61378 research outputs found
Sort by
Usages and perceptions of Generative AI tools by students at the University of Luxembourg
No full textChatGPT and other generative AI tools have become an integral part of our landscape, including in higher education, where students have widely adopted them (Jo, 2023; Playfoot et al., 2024).
While conducting workshops for teaching staff at the UL, I had the opportunity to discuss and identify key questions regarding students' use and perceptions of generative AI. Through this working paper (and others that will be released soon), I aim to provide a few answers.
Today, we will explore three questions:
1.How do students use ChatGPT?
2.How do students believe ChatGPT can impact their studies?
3.What concerns do students have regarding ChatGPT?
The present working paper builds on Ravšelj et al. (2025) work while focusing on students enrolled at the University of Luxembourg
Do AI Assistants Help Students Write Formal Specifications? A Study with ChatGPT and the B-Method
Get PDFpeer reviewedThis paper investigates the role of AI assistants, specifically OpenAI's ChatGPT, in teaching formal methods (FM) to undergraduate students, using the B-method as a formal specification technique. While existing studies demonstrate the effectiveness of AI in coding tasks, no study reports on its impact on formal specifications. We examine whether ChatGPT provides an advantage when writing B-specifications and analyse student trust in its outputs. Our findings indicate that the AI does not help students to enhance the correctness of their specifications, with low trust correlating to better outcomes. Additionally, we identify a behavioural pattern with which to interact with ChatGPT which may influence the correctness of B-specifications
Improving accuracy in the estimation of probable dementia in racially and ethnically diverse groups with penalized regression and transfer learning.
Get PDFpeer reviewedAlgorithmic estimations of dementia status are widely used in public health and epidemiological research, however, inadequate algorithm performance across racial/ethnic groups has been a barrier. We present improvements in the accuracy of group-specific "probable dementia" estimation using a transfer learning approach. Transfer learning involves combining models trained on a large "source" dataset with imprecise outcome assessments, alongside models trained on a smaller "target" dataset with high-quality outcome assessments. Transfer learning improves model accuracy by leveraging large source data while refining estimations with smaller, target data. We illustrate with data from the Health and Retirement Study (source data: N=6,630) and the Harmonized Cognitive Assessment Protocol (target data: N=2,388). Models for dementia status estimation were evaluated through overall accuracy (Brier score), calibration (intercept, slope), and discriminative ability (area under the receiver operating characteristic curve, AUR; area under the precision-recall curve, AUPRC). The transfer-learned algorithm showed higher accuracy compared to the best previously reported algorithm among both non-Hispanic Black participants (Brier 0.049 vs. 0.061; AUC 0.84 vs. 0.81; AUPRC 0.52 vs. 0.39) and Hispanic participants (Brier 0.052 vs. 0.056; AUC 0.89 vs. 0.87; AUPRC 0.61 vs. 0.56). Transfer learning can improve dementia status estimation for groups historically underrepresented in research.10. Reduced inequalities3. Good health and well-bein
No Way Out: Dual Channels of Manipulation in Agenda Institutions
Get PDFA large body of literature in Political Science emphasizes the importance of limiting opportunities for manipulation of legislative institutions by self-interested actors. This note shows that that the very conditions that shield institutions from agenda manipulation are precisely those that expose them to capture by special interests. This result holds in a highly general dynamic framework that encompasses a broad range of empirically relevant agenda institutions and policy-making environments, including those with policy uncertainty and experimentation.Economic Insecurity: Causes, Consequences and Actions, EICC
Irreducible polyadic semigroups admitting the adjunction of a neutral element
Get PDFIt was claimed in [4] that for any integer n>=2, a neutral element can be adjoined to an n-ary semigroup if and only if the n-ary semigroup is reducible to a binary semigroup. We show that the `only if' direction of this statement is incorrect when n is odd. Moreover, we offer a comprehensive characterization of the class of irreducible n-ary semigroups, for odd n, that admit the adjunction of a neutral element
AutoTag & TagMap: LLM-Powered Moodle Plugins for Pedagogical Alignment Checks
Get PDFpeer reviewedPedagogical alignment denotes the coordination between learning outcomes, teaching and learning activities and assessment tasks. For any learning outcome of a course, teachers should design corresponding learning activities and consequently assess its achievement. Fair and valid assessments require a proper pedagogical alignment. At a low-level, this can be verified by tagging learning material, e.g., lecture notes or presentations, and assessment items, e.g., quiz questions, and checking a homogeneous coverage. Learning Management Systems (LMS) such as Moodle enable teachers to tag both resources and questions. To ease the tagging, named entity recognition technologies can be used. With the advent of Large Language Models (LLMs) such as GPT-4, this task has seen a new momentum. In this paper, we present AutoTag and TagMap, two Moodle plugins which will help teachers to check the pedagogical alignment of their online courses. The first plugin, AutoTag, leverages GPT-4 to provide automatic resource tagging support to teachers. An existing plugin for question generation also implements this logic. The second plugin, TagMap, independent of the other, visualizes concept coverage in both resources and questions to help teachers in verifying the pedagogical alignment and identifying possible shortcomings. We exemplify the usage of both plugins in a nephrology and urology course
Sponsored by the State: The Private Regulation of Government Influencers
No full textpeer reviewedThe popularity of influencer marketing is ever growing. Based on parasocial relationships rooted in authenticity and relatability, the appeal of influencers is effectively used to promote commercial goods and services. This popularity is increasingly migrating outside of commercial advertising. In the past years, governments around the world have collaborated with influencers for public interest communication such as supporting wars, promoting Covid public health policies or financial literacy. Although entrenched in promoting the public good and facilitated by public funding, the dynamics of these collaborations remain very much unknown. Shedding light on how governments employ influencers can help us understand how commercial strategies shape the advertising of public goods as state propaganda. From a regulatory perspective, commercial advertising has been subject to a lot of rules relating to the content as well as the transparency of commercial messaging. Yet government communication—whether called propaganda, public service communication, or the advertising of public goods—has not been governed with the same level of clarity. This study explores comprehensive materials from 10 freedom of information requests on government influencer campaigns answered by the Dutch government between 2020 and 2024 (N = 1302 pages). Using qualitative content analysis, we focus on understanding the characteristics of advertising contracts between the government and the influencers in their service, in order to critically reflect on the transparency of the monetisation entailed by these transactions
A meta-analysis on the effects of high-performance work practices in small and medium-sized enterprises: An exploration of organizational- and individual-level outcomes
Get PDFpeer reviewedThis research aims to achieve two objectives: to confirm results about the effects of high-performance work practices (HPWPs) at the organizational level, and to explore the effects of HPWPs on individual employee performance in small and medium-sized enterprises (SMEs). We conducted a meta-analysis of 115 studies to investigate how high-performance work practices are positively related to organizational and individual outcomes in SMEs, identifying critical benefits HPWPs offer. At the organizational level, HPWPs are positively related to firm performance, growth, and innovation, while negatively related to turnover and absenteeism rates. At the individual level, HPWPs are positively related to employee engagement, motivation, creativity, entrepreneurial orientation, job satisfaction, and organizational commitment, while negatively related to turnover intention. We nuance the applicability of HPWPs to the SME context and we contribute to the literature by highlighting the role of HPWPs at the individual level
