CHIRA 2024 Abstracts

Area 1 - Interactive Devices

Full Papers

Paper Nr:	15
Title:	An Examination of Pre-School Children’s Usage Behavior of Augmented Reality: Traditional vs. AR-Assisted LEGO® Building
Authors:	Enes Yigitbas and Alessio Dell'Aquila
Abstract:	Many children are introduced to LEGO® bricks for the first time at a young age. LEGO® models are usually built according to a set of building instructions, each instruction step being printed onto paper as an orthographic projection. However, as children’s spatial reasoning skills are yet to be fully developed, they tend to misinterpret positions and shapes from these types of instructions, resulting in suboptimal performance in LEGO® construction tasks. With Augmented Reality (AR), users can perceive and interact with three-dimensional, virtual content as if it was present in the real world, eliminating the need to convert two-dimensional instructions into three-dimensional models. In this work, an AR-Assisted LEGO® Building Instruction (ARALBI) application was developed, providing three-dimensional reference LEGO® models. ARALBI was specifically designed to be used by preschool children, with them constructing the real model step by step next to the virtual model. It was tested against typical paper-building instructions in a user study based on the General Assembly Task Model (GATM). Using AR instructions, preschool children performed better in terms of effectiveness (i.e. made fewer mistakes) but not efficiency (i.e. required more time to finish assembling the model) when compared to paper instructions. The results of this study indicated that preschool children, who never used AR technology before, enjoyed the use of the AR application and preferred it over paper-building instructions.

Paper Nr:	46
Title:	Implementing and Evaluating Trustworthy Conversational Agents for Children
Authors:	Marina Escobar-Planas, Roberto Ruiz-Sánchez, Pedro Frau-Amar, Vicky Charisi, Carlos-D. Martínez-Hinarejos, Emilia Gómez and Luis Merino
Abstract:	Conversational Agents (CAs) have become increasingly popular in many settings, including households. However, despite the increasing frequency of children’s interactions with these systems, there is still little research on the ethical design of CAs, particularly for this special population. To address this gap, in this study we design, develop and evaluate a Child-Friendly CA for collaborative storytelling, implementing specific guidelines to ensure a trustworthy design for children based on key principles such as human agency, data privacy or transparency as outlined by the High-Level Expert Group on artificial intelligence (HLEG). To evaluate the trustworthiness of the Child-Friendly CA, designers and developers conduct a collaborative assessment by applying the Assessment List for Trustworthy Artificial Intelligence (ALTAI) using the Delphi methodology. Our results demonstrate that our Child-Friendly CA design improves the trustworthiness of the system and highlights the importance of designing CAs that consider the particularities of children’s interactions. Our findings contribute to the still scarce literature on trustworthy CAs and provide insights for developers striving to ensure a trustworthy experience for children.

Paper Nr:	60
Title:	Assessing Comfort During Human-Robot Collaboration Using Virtual Reality Scenarios
Authors:	Gina M. Notaro, Ryan Mustari, Arya K. Haghighat, Dalong Gao, Vahidreza Molazadeh and Miguel Saez
Abstract:	Maintaining comfort during human-robot collaboration is critical for the efficient use of, and engagement with, emerging robotic technologies. In this paper, we describe our efforts towards designing and implementing a study to investigate the impact of robotic behaviors on human teammate comfort within manufactur-ing scenarios. We first developed immersive virtual reality (VR) human-robot collaboration scenarios in which we manipulated virtual robotic arm behavior pa-rameters. These experimental manipulations included robot arm movement speed, human-robot proximity, and inconsistency of speed or proximity (i.e., predictabil-ity). We found that the lowest overall comfort ratings were reported for the very close proximity and very fast speed robot arm manipulations, particularly for the unpredictable conditions. At the end of the experiment, most participants noted that the very close proximity scenarios made them more uncomfortable than the fast speed conditions, suggesting the virtual robotic arm was considered as social entity with respect to proxemics. These findings and approach combined can help elucidate human perceptions of robotic behaviors for extension to real-world col-laboration scenarios, with applications in manufacturing and beyond.

Paper Nr:	74
Title:	Understanding Human Responses to Robot Errors to Enhance Human-Robot Interaction Design in a Non-Industrial Context
Authors:	Simona D'Attanasio and Anna Studzinska
Abstract:	Collaborative robots (cobots) are designed to work alongside humans, offer-ing flexibility and cost-effective solutions with quick and easy programming. Despite their potential, many cobot applications lack true collaboration and are confined to industrial environments. This study investigates human error recovery strategies with cobots in a non-industrial context, using a real-world task from an administrative department. Ten participants interacted with a cobot simulating errors, and their responses were observed. The study employed a Wizard of Oz setup to simulate interaction modalities, including voice control and visual and auditory feedback, and collected data through questionnaires assessing usefulness, user experience, and quality satisfac-tion. The results indicated high user satisfaction and appreciation for the cobot. Findings reveal that intuitive user-centered interaction is crucial for improving user experience and the adoption of collaborative robots in vari-ous professional fields.

Short Papers

Paper Nr:	14
Title:	Arm in Motion: How Motion Modality and Erratic Behavior of a Robotic Arm Shape User Perception
Authors:	E. Liberman Pincu and T. Oron-Gilad
Abstract:	This study examines the impact of motion design on user perceptions and interac-tions with robotic arms, which are expanding from industrial applications to sup-porting daily human tasks. The research investigates how different motion com-ponents influence user perceptions and preferences. Employing an online ques-tionnaire, we analyze participants’ responses to videos of robotic arms perform-ing laundry sorting tasks, revealing significant relationships between motion mo-dalities, erratic behavior, and characteristic attribution. The findings contribute to the design of robotic arm movements to effectively communicate and engage with users, enhancing human-robot interaction in both industrial and social contexts.

Paper Nr:	28
Title:	Enhancing EEG-Based User Verification with a Normalized Neural Network Ensemble Approach
Authors:	Roberto Saia, Riccardo Balia, Alessandro Sebastian Podda, Livio Pompianu, Salvatore Carta and Alessia Pisu
Abstract:	The development of user identity verification approaches using biometric systems based on EEG data holds significant promise across various domains. However, the inherent complexity and variability of this data make designing reliable solutions challenging. In response to these challenges, this work introduces a Normalized Neural Network Ensemble (NNNE) approach for EEGbased user verification. It leverages neural networks to enhance the current stateof- the-art performance, aiming to overcome the problems associated with EEG data by capturing spatial and temporal patterns in EEG signals more effectively. In detail, the proposed approach relies on an architecture centered around an ensemble of Multi-Layer Perceptron artificial neural networks regulated by a soft voting criterion. As part of the preprocessing steps, the input data is normalized by transforming features based on quantile information. Additionally, the MLP hyperparameters and the number of MLP evaluators in the ensemble are automatically optimized. Considering the high heterogeneity of the state-of-the-art works in this field, which are characterized by a wide variability in the choices of components, approaches, and strategies, making comparisons between their performances difficult and sometimes impossible, this paper exploits the opportunity offered by the Biometric EEG Dataset (BED), which provides benchmark values that facilitate comparisons within the context of widely adopted approaches in literature in terms of stimuli and feature extraction techniques. The experimental results show that the proposed NNNE approach improves the performance of the state-of-the-art one (Hidden Markov Model) used by the authors of the dataset to define the reference values, significantly.

