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Resources designed and used in statistics education in Bachelor of Technology courses in France
Full text linkThe French education system has numerous higher education institutions with various specializations. IUTs, established in the late 1960s, provide specific training. These schools offer three-year, practice-oriented education that enables students to work or pursue a master's degree. They are widely accessible and popular, even in small towns, and offer 24 nationally defined curricula in two areas: science and management.
The teaching of statistics in IUTs is unique since it is present in almost all specialties. Studying the teaching and learning of statistics in IUTs enables us to comprehend didactic phenomena in a teaching system that has been established for a long time throughout the country and is a privileged field for meeting teachers whose activity has been tried and tested and is part of a continuum. This research explores the factors that influence the format and nature of the resources designed and utilized in these lessons, how they are integrated into teaching, and what functions they serve.
Semi-structured interviews were conducted with seven mathematics teachers responsible for statistics courses. Often coming from secondary education, these teachers had to adjust the content taught to the objectives and teaching situations typical of French higher education
When to Explain? Model Agnostic Explanation Using a Case-based Approach and Counterfactuals
Full text linkExplainableArtificialIntelligence(XAI)systemshavegained importance with the increasing demand for understanding why and how an artificial intelligence system makes decisions. Counterfactual expla- nations, one of the rising trends of XAI, benefit from human counter- factual thinking mechanisms and aim to follow a similar way of rea- soning. In this paper, we create an eXplainable Case-Based Reasoning system using counterfactual samples with a model-agnostic approach. While CBR methodology allows us to use past experiences to create new explanations, using counterfactuals helps to increase understandability. The main idea of this paper is to generate an explanation when necessary. The proposed method is sample-centric. Thus, an adaptive explanation area is calculated for each data point in the dataset. We detect if there is any existing counterfactual of the samples to increase the coverage of the system, and we create explanation cases from detected sample- counterfactual pairs. If a query case is in the explanation area, at least one explanation case will be triggered, and a two-phase explanation will be created using a text template and a bi-directional bar graph. In this work, we will show (1) how explanation cases are created, (2) how the nature of a dataset influences the explanation area, (3) how understand- able explanations are created, and (4) how the proposed method works on open datasets
Teachers’ judgement, learning materials and curriculum: Navigating in a changing educational landscape
Full text linkTeachers’ choices of learning materials are made under conditions of a changing educational landscape. This small-scale qualitative study investigates how teachers reflect on their choice and use of learning materials in light of changes in the curriculum in Norway and the development of digital and analogue learning materials. It is based on focus group interviews with two groups of experienced teachers. The focus is on the subjects L1 (Norwegian), English and social studies. Our hypothesis is that there is often a tension between the teachers’ professional judgement, the demands of the curriculum, and the available learning materials. The analysis of the interviews shows that the changes in the Norwegian curriculum pose challenges for the teachers, but also that the interviewed teachers are ready for these challenges. With the development of digital learning materials, the teachers do not see the analogue textbook as obsolete, but they have an intention to be able to combine analogue and digital learning materials. The study shows the need for supporting the teachers’ professional judgement in light of the changes in the curriculum and the development of learning materials, both digital and analogue
Attack vectors to re-identify individuals from the anonymised Smittestopp dataset
Full text linkThe first version of “Smittestopp”, the Norwegian Institute of Public Health’s (NIPH) contact tracing application, centrally stored data about the population’s contact patterns with reference to a static personal identifier, a decision that has been widely discussed and criticised. After the Norwegian Data Protection Authority had temporarily forbidden further data collection and processing in June 2020, NIPH announced to discontinue the app and stated that all data related to the application would be deleted. Nevertheless, in October 2021, researchers from an institution involved in the development of the app published a paper called “Nationwide rollout reveals efficacy of epidemic control through digital contact tracing” [3]. In their paper, they analysed a derived dataset based on the Smittestopp data that was announced to be deleted. The authors claim that this derived dataset was anonymised and therefore does not include any personal data. We challenge this assumption by explaining how different external sets of personal data can be matched with the dataset, which potentially leads to a re-identification of persons and a disclosure of their private contacts. We conceptually show how some of these methods can be applied on an example case using publicly available information on Erna Solberg, Norway’s former prime minister. We conclude that it appears reasonably likely that individuals can be re-identified and that the dataset should not be considered anonymised
Explainable Visualization for Morphing Attack Detection
Full text linkDetecting morphed face images has become critical for maintaining trust in automated facial biometric verification systems. It is well demonstrated that better biometric performance of the Face Recognition System (FRS) results in higher vulnerability to face morphing attacks. Morphing can be understood as a technique to combine two or more look-alike facial images corresponding to the attacker and an accomplice, who could apply for a valid passport by exploiting the accomplice’s identity. Morphing Attack Detection (MAD), with the help of Convolutional Neural Networks (CNN), has demonstrated good performance in detecting morphed images. However, they lack transparency, and it is unclear how they differentiate between bona fide and morphed facial images. As a result, this phenomenon needs careful consideration for safety and security-related applications. This paper will explore Layer-wise Relevance Propagation (LRP) to determine the most relevant features. We fine-tune a VGG pre-trained network for face morphing attack detection and LRP is then used to investigate the decision-making processes to understand what input pixels take part in the attack detection. This paper shows that CNN considers only a small part of the image, usually around the eyes, nose, and mouth
Recursos y enseñanza por indagación: El papel de los esquemas de los profesores de matemática en servicio
Full text linkThis research analyses the interaction of 62 in-service maths teachers with a resource called Study and Research Path (SRP). The SRP are resources developed to carry out inquiry-based teaching in the framework of Chevallard's anthropological theory of didactics. The aim of the work is to describe the teacher’s schemes in two situations: study and analyse the SRP and then organise a teaching plan. The schemes generated in each situation are described from the theory of conceptual fields and the instrumental approach, analysing the individual written responses of teachers to both situations. The work shows the diversity and richness of the instruments generated by teachers and allows us to understand their difficulties in developing inquiry-based teaching.Esta investigación analiza la interacción de 62 profesores de matemáticas en servicio con un recurso denominado Recorrido de estudio e investigación (REI). Los REI son recursos desarrollados para realizar enseñanza por indagación en el marco de la Teoría Antropológica de lo didáctico. El objetivo del trabajo es describir los esquemas de los docentes en dos situaciones: estudiar y analizar el REI y luego organizar una propuesta de enseñanza. Los diferentes esquemas generados en cada situación se describen a partir de la Teoría de los campos conceptuales y el enfoque instrumental, analizando las respuestas escritas individuales de los profesores a ambas situaciones. El trabajo muestra la diversidad y riqueza de los instrumentos generados por los docentes y permite comprender sus dificultades para desarrollar enseñanza por indagación
Exploration of Health Data Management Systems; a Scandinavian Point of View
Full text linkIn the era of digitalization, healthcare has become highly dependent on data management. As a result, health data management systems have become increasingly important in cost reduction, treatment improvement, and healthcare procedures enhancement. This study explores blockchain-based health data management systems and their development factors in the context of smart city assets. The features and challenges of blockchain-based development solutions are explored based on the General Data Protection Regulation act and Regulations for the Directorate for e-Health of Norway. Latent Semantic Analysis correlation examination and word cloud analysis were conducted on scholarly documents and Tweets and a conceptual smart asset development framework for health data management systems has been proposed from a Scandinavian point of view. Moreover, based on the findings, this paper proposes a conceptual patient-centered blockchain-based architecture for the development of current health data management systems in Scandinavia
Making Data Work: A Systematic Mapping of Collaborative Data Curation Practices
Full text linkA growing body of literature in Information Systems focuses on the collaborative data curation practices that support the use of novel technologies in the ongoing datafication of work and organizing. In this study, we map the practices and processes that help make data useful and meaningful so that organizations can take advantage of these technologies. We examine 54 empirical studies and focus on the individuals and groups that collaborate to make data useful and meaningful. We identify the following collaborative data curation practices: (i) engaging multiple users in cooperation, (ii) involving higher-level stakeholders, and (iii) using shared resources. We contribute to the IS literature by broadening the view of data curation as an organizational practice that requires the collective, situated, and ongoing engagement of multiple actors making flexible and interpretive decisions to identify and resolve challenges related to working with data
Tower of Babel Bias: Is There More to Learn about Employee-Driven Digital Innovation?
Full text linkWith its origins in medical sciences, systematic literature reviews (SLRs) have gained popularity and widespread acceptance in a variety of disci-plines. The systematic processes ensure an exhaustive inclusion of all relevant material and strength of conclusions. Three approaches are known to improve the comprehensiveness of SLRs: 1) extending the search with snowballing of references and citations, 2) including “grey literature” (multi-vocal reviews), and 3) verifying the list of included studies with field experts. In this paper, we explore another strategy – inclusion of studies written in languages other than English, the usefulness of which is debated. Our goal is to understand whether the Tower of Babel Bias (exclusion of articles based on language) introduces important gaps in evidence. The results of multilingual extensions an existing SLR on employee-driven innovation that included articles written in Russian language show that the extension provides unique insights and perspectives not elucidated in the research published in English, namely the employee innovativeness. We conclude that multilingual literature reviews may be time-consuming endeavors with very limited return on the invested time but may as well result in enriching the understanding of the topic of interest from a unique perspective, especially with respect to regional peculiarities. Finally, we discuss the challenges related to performing a multilingual review
Popularity Bias as Ethical and Technical Issue in Recommendation: A Survey
Full text linkRecommender Systems have become omnipresent in our ev- eryday life, helping us making decisions and navigating in the digital world full of information. However, only recently researchers have started discovering undesired and harmful effects of automated recommendation and began questioning how fair and ethical these systems are, while in- fluencing our day-to-day decision making, shaping our online behaviour and tastes. In the latest research works, various biases and phenomena like filter bubbles and echo chambers have been uncovered among the resulting effects of recommender systems and rigorous work has started on solving these issues. In this narrative survey, we investigate the emer- gence and progression of research on one of the potential types of biases in recommender systems, i.e. Popularity Bias. Many recommender al- gorithms have been shown to favor already popular items, hence giving them even more exposure, which can harm fairness and diversity on the platforms using such systems. Such a problem becomes even more com- plicated if the object of recommendation is not just products and content, but people, their work and services. This survey describes the progress in this field of study, highlighting the advancements and identifying the gaps in the research, where additional effort and attention is necessary to minimize the harmful effect and make sure that such systems are build in a fair and ethical way