Socio-critical principles to guide ethical decision-making

The need for ethical desicion-making should not be seen as regulatory hurdles that need to be jumped through at the beginning of the research process in order to address concepts such as vulnerability, harm, respect for persons, and beneficiaries are addressed, but rather as a process that ground ethical inquiry (Markham and Buchanan 2012:5). “Harm” is defined contextually, therefore ethical principles are more likely to be understood inductively than applied universally (Markham and Buchanan 2012:4).

Rather than one-size-fits-all pronouncements, ethical decision making is best approached through the application of practical judgment attentive to specific contexts (Markham and Buchanan 2012:4). Although one set of norms, values, principles and usual practices can be seen as legitimately applied to the issue(s) involved, it becomes difficult to make judgements as to which sets apply, especially if one set conflicts with another in one or other way (Markham and Buchanan 2012:5). The need for guidelines during the research process is emphasised by the fact that learning Analytics increase an institution’s scrutiny of student data related to ownership of the data and student privacy. Therefore, it is necessary to understand the opportunities and ethical challenges of learning analytics research.

Learning Analytics is one of the key emerging trends in higher education, but a number of issues need to be addressed (Siemens 2011). One of the issues relates to ethical decision making (Markham and Buchanan 2012:5). Therefore researchers are forced to determine which is relevant in a specific context or at particular junctures during the research process (Markham and Buchanan 2012:5). Ethical decision making is a deliberative process, and researchers should consult as many people and resources as possible in this process, including fellow researchers, people participating in or familiar with contexts/sites being studied, research review boards, ethics guidelines, published scholarship (within one’s discipline but also in other disciplines), and, where applicable, legal precedent (Markham and Buchanan 2012:5). Markham and Buchanan (2012:5) agues that we need guidelines rather than a code of practice so that ethical research can remeain flexible, responsive to diverse contexts, and adaptable to continually changing etchnologies. In this regard,Ethical issues may arise and need to be addressed during all steps of the research process, from planning, to research conduct, to publication and dissemination (Markham and Buchanan 2012:5). According to Slade and Prinsloo (2013:2) ethical decision-making depend on a range of ideological assumptions and epistemologies.

From a social-critical perspective, the role of power, the impact of surveillance, the need for transparency and an acknowledgement that the student identity is a transient, temporal and context-bound construct is regarded as important (Slade and Prinsloo 2013:2). Each of these affects the scope and definition of the ethical use of information collected, therefore Slade and Prinsloo (2013:2) proposed six principles as a framework for a number of considerations to higher education institutions to address ethical issues in learning analytics and challenges in context-dependent and appropriate ways.  Slade and Prinsloo (2013) proposed six principles that should serve as guidelines for higher education institutions using or planning to use data.

Principle 1: Learning analytics as moral practice

Learning analytics should not only focus on what is effective, but also aim to provide relevant pinters to decide what is appropriate and morally necessary (Slade and Prinsloo 2013:12). According to Slade and Prinsloo (2013:12) education is primarily a moral practice, not a causal one. Therefore learning analytics should focus primarily as a moral practice resulting in understanding rather than measuring (Reeves 2011).

All digital information at some point involve individual persons therefore, considerations of principles related to research on human subjects may be necessary even if it is not immediately apparent how and where persons will be involved in the research (Markham and Buchanan 2012:4). Learning analytics should do much more than contributing to a data-driven university or leading to a world where data drive our actions.

Principle 2: Students as agents

Principle 3: Student identity and performance as temporal dynamic constructs

Principle 4: Student success is a complex and multidimensional phenomenon

One of the benefits of learning analytics is to contribute to a better understanding of student demographics and behaviours (Bichel 2012), but it is important to see student success as the results of

Principle 5: Transparency (Slade and Prinsloo 2013:14) provided the following guidelines:

  • State a clear purpose for using the data
  • Under which conditions will the data be collected?
  • Who will have access to the data?
  • What measures will be taken to protect the identity of individuals?

Please note: Markham and Buchanan (2012) argues that participation in public online forums do not provide blanket permission for using data. Therefore, the greater the vulnerability of the community, author, participant, the greater the obligation of the researcher to protect the community, author or participant. Therefore, higher education have an obligation to protect student data on the institutional LMS, and also to inform students of possible risks when teaching and learning occurs outside the boundaries of institutional jurisdiction (Slade and Prinsloo 2013:14).

Principle 6: Higher education cannot afford not to use data

The triggers for adopting learning analytics depend on the main purpose for collecting data, whether it is to improve profit or learner results (Slade and Prinsloo 2013:14). Institutions should be able to use the data to better understand and then engage with the outcomes (see Slade and Prinsloo 2013:14). To ignore information which might help to improve the outcomes seems to be shortsighted in the extreme since higher education is accountable to the stakeholders, government and the students themselves (Slade and Prinsloo 2013:14), If used for this purpose, learning analytics can penetrate the fog that has settled over much of higher education (Long and Siemens 2011:40).Therefore, Markham and Buchanan (2012:4) argues that researchers need to balance the rights of the subjects (as authors, research participants or people) with the social benefits of research and the rights to conduct research. In different contexts the rights of the subjects might outweigh the benefits of the research.

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