Paper Nr:	56
Title:	Mix ISO 9241 and Design Thinking for a Collaborative Interface Design Process
Authors:	Wendgounda Francis Ouedraogo
Abstract:	Skills and experiences of individuals are different in the use of intelligent systems. Designing and implementing a user interface that meets user habits can be a major asset to the acceptance of these systems. Usability aspects must therefore be placed at the heart of interactive technological solutions. This assumes active involvement of potential end users in collaborative design processes. The ISO 9241 - Human-centered design for interactive systems standards - offers a framework in parts 110, 112, and 210. Design Thinking, which is a non-linear methodology, supports an approach for the practical implementation of this ISO 9241 tool. The results obtained and the evaluation that followed encourage this process using these tools and methods to place potential end users at the heart of the interactive platform development process.

Paper Nr:	61
Title:	Playing Jazz with the Pupil Accommodative Response: A Novel Unexplored Pupil-Based Interaction Mode
Authors:	Livia Colucci, Leonardo Cardinali and Silvestro Roatta
Abstract:	In recent years, the Pupil Accommodative Response (PAR) has emerged as a promising communication strategy in Human-Computer Interaction (HCI) and augmentative and alternative communication devices. In fact, the PAR is a repetitive, high-magnitude and low-noise innate response. Previous studies exploited the far-to-near focus switch that induces the PAR to extract a binary output. This preliminary study has introduced the potential for detecting intermediate levels of response, with the aim of extracting a non-binary output from pupil size variations induced by shifts in focus between multiple targets. In the current context, this strategy was applied to a music machine, where the pupil size is continuously monitored and converted into musical notes resulting in a jazz melody. This article aims to present the preliminary results of the developed system and to explore the challenges and limitations associated with this type of application. In addition to entertainment, usesfulness of this approach includes enhancing user awareness about the physiological function and the voluntary control of pupil size. In perspective, the approach adopted for the music machine may be exploited in pupil-based HCIs to achieve higher information transfer rates.

Paper Nr:	68
Title:	On the Adaptive Interplay of Mirroring and Bonding by Homophily in Joint Decision Making: A Second-Order Adaptive Network Model
Authors:	Caroline F. Tichelaar and Jan Treur
Abstract:	In this paper, the adaptive interplay between bonding by homophily and adaptive mirroring by Hebbian learning within the context of joint decision-making is ex-plored by second-order adaptive network modeling. Second-order adaptive mechanisms were applied to capture the adaptive dynamic interplay between these processes. Several simulation experiments were conducted across different sce-narios to investigate the influence of various characteristics on formation and maintenance of social bonds, learning, and decision-making. The obtained model may be applied for computational analysis of collaborative human-bot interactions in order to jointly make decisions while bonding and adapting.

Paper Nr:	72
Title:	Sound Blocks VR: An Accessible Virtual Reality Musical Instrument
Authors:	Marta Gioiosa, Federico Avanzini, Luca Andrea Ludovico, Susanna Brambilla and Laura Ripamonti
Abstract:	In recent years, immersive technologies such as augmented and virtual reality have gained significant popularity and found applications across various research domains. This paper focuses on the adoption of such technologies for musical purposes, particularly in enhancing accessibility in musical performance. In the domain of Digital Musical Instruments, extensive efforts have been made to develop accessible designs and interfaces for music creation. Concerning Virtual Reality Musical Instruments (VRMIs), one notable challenge is the discomfort stemming from using controllers to interact with objects in the virtual world, specifically for people with a physical disability. In fact, the design of these applications often incorporates objects that require precise control. The proposed solution is an accessible VRMI, called Sound Blocks VR, which accommodates both controller-based and hand-tracking interactions to address the needs of individuals with physical disabilities or, in general, who feel uncomfortable using controllers. Where available, the passthrough feature can also be exploited. The usability of Sound Blocks VR was evaluated using the System Usability Scale through interviews with musicians and nonmusicians. The average usability score computed on 17 participants is 87.94 out of 100, which indicates that participants found the experience intuitive and user-friendly. Moreover, some qualitative questions were posed to investigate specific aspects of the experience design.

Paper Nr:	23
Title:	Bridging Medical Genetics, Genetic Counselling, and Patients: Proposing an Immersive, Interactive, and Holographic Health Information Platform with Evaluation Methods for Personalized Patient Education
Authors:	S. Chan-Bormei, C. Srisukajorn, P. Teekakirikul and H. Miri
Abstract:	This paper proposes the use of a personalized and interactive health information platform, dubbed HoloGrad, to explore the intersection of medical genetics and patient engagement. HoloGrad is an immersive and user-centered health information system, using virtual and holographic visualization for 3D interactions in medical genetics. This enables clear and comprehensible presentation and delivery of specialized information to patients. We posit that our approach to individualized genetic counselling can enhance information comprehension, increase retention, improve doctor-patient communication, and reduce genetic counseling time. This is achieved by presenting 3D visualizations on mixed-reality headsets, such as HoloLens and MetaQuest. Patients can see in 3D what a medical geneticist or genetic counselor is demonstrating through holograms and virtual simulations. This makes it easier to view, manipulate, and understand complex genetic structures and procedures. HoloGrad also boasts an interactive Pedigree Tree feature – a fully editable graphical tool for visualizing genealogical relationships and assessing disease risk by tracking family health history. To our knowledge, HoloGrad is the first platform to integrate a fully-fledged Pedigree Tree feature that allows medical professionals and patients to create a comprehensive overview of familial health, aiding in identifying potential genetic pre-dispositions and empowering informed decision-making regarding preventative measures, monitoring plans, and treatment options. The evaluation methods and assessment strategies outlined in this paper offer valuable insights and guidelines, serving as a pivotal resource for those engaged in the exploration of virtual and holographic technologies and visualization tools.

Paper Nr:	35
Title:	Caregiver Acceptability of an LLM-powered Assistant Interface to Improve Sleep Quality of the Elderly
Authors:	Marco Ajovalasit, Irene Attori, Massimo Caon, Fabio Salice, Shengnan Zhou and Sara Comai
Abstract:	While increased longevity and improved health at older ages are notable achievements of the 21st century, they pose significant challenges, particularly in informal care. This paper discusses NightCare Assistant, a human-centric system that uses nighttime data and Large Language Models (LLM) to translate sleep quality into practical suggestions for improving the daily routine of ageing individuals. These suggestions are displayed through a tablet application, allowing caregivers to interact with an AI assistant. The research aims to understand the acceptability of this solution, focusing on caregivers’ reactions to different AI-generated outputs and their willingness to follow these suggestions. An online questionnaire tested the system’s acceptability, examining caregivers’ perceptions of text, image, and audio outputs generated by AI. Results indicate significant interest among caregivers in adopting technological solutions to ease caregiving responsibilities. Caregivers found audio feedback the most reliable and understandable, followed by text and image outputs. Caregivers’ willingness to follow NightCare Assistant’s advice supports the system’s potential to improve care quality and safety for ageing individuals. The study highlights the necessity of addressing both nighttime behaviours and daily routines to effectively support cognitive health. NightCare Assistant’s integration of nighttime monitoring data into actionable daily interventions provides a comprehensive strategy for enhancing the well-being of older adults and their caregivers. Its acceptance among caregivers suggests that similar technological interventions can support autonomous living and reduce caregiver burden.

