Do Engineering Students Learn Ethics From an Ethics Course?

The goal of the present research is to develop machine-assisted methods that can assist in the analysis of students’ written compositions in ethics courses. As part of this research, we analyzed Social Impact Assessment (SIA) papers submitted by engineering undergraduates in a course on engineering ethics. The SIA papers required students to identify and discuss a contemporary engineering technology (e.g., autonomous tractor trailers) and to explicitly discuss the ethical issues involved in that technology. Here we describe the ability of three machine tools to discriminate differences in the technical compared to ethical portions of the SIA papers. First, using LIWC (Language Inquiry and Word Count) we quantified differences in analytical thinking, expertise and self-confidence, disclosure, and affect, in the technical and ethical portions of the papers. Next, we applied MEH (Meaning Extraction Helper) to examine differences in critical concepts in the technical and ethical portions of the papers. Finally, we used LDA (Latent Dirichlet Allocation) to examine differences in the topics in the technical and ethical portions of the papers. The results of these three tests demonstrate the ability of machine-based tools to discriminate conceptual, affective, and motivational differences in the texts that students compose that relate to engineering technology and to engineering ethics. We discuss the utility and future directions for this research.Cockrell School of Engineerin

Research Priorities for Robust and Beneficial Artificial Intelligence

Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.Comment: This article gives examples of the type of research advocated by the open letter for robust & beneficial AI at http://futureoflife.org/ai-open-lette

DATUM in Action

This collaborative research data management planning project (hereafter the RDMP project) sought to help a collaborative group of researchers working on an EU FP7 staff exchange project (hereafter the EU project) to define and implement good research data management practice by developing an appropriate DMP and supporting systems and evaluating their initial implementation. The aim was to "improve practice on the ground" through more effective and appropriate systems, tools/solutions and guidance in managing research data. The EU project (MATSIQEL - (Models for Ageing and Technological Solutions For Improving and Enhancing the Quality of Life), funded under the Marie Curie International Research Staff Exchange Scheme, is accumulating expertise for the mathematical and computer modelling of ageing processes with the aim of developing models which can be implemented in technological solutions (e.g. monitors, telecare, recreational games) for improving and enhancing quality of life.1 Marie Curie projects do not fund research per se, so the EU project has no resources to fund commercial tools for research data management. Lead by Professor Maia Angelova, School of Computing, Engineering and Information Sciences (SCEIS) at Northumbria University, it comprises six work packages involving researchers at Northumbria and in Australia, Bulgaria, Germany, Mexico and South Africa. The RDMP project focused on one of its work packages (WP4 Technological Solutions and Implementation) with some reference to another work package lead by the same person at Northumbria University (WP5 Quality of Life). The RDMP project‟s innovation was less about the choice of platform/system, as it began with existing standard office technology, and more about how this can be effectively deployed in a collaborative scenario to provide a fit-for-purpose solution with useful and usable support and guidance. It built on the success of the Datum for Health project by taking it a stage further, moving from a solely health discipline to an interdisciplinary context of health, social care and mathematical/computer modelling, and from a Postgraduate Research Student context to an academic researcher context, with potential to reach beyond the University boundaries. In addition, since the EU project is re-using data from elsewhere as well as creating its own data; a wide range of RDM issues were addressed. The RDMP project assessed the transferability of the DATUM materials and the tailored DATUM DMP

Motivation, Design, and Ubiquity: A Discussion of Research Ethics and Computer Science

Modern society is permeated with computers, and the software that controls them can have latent, long-term, and immediate effects that reach far beyond the actual users of these systems. This places researchers in Computer Science and Software Engineering in a critical position of influence and responsibility, more than any other field because computer systems are vital research tools for other disciplines. This essay presents several key ethical concerns and responsibilities relating to research in computing. The goal is to promote awareness and discussion of ethical issues among computer science researchers. A hypothetical case study is provided, along with questions for reflection and discussion.Comment: Written as central essay for the Computer Science module of the LANGURE model curriculum in Research Ethic

Beta: Bioprinting engineering technology for academia

Higher STEM education is a field of growing potential, but too many middle school and high school students are not testing proficiently in STEM subjects. The BETA team worked to improve biology classroom engagement through the development of technologies for high school biology experiments. The BETA project team expanded functionality of an existing product line to allow for better student and teacher user experience and the execution of more interesting experiments. The BETA project’s first goal was to create a modular incubating Box for the high school classroom. This Box, called the BETA Box was designed with a variety of sensors to allow for custom temperature and lighting environments for each experiment. It was completed with a clear interface to control the settings and an automatic image capture system. The team also conducted a feasibility study on auto calibration and dual-extrusion for SE3D’s existing 3D bioprinter. The findings of this study led to the incorporation of a force sensor for auto calibration and the evidence to support the feasibility of dual extrusion, although further work is needed. These additions to the current SE3D educational product line will increase effectiveness in the classroom and allow the target audience, high school students, to better engage in STEM education activities

DATUM for Health: Research data management training for health studies

This collaborative project sought to promote research data management skills of postgraduate research students in the health studies discipline through a specially-developed training programme which focuses on qualitative, unstructured research data. The project aimed to: design and pilot a training programme on research data management for postgraduate research students in health studies as an integral part of a doctoral training programme evaluate the usefulness and effectiveness of the training with participants and other research stakeholders provide other Higher Education Institutions with a model for research data management skills training make recommendations for sustainable research data management training and associated infrastructure requirements. The project was funded by JISC under their Managing Research Data (JISCMRD) Programme. The project ran from 1st October 2010 to 31st July 2011

Informatics Research Institute (IRIS) March 2009 newsletter

This is the first newsletter following the outcome of the Research Assessment Exercise which confirmed IRIS as one of the leading multidisciplinary research institutes that brings together expertise in social, technological and computational aspects of information systems. Research Fortnight ranked IRIS activities in the top two submissions in the country, with 75% of activities at international level and 25% at world leading level. The reviewers were particularly impressed with the Research Environment, which was highlighted as having 50% of activities at world leading level. I’d like to thank all members of IRIS whose commitment to pursuing high quality research has contributed to this success. This newsletter highlights some activities immediately following the RAE, showing that we are not content with the excellent RAE results but building further on our successful research. It includes examples of important research events that we are organising, publications in major outlets, funded projects and students who have successfully completed their PhDs