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Within the Computer Science community, many ethical issues have emerged as significant and critical concerns. Computer ethics is an academic field in its own right and there are unique ethical issues associated with information technology. It encompasses a range of issues and concerns including privacy and agency around personal information, Artificial Intelligence and pervasive technology, the Internet of Things and surveillance applications. As computing technology impacts society at an ever growing pace, there are growing calls for more computer ethics content to be included in Computer Science curricula. In this paper we present the results of a survey that polled faculty from Computer Science and related disciplines about teaching practices for computer ethics at their institutions. The survey was completed by respondents from 61 universities across 23 European countries. Participants were surveyed on whether or not computer ethics is taught to Computer Science students at each institution, the reasons why computer ethics is or is not taught, how computer ethics is taught, the background of staff who teach computer ethics and the scope of computer ethics curricula. This paper presents and discusses the results of the survey.

Purpose Computing ethics represents a long established, yet rapidly evolving, discipline that grows in complexity and scope on a near-daily basis. Therefore, to help understand some of that scope it is essential to incorporate a range of perspectives, from a range of stakeholders, on current and emerging ethical challenges associated with computer technology. This study aims to achieve this by using, a three-pronged, stakeholder analysis of Computer Science academics, ICT industry professionals, and citizen groups was undertaken to explore what they consider to be crucial computing ethics concerns. The overlap between these stakeholder groups are explored, as well as whether their concerns are reflected in the existing literature. Design/methodology/approach Data collection was performed using focus groups, and the data was analysed using a thematic analysis. The data was also analysed to determine if there were overlaps between the literature and the stakeholders’ concerns and attitudes towards computing ethics. Findings The results of the focus group analysis show a mixture of overlapping concerns between the different groups, as well as some concerns that are unique to each of the specific groups. All groups stressed the importance of data as a key topic in computing ethics. This includes concerns around the accuracy, completeness and representativeness of data sets used to develop computing applications. Academics were concerned with the best ways to teach computing ethics to university students. Industry professionals believed that a lack of diversity in software teams resulted in important questions not being asked during design and development. Citizens discussed at length the negative and unexpected impacts of social media applications. These are all topics that have gained broad coverage in the literature. Social implications In recent years, the impact of ICT on society and the environment at large has grown tremendously. From this fast-paced growth, a myriad of ethical concerns have arisen. The analysis aims to shed light on what a diverse group of stakeholders consider the most important social impacts of technology and whether these concerns are reflected in the literature on computing ethics. The outcomes of this analysis will form the basis for new teaching content that will be developed in future to help illuminate and address these concerns. Originality/value The multi-stakeholder analysis provides individual and differing perspectives on the issues related to the rapidly evolving discipline of computing ethics.

Gamification has been hailed as a meaningful solution to the perennial challenge of sustaining student attention in class. It uses facets of gameplay in an educational context, including things such as points, leaderboards and badges. These are clearly efforts to make the student experience more entertaining and engaging, but nonetheless, they are also clearly digital nudges and attempts to change the students’ behaviours and attitudes to a specific set of concepts, and in which case they must, and should, be subject to the same ethical scrutiny as any other form of persuasion technique, as they may be unintentionally eroding the choices that students feel they have. This research therefore discusses some of the key ethical considerations and concerns associated with gamification, and presents a new framework that incorporates ethical tests into each stage of a pre-existing model of instructional design, that can be used when introducing gamification into an educational process.

Digital Pills are a drug-device technology that allow for the combination of traditional medications with a monitoring system that automatically records data about medication adherence and patients' physiological data. They are a promising innovation in digital medicine; however, their use has raised a number of ethical concerns. In this paper, we outline some of the main Digital Pills technologies and explore key ethical challenges surrounding their use. In this paper, we introduce educational materials we have developed that provide an insight into the technologies and ethical aspects that underpin Digital Pills.

Many users experience a phenomena when they are shopping on-line where they feel they are being pressured to either spend more money than they had intended, or to share more personal data than they wanted. In academic circles we use the term “Dark Patterns” to describe these deceptive practices, and categorize them as being within the discipline of User Experience (Narayanan, 2020). As academics it is important to name phenomena, and to categorize them, so that we can discuss and analyze these issues. However, this particular topic is one that all users should be made aware of when interacting online, and therefore these ideas should be explained in a manner to ensure that the terminology does not prove to be a barrier to understanding these concepts (Gordon, et al., 2014). To overcome the terminological barriers, this research proposes the use of a model of instructional design called Elaboration Theory, developed by Charles Reigeluth (1999). Crucially this model proposes that when explaining a new concept, the last thing the instructor should do is to mention the name of the concept, they should first explain the concept, and at the very end of an instructional session, say “And by the way, this concept is called…”. This model also contends that the instructor should explain the concept in simple terms first, and then continue to elaborate on that explanation throughout the teaching process (adhering to the notion of a Spiral Curriculum). It also suggests that the content should be summarized at each level of explanation, and analogies should be used to help clarify concepts. Therefore, this research proposes the redevelopment of existing teaching content about Dark Patterns, where these patterns are retitled as “Online Shopping Tricks”, and the teaching content is redesigned to begin with a simple explanation of Dark Patterns and to elaborate with more complexity at a number of levels of explanation, and including summarizers and analogies at the end of each stage. This content will be subsequently piloted on a number of non-academic participants to determine whether or not this redesign process has been effective.