Paper Nr:	44
Title:	EEG Biometrics with GAN Integration for Secure Smart City Data Access
Authors:	Roberto Saia, Riccardo Balia, Alessandro Sebastian Podda, Livio Pompianu, Salvatore Mario Carta and Alessia Pisu
Abstract:	Biometric systems leveraging ElectroEncephaloGram (EEG) data for user authentication present significant potential in diverse contexts, especially in Smart City ecosystems where secure access to sensitive data is crucial (e.g., healthcare systems, intelligent transportation, smart grids, public safety, and citizen services). However, the complexity and variability of EEG data raise challenges in developing effective solutions. In this context, after a preliminary series of experiments used to find the best feature extraction method for the input, and performed by exploiting the Biometric EEG Dataset (BED), this paper proposes a novel EEG-based user verification framework. It utilizes Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction, followed by feature selection via the Boruta strategy and automated data quantization. An important aspect of this approach is the integration of Generative Adversarial Networks (GANs) to generate synthetic EEG data, which, along with real data, is employed to train an ensemble of Artificial Neural Networks (ANNs). The ensemble decision is made using soft voting mechanisms, promising a robust and competitive solution compared to current state-of-the-art techniques. Initial experiments suggest that this framework has significant potential for further development and optimization.

Area 2 - Adaptive and Intelligent Systems

Short Papers

Paper Nr:	22
Title:	Emotion-Aware Interfaces: Empirical Methods for Adaptive User Interface
Authors:	Syrine Haddad, Olfa Daassi and Safya Belghith
Abstract:	Designing User Interfaces (UIs) that can interpret and respond to user emotions has evolved from a passing trend to a core tenet of design philosophy. As technology advances, it becomes increasingly important to predict users’ emotional states during interface interactions. This paper proposes a cutting-edge deep learning model designed to predict a wide range of emotions in users, such as Happiness, Anger, Calmness, and Surprise. The research started with a thorough survey, gathering feedback from 72 users regarding UI designs tailored to various emotions. Using these insights, interfaces were developed to address different emotional states. Following the design phase, a user interaction study was conducted involving 29 participants interacting with these interfaces while their facial expressions were recorded. Subsequently, a predictive model for user emotions was developed, achieving an accuracy of 83%, showcasing its robustness and reliability in discerning and predicting user emotions based on interactions with UIs. This model was seamlessly integrated into a proposed real-time adaptive UI system. Notably, existing literature has traditionally relied on pre-existing software for emotion detection in adaptive systems. Our contribution is to demonstrate an Emotional Interface Adaptation System that uses a trained model in real-world circumstances to provide a dynamic and responsive user experience that adapts in real-time to users’ emotional cues.

Paper Nr:	31
Title:	Design and Implementation of a Practice Record Visualization System Using Piano Performance Tracking Technology
Authors:	Haruna Mori, Mio Sasaki, Kaede Noto, Yoshinari Takegawa and Keiji Hirata
Abstract:	The purpose of this study is to develop a practice record visualization system using a piano performance tracking technology that utilizes gaze information. In general, piano lessons are held regularly, e.g., once a week, and the teacher observes the student’s skills at a fixed point. However, it can be difficult for the teacher to fully understand and address all areas how the student has practiced from the previous lesson to the current lesson and need improvement. This makes it difficult to provide appropriate guidance in lessons, such as determining whether students are too nervous to perform well in front of the teacher, or whether they are also unable to perform well in home practice. To solve this problem, we propose a performance tracking algorithm that can handle keystroke errors and replaying, and a system that visualizes the amount of practice and other practice progress. The proposed system visualizes the amount of practice and errors in various units, such as notes and measures. To verify the usefulness of the proposed system, we conducted an evaluation experiment comparing the case of using the proposed system and not using the proposed system.

Paper Nr:	47
Title:	Teaching LLMs the Nuances of Hospital Funding Instruments
Authors:	Tapio Pitkaranta
Abstract:	Recent advancements in large language models (LLMs) have sparked significant interest across a broad spectrum of use cases and business domains [12] [5] [2]. This paper delves into the application of LLMs in interpreting the complex logic of the hospital funding instru- ments such as the NordDRG system [3]. The integration of Large Language Models with the NordDRG specifi- cation offers significant advancements in leveraging artificial intelligence (AI) for healthcare management systems, particularly in the manage- ment and development of CaseMix systems. This paper evaluates the effectiveness of three distinct AI architectures—Custom GPT, Retrieval Augmented Generation (RAG), and Multi-Agent Systems (MAS)—in interpreting and responding to complex queries within the NordDRG framework. Our findings suggest that most current general LLMs, such as GPT-4, struggle to effectively handle the NordDRG logic. However, when LLMs are enhanced with Retrieval Augmented Generation (RAG) [6], the enhanced NordDRG AI agent is capable of engaging in natural language conversations with various stakeholders. Also, the introduction of the most advanced models, such as GPT-4o, reaches the same level of results as previous generation models with RAG. This paper provides a comparative analysis between the three AI design patterns. Such progress marks a significant stride in healthcare information systems, presenting a user- friendly interface for intricate medical coding systems. Our research makes a significant contribution by establishing the inaugural casemix benchmark dataset for evaluating large language model (LLM) capabilities using the NordDRG system. To the best of our knowledge, this is the first benchmark of its kind. Through rigorous testing across various real-world scenarios, we assess the adaptability, accuracy, and efficiency of these models in handling intricate healthcare data, aiming to streamline the decision-making pro- cess for healthcare providers and administrators. Our findings highlight the potential of LLMs to transform CaseMix system development by providing robust, scalable, and context-aware AI solutions.

Paper Nr:	67
Title:	Support for Dynamic Social Cooperation
Authors:	Pascal Francois Faye, Jeanne Ana Awa Faye and Mariane Senghor
Abstract:	In developing countries, agriculture is a means of development. Several structures are set up as cooperative, economic interest group, etc. However, these structures have very little interdependency that can allow them to go beyond their limits such as access to finance, access to national and international markets, etc. This raises new challenges of collaboration between structures that we can consider each structure as a coalition. This work provides a coalition's migration (dynamic merging and splitting coalition) mechanism that allows the emergence and maintenance of stable coalitions of self-interested agents in unstable and uncertainty context. Specifically, we assume uncertainties regarding task interaction, agent and resource availability, and interdependencies among agents, resources and tasks. We address the case in which agent and environment inherent uncertainties prohibit the computation of coalition stability ahead of stochastic task execution. Facing such uncertainties, we propose a core-stable, auto-stabilizing anytime coalition formation mechanism which we denote as DMS (Dynamic Merging and Splitting) mechanism. The mechanism arrives at a stability, maximizes social welfare, and converges gradually to near optimal results. DMS combines game theory methods and the laws of probability. Our experiments and their analysis demonstrate the efficiency of DMS.

Paper Nr:	69
Title:	Managing Classified Information by a Third-Party Contractor: A Computational Cybersecurity Analysis
Authors:	Sebastiaan Keijzer, Daan Lochtenbergh, Thom Marsman, Sam Voorhoeve, Natalia Zwarts, Debby Bouma, Jan Treur and Peter H. M. P. Roelofsma
Abstract:	In this paper, a computational analysis is contributed of the process of a third-party contractor being contracted by a governmental body to store classified documentation. The several steps to complete this process are modeled in a network-oriented manner including contractualization and deployment of suppressing risk measures to mitigate the risks and limit the damages potentially caused by the compromise of these documents. What-If analysis has been performed for the simulation experimental setup.

Area 3 - Human Factors for Interactive Systems, Research, and Applications

Full Papers

Paper Nr:	13
Title:	How Different Blink Patterns of Pet Robots Evoke Feelings of Affection in People
Authors:	Junko Ichino
Abstract:	An alternative to animals, which bring various benefits to people but are not al-ways easy to own, is pet robots, whose central role is to communicate with peo-ple. However, there is insufficient research on how pet robots should behave to evoke feelings of affection in people. We focused on blinking as one of the be-haviors of the eye and investigated what type of pet robot blinking pattern evokes more feelings of affection in people. First, we designed seven different blink pat-terns combining short and long blinks through a pilot study. We then conducted a study with 15 participants to compare the patterns using a paired comparison method. The results showed that the blink patterns that were more likely to evoke affection were those with consecutive short eye closures (three times rather than two), whereas the blink patterns that were less likely to evoke affection were those with several long eye closures.

