User-system Interaction Research Articles

Participatory Design of an Embodied Mixed Reality Experience Aimed to Assessing Individual and Collaborative Behaviors of Children

This study is part of a broader project exploring the integration of Mixed Reality (MR) in fostering prosocial behaviors among children, particularly focusing on interpersonal synchrony (IPS) and its impact on collaboration. IPS, the coordination of rhythmic movements among individuals, has been associated with improved group cohesion and prosocial behaviors, such as collaboration. Traditional assessments of prosociality typically involve structured play activities for dyads, making them difficult to adapt to other settings. To address these limitations, this research aims to design a flexible embodied MR experience that allows children to choose between collaborative or individual engagement, reflecting the natural dynamics of children's play interactions. For this purpose, we conducted an embodied participatory design (PD) and usability study with 50 children aged 8-10 years. We provide a detailed account on how the PD process was orchestrated and an evaluation of user-system interaction, children's perceptions of play modes, and experience satisfaction. The results show how the MR experience, codesigned with children, supports a free play environment, allowing children to choose their preferred play mode. This study highlights the potential of MR in psychological research and child development, providing a new avenue for assessing individual and collaborative behaviors in larger groups of children.

Digital Twin of Space Environment: Development, Challenges, Applications, and Future Outlook

This paper explores and discusses the revolutionary applications of digital twin technology in space environments and its profound impact on future space exploration activities. Originating from a proposal by the National Aeronautics and Space Administration (NASA) in 2002, digital twin technology aims to enhance the safety and reliability of space missions by creating precise virtual models. As the technology has evolved, its applications have successfully expanded beyond aerospace to include Industry 4.0, healthcare, and urban management, demonstrating remarkable cross-industry adaptability and broad impact. In space applications, digital twin technology can not only improve spacecraft design and maintenance processes but also enhance the efficiency of mission planning and execution. It plays a crucial role in astronaut training and emergency response as well. Particularly in extreme space conditions, this technology provides real-time monitoring and fault prediction, significantly enhancing mission safety and success rates. However, despite its recognized potential, the implementation of digital twins in space environments faces numerous challenges, including data transmission delays, model accuracy, and the design of user–system interactions. In the future, as artificial intelligence (AI) and machine learning (ML) technologies become mature and integrated, the digital twin will play a more central role in space missions, especially in remote operations, complex system management, and deep space exploration. This article is to overview key technical features, application examples, and challenges of digital twin technology, aiming to provide a comprehensive reference framework for researchers and developers while inspiring further in-depth studies and innovative applications.

Analysis and Design of Customer Relationship Management System on the SMEs Using Iconix Process

Background: Integrating Customer Relationship Management (CRM) systems is crucial for small and medium enterprises (SMEs) to enhance customer relations and profitability. Many SMEs in Indonesia, including Go-Sumber Plastik, still need to fully utilize CRM systems, which are essential for managing customer data, improving satisfaction, and retaining customers. Objective: The purpose of this research is to analyze and design a web-based CRM system for Go-Sumber Plastik using the Iconix Process methodology to enhance user interaction and overall system effectiveness. Methods: The study employed the Iconix Process methodology, which includes a use case, robustness, sequence diagrams, a GUI prototype, and a test plan. The design was tested using Maze to measure user interaction efficiency and satisfaction. Results: The research revealed significant challenges in user understanding of the CRM system, particularly in managing activities and adding customer information. Tasks such as reporting and logging in had good user performance. The overall user interaction score was 81.1, indicating moderate effectiveness of the initial design. Conclusion: The results underscore the necessity for a more intuitive and streamlined CRM system interface for Go-Sumber Plastik. Implementing an effective CRM system can improve SMEs' competitiveness and profitability by systematically enhancing communication, managing customer data, and boosting business performance. Future research should focus on refining the user interface to reduce error rates and improve task completion efficiency. Enhanced visibility and user guidance are recommended to optimize system usability and customer satisfaction.

