Cheating in engineering education: modern methods and potential counter measures

Engineers must engender trust in order to collaborate successfully to produce solutions that the world needs. As part of building this confidence, students with an accredited degree must meet learning outcomes i.e. demonstrate skills to an acceptable standard. Cheating during such assessments reduces professional integrity and future work quality. Through careful assessment practice and encouraging a professional culture with ethics, we may minimise student’s opportunity and motivation to take short-cuts. With this in mind, it is useful to understand which technical and professional skills are most affected. Cheating is evolving, with more collaborative online opportunities. Previous research suggests a majority of student’s admit to dishonesty at least once, and that there are several motivations, including individual, demographic, institutional, and societal. We describe today’s engineering education environment in terms of how it affords cheating behaviours and their methods, including the popularity of online services such as Chegg. By analysing potential cheating methods against a current agreed inventory of contemporary engineering skills, we highlight where educators might focus efforts to reduce bad learning practices. We also consider how the covid pandemic with more online and remote studying amplifies the situation

Engineering Student Belonging To Prevent Early Leavers Through Curriculum Decolonization, Academic Self-Concept, And Psychologically Safe Teamwork

The proportion of early leavers from engineering degrees closely follows the higher education sector throughout Europe; around 10% leave before graduation. Students are more likely to drop-out if they do not feel that they belong in the learning community. While research shows that academic achievement is a primary factor contributing to student drop-out, other student-centric social factors, such as belonging are equally important to student drop-out rates within higher education. The aim of this paper is to present a model constructed on student belonging. The model consists of 3 pillars, namely academic self-concept & professional identity, psychologically safe teamwork, and decolonisation. The study was based on the development and continuous refinement of interventions that could assist students with feeling a sense of belonging. While the primary intention of this project is to present a body of work that highlights belonging as a contributing factor that may be pivotal to a student remaining in higher education or dropping out, readers will also learn about how best to support students in gaining a sense of belonging through self-concept, providing safe teamwork and by decolonising the curriculum

Maximising Academic and Social Outcomes

The MASOEE project brings together engineering faculties in the EUniWell alliance to share best practices for teaching transversal skills so that engineers contribute to societal well-being. The study combines the expertise of several engineering faculties at European universities. It focuses on sharing and developing expertise to improve the social outcomes of engineering students. Namely, researchers examine the similarities and differences between partners regarding their student bodies, teaching, programme structures, and institutions’ culture. Moreover, the work also explores how transversal skills are taught, what student attitudes are in terms of learning these skills, and how educators can better teach them. The research design includes several activities across four work packages (WPs). To ensure that partners use the same skill descriptions, we use well-established organizations' existing definitions. WP1 strives to identify best practices within EUniWell based on the 15 entrepreneurial competencies defined in EU EntreComp Framework. WP2 targets engineering students' ability to solve complex challenges, communication, and networking skills defined in the "21st century skills" by the World Economic Forum. WP3 investigates the engineering schools’ capacity to train engineering students in sustainable competence, forming responsible engineers capable of developing sustainable solutions using the skills defined by the EU GreenComp. WP4 supports the other packages with engineering education research, specifically data collection and analysis, knowledge forming, and evaluation. The project runs from August 2022 until September 2023. The MASOEE project partners gather knowledge within their organisations through joint surveys and focus groups and collectively identify and share best practices. The engineering identity, taught as transversal skills by participating partners, can evolve from a traditional technologist identity along three paths: the self-made engineer, the progressive technologist, and the responsible engineer. By sharing best practices for teaching these skills, we believe we will better understand what the future engineer - who integrates all three identities – will be.<br/