Paper Nr:	18
Title:	Towards Multi-Stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-Matching System
Authors:	Takuya Yokota and Yuri Nakao
Abstract:	While machine learning (ML) technology affects diverse stakeholders, there is no one-size-fits-all metric to evaluate the quality of outputs, including performance and fairness. Using predetermined metrics without soliciting stakeholder opinions is problematic because it leads to an unfair disregard for stakeholders in the ML pipeline. In this study, to establish practical ways to incorporate diverse stakeholder opinions into the selection of metrics for ML, we investigate participants’ preferences for different metrics by using crowdsourcing. We ask 837 participants to choose a better model from two hypothetical ML models in a hypothetical job-matching system twenty times and calculate their utility values for seven metrics. To examine the participants’ feedback in detail, we divide them into five clusters based on their utility values and analyze the tendencies of each cluster, including their preferences for metrics and common attributes. Based on the results, we discuss the points that should be considered when selecting appropriate metrics and evaluating ML models with multiple stakeholders

Paper Nr:	27
Title:	Evaluating Remote Communication Applications Using Student Usability Reviews
Authors:	Alecsandru Grigoriu
Abstract:	The paper investigates and assesses the user interface design of wellknown remote communication applications (e.g., Zoom, Microsoft Teams, Google Meet) for improved user experience and interaction. University students evaluate the applications as part of a series of creative challenges, covering important HCI (Human-Computer Interaction) aspects such as existing affordances, visual variables, or interaction flows. The study contributes to an already-established literature review of the uses and effects of video-conferencing tools during and after the COVID-19 pandemic. With volunteer students as participants, they offer a new perspective for the research by acting both as users and evaluators. The study consisted of two connected experiments between early 2023 and 2024, learning and improving with each iteration transitioning from an ad-hoc qualitative-focus approach to a well-defined quantitative-centered tactic. The results for the first experiment showed that the participants preferred Zoom, Discord, and Webex as the top three choices out of nine distinct alternatives. The second experiment positioned Discord as the most advantageous of the final three—the application dominated with a Mean SUS (System Usability Scale) score of 77.42, and ranked first in six out of eight criteria (and one tie) using a custom rating scale

Paper Nr:	36
Title:	User Experience and Information Security Heuristics for Digital Identity Wallets
Authors:	Max Sauer, Christoph Becker, Andreas Oberweis, Sabine Schork and Jan Sürmeli
Abstract:	In digital identity wallets, users can store and manage their digital identities and verification documents such as driving licences and membership cards. Current digital identity wallets face notable challenges in user experience and information security. Users struggle to understand the concept of digital identity wallets, resulting in personal information being either inadequately stored or inadvertently shared with untrustworthy parties. Thus, digital identity wallets should provide a sufficient level of user experience and information security. For evaluating and improving user experience and information security, heuristics can be used to check the degree of fulfilment for each heuristic and to improve digital identity wallets according to the respective heuristics. This paper reports on the development and evaluation of user experience and information security heuristics for digital identity wallets. To this end, an existing method for user experience heuristics was adapted to also cover information security heuristics. As particular evaluation methods, expert interviews and heuristic evaluations were applied. In total, twelve user experience and six information security heuristics were developed and evaluated.

Paper Nr:	39
Title:	An Assistive System for Non-Vocal Patients in Intensive Care Units
Authors:	Jan Patrick Kopetz, Börge Kordts, Tim Schrills and Nicole Jochems
Abstract:	Critical care patients in intensive care units often require mechanical ventilation. This intervention usually involves a loss of the patient’s verbal communication for the duration of the ventilation. The weaning process from ventilation, in particular, causes increased stress. This significantly challenges patients and all others involved in the recovery process. Augmentative and Alternative Communication concepts may offer various options to mitigate this limitation. A novel assistive system for communication, information, and control, based on a ball-shaped interaction device, was designed to meet the needs of these weaning patients. To examine the maturity of the prototype before clinical trials, it was evaluated in a laboratory usability study with healthy elderly adults (N=22) regarding the learnability of the interaction, suitability for communication purposes, and the overall user experience. The results indicated that participants quickly learned the interaction and could successfully use the system as intended. This provides a solid foundation for a comprehensive field study with the weaning patient population.

Paper Nr:	62
Title:	AI and Digital Nomads: Glimpsing the Future Human-Computer Interaction
Authors:	Marcos Antonio de Almeida, António Correia, Carlos Eduardo Barbosa, Jano Moreira de Souza and Daniel Schneider
Abstract:	Amid pandemic lockdowns, digital nomads exhibit remarkable resilience and adaptability, showcasing the evolving dynamics of remote work. As Artificial Intelligence (AI) intersects with digital nomadism, it offers profound insights into the future of work, transcending geographical borders and reshaping traditional workplace norms. Leveraging the Gioia methodology, this work discusses how digital nomads integrate AI into their work and lifestyles, navigate concerns about the job market, and seize AI-related employment opportunities. The findings underscore digital nomads’ frequent use of pivoting as a resilience strategy in response to AI disruptions in niche businesses or professional careers, alongside widespread adoption of AI tools for personal use, meeting practical and strategic needs. This research contributes to the existing literature by effectively aligning emerging concepts with the theoretical framework of digital nomadism, offering valuable insights into the interests and behaviors of stakeholders within the ecosystem supporting digital nomad activities.

Paper Nr:	66
Title:	Negotiating with LLMs: Prompt Hacks, Skill Gaps, and Reasoning Deficits
Authors:	Johannes Schneider, Steffi Haag and Leona Chandra-Kruse
Abstract:	Large language models (LLMs) like ChatGPT have reached the 100 Mio. user barrier in record time and might increasingly enter all areas of our life leading to a diverse set of interactions between those Artificial Intelligence models and humans. While many studies have discussed governance and regulations deductively from first order principles, few studies provide an inductive, data-driven lens based on observing dialogues between humans and LLMs – especially, when it comes to non-collaborative, competitive situations that have the potential to pose a serious threat for people. In this work, we conduct a user study engaging over 40 individuals across all age groups in price negotiations with an LLM. We explore how people interact with an LLM, investigating differences in negotiation outcomes and strategies. Furthermore, we highlight shortcomings of LLMs with respect to their reasoning capabilities and, in turn, susceptiveness to prompt hacking, which intends to manipulate the LLM to make agreements that are against its instructions or beyond any rationality. We also show that the negotiated prices humans manage to achieve span a broad range, which points to a literacy gap in effectively interacting with LLMs.

