In the socio-technical imaginary of higher education, algorithmic decision-making offers huge potential, but we also cannot deny the risks and ethical concerns. In fleeing from Frankenstein's monster, there is a real possibility that we will meet Kafka on our path, and not find our way out of the maze of ethical considerations in the nexus between…

Drawing on Latour's (Reassembling the social: an introduction to actor--network-theory, Oxford University Press, New York, 2005), this manuscript discusses a study of a robotics class in a public, Title I elementary school. Compared with theoretical frameworks (e.g., constructivism and constructionism) dominant in the field of early childhood…

Productive "Third Spaces" are often an afterthought when designing learning environments, both in a physical sense and online. These areas, properly mediated by technology and designed around humans, can often be a key facilitator for student success. The STAC Model is designed to provide a framework for understanding what makes these…

Engineering virtual internships are simulations where students role play as interns at fictional companies, working to create engineering designs. To improve the scalability of these virtual internships, a reliable automated assessment system for tasks submitted by students is necessary. Therefore, we propose a machine learning approach to…

In this digital era, learning from data gathered from different software systems may have a great impact on the quality of the interaction experience. There are two main directions that come to enhance this emerging research domain, Intelligent Data Analysis (IDA) and Human Computer Interaction (HCI). HCI specific research methodologies can be…

By providing students with a highly interactive and hands-on learning experience, robotics promises to inspire a new generation of mathematical learning. This paper aims to review the empirical evidence on the application of robotics in mathematics education and to define future research perspectives of robot-assisted mathematics education. After…

Organizations interested in increasing their user experience (UX) capacity lack the tools they need to know how to do so. This dissertation addresses this challenge via three major research efforts: 1) the creation of User Data Spectrum theory and a User Data Spectrum survey for helping organizations better invest resources to grow their UX…

As artificial intelligence (AI) increasingly enters K-12 classrooms, what do teachers and students see as the roles of human versus AI instruction, and how might educational AI (AIED) systems best be designed to support these complementary roles? We explore these questions through participatory design and needs validation studies with K12 teachers…

This report, the product of a collaboration between the Organisation for Economic Co-operation and Development (OECD) and the UK-based charity, Education and Employers, offers a glimpse of how children see their future, and the forces that, if properly understood and harnessed, will drive them forward to realise their dreams. Through concerted…

This dissertation investigates how the emergence of the Internet of Things and the embeddedness of sensors and networked connectivity onto things, physical spaces and biological bodies rearticulates embodied spaces, devises practices of self-making and forms of power in the governance of the self and society. (Abstract shortened by ProQuest.).…

In modern video games, music can come in different shapes: it can be developed on a very high compositional level, with sophisticated sound elements like in professional film music; it can be developed on a very coarse level, underlying special situations (like danger or attack); it can also be automatically generated by sound engines. However, in…

The computing education research literature contains a wide variety of methods that can be used to identify students who are either at risk of failing their studies or who could benefit from additional challenges. Many of these are based on machine-learning models that learn to make predictions based on previously observed data. However, in…

Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to receive an A or B or students likely to receive a grade of C, D, F or withdraw from the class. Early prediction could better allow the direction of educational…

This article aims to lay a foundation for the research and practice of machine learning education for creative practitioners. It begins by arguing that it is important to teach machine learning to creative practitioners and to conduct research about this teaching, drawing on related work in creative machine learning, creative computing education,…

This paper details the design, development and evaluation of an affective tutoring system (ATS)--an e-learning system that detects and responds to the emotional states of the learner. Research into the development of ATS is an active and relatively new field, with many studies demonstrating promising results. However, there is often no practical…