Maximising Academic and Social Outcomes

The MASOEE project brings together engineering faculties in the EUniWell alliance to share best practices for teaching transversal skills so that engineers contribute to societal well-being. The study combines the expertise of several engineering faculties at European universities. It focuses on sharing and developing expertise to improve the social outcomes of engineering students. Namely, researchers examine the similarities and differences between partners regarding their student bodies, teaching, programme structures, and institutions’ culture. Moreover, the work also explores how transversal skills are taught, what student attitudes are in terms of learning these skills, and how educators can better teach them. The research design includes several activities across four work packages (WPs). To ensure that partners use the same skill descriptions, we use well-established organizations' existing definitions. WP1 strives to identify best practices within EUniWell based on the 15 entrepreneurial competencies defined in EU EntreComp Framework. WP2 targets engineering students' ability to solve complex challenges, communication, and networking skills defined in the "21st century skills" by the World Economic Forum. WP3 investigates the engineering schools’ capacity to train engineering students in sustainable competence, forming responsible engineers capable of developing sustainable solutions using the skills defined by the EU GreenComp. WP4 supports the other packages with engineering education research, specifically data collection and analysis, knowledge forming, and evaluation. The project runs from August 2022 until September 2023. The MASOEE project partners gather knowledge within their organisations through joint surveys and focus groups and collectively identify and share best practices. The engineering identity, taught as transversal skills by participating partners, can evolve from a traditional technologist identity along three paths: the self-made engineer, the progressive technologist, and the responsible engineer. By sharing best practices for teaching these skills, we believe we will better understand what the future engineer - who integrates all three identities – will be.<br/

Uncertainty quantification and weak approximation of an elliptic inverse problem

We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a linear uniformly elliptic partial differential equation in divergence form, in a bounded domain in dimension $d \le 3$, from measurements of the solution in the interior. We adopt a Bayesian approach to the problem. We place a prior random field measure on the log permeability, specified through the Karhunen-Lo\`eve expansion of its draws. We consider Gaussian measures constructed this way, and study the regularity of functions drawn from them. We also study the Lipschitz properties of the observation operator mapping the log permeability to the observations. Combining these regularity and continuity estimates, we show that the posterior measure is well-defined on a suitable Banach space. Furthermore the posterior measure is shown to be Lipschitz with respect to the data in the Hellinger metric, giving rise to a form of well-posedness of the inverse problem. Determining the posterior measure, given the data, solves the problem of uncertainty quantification for this inverse problem. In practice the posterior measure must be approximated in a finite dimensional space. We quantify the errors incurred by employing a truncated Karhunen-Lo\`eve expansion to represent this meausure. In particular we study weak convergence of a general class of locally Lipschitz functions of the log permeability, and apply this general theory to estimate errors in the posterior mean of the pressure and the pressure covariance, under refinement of the finite dimensional Karhunen-Lo\`eve truncation.Comment: 19 pages, 0 figures, submitted to SIAM Journal on Numerical Analysi

Influencing human affective responses to dynamic virtual environments

Detecting and measuring emotional responses while interacting with virtual reality (VR), and assessing and interpreting their impacts on human engagement and “immersion,” are both academically and technologically challenging. While many researchers have, in the past, focused on the affective evaluation of passive environments, such as listening to music or the observation of videos and imagery, virtual realities and related interactive environments have been used in only a small number of research studies as a mean of presenting emotional stimuli. This article reports the first stage (focusing on participants' subjective responses) of a range of experimental investigations supporting the evaluation of emotional responses within a virtual environment, according to a three-dimensional (Valence, Arousal, and Dominance) model of affects, developed in the 1970s and 1980s. To populate this three-dimensional model with participants' emotional responses, an “affective VR,” capable of manipulating users' emotions, has been designed and subjectively evaluated. The VR takes the form of a dynamic “speedboat” simulation, elements (controllable VR parameters) of which were assessed and selected based on a 35-respondent online survey, coupled with the implementation of an affective power approximation algorithm. A further 68 participants took part in a series of trials, interacting with a number of VR variations, while subjectively rating their emotional responses. The experimental results provide an early level of confidence that this particular affective VR is capable of manipulating individuals' emotional experiences, through the control of its internal parameters. Moreover, the approximation technique proved to be fairly reliable in predicting users' potential emotional responses, in various affective VR settings, prior to actual experiences. Finally, the analysis suggested that the emotional response of the users, with different gender and gaming experiences, could vary, when presented with the same affective VR situation. </jats:p