Paper Nr:	77
Title:	Generation Gap or Diffusion Trap? How Age Affects the Detection of Personalized AI-Generated Images
Authors:	René Lüdemann, Alexander Schulz and Ulrike Kuhl
Abstract:	AI-generated content, particularly artificially generated image data, presents a fascinating challenge as it blurs the line between reality and fabrication in digital media. This study explores the ability of different age groups to distinguish between real and AI-generated images, using a custom model based on Stable Diffusion to create personalized synthetic images of the same individual. Participants (N=112) showed an overall accuracy of 87.01%, with younger individuals outperforming older ones in both detection accuracy and confidence. Older participants also took longer to make their decisions, indicating either an age-related decline in processing speed, or a more careful and deliberate analysis of the presented content. These findings highlight the importance of improving digital literacy across age groups and developing robust detection tools to better equip users to navigate an increasingly AI-driven digital landscape. In the interest of reproducible research, the entire code, images, and data is available at: https://github.com/ukuhl/GenGapCHIRA2024

Short Papers

Paper Nr:	17
Title:	An Experiment to Investigate Changes in Physiological Signals During Subtle Wind and Scent Presentation for Designing Subtle Notifications
Authors:	Masaki Omata and Takumi Shioda
Abstract:	Notifications for visual and auditory modalities from smart phone have some problems. For the visual modality, the user needs to actively control his or her viewpoint toward the phone. For the auditory modality, the user may not hear the notification sound because it is drowned out by surrounding sound. As a solution to the problems, we have proposed a subtle notification system that uses wind and scent to notify users of less important notifications and identify the user’s awareness of the notification based on changes in the user’s physiological sig-nals. In this paper, we conducted an experiment to measure and analyze physio-logical signals when subtle wind and scent stimuli were presented to participants performing a reading task, in order to design the proposed system. The results show that the wind stimulus caused a change in skin conductance and the scent stimulus caused a change in the amplitude of respiratory movement. This suggest that even such weak and invisible stimuli are noticed by a user performing a task and are reflected in the user’s physiological responses.

Paper Nr:	24
Title:	Why Do(n’t) You Trust Us? Highlighting the Importance of Trust and Transparency for Designing B2B Platforms in Electronics Manufacturing
Authors:	Rafael Vrecar, Astrid Weiss, Wilfried Lepuschitz, Aaron Wedral and Michaela Gaea Čolakovová
Abstract:	As online platforms have become increasingly important in the last decade, it also makes sense to conduct B2B (Business to Business) operations on online platforms. This paper deals with the aspects of trust and transparency in a B2B context, specifically in the development (and operation) of a platform where microelectronics manufacturers are connected with customers who want to produce a certain (part of a) product and find the best company to do so. The methods used were workshops with different stakeholder groups and expert reviews of the user interfaces of the platform under development. Our findings include that transparency and the power/freedom to do and undo actions within such a platform are essential for potential users as well as the care for their intellectual property. Additionally, we identified pitfalls in the current design which could reduce trust, e.g., as in our context, inconsistency regarding error messages.

Paper Nr:	30
Title:	The Effect of Progressive Disclosure in the Transparency of Large Language Models
Authors:	Deepa Muralidhar, Rafik Belloum, Kathia Marçal de Oliveira, Ashwin Ashok and Pardaz Banu Mohammad
Abstract:	Recent advances in artificial intelligence (AI) text generation systems have resulted in their ability to provide precise recommendations in response to users’ questions (prompts). However AI models often operate as black boxes, making it challenging for users to comprehend their inner workings. The transparency of these models is crucial for users to gain a better understanding of how AI systems function. While the Human-Computer Interaction (HCI) community has advocated for design principles like progressive disclosure to improve transparency, we still lack empirical evidence validating its efficacy for AI systems, especially in the context of LLM-based text generation. Addressing this gap, this paper presents a user study with 30 participants aimed at investigating the effect of progressive disclosure and adjusting the explanations so as to adapt to users’ mental models for improving the transparency of AI text generation systems. The findings suggest that users prefer on-demand explanations and value diverse explanation methods, especially when the explanations gradually give the users a better understanding of the AI system. Additionally, qualitative data shows a marginal preference for word clouds over keyword highlighting. User feedback indicates that explanations such as word-pair cosine values, which leverage the interpretability of AI models, are less suitable for lay users. Altering the visual presentation of these word-pair cosine values from a table of numbers to a bar graph did not increase user satisfaction with this explanation technique.

Paper Nr:	38
Title:	Evaluating Immersion in Digital Video Using EEG and Subjective Measures: A Pilot Study
Authors:	Ioannis Doumanis, Daphne Economou and Konstantinos Tsioutas
Abstract:	Immersion in digital video refers to the degree to which digital content engages and absorbs viewers. Today, viewers primarily consume digital video online. De-spite ample bandwidth availability, network disruptions (e.g., congestion and out-ages) can degrade quality and interrupt the viewing experience, thereby breaking immersion. In a pilot study, we evaluated viewer immersion while watching digi-tal video content on two streaming services (IPTV and HLS) delivered via con-ventional IP and our POINT network under regular and exceptional network conditions (congestion and link failures). We used Electroencephalography (EEG) and user interviews to gather data. EEG data indicate that videos streamed through POINT create a more immersive experience in terms of presence, senso-ry engagement, realism, and detail compared to conventional IP, although the im-pact varies by service. Interview data corroborate the EEG measures but indicate that POINT’s impact was independent of the specific service used (IPTV or HLS). These findings suggest that POINT enhances viewer immersion over tra-ditional IP networks, particularly under challenging network conditions, but the impact may be service-specific. We plan to conduct a follow-up study with a larger user group and incorporate additional sensors (emotion analysis and eye-tracking) to more comprehensively measure viewers’ emotional and cognitive states under each experimental condition.

Paper Nr:	40
Title:	Strategies and Tools to Support Place-Belongingness in Smart Cities
Authors:	Hesam Mohseni, António Correia, Johanna Silvennoinen, Tuomo Kujala and Tommi Kärkkäinen
Abstract:	Smart cities have the potential to reduce socio-spatial barriers and foster place-belongingness among citizens. However, this potential remains largely unmapped. We conducted a literature review to address this gap. Our findings suggest that promoting inclusive dynamics and emphasizing urban identity are key strategies for supporting place-belongingness in smart cities. Additionally, digital platforms and information and communication technologies (ICTs), gamification, crowdsensing, urban heritage technologies, and digital placemaking are the most popular digital tools used to achieve this. This literature review indicates that place-belongingness is underexplored in smart city studies, and further research is needed to fully understand the potential of smart cities to support place-belongingness.

Paper Nr:	50
Title:	Poor Handwriting in Children with and Without DCD: Exploring the Relationship Between Product and Process Characteristics
Authors:	Elisa De Francesco, Giuliana Lentini, Barbara Caravale and Carlo Di Brina
Abstract:	Poor handwriting is a common issue in the general school population, particularly among children with developmental coordination disorder (DCD) [1]. A compre-hensive handwriting assessment could combine traditional paper-and-pencil methods with computer-based analyses that objectively evaluate factors such as writing speed, pressure, and letter height. However, the literature provides mixed evidence on the relationship between these process-based factors and handwriting legibility [2; 3]. This study explores the relationship between selected process-based factors and traditional product-based measures of handwriting quality in children with DCD and typically developing (TD) children. We evaluated 96 typically developing children (mean age: 113.64 months, SD: 7.68) and 22 children with DCD (mean age: 110.28 months, SD: 9.12) from the 3rd and 4th grades, matched by age. Traditional product-based handwriting assessments, including the BHK (which evaluates legibility and speed) and the VMI (which assesses visual-motor integration), were conducted. These were compared with computer-based measures of the handwriting process, including writing velocity (V), axial pen pressure (APP), and letter height (LH). The tasks involved three handwriting ex-ercises (repeating letters under normal, fast, and accurate conditions) and two drawing exercises (repeating wheels and eggs). In nearly all tasks, we observed a moderate positive correlation between BHK legibility scores and two process-based variables: V and LH. No significant cor-relation was found between legibility and APP. Our preliminary results suggest that higher writing velocity and larger letter dimensions may serve as key indicators for identifying poor handwriting. These findings underscore the importance of further investigation into letter dimension analysis in both children with DCD and typically developing populations.

