http://publications.cetis.ac.uk/wp-content/uploads/2012/12/Institutional-Readiness-for-Analytics-Vol1-No8.pdf.〕 In that briefing paper, Powell and MacNeil go on to point out that some motivations and implementations of analytics may come into conflict with others, for example highlighting potential conflict between analytics for individual learners and organisational stakeholders.〔 Gašević, Dawson, and Siemens argue that computational aspects of learning analytics need to be linked with the existing educational research if the field of learning analytics is to deliver to its promise to understand and optimize learning. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「learning analytics」の詳細全文を読む スポンサード リンク
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