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Title:Where do we Stand? Working Toward an ALISE Position Statement on Learning Analytics in Higher Education
Author(s):Jones, Kyle; Burgess, John
Subject(s):Higher education
Learning analytics
Educational data mining
Information ethics
Abstract:Institutions are increasingly using learning analytics to mine and analyze data and information about students and faculty. Often, these tools are viewed positively; they serve as means by which to facilitate educational activities in bureaucratic and complex institutions and bring about improved learning outcomes. But, in the sociology of education tradition, researchers have neither considered educational technologies as neutral nor benign: they are representations of power and political artifacts. Critical data studies scholars promote a view that the data driving educational technology needs to be examined for, inter alia, issues of justice, fairness, autonomy, and reductionism. Learning analytics brings forth serious questions concerning surveillance, privacy rights, appropriateness of use, and how institutional policy accounts for such things. The ALISE Information Ethics Special Interest Group proposes that now is the time for library and information science (LIS) faculty to seriously address and respond to the pressing issues learning analytics is raising by developing an advocacy statement. A position statement on learning analytics has utility beyond taking a stand on an important educational issue. It has the potential to provide a touchstone for faculty to evaluate and critique their institution’s learning analytics practices. Statements of this kind create ethical clarity, establish priorities, identify and give voice to the interests of vulnerable parties, and spread shared values. For educators, the efficiency of a carefully crafted statement can also lead to teachable content that can serve as learning objectives in LIS courses. However, the greatest utility of all is ensuring that in carrying out our multifaceted duties we do not contribute to unethical learning analytics and educational data mining practices, and instead serve as models for those we educate. The intention with such a statement is not to enforce uniformity of behavior, but is instead to promote awareness, summarize emerging dilemmas, and recommend further action. While there is a limit to what can be accomplished in a conference session, the intent is to use this session as a catalyst to energize further discussion and research on the topic.
Issue Date:2020-10-13
Series/Report:Information Ethics
Information Policy
Data Mining
Genre:Conference Paper / Presentation
Type:Text
URI:http://hdl.handle.net/2142/108791
Date Available in IDEALS:2020-10-09


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