Paper Nr:	51
Title:	Computational Analysis of Disruptions of Mobile Networks During Wartime: an Adaptive Network Modeling Approach
Authors:	Jakailah Bart, Shadira Milani, Senja Raïkkönen, Darja Sultani, Femke van ‘t Hoff, Natalia Zwarts, Charlotte Hoffmans, Jan Treur and Peter H. M. P. Roelofsma
Abstract:	This study presents an analysis of a cyber-attack scenario targeting the Ukrainian telecommunications network, with SandWorm identified as the threat actor. Through meticulous model development, the dynamics of the scenario are ex-plored, highlighting cause-and-effect relationships between different states over time. A What-If analysis is conducted to assess the impact of changing certain factors, leading to insights into potential outcomes and risk assessment. The study concludes with reflections on its implications for understanding cybersecu-rity risks and network adaptability.

Paper Nr:	53
Title:	The Delicate Balance of Ethics and Control for Smart Cities: A Network-Oriented Analysis Approach
Authors:	Moaz Daza, Doris Duivesteijn, Maria Jouma, Florian Reichardt, Nick Barelds, Debby Bouma, Jan Treur and Peter H. M. P. Roelofsma
Abstract:	This paper focuses on the complex interplay between personal privacy, techno-logical monitoring, and government response in a healthcare scenario. A patient's journey illustrates the dynamic relationship between these elements and reveals significant insights into how privacy concerns can shape public satisfaction and governmental actions. This is analysed computationally using a designed adaptive network model.

Paper Nr:	58
Title:	IRIS: A Prototype for GDPR Health Research Compliance
Authors:	Liliana Ferreira, Teresa Martins, Emanuel Dias and Ana Ferreira
Abstract:	The aim of this study is to present the research and development regarding the implementation of a high-fidelity prototype of a recommendation platform (IRIS) for compliance of health projects with GDPR. Findings from our user research corroborate current literature insights that health researchers are concerned in keeping personal and sensitive data processing private and secure, while manag-ing their research project. Participants also agree on the complexity and impact of implementing GDPR compliance in practice, and the need for support and guid-ance, preferably with the use of interactive/dynamic tools that can help them dur-ing the whole process. Findings from the user centered design guided the creation of the IRIS prototype, which was tested in two iterations for its usability, interac-tion experience and satisfaction. IRIS has been positively assessed and sets the ground to integrate more complex, intelligent and interactive features. IRIS aims to become a free and adaptable tool for health projects to comply with the various personal data privacy requirements that researchers face every day.

Paper Nr:	79
Title:	Assessment of Dance Movement Therapy Outcomes: A Preliminary Proposal
Authors:	Said Daoudagh, Giacomo Ignesti, Davide Moroni, Laura Sebastiani and Paolo Paradisi
Abstract:	Context: Dance Movement Therapy (DMT) is a therapeutic modality that utilizes movement to promote holistic well-being. Current DMT assessment methods rely heavily on the subjective judgment of the DMT professional. Objective: Our research aims to develop a framework composed of different components with specific functionalities that can be integrated with the DMT modality to improve the objectivity and efficiency of DMT evaluations. Method: The DMT framework consists of an experimental protocol for data collection and a reference-supporting architecture that includes components for video analysis, physiological signal management, and evaluation tools. Artificial Intelligence (AI) based human pose estimation techniques are also employed to derive the DMT participants’ poses during the DMT sessions for more reliable movement analysis. Results: Our preliminary results consist of demonstrating the effectiveness of the AI-based pose estimation tool, YOLO-NAS-Pose, in accurately detecting participants’ poses. Conclusion: The proposed framework offers a promising approach to improving DMT practices by integrating and leveraging AI-based human pose estimation to evaluate participants’ movement in the DMT setting objectively. Future research will focus on refining the framework and developing user-friendly tools for widespread adoption in real DMT contexts.

Paper Nr:	80
Title:	User Perception of Ontology-Based Explanations of AI Models
Authors:	Anton Agafonov, Andrew Ponomarev and Alexander Smirnov
Abstract:	For using AI models in high-stake applications it is crucial for a decision maker to understand why the model came to a certain conclusion. Ontology-based explanation techniques of artificial neural networks aim to provide explanations adapted to domain vocabulary (which is encoded using ontology) in order to make them easier to interpret and reason about. However, few studies actually explore the perception of ontology-based explanations and their effectiveness with respect to more common explanation techniques for neural networks (e.g., LIME, GradCAM, etc.). The paper proposes two benchmark datasets with different task representations (tabular and graph) and a methodology to compare users' effectiveness of processing explanations, employing both objective (decision time, accuracy) and subjective metrics. The methodology and datasets were then used in a user study to compare several explanation representations (non-ontology-based, textual representation of ontological inference, inference graph). It was found that according to subjective evaluation, graph and textual explanations caused the least difficulty for the participants. Objective metrics vary with the size of the ontology, but inference graphs show good results in all the examined cases. Surprisingly, non-ontology-based explanations have almost the same positive effect on decision-making than ontology-based (although, a bit harder subjectively).

Paper Nr:	32
Title:	User Issues and Concerns in Generative AI: A Mixed-Methods Analysis of App Reviews
Authors:	Vanessa Bracamonte, Sascha Loebner, Frederic Tronnier, Ann-Kristin Lieberknecht and Sebastian Pape
Abstract:	Generative AI models such as ChatGPT and Stable Diffusion have become easily available to end users through various apps. Research has identified several safety risks and limitations of generative AI, but the experiences and issues faced by real users of this technology in the wild have not been systematically investigated. In this paper, we identify user issues related to trustworthiness dimensions of generative AI, by analyzing user reviews of AI apps using a hybrid approach that combines unsupervised topic modeling and manual qualitative analysis. The results revealed user issues related to the validity, reliability, safety, security and privacy of the AI. Validity-related issues, such as incorrect output, were often found, but these issues appeared to result from high expectations about the capabilities of the technology, rather than an accurate reflection of its limitations. Concerns about safety issues, such as bias and the handling of inappropriate content, also appeared frequently, although users had conflicting expectations on how these should be handled. On the other hand, the user reviews contained fewer instances of concern related to the security and privacy of the AI itself. Overall, the results suggest that real users of generative AI have inadequate information about the characteristics and limitations of these models.

Paper Nr:	45
Title:	Virtualization of the Human Body: Deep-Fake Pornography - Its Ethical and Political Implications
Authors:	Maria Cernat, Dumitru Borţun and Corina Matei
Abstract:	In June 2019, a programmer released an app that enabled users to digitally undress individuals in photographs. Shortly after its launch, the publication Vice reported that the programmer withdrew the application due to concerns about the potential negative consequences of its use. Nevertheless, within a few days, the app was downloaded by over 95,000 users. Deep Nude is among several applications that generate highly realistic imitations of a person's voice or body. These technological advancements do not alter prevailing social norms of patriarchy, as demonstrated by Deep Nude's initial focus on photos of women; the program would utilize neural networks to fabricate intimate body parts when presented with images of men. In the context of modern technology, women’s bodies have become commodified images that can be weaponized against them. Feminist activists argue that while politicians express concern over the censorship of misleading political information, the most vulnerable victims of deepfake technology remain women. We contend that the most effective approach to assessing the implications of this phenomenon is through a political economy lens, specifically examining the processes of producing, distributing, and consuming deepfake pornography. Additionally, it is crucial to recognize that the conception of cyberspace as a libertarian utopia contributes significantly to the challenges authorities encounter in their efforts to protect potential victims from this form of gendered violence.