In the past decade software products have become pervasive in many aspects of people's lives around the world. Unfortunately, the quality of the experience an individual has interacting with that software is dependent on the quality of the software itself, and it is becoming more and more evident that many large software products contain a range of issues and errors, and these issues are not known to the developers of these systems, and they are unaware of the deleterious impacts of those issues on the individuals who use these systems. The authors of this paper are developing a new digital ethics curriculum for the instruction of computer science students. In this paper we present case studies that were explored to demonstrate programming issues to First Year Computer Science students. Each case study outlines key issues associated with a particular scenario and is accompanied by specific questions to be used by the instructor to allow students to begin to reflect on, and evaluate, the implications of these issues. The objective of this teaching content is to ensure that the students are presented with, and engage with, ethical considerations early in their studies and well before they encounter them in an employment setting.

Within the Computer Science community, many ethical issues have emerged as significant and critical concerns. In this paper we present the concept of adaptable and re-usable educational bricks for the teaching ethics to Computer Science students. The importance of integrating ethical aspects into Computer Science programmes has been highlighted by many scholars [1, 2, 3]. For example in [1] Grosz et al. argue that modern technology cannot be considered "value-neutral", that it can have unplanned consequences and that Computer Science students should be trained to identify the potential harmful effects of the technologies they help develop. We are also inspired by the research of Chuck Huff and C Dianne Martin [4] which places emphasis on empathy, and students imagining the consequences of their own work and actions. The research presented in this paper is taking place in the content of the ethics4EU project, an Erasmus+ project that aims to provide a central repository of useful re-usable/adaptable education bricks for the teaching of digital ethics, following an “open” model, e.g. [5], such as seen with the creative commons approach. This platform will manage teaching materials following good software engineering practices - as outlined in [6] for improved maintainability and sustainability. We use a standard template for the development of educational bricks with 6 subsections. These are prerequisites, learning objectives (ethical, computing and transverse), teaching materials, evaluation approach(es), support material (for teachers and students), and links to other bricks. In this paper we describe our approach to developing educational ‘bricks’ using a one of the developed bricks – learning resources for teaching the topic of dark patters - to demonstrate the concept. Dark patterns are duplicitous user interfaces that trick the user into either sharing more information than they intend to, or spending more money than they want to. We also outline an evaluation framework for testing the developed educational content (bricks) that draws on standard instruments such as LORI (Learning Object Review Instrument), TAM (the Technology Assessment Model) as well reflections from the teacher and student feedback.

International audience; The impact of COVID-19 has been widespread and far-reaching, and one domain that has experienced severe disruption is the university education sector, where the entire apparatus of teaching and assessment for many programmes of study had to move on-line in a matter of days 10. This was accomplished notably through enormous cooperation between staff and students in educational institutions (Adnan and Anwar, 2020). The negative economic impacts of COVID-19 on university students has been highlighted in terms of poor access to online resources, delayed graduation and lost internships with this effect felt more keenly by students from low socioeconomic backgrounds (Aucejo, et al. 2020). However, an issue that has been less reported is how the crisis highlighted mismatches between on the one hand the regulations and requirements of the educational institutions, and on the other hand the privacy rights (and needs) of the students.

This paper addresses issues associated with the development of eLearning software systems. The development of software systems in general is a highly complex process, and a number of methodologies and models have been developed to help address some of these complexities. Generally the first stage in most development processes is the gathering of requirements which involves elicitation from end-users. This process is made more complex by problems associated with ambiguous terminology. Types of ambiguous terminology include homonymous, polysemous and inaccurate terms. This range of ambiguous terminology can cause significant misunderstandings in the requirements gathering process, which in turn can lead to software systems that do not meet the requirements of the end-users. This research seeks to explore some of the more common terms that can be ambiguously interpreted in the development of eLearning systems, and suggests software engineering approaches to help alleviate the potentially erroneous outcomes of these ambiguities.