Informating and Automating in Systems Design: Extending the Zuboffian View of Technology Ready-to-Use vs. Technology Unintuitive-to-Use

ABSTRACT Previous literature has treated software functionalities as a binary choice between informating and automating, based on Zuboff’s definitions. We suggest that the space between the role of a user engaging with a system (informate) and what the system can accomplish for the user (automate) has increasingly become blurred, moving toward a more nuanced continuum. We present a user-system interaction framework that analyzes this continuum with a focus on the user’s perspective. Using cases from archival data, this paper provides an analysis of what goes well and badly in the locus of control handoff between users and systems, highlighting the implications of software that is created in one region but used globally. The paper contributes to the literature by extending Zuboff’s informate vs. automate discussion and identifying design decisions that could help to avoid potentially catastrophic design errors. Using the interaction framework, we argue that it would be beneficial for system designers to move toward the informate end of the continuum, when designing systems for users with a high level of domain knowledge and expertise, and when there are significant differences between the environment in which the system is designed and the one in which the system is used.

Occupant behavior model and its involvement in building optimization design: a review

ABSTRACT The occupant behavior has a significant impact on the building performance. This review offers researchers and practitioners a clear understanding of the evolution of the occupant behavior model and its involvement in building optimization design, providing guidance for future research. Studies are selected if they are peer-reviewed conference proceedings and journal papers published from 2005 to 2023. By analyzing 203 core papers from the Web of Science, a bibliometric study is conducted using CiteSpace. The findings indicate that research on occupant behavior has advanced significantly since 2005, with China being the most active country. The interaction between occupant and building performance, development of occupant behavior model, building optimization framework, and optimized strategies in buildings are the four fundamental topics. Finally, the current challenges and future opportunities are discussed. Future research should focus on conducting real-case quantitative studies, expanding performance simulation, developing comprehensive techniques, improving user-system interaction, and exploring feasible social practices. However, limitations arise due to deficiencies in the thoroughness and depth of analyses resulting from sample constraints. To obtain more reliable results, a broader and more systematic approach to collecting publications is needed.

Development of Rule-Based Expert System for Variable Cost and Gross Profit Calculations of Agricultural Products: A Case Study

Cost and gross profit calculations of agricultural products are a comprehensive and difficult process. Many different parameters, such as soil cultivation, pruning, spraying, irrigation, storage, drying, harvesting, transportation, and marketing, need to be evaluated together. Currently, cost calculations of agricultural products are made with classical programs and simple mathematical methods. For this reason, the results vary depending on the person and organization making the evaluation. This creates some limitations, making cost planning, which is a dynamic process, unreliable. In the study, a rule-based expert system was developed for the cost and gross profit calculation of apricots. The expert system developed is called Apricot Information System (APRIS). The developed expert system aims to provide more accurate solutions by adding the precision and speed of the computer to the calculation process. The main contribution of this study is the development of a complete decision support set covering all processes from tillage to marketing and the design of rule-based user-system interaction. The designed system found the apricot variable cost calculation to be 1126.36 TL/da for 2020. This value largely overlaps with the values obtained from the field in the previous year. The developed expert system will be a platform that can be used in cost calculations of many agricultural products.

Eye tracking-based evaluation of accessible and usable interactive systems: tool set of guidelines and methodological issues

AbstractThis paper describes some fundamentals and challenges in using eye tracking for the assessment of usability and accessibility in the fields in Human–Computer Interaction and Educational Computing. This technique has great potential since it allows considering human factors and individual differences in these areas. This non-invasive method, of physiological nature, allows to know, in an objective way, the visual behavior of the users when facing a user interface or educational material, allowing to infer conclusions related to psychological processes, such as attention or cognitive load. The purpose of this work is to propose a tool set of guidelines and measures, as well as a methodological approach, to be used in eye tracking assessments. This proposal is based on and validated by the authors’ previous experience and results in the application of this technique.

Low-code development using requirements and knowledge representation models

Low-Code Development is a new software development paradigm which is typically used to generate web applications from high-level visual notations. These notations allow to express the User Interface and Application Logic (usersystem interactions) in a way which is understandable by the end-users. Using certain model-driven approaches, the low-code environments allow for generating the front-end layer and basic CRUD operations in the back-end. Yet still, non-standard domain logic (data processing) operations still necessitate the use of traditional programming. In this article we present a visual language, called RSL-DL that can be used to represent such non-standard domain logic in a visual form. It allows to capture domain knowledge with complex domain rules aligned with requirements models. The language synthesises and extends approaches found in knowledge representation (ontologies) and software modelling language engineering. The development environment of RSL-DL enables fully automatic generation of domain logic code by reasoning over and reusing domain knowledge. The environment includes a dedicated model editor and a transformation engine. The language?s abstract syntax is defined using a meta-model expressed in MOF. Its semantics is expressed with several translational rules that map RSL-DL models onto typical programming language constructs. The article presents a list of these rules in an informal way, and then introduces their formalisation using a graphical transformation notation. The RSL-DL environment includes an inference engine that enables processing queries to domain models and selecting appropriate invocations to generated code. It was also initially validated through studies that involve understandability, operability and complexity assessment. Based on these results, we conclude that declarative knowledge representations can be successfully used to produce imperative backend code with non-trivial logic.

