Ethics of AI in Education: Towards a Community-Wide Framework

While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically, to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community’s leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise the contributions of the 17 respondents, and discuss the complex issues that they raised. Specific outcomes include the recognition that most AIED researchers are not trained to tackle the emerging ethical questions. A well-designed framework for engaging with ethics of AIED that combined a multidisciplinary approach and a set of robust guidelines seems vital in this context

A Learning Management System-Based Early Warning System for Academic Advising in Undergraduate Engineering

This chapter describes a design-based research project that developed an early warning system for an undergraduate engineering mentoring program. Using near real-time data from a university’s learning management system, we provided academic advisors with timely and targeted data on students’ academic progress. We discuss the development of the early warning system and detail how academic advisors used it. Our findings point to the value of providing academic advisors with performance data that can be used to direct students to appropriate sources of support.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107974/1/Krumm_etal_2014_LA.pd

Cognitive Load Theory: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement

The contributions to this special issue document some recent advances of cognitive load theory, and are based on contributions to the Third International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The contributions focus on developments in example-based learning, amongst others on the effects of integrating worked examples in cognitive tutoring systems; specify the effects of transience on cognitive load and why segmentation may help counteract these effects in terms of the role of time in working memory load; and discuss the possibilities offered by electroencephalography (EEG) to provide a continuous and objective measure of cognitive load. This article provides a short introduction to the contributions in this issue

Feedback Authoring for Exploratory Activities: The Case of a Logo-Based 3D Microworld

This paper presents AuthELO an authoring environment that can be used for the configuration of logging and authoring of automated feedback for exploratory learning objects (ELOs). ELOs are web components (widgets) that can be integrated with learning platforms to synthesise highly interactive learning environments. AuthELO has been developed in the context of the MCSquared project that is developing a platform for authoring interactive educational e-books. This platform comprises an extendable set of diverse widgets that can be used to generate instances of exploratory activities that can be employed in various learning scenarios. AuthELO was designed and developed to provide a simple, common and efficient authoring interface that can normalise the diversity of these widgets and give the ability to non-experts to easily develop or customise the feedback that is provided to students using a data-driven approach. In this paper we describe the architecture and design characteristics of AuthELO and a small-scale evaluation with activities in a logo-based 3D microworld called Malt+. We reflect on both the challenges of the authoring process and the pedagogical potential of the feedback when these activities are used by students