China currently has one of the world's fastest growing software industries. However the demand for skilled software engineers is currently outstripping supply. Educational institutes are the primary provider of software engineers. Not only can China's educational institutes not meet the demands of software engineers in terms of quantity, the quality of software engineering graduates at the moment is considered insufficient. The need for educational institutes to be more aware of industry requirements for software engineering graduates and to tailor the curriculum and teaching and learning practice to better fulfill these has been recognized as critical to China's success. To assist with this the Emersion project was established in 2003 to attempt to exchange knowledge and expertise between the EU and China with the goal of developing an industry-oriented education model for software engineering in China. In this paper, we describe our experiences in developing the curriculum which is at the heart of this model and which is based on published best practice and experience of industry and academia in the EU and China.

The Emersion education model was designed by embracing experience from industry and academia in Ireland, the UK and China. A significant part of the model is a curriculum for an honours degree programme in Computer Science to be delivered in the Harbin Institute of Technology, China. Elements of the curriculum are strongly aligned in three ways: constructively, horizontally and vertically. Constructive alignment is the well accepted approach to curriculum design which emphasises that learning, teaching and assessment must be aligned with the learning outcomes of all components of the programme. Horizontal alignment of elements requires the student to transfer problem solving knowledge between domains at the same stage of the programme. Vertical alignment requires that elements are structured to build on foundational knowledge and provide a platform for future elements. When combined, the three dimensions of alignment guide the curriculum development process. Our 3D aligned curriculum demonstrates how components interlink at various layers in a hierarchy to support the development of both the technical and transferrable skills required by the software industry in China and elsewhere.

Increasingly movies are being produced which feature plots that incorporate elements of computer security and hacking, and cumulatively these movies are creating a public perception as to the nature of computer security. This research examines movies that feature hackers (and hacking) to identify if any common themes emerge from these movies in their representation of these issues. To achieve this, first a corpus of hacking movies is created, and then using a qualitative data analysis technique, guidelines are developed which distinguish those movies that actually have the potential to create a perception with the general public. The resultant dataset is analysed and the salient details are compared to the reality of hacking. This research has implications in a range of fields, including in the education of computer students, organisation computer security and in the behaviour of the general public when using computers.

In a continuation of studies into metal-catalysed 5-endo-dig cyclisations, we investigated their application to the synthesis of a range of N-heterocycles: indoles, pyrazoles and pyrroles. The second chapter describes an investigation of the application of silver(I) cyclisation methodology to the synthesis of 1,2-disubstituted indoles. Our methodology was applicable to a range of functional groups in both positions, allowing for terpenes, alkenes, aromatic, alkyl and alcohol substituents in position two. Additionally, a range of nitrogen protecting groups were tolerated, including sulfonamides, carbamates, amides and even methyl groups. A few substrates would not cyclise; we propose that the current hypothesis that this is due to pKa differences is insufficient to explain the differing reactivities. This is supported by computational work carried out by a collaborator. Also reported is a successful synthesis of an indole in a flow system; this was achieved using silver nitrate on silica as the stationary phase. Chapter three focuses on the synthesis of pyrazoles from hydrazines prepared using the Mitsunobu alkylation. A regioselective Mitsunobu alkylation has been defined using non-symmetrical disubstituted hydrazines to give a single regioisomer. Exposure of these hydrazines to silver(I) met with limited success with steric hindrance believed to be the explanation as to why some for the hydrazines would not cyclise. Chapter four reports the synthesis of pyrroles using silver(I) and copper(II). The first part focuses on the improvement of Sharland's copper(I)-catalysed pyrrole synthesis which, upon improvement, gave pyrroles cleanly in high yields. Also reported are the successful silver(I)-catalysed synthesis of fused pyrroles such as annulated pyrroles and N-fused pyrrolizines and indolizines by use of silver(I). Finally the silver(I) cyclisation methodology was applied to the successful synthesis of a natural product, pyrrolostatin.

A focus on widening access and participation in Higher Education has resulted in increased numbers of tertiary students with hidden disabilities in recent decades, globally. While academic supports at an institutional level are available for this student population, issues are reported with them consistently, which often leads to their non-utilisation. This is one possible explanation for why these students experience inequitable academic circumstances compared to their peers concerning lower grades and welfare levels, and higher withdrawal and failure rates. There is a paucity of research available on adequate accommodations that support the academic success of students with hidden disabilities in Higher Education. In addition, few studies focus on how alternative tools such as online learning methods could be of use. This study addresses these gaps in the literature. Quantitative and qualitative research methods were employed in the form of an online questionnaire and in-depth, semi-structured follow-on interviews to explore how to support students with hidden disabilities in Higher Education from their perspectives. The form was completed by 22 respondents with different conditions, of whom 2 were in a control group. In addition, the interviews were conducted online with two students who had several different conditions, diagnostic statuses, and disability registration statuses. Questions centred on perceptions of online learning tools, on-campus classes, and disability support services, through the lens of academic compatibility, hidden- disability compatibility, and welfare. Analysis of the results leads to the conclusion that the most suitable curriculum for students with hidden disabilities is flexible, and affords them online and on-campus learning options in addition to accommodations. It is recommended that staff in third-level institutions receive more training concerning how best to accommodate this student population, and, in addition, designated online learning staff with specialist training could be employed.