Visit planner: A personalized mobile trip design application based on a hybrid recommendation model

The paper presents Visit Planner (ViP), a mobile application prototype that provides a solution to the challenging tourist trip design problem. ViP follows a holistic approach offering personalized recommendations for Points of Interest (POIs) based on preferences either explicitly collected by the application, or inferred by the users? ongoing interaction with the system. ViP proposes to the final user, a trajectory of POIs calculated using an Expectation Maximization method that maximizes user satisfaction taking into consideration a variety of time and spatial constraints for both users and POIs. Additionally, POIs are divided into categories, so that a certain number of POIs from each category to be included in the final itinerary. The application is implemented as a user-interactive system that allows the flexibility for easy content adaptation and facilitates management of content and services by the user. The prototype has been implemented for Android-based smartphones, on an open application environment, using standard communication protocols and open database technology. Currently, it is applied to the city of Agios Nikolaos in Crete, and is available for download from Google play.

Design of smart user interaction system utilizing enchased feedback and state control

The article aims to review existing issues and look for novel ways of human-computer digital systems design and interaction. Such interaction takes place, as a rule, through an appropriate interface, which can be mechanical, digital, analog, with a touch screen, etc. For the end user of the relevant application or system, it is important how this interaction process will be implemented, presented, and programmed. That is, what controls, actions for interaction, and feedback mechanisms from the system to the user will be available. The research methods are based on the main methodologies of design and analysis of digital products with an emphasis on user experience, research of user requirements, the context of application use, and the presentation of the menu of interaction with a digital service. The article presents the results of a detailed description and modeling of the main process of user interaction with the feedback system (cyclic process). The context of using the application, the main desires and goals of the user when interacting, as well as the types of available options for interacting with the interactive system are taken into account. The seven-step process of user interaction presented in the paper includes functions, data, software systems and modules, appropriate software and hardware architecture, and methods of internal communication between cycle functions. A process of interactive interaction has been developed, which describes the full cycle from the beginning to the end of the user's work with any digital, analog, computing device, application, or service. This process can be used by designers, software developers, and scientists/researchers at the stage of planning a new interactive system or to improve an existing one.

Data-Driven Cyber Threat Intelligence: Leveraging Behavioral Analytics for Proactive Defense Mechanisms

As the cyber threat landscape becomes increasingly sophisticated, traditional defense mechanisms often fall short in anticipating and mitigating advanced attacks. The paper explores the critical role of behavioral analytics in transforming cyber threat intelligence (CTI) into a proactive defense strategy. This study underscores the importance of analyzing user behavior patterns, network activity, and system interactions to detect anomalies that may indicate potential threats. By leveraging large datasets and advanced analytical techniques, organizations can move beyond reactive cybersecurity measures, instead anticipating and preventing attacks before they fully manifest. The integration of behavioral analytics with CTI provides a comprehensive understanding of both external threats and internal vulnerabilities, enabling the development of dynamic defense mechanisms that adapt to the evolving threat environment. The research also discusses the benefits of automated threat intelligence platforms, which use machine learning algorithms to continuously analyze behavioral data and refine threat detection models in real-time. This approach reduces the reliance on manual analysis, enhances the speed and accuracy of threat detection, and minimizes false positives. Moreover, the study highlights the importance of cross-sector collaboration and data sharing in building a robust CTI framework that leverages collective intelligence to combat cyber threats. Case studies of successful implementations in various industries demonstrate the practical applications and efficacy of behavioral analytics in enhancing cybersecurity resilience. The findings suggest that organizations that adopt data-driven, behavior-focused CTI are better equipped to defend against both known and unknown threats, ensuring a more secure digital environment. This proactive approach to cybersecurity not only strengthens organizational defenses but also contributes to the broader goal of creating a safer cyber ecosystem by identifying and neutralizing threats at their inception. Keywords: Data-Driven, Cyber Threat, Intelligence, Bahavioral Analytics, Proactive Defense Mechanism.