Paper Nr:	57
Title:	User Experience In Dataset Search
Authors:	Yihang Zhao, Albert Meroño-Peñuela and Elena Simperl
Abstract:	This research investigates User Experience (UX) issues in dataset search, targeting Google Dataset Search and data.europa.eu. It focuses on 6 areas within UX: Initial Interaction, Search Process, Dataset Exploration, Filtering and Sorting, Dataset Actions, and Assistance and Feedback. The evaluation method combines 'The Pandemic Puzzle' user task, think-aloud methods, and demographic and post-task questionnaires. 29 strengths and 63 weaknesses were collected from 19 participants involved in roles within technology firm or academia. While certain insights are specific to particular platforms, most are derived from features commonly observed in dataset search platforms across a variety of fields, implying that our findings are broadly applicable. Observations from commonly found features in dataset search platforms across various fields have led to the development of 10 new design prototypes. Unlike literature retrieval, dataset retrieval involves a significant focus on metadata accessibility and quality, each element of which can impact decision-making. To address issues like reading fatigue from metadata presentation, inefficient methods for results searching, filtering, and selection, along with other unresolved user-centric issues on current platforms. These prototypes concentrate on enhancing metadata-related features. They include a redesigned homepage, an improved search bar, better sorting options, an enhanced search result display, a metadata comparison tool, and a navigation guide. Our aim is to improve usability for a wide range of users, including both developers and researchers.

Paper Nr:	59
Title:	HCI: Research into the Effects XR has on Users, an Exploratory Study (tested with a Native visionOS app, on Apple Vision Pro)
Authors:	Panagiotis-Efstratios Chontas, Adrian Iftene and Sabin-Corneliu Buraga
Abstract:	Recent increases in XR headset sales suggest a growing consumer preference for AR/VR in home and institutional environments. As XR technology becomes mainstream and evolves, it is essential to examine its physical and mental impacts. While recent studies emphasize the positive effects of XR, this paper argues for investigating potential negative outcomes to ensure user well-being and ethical standards. This study involved young adults (ages 18-29) using the Apple Vision Pro headset within a visionOS environment, designed to encompass a range of user interactions. Questionnaires and health tests were conducted to evaluate participants. Findings indicate users’ adeptness in interacting with XR technologies, particularly favoring experiences that simulate real-life environments in three dimensions. However, despite their familiarity with technology and extensive screen time, young adults experienced physical side effects early in the testing process. This research underscores the necessity of a balanced understanding of XR’s implications to guide its development responsibly.

Paper Nr:	64
Title:	User-Centered-Development: A Hackathon for Bridging Engineering and Design Disciplines
Authors:	Adi Katz and Hadas Chassidim
Abstract:	This paper presents a collaborative hackathon initiative between the Software Engineering (SE) and Visual Communication (VC) departments at an academic engineering college. The hackathon brought together students from "Software Project Management" and "User Experience and Cognition" courses, working in agile development teams to bridge the gap between technical and design focuses. By fostering active learning and simulating real-world digital system development, the hackathon allowed SE students to apply their technical expertise while learning design thinking and usability principles. VC students gained experience translating technical requirements into visually compelling designs. This collaboration facilitated a deeper understanding of user-centered design and the software agile development process, promoting critical thinking and creativity aligned with Bloom's highest learning levels: analyzing, evaluating, and creating. Student feedback reflected a mix of positive insights and constructive criticism, emphasizing the value of interdisciplinary collaboration in enhancing user experience while identifying areas for improvement, such as feedback clarity and the need for better time management during the hackathon. The study’s approach mirrors key aspects of professional environments, preparing students to tackle the real-world challenges they will encounter after graduation.

Area 4 - Interaction Design

Full Papers

Paper Nr:	16
Title:	Interviewing ChatGPT-Generated Personas to Inform Design Decisions
Authors:	Jemily Rime
Abstract:	This paper uses the example of the development of a new podcast production tool to pinpoint some of the successes and limitations of relying on Large Language Models (LLMs) to assist software developers in User-centred design (UCD) methods. We ask ChatGPT to create 16 personas of podcast creators and answer in character to a set of questions that was asked to 16 human creators to gather design feedback, in order to make a new podcasting tool. From this comparison, we discover that the personas generated are credible, but expose some data-privacy issues, and confirm the skewed, incomplete, nature of ChatGPT’s training dataset. We find a correlation between a generated persona and its answers, and that its role-playing could be valuable but lacks the more extreme, or clear-cut opinions, often most helpful when gathering user opinions for development. From the lessons learned through this comparative exercise, we share recommendations regarding the possible uses of LLMs in UCD.

Paper Nr:	76
Title:	Effective Nudging in Digital Environments
Authors:	Synne Storhaug, Siri Fagernes and Pietro Murano
Abstract:	This research investigates the user experience of receiving digital nudges. The nudges were designed as being either gain-framed or loss-framed, informing users of the benefits of exercise and were sent as push notifications in a fitness app. Qualitative data from semi-structured interviews were analysed using a thematic analysis. The overall results suggest that nudges via push notifications are well-accepted by users, particularly if trustworthy, short, easy to read and well-timed. Differences in opinion between gain-framed or loss-framed nudges were not strong. However, those who did express a dislike for loss-framed nudges tended to do so strongly. This paper is novel and useful to designers of digital nudges as our results can inform designers of best practices. To the best of our knowledge, there are a lack of studies that actually carry out the design, implementation and evaluation of digital nudging interventions (by its true forms), with the aim of understanding users’ perception and experience of digital nudging. Further, as far as we have been able to ascertain, a systematic qualitative study of the user experience of digital nudges using push notifications has not been done until now.

Short Papers

Paper Nr:	21
Title:	Current Design Practices in Applied Augmented Reality Research
Authors:	Lukas D. Teutenberg, Lukas R. G. Fitz and Jochen Scheeg
Abstract:	Successful Augmented Reality (AR) solutions require high technology ac-ceptance and desire among users. Applying appropriate design methodologies can enhance the development of desirable AR systems and help to streamline de-sign research projects. This article presents a methodological literature review of 58 pertinent articles, exploring the representation of methodological design frameworks in currently applied AR research practice. In result, User-Centered Design was identified most frequently by a large margin. Though, it could be ob-served that most articles from the field of applied AR only marginally describe any design processes. Moreover, Human-Centered Design, Participatory Design and Value Sensitive Design were only scantily represented; less than half of the papers followed a Design Science Research or Action Design Research approach. Several implications for applied research and practice are derived from these findings and discussed together with future research opportunities. Overall, this study contributes to the refinement of methodological design practice in the field of applied AR research.

Paper Nr:	26
Title:	Enriched with Behaviour Theory Topic Guide Template for Digital Behaviour Change Interventions
Authors:	Farhat-ul-Ain, Kelly Toom and Vladimir Tomberg
Abstract:	Interviews and focus groups are interaction design user research methods that aim to understand user needs and goals regarding the potential use of digital products. In the case of designing Digital Behaviour Change Interventions (DBCIs) for health, these methods need to be adjusted to allow explicit focus on understanding determinants that possibly influence individual health-related be-haviours (for example, beliefs, motivations, social pressure). Behaviour change theories and models help to identify these determinants of influencing behaviours. However, interaction designers are not competent in having knowledge of behav-iour change theories, which makes it difficult to integrate this knowledge into in-teraction design user research. It can limit the design for theory-based DBCIs. The current study proposed and evaluated a generic topic guide template for inter-action design user research enriched with a behaviour change theory. The paper proposes guidelines for adapting and analysing the data. The proposed topic guide template was adapted to understand the needs and age-related differences of children with type I diabetes. Focus groups were conducted with parents and medical professionals. Results indicated various behaviour change-related needs of the children and highlighted age-related differences in children's skills, independence, and motivation to manage diabetes. Various behaviour change theory-based design implications for interaction design were derived. The results high-light the importance of enriching the user research methods with behaviour change theories and models for designing DBCIs for health.

