Course Outline

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Course Tag: #ethics21

-1. Getting Ready

Connectivism is based on the idea that knowledge is essentially the set of connections in a network, and that learning therefore is the process of creating and shaping those networks. To get started we'll look at what to do to set up and how to learn in a connectivist course.

1. Introduction

This module addresses the idea of ethics in general, outlines what we mean by analaytics, and looks at how the two come together. It frames the course as an exploration of how we as a society ought to address ethical issues in analytics. What is the scope of the problem facing us? What are the historically relevant approaches to social dilemmas, and why do they seem unequal to the task before us today?

2. Applications of Learning Analytics

Any assessment of the ethics of learning analytics requires a comprehensive understanding of these applications and their impact. We classify the potential applications of learning analytics based on what analytics can do and how they work. Development in many of these application areas has already started, so this is as much a snapshot of the state of the art today as it is a prediction of future technology.

3. Ethical Issues in Learning Analytics

The ethics of analytics is particularly complex because issues arise when analytics works, issues that arise because analytics are not yet reliable, and issues that arise in cases where the use of analytics seems fundamentally wrong. To these three sets of issues we will add a fourth describing wider social and cultural issues that arise with the use of analytics and AI, and a set of issues related specifically to bad actors.

4. Ethical Codes

The purpose of this chapter is to showcase the wide range of ethical codes that are employed in different professions, some of which are directly related to the use of analytics in that profession, and others which describe ethics in the profession generally. There is often a presumption, if not an explicit assertion, that the values in these ethical codes, and in ethics generally, are common, core, and universal. But they are not.

5. Approaches to Ethics

What is the basis for statements about the ethics of learning analytics? In this module we look at differnet approaches to ethics, ranging from ethical character, appeal to consequences, moral imperatives, and ethical duties. We also loso look at concepts such as justice, fainess and equity.

6. The Duty of Care

Recent work in ethics, especially in professions with clients such as education and medicine, has introduced the concept of the 'duty of care'. This is at once a legal term and also an approach to ethics based in feminist theory. In this module we look at the origins of the duty of care and consider how it applies to the ethics of analytics.

7. The Decisions We Make

What is it to use learning analytics? In this section we look more closely at the nature of artificial intelligence and machine learning in order to understand where the decisions we make have an ethical outcome. In this module we look at the entire lifecycle of an analytics application, including but not limited to the framing of the problem, the data set, application and testing.

8. Ethical Practices in Learning Analytics

What have we learning? What does it mean to talk about ethics in learning analytics? What are the practical applications of the theories and issues we have considered? What do we need to do going forward?