A Mobile-Based Used Vehicle Buying System Implementation

Aspect-oriented software is characterized by enhanced reusability and maintainability compared to object-oriented software. In aspect-oriented software development, concerns scattered across objects are separated and modularized into aspects. This research is motivated by the buyer's mistrust in used vehicle transactions due to concerns over potential fraud. To address this, the study proposes designing an e-commerce application that facilitates interactions between prospective vehicle sellers and buyers, alleviating transactional apprehensions. The analysis and design phases of the software development cycle employ Use Cases to facilitate the identification and separation of concerns. Use Cases are chosen for their direct illustration of user-system interactions. The case study focuses on a mobile e-commerce application for used vehicle sellers and buyers. The research aims to analyze the impact of consumer motivation, perceived quality, and consumer attitudes on the decision to purchase used vehicles. The findings are expected to aid sellers in marketing their vehicles and assist buyers in making informed purchasing decisions

Usability evaluation of emergency information systems in educational hospitals in Kerman, Iran

BackgroundSmart and practical health information systems and applications with fewer errors are crucial for healthcare facilities. One method that ensures the proper design of health information systems (HIS) and applications is usability evaluation.ObjectiveThis study aimed to evaluate the usability of the emergency information systems used at the emergency departments of four educational hospitals in Kerman, Iran.MethodThis study was conducted in two phases. In the first phase, the information systems' errors and shortages were identified using a semi-structured questionnaire by users (nurses and the IT staff). In the second phase, based on the results of the first phase, two questionnaires were designed for each group of users to their opinions about the usability of the emergency information systems.ResultsThe average score of “reducing and facilitating user’s daily activities” was significantly different among hospitals (p = 0.03). Shahid Beheshti Hospital obtained the lowest usability score (17.5), and Afzalipour Hospital received the highest usability score (21.75). Moreover, the average score in “use of the HIS” for nurses and IT staff was 2.93 and 3.54 on a scale of 5, respectively.ConclusionUsability evaluation of health information systems is essential to ensure that these systems provide sufficient and accurate information and requirements for users and health care providers. Also, modifying health information systems based on the user views and expectations improves the quality of the system and user-system Interaction.

Predicting Changes in User-Driven Requirements Using Conditional Random Fields in Agile Software Development

Agile development encourages requirements change. The accurate predictions of changes in user requirements could help software evolve in the right direction to increase user satisfaction. Previous research on requirement predictions mostly relies on historical defects or user feedback. In this article, we aim to predict requirement changes based on user–system interactions in agile software development. We focus on the user–system interaction behaviors used to infer user intentions and predict requirement changes to drive the incremental iterations of agile development. Through a prototype system with two incremental iterations, an embedded program in the system captures the user runtime interaction behavior data. We utilize the conditional random fields to explore the user potential intentions and infer the emerging requirements accordingly. The increased accuracy of results in the iterations proves the effectiveness of our approach in predicting user requirement changes.

The PGIRec Software to Support the Evaluation of User-System Interaction with a Synchronous and Multi-perspective Recording System

Audiovisual recording is a highly relevant activity when investigating and analyzing qualitative data, both for scientific researches and for the industry. Games are a particularly challenging application for user experience and interaction evaluation, given the multitude of platforms, modes of operation, number of players and game environments that may occur through different games genres. This diversity of interaction possibilities makes it difficult for employing current audiovisual recording tools in a number of scenarios, especially considering multi-user interaction in the same or in separate environments. In this context, this paper presents an open-source recording tool, called Player-Game Interaction Recorder (PGIRec), specialized in synchronous recording of multiple sources of audio and video. The software was evaluated using brain-computer interface games in two different studies, with a total of 22 participants and over 16 hours of recorded activities using different experimental setups. The evaluation showed that the solution was stable and adaptable, since it generated audiovisual media without occurrences in different situations, with multiple audio and video sources concurrently.

Transfer learning for collaborative recommendation with biased and unbiased data

In a recommender system, a user's interaction is often biased by the items' displaying positions and popularity, as well as the user's self-selection. Most existing recommendation models are built using such a biased user-system interaction data alone. In this paper, we introduce an additional specially collected unbiased data, and then have a new problem called collaborative recommendation with biased and unbiased data.We first formalize the studied problem and list three challenges, including the bias challenge, the heterogeneity challenge and the unbalance challenge. Then we propose a novel transfer learning-based AI solution, i.e., transfer via joint reconstruction (TJR), to achieve knowledge transfer and sharing between the biased data and unbiased data. Specifically, in our TJR, we use two different models to extract the users' preferences and bias information, and then refine the prediction via the latent features containing the bias information in order to obtain a more accurate and unbiased recommendation. We further integrate the two data by reconstructing their interaction in a joint learning manner. Moreover, in order to better address the unbalance challenge, we introduce a bias regularization term and integrate bidirectional knowledge distillation. Finally, we adopt four representative methods, i.e., variational autoencoders, matrix factorization, neural collaborative filtering and graph convolution network, as the backbone models of our TJR and conduct extensive empirical studies on three public datasets, showcasing the effectiveness of our transfer learning solution over some very competitive baselines.

A Systematic Review of Cost, Effort, and Load Research in Information Search and Retrieval, 1972–2020

During the information search and retrieval (ISR) process, user-system interactions such as submitting queries, examining results, and engaging with information impose some degree of demand on the user’s resources. Within ISR, these demands are well recognised, and numerous studies have demonstrated that the cost, effort, and load (CEL) experienced during the search process are affected by a variety of factors. Despite this recognition, there is no universally accepted definition of the constructs of CEL within the field of ISR. Ultimately, this has led to problems with how these constructs have been interpreted and subsequently measured. This systematic review contributes a synthesis of literature, summarising key findings relating to how researchers have been defining and measuring CEL within ISR over the past 50 years. After manually screening 1,109 articles, we detailed and analysed 91 articles which examine CEL within ISR. The discussion focuses on comparing the similarities and differences between CEL definitions and measures before identifying the limitations of the current state of the nomenclature. Opportunities for future research are also identified. Going forward, we propose a CEL taxonomy that integrates the relationships between CEL and their related constructs, which will help focus and disambiguate future research in this important area.

Integrated biosensing system of electrochemistry and electrophysiology for cortisol and skin conductance analysis on smartphone

High level of mental stress will lead to negative psychological and health consequences, such as insomnia, depression, and cardiovascular disease, which will increase the suicide rate and affect social stability. Mental stress has been proved to be related to biomarkers cortisol and skin conductance, and reflects the complementary advantages of stress monitoring. Based on electrochemistry and electrophysiology analysis technology, combined with microelectronic design and biosensors, this paper constructed an integrated physiological and biochemical sensing system, and an intelligent user interaction system. Firstly, a molecularly imprinted biosensor with gold nanoparticles (AuNPs), prussian blue (PB), and polypyrrole (PPy), achieved highly sensitive detection of cortisol in the range of 1–10000 ng/mL and demonstrating good specificity. The cortisol detection unit used differential pulse voltammetry (DPV) method by dual power amplifier chip AD8674, which was a precision operational amplifier with low noise, low input bias current, and unit gain stability. Then, the skin conductance detection unit was mainly composed of a pulse width modulation (PWM) drive circuit, which was designed to achieve a 100 Hz voltage output. The integrated system was designed with microcontroller module, transimpedance amplifier (TIA) module, power management module, signal transmission module, cortisol and skin conductance detection module, which was suitable for constructing precision voltage control and weak current signal conditioning. Finally, based on the software and hardware platform of smartphones, an intelligent analysis system was developed to improve the portability and user interaction convenience. Our system achieved the physiological and biochemical joint detection for the first time, showing enormous application potential in future multimode sensing monitoring.

The Impact of Digital Coaching Intervention for Improving Healthy Ageing Dimensions among Older Adults during Their Transition from Work to Retirement.

Retirement is a critical step in older adults' lives, so it is important to motivate them to stay physically active, mentally healthy, and socially connected in the transition from work to retirement, including through digital health coaching programs. This study aims to: evaluate the impact of a digital coaching intervention to enhance three healthy ageing dimensions, i.e., physical activity, mental well-being, and socialization of a group of adults near retirement; understand the users' experience; and identify the system strengths and weaknesses. This longitudinal mixed-methods study, carried out in 2021 in Italy and the Netherlands, enrolled 62 individuals. In the first 5 weeks of the trial, participants used a digital coach with the support of human coaches, and then they continued autonomously for another 5 weeks. The use of the digital coach improved the participants' physical activity, mental well-being and self-efficacy during the first period and only the physical activity in the second. An effective coaching system should be flexible and attractive. High levels of personalization remain the golden key to aligning the health program to the physical, cognitive and social status of the intended target, thus increasing the user-system interaction, usability, and acceptability, as well as enhancing adherence to the intervention.

Lessons Learned from Modