Participatory Design of AI with Children: Reflections on IDC Design Challenge

Children growing up in the era of Artificial Intelligence (AI) will be most impacted by the technology across their life span. Participatory Design (PD) is widely adopted by the Interaction Design and Children (IDC) community, which empowers children to bring their interests, needs, and creativity to the design process of future technologies. While PD has drawn increasing attention to human-centered AI design, it remains largely untapped in facilitating the design process of AI technologies relevant to children and their community. In this paper, we report intriguing children's design ideas on AI technologies resulting from the "Research and Design Challenge" of the 22nd ACM Interaction Design and Children (IDC 2023) conference. The diversity of design problems, AI applications and capabilities revealed by the children's design ideas shed light on the potential of engaging children in PD activities for future AI technologies. We discuss opportunities and challenges for accessible and inclusive PD experiences with children in shaping the future of AI-powered society

AI and Literacy for Non-Technical Students: A Hybrid-Augmented Learning Factory

Artificial Intelligence (AI) has made a strong impact on business and private life. Nonetheless, understanding how AI works and which role data specifically plays in this context remain unclear for many people. We argue that especially students with non-technical backgrounds should build up AI & data literacy to understand the key concepts and leverage their potential in their field of study and research. For this purpose, we present the concept of a hybrid-augmented learning factory, where students can explore AI & data concepts with interactive and immersive technologies in a physical and virtual environment. In this workshop paper, we demonstrate our overarching idea of the hybrid-augmented learning factory as well as our current progress on implementing learning applications for the learning factory

Digital Literacy in Academic Libraries: Frameworks, Case Studies, and Considerations

Digital literacy has been explored by academic librarians for many years, however, throughout the ‘post’ pandemic world there has been an increase in digital literacy instruction in reaction to a world of thriving mis- and dis-information. Implementation of new library programs, especially regarding evolving digital skills and technologies can be both time consuming and intimidating. The intention of this report is to provide resources for the implementation of a successful digital literacy program in the post-secondary context. This report will describe a widely used digital literacy framework, explore successful case studies of the implementation of an institutional specific digital literacy framework, and detail successful case studies of digital literacy instruction from academic librarians around the world. This report intends to provide a digital literacy resource report of frameworks, case studies, and recommendations which could be helpful to academic librarians updating or creating a new program for digital literacy within their own academic institutions

Migrants' Imaginaries and Awareness of Discrimination by Artificial Intelligence: A Conceptual Framework for Analysing Digital Literacy

This paper asks what skills migrants need to be able to deal with artificial intelligence (AI) technologies in a self-determined way in their everyday lives. We propose a conceptual framework to empirically identify migrant's awareness and perceptions of possible discrimination through AI. Following Bucher (2017, 40), we argue that by experiencing AI systems in their digital environments, people develop AI imaginaries that shape their attitudes, interactions, and practices with AI. We assume that experiences of discrimination evoke affects, feelings, and emotions that at first glance are not associated with AI technologies. The paper provides relevant research questions that address AI imaginaries. In addition to studying knowledge about and perceptions of AI, research should increasingly focus on users' attitudes towards AI, their evaluations of AI, and their feelings, emotions, and affects related to AI. Subsequently, we elaborate on dimensions of digital literacy based on these AI imaginaries. Finally, we will describe the digital skills that are necessary to confidently cope with discrimination by AI technologies

How to Enable Sovereign Human-AI Interactions at Work? Concepts of Graspable Testbeds Empowering People to Understand and Competently Use AI-Systems

Artificial intelligence (AI) strategies are exhibiting a shift of perspectives, focusing more intensively on a more human-centric view. New conceptualizations of AI literacy (AIL) are being presented, summarizing the competencies human users need to successfully interact with AI-based systems. However, these conceptualizations lack practical relevance. In view of the rapid pace of technological development, this contribution addresses the urgent need to bridge the gap between theoretical concepts of AIL and practical requirements of working environments. It transfers current conceptualizations and new principles of a more human-centered perspective on AI into professional working environments. From a psychological perspective, the project focuses on emotional-motivational, eudaimonic, and social aspects. Methodologically, the project presented develops AI testbeds in virtual reality to realize literally graspable interactions with AI-based technologies in the actual work environment. Overall, the project aims to increase the competencies and the willingness to successfully master the challenges of the digitalized world of work

Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making

Automated decision systems (ADS) have become ubiquitous in many high-stakes domains. Those systems typically involve sophisticated yet opaque artificial intelligence (AI) techniques that seldom allow for full comprehension of their inner workings, particularly for affected individuals. As a result, ADS are prone to deficient oversight and calibration, which can lead to undesirable (e.g., unfair) outcomes. In this work, we conduct an online study with 200 participants to examine people’s perceptions of fairness and trustworthiness towards ADS in comparison to a scenario where a human instead of an ADS makes a high-stakes decision—and we provide thorough identical explanations regarding decisions in both cases. Surprisingly, we find that people perceive ADS as fairer than human decision-makers. Our analyses also suggest that people’s AI literacy affects their perceptions, indicating that people with higher AI literacy favor ADS more strongly over human decision-makers, whereas low-AI-literacy people exhibit no significant differences in their perceptions

COOPERATIVE LEARNING FOR ENHANCED READING COMPREHENSION: A STUDY WITH FIRST-YEAR STUDENTS

This research aimed to determine the effectiveness of teaching reading comprehension using a cooperative learning model for first-year students at Universitas Muhammadiyah Bone. The study employed a quasi-experimental design, involving two groups: an experimental group (30 students) and a control group (30 students). Both groups underwent pre-test assessments, material presentations, and post-test evaluations. The data, collected through multiple-choice items, were analyzed using mean scores and the t-test formula. The research revealed that reading comprehension improved significantly in the experimental group (mean score 83.11) compared to the control group (mean score 61.56). The t-test also indicated a significant difference between the two groups, favoring the cooperative learning model. In conclusion, the use of the cooperative learning model effectively enhances students' reading comprehension.

Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making

Many important decisions in daily life are made with the help of advisors, e.g., decisions about medical treatments or financial investments. Whereas in the past, advice has often been received from human experts, friends, or family, advisors based on artificial intelligence (AI) have become more and more present nowadays. Typically, the advice generated by AI is judged by a human and either deemed reliable or rejected. However, recent work has shown that AI advice is not always beneficial, as humans have shown to be unable to ignore incorrect AI advice, essentially representing an over-reliance on AI. Therefore, the aspired goal should be to enable humans not to rely on AI advice blindly but rather to distinguish its quality and act upon it to make better decisions. Specifically, that means that humans should rely on the AI in the presence of correct advice and self-rely when confronted with incorrect advice, i.e., establish appropriate reliance (AR) on AI advice on a case-by-case basis. Current research lacks a metric for AR. This prevents a rigorous evaluation of factors impacting AR and hinders further development of human-AI decision-making. Therefore, based on the literature, we derive a measurement concept of AR. We propose to view AR as a two-dimensional construct that measures the ability to discriminate advice quality and behave accordingly. In this article, we derive the measurement concept, illustrate its application and outline potential future research

Tahfidz Al-Qur'an: A Study of Learning Management Systems in Higher Education

This research is motivated by the condition of new students who enter Ma'had Al-Jami'ah IAIN Curup who have different educational backgrounds in understanding the Qur'an. This study aimed to understand the management of Tahfidz Qur'an learning at IAIN Curup. This research is a qualitative research type of case study. Observation, interviews, and documentation carried out data collection techniques. The subjects of this research are administrators, ustadz and ustazah, and students. Then the data analysis starts with data reduction, presentation, and conclusion drawing. The results showed that; Tahfidz Al-Qur'an learning management at IAIN Curup includes three stages, namely, planning, which consists of praying and memorizing muraja'ah; implementation consisting of recitation techniques, and understanding the meaning, memorization techniques, and deposit techniques and the evaluation stage in the form of an oral test. Furthermore, the application of the method used at Ma'had Al-Jami'ah IAIN Curup is unique, namely the technique of understanding meaning