[data (scrabble)]1Interesting new paper Johnson, J. A. (2014). [The Ethics of Big Data in Higher Education.]2 International Review of Information Ethics, 7. although I think unfair to at least some (but certainly not all) data-mining research efforts so far. Argues that, insofar as they limit autonomy, course recommender systems and similar data-mining ‘products’ are problematic, and should explicitly (and on a case-by-case basis) justify their ethical position with regard to such limiting (e.g. saving tax payers money, helping students with their original aims – to gain education, etc.). Also argues empirical and normative assumptions built into data mining process, which can be obscured (by data-scientists tending towards scientism) and lead to a ‘fetishization of the scientific method’ (p.5) e.g. through policies such as PISA.  Suggests that an alternative model would critically evaluate methods and evidence before assuming causal relations. Overall suggests considering data-mining as part of ‘technosocial system’, particularly focussing on policies in which data-mining will play a role. “The ethical questions presented in data mining will be clearer when building a data mining model is situated in relation to the perceived need for the policy, the interventions that are proposed, the expected outcomes of the policy, and the ways in which the policy will be evaluated; problems such as incompatibilities between the assumptions of the data model and those of the intervention will only be apparent from this perspective.” (p.6).  Through such analysis, data mining can deliver on its potential, ethically and effectively.   If you like this area, you might also like my paper: Knight, S., Buckingham Shum, S., & Littleton, K. (2014). [Epistemology, assessment, pedagogy: where learning meets analytics in the middle space]3. Journal of Learning Analytics, In-press.


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  2. http://www.i-r-i-e.net/inhalt/021/IRIE-021-Johnson.pdf

  3. http://oro.open.ac.uk/39226/