Paper Nr:	29
Title:	Systematic Literature Review of Gamification Design in Higher Education Programming Courses: Methodological Rigor Exposed
Authors:	Marisa Venter and Lizette De Wet
Abstract:	A significant increase has been noted in the application of gamification design in-terventions in programming education, which sparked enthusiasm in students and enhanced their levels of enjoyment and engagement, while improving learning outcomes. By utilizing gamified learning activities and software applications, in-structors can develop learning environments which greatly enhance the experi-ences of student interaction in gamified learning environments. Positive reported experiences of students in higher education programming learning environments, promise to steer students towards achievement in their programming pursuits. However, it is not clear if these positive reports might be inaccurate due to vari-ous inadequacies in research methodologies used in studies conducted in a gami-fied programming learning higher education context. To date, no systematic re-view has focused specifically on the methodological rigor of studies that investi-gated the gamification of higher education programming courses. The systematic literature review reported by this study, fills this gap, by exposing various meth-odological shortcomings observed in the reviewed literature. The study provides recommendations to researchers to improve research efforts in the future. The hope is that these guidelines will contribute to enhancing the overall quality and reliability of research findings related to the gamification of higher education pro-gramming courses.

Paper Nr:	37
Title:	Supporting Behaviour Change Techniques with Interaction Design Patterns
Authors:	Farhat-ul-Ain, Olga Popovits, Gulassyl Amirgaliyeva and Vladimir Tomberg
Abstract:	Design patterns provide a structured method for addressing common design problems by offering proven solutions that can be reused across different con-texts. In the case of designing digital behaviour change interventions, interaction designers may face challenges in translating Behaviour Change Techniques (BCTs) knowledge into digital interventions. Interaction design patterns for BCTs can help overcome this challenge by providing descriptions, examples, rationale for using BCTs, and proven solutions. The current study examines six patterns for commonly used BCTs in digital interventions (reminder, social sup-port, goal setting, self-monitoring, and instruction on performing behaviour and feedback on behaviour). The proposed design patterns were evaluated by four interaction design experts. They found the descriptions and examples provided in the design patterns to be clear and comprehensible. The experts appreciated the balance between concreteness and abstractness. The resulting design patterns can contribute to the informed design of digital behaviour change interventions and are helpful for designers, developers, researchers and product managers. Experts suggested that the language of the design patterns needs to be simplified for industry professionals to ensure that they can understand and apply them. Experts also indicated the need for shorter versions of the patterns, such as plain summaries or mind maps. Future design efforts to refine and simplify the proposed patterns and to develop additional patterns covering a broader range of BCTs are required.

Paper Nr:	43
Title:	How Can Heuristics Be Communicated?
Authors:	Isabel Evans, Chris Porter and Mark Micallef
Abstract:	This position paper proposes a model for choosing how to communicate heuristics in a meaningful, usable and accessible manner. The model is a matrix of nine shapes, where we define `shape' as a combination of the heuristic's format and its directiveness. Examining heuristics used in UX and software testing practices, we found a variety of formats and levels of directiveness. We discuss these shapes with example heuristics from UX, software testing, and everyday life. We present the outcome from a pilot of how the model could be used in one specific context. The shape of a heuristic contributes to its understandability and usefulness in specific contexts, while different contexts may necessitate different ways of communicating heuristics. This includes considering the effect that the shape of a heuristic has on its accessibility and inclusion, and we suggest that shape is therefore one important aspect of heuristics' design and evaluation.

Paper Nr:	63
Title:	From Zero to Hero: When a Simple Line Can Make All the Difference
Authors:	Kai Marquardt, Elias Kia, Anne Koziolek and Lucia Happe
Abstract:	Online platforms with automated feedback mechanisms offer a solution, ensuring all students receive timely and scalable feedback. Despite their potential, studies specifically assessing the impact of different feedback types in online learning environments are limited. This work-in-progress study addresses this gap by exploring the use of progress bars as a feedback tool in educational online courses. Through a pilot case-control study involving 21 students, we aim to evaluate the potential of progress bars to improve student motivation and engagement. Our findings indicate the potential of progress bars in educational online courses to enhance the learning experience by providing a clear visualization of progress, fostering a sense of accomplishment, and motivating students to complete tasks. These insights underscore the importance of integrating progress bars into online learning platforms, highlighting their untapped potential to enrich educational outcomes. By laying the groundwork for further exploration, this research advocates for the broader adoption of simple yet effective feedback mechanisms, ultimately aiming to enhance online education and benefit both students and educators

Paper Nr:	11
Title:	Systematic Integration of Design Prototypes into the LMS: Methods and Challenges in Practice
Authors:	Thorleif Harder, Gilbert Drzyzga, Jan-Marco Bruhns and Anna-Lena Langhans
Abstract:	Digitization has a central role to play in the ever-changing educational landscape, with learning management systems (LMS) such as Moodle becoming increasingly important. The integration of user-centered design prototypes into such systems is a significant challenge, particularly due to technical limitations and the need to maintain a high level of usability. This paper discusses a methodologically based approach, developed on the basis of a research project, to effectively transfer design prototypes into a functional Moodle plugin. Technical and design challenges are addressed through iterative development and the continuous involvement of students. The results show the various challenges of integrating design prototypes into the LMS Moodle, especially when adapting cascading style sheets (CSS) styling and structuring modular templates. It is also shown that the handling of dynamic content and visualization problems are crucial factors for effective implementation. Based on these findings, best practices were developed that emphasize the adaptation of design prototypes to technical environments and proactive adaptation to dynamic content. These practices provide valuable guidelines for developing LMS plugins that are not only technically functional, but also useable and adapted to specific learning needs.

Paper Nr:	12
Title:	Towards Augmenting Human-Centred Design: Generative AI Tools for Interaction Research and Design
Authors:	Tom Gross
Abstract:	Generative AI tools are hailed as a motor for revolutionising our work and life. Recently, tools based on large language and foundation models, such as ChatGPT, have also become a hot topic in interaction research and interaction de-sign. This paper contributes a discussion of whether and how Generative AI tools can be used to augment interaction research and interaction design through-out the whole process of Human-Centred Design for Interactive Systems as de-fined by the International Organization for Standardization. The paper compiles an extended, up-to-date version of the process model covering highly relevant additions of methods bridging the gap between interaction research and interac-tion design in each of the processes. It then suggests Generative AI tools to sup-port those methods. Finally, it discusses vital aspects of interaction research and interaction design concerning the current design practice, the respective design situation, and the design circumstances at large.

Paper Nr:	54
Title:	Design and Evaluation of the UI/UX of GAmified LEarning Design Editor (GALEDE)
Authors:	Jihed Hammami, Maha Khemaja and José-Luis Sierra-Rodríguez
Abstract:	This paper is focused on the UI/UX aspects of the graphical learning design au-thoring tool GAmified LEarning Design Editor (GALEDE). GALEDE is de-signed to help educators create gamification-based flipped learning scenarios. It is built as a model-driven approach leveraging the capabilities of the Eclipse Sirius platform and Obeo Designer. It addresses the challenge of designing these learn-ing scenarios by offering an intuitive interface that simplifies the design process. The functionalities and features of the tool provide various levels of user guid-ance and assistance. Moreover, the paper includes an evaluation that involves ed-ucators from different domains. Results highlighted its strengths. The latter in-volves an easy-to-use interface, rich support for gamification elements, and cus-tomisation. Improvement areas that lead to upcoming enhancements are also iden-tified. These insights address GALEDE’s potential as a valuable tool for design-ing gamified flipped learning scenarios.