The motivation for this dissertation is rooted in a real business need. The Property Registration Authority is the state organisation tasked with maintaining a register of land ownership on the island of Ireland. The PRA currently faces a series of challenges; a high level of staff retiring and the inherent loss of knowledge associated with this trend, a lack of recruitment in recent years and a large increase in lodgement of applications for first registration as a result of legislation. The organisation therefore requires a reliable system for predicting future intake. Prior to this project, there has also been a lack of understanding of the factors that influence intake, and that go much of the way to explaining the peaks and troughs in intake levels that have been seen over recent years. Therefore, this dissertation seeks to identify the factors that influence intake of applications for first registration, and to ascertain if these features may be used to build models to predict future intake. To answer these questions, an exercise in data analytics has been designed and implemented, following the industry standard CRISP-DM methodology. As part of this process, a review of contemporary literature has been carried out, on the subjects of the Irish property market, the factors that influence the level of demand for registration, and modelling approaches applied to variable selection and predictive modelling. Using the insights gleaned from this research, a varied dataset has been sourced, assembled, explored and prepared which includes property registration data, house sale data and economic indicator data. The final dataset has been used to build a series of predictive models, and after evaluation the results show the Random Forest model to be the most effective. A further finding is that the combined outcome of all of the models indicates that the number of houses sold is the single most important factor in predicating volume of applications for registration. The series of experiments conducted and the body of research analysed have presented several valuable insights into the housing market and the factors that influence it, the modelling techniques that can be applied to intake prediction and the key prediction factors that influence intake. The overall conclusion of the study is that the null hypothesis has been rejected and that intake of ‘first registration’ applications in the Property Registration Authority can be predicted through analysis of historical intake data and external factors. However, it is acknowledged that further work will be required to develop a data gathering and analysis process that can be operationalised in the PRA context.

The analysts of Datamonitor describe the knowledge management and collaboration as 2009 trends to watch. Why is collaboration and KM so important? It can be managed for unstructured business processes through sharing knowledge, best practices and experience on the business process context, soliciting feedback on problem resolution, seeking support from colleagues or communicating with other partner and customer communities. The challenge for organisations, especially for sales oriented teams is finding a way of structured managing and supporting the combination of the benefits based on the exchange of information in already existing unstructured activities in collaborative environments. This research aims to show how an approach of bringing knowledge sharing to a sales oriented team in a dynamic organisation can be realised with familiarising the reader with an understanding of the concepts of knowledge management and existing ideas and concepts. The organisation in this context will be represented by a team that is part of the overall organisation. The author will show how a framework of methods can be established as the beginning of implementing a solution for knowledge sharing into the team. The intention of this work is to use existing approaches of knowledge management to analyse the team at the beginning and demonstrate how – based on the findings and the results of the analysis – the implementation of a framework for knowledge sharing with the goal to eliminate or reduce the identified issues within the team and to elicit participation to improve the quality of work. This work is used to define a method of how to introduce starting points of knowledge management into a team with using best practices and gathered information out of this project.

Management itself is not always clearly understood, however, the confusion can be sorted if the underlying theory is clearly distinguished from its implementations. There also may be a specific role for computing in Knowledge Management. It is suggested that Knowledge Management technologists seek a unique strategic position for Computing in Knowledge Management, for reasons of clarity and differentiation from Information Systems. The effective transfer of knowledge is one of the main themes or core competency in Knowledge Management. This is also one of the areas where Knowledge Management technologists may find the niche for a distinct and unique contribution the field of computing can provide. This dissertation finds that Computing for Knowledge Management can be seen as the meeting of the computer sciences, cognitive psychology and sociology since this combination is fit to produce a uniquely user centric outcome. Scientists working the field of Visualisation have already created the foundations on which Knowledge Management technologists may start building. This applies particularly to its subsection of Knowledge Visualisation and by extension to Knowledge Maps. This dissertation investigates the advantages of Knowledge Management tools based on Knowledge Maps, how such a system might be implemented and what issues in terms of people, process and technology must be expected to arise. An experiment was conducted to find out about these issues. The same knowledge base content was presented to two groups of users, one group was presented with a tabular yellow pages type of knowledge map; the other was presented with a graphic knowledge map interface. Participants had to perform a search task and were given a recall test. The experiment tool recorded user activity and answers given for statistical analysis. Participation was too low to lead to any conclusions but the experiment still yielded useful results.