TRECVID 2004 experiments in Dublin City University

In this paper, we describe our experiments for TRECVID 2004 for the Search task. In the interactive search task, we developed two versions of a video search/browse system based on the Físchlár Digital Video System: one with text- and image-based searching (System A); the other with only image (System B). These two systems produced eight interactive runs. In addition we submitted ten fully automatic supplemental runs and two manual runs. A.1, Submitted Runs: • DCUTREC13a_{1,3,5,7} for System A, four interactive runs based on text and image evidence. • DCUTREC13b_{2,4,6,8} for System B, also four interactive runs based on image evidence alone. • DCUTV2004_9, a manual run based on filtering faces from an underlying text search engine for certain queries. • DCUTV2004_10, a manual run based on manually generated queries processed automatically. • DCU_AUTOLM{1,2,3,4,5,6,7}, seven fully automatic runs based on language models operating over ASR text transcripts and visual features. • DCUauto_{01,02,03}, three fully automatic runs based on exploring the benefits of multiple sources of text evidence and automatic query expansion. A.2, In the interactive experiment it was confirmed that text and image based retrieval outperforms an image-only system. In the fully automatic runs, DCUauto_{01,02,03}, it was found that integrating ASR, CC and OCR text into the text ranking outperforms using ASR text alone. Furthermore, applying automatic query expansion to the initial results of ASR, CC, OCR text further increases performance (MAP), though not at high rank positions. For the language model-based fully automatic runs, DCU_AUTOLM{1,2,3,4,5,6,7}, we found that interpolated language models perform marginally better than other tested language models and that combining image and textual (ASR) evidence was found to marginally increase performance (MAP) over textual models alone. For our two manual runs we found that employing a face filter disimproved MAP when compared to employing textual evidence alone and that manually generated textual queries improved MAP over fully automatic runs, though the improvement was marginal. A.3, Our conclusions from our fully automatic text based runs suggest that integrating ASR, CC and OCR text into the retrieval mechanism boost retrieval performance over ASR alone. In addition, a text-only Language Modelling approach such as DCU_AUTOLM1 will outperform our best conventional text search system. From our interactive runs we conclude that textual evidence is an important lever for locating relevant content quickly, but that image evidence, if used by experienced users can aid retrieval performance. A.4, We learned that incorporating multiple text sources improves over ASR alone and that an LM approach which integrates shot text, neighbouring shots and entire video contents provides even better retrieval performance. These findings will influence how we integrate textual evidence into future Video IR systems. It was also found that a system based on image evidence alone can perform reasonably and given good query images can aid retrieval performance

Euniwell: Maximising Academic And Social Outcomes In Engineering Education

The ERASMUS+ European University for Well-Being (EUniWell) alliance’s mission aims to resolve the paradox of Europeans’ relative prosperity against the global security and sustainability challenge. “Maximising Academic and Social Outcomes in Engineering Education” is a project which interprets this contradiction for engineering educators; how to best teach non-technical skills to ensure engineers make the utmost contribution to societal wellbeing? Appreciably, the social outcome for the person who becomes an engineer is positive because the profession is relatively well-paid. Therefore, engineering education is good for social mobility providing the learning environment narrows attainment gaps between disadvantaged and mainstream cohorts. Accordingly, our strategy is to bring together the expertise of the British, French, Italian and Swedish faculties to transfer best practice for professional, business and sustainability skill teaching, while contrasting how their disadvantaged cohorts present. The project has two primary objectives: To understand how partners differ in terms of skill teaching, and how students from disadvantaged backgrounds are accommodated. The paper describes the background and rationale of the project, and its research design and methodology. Although the project is still in progress and data collection is still underway, this paper provides insights and perspectives for engineering educators looking to design similar collaborations to share best practice, while considering engineering identities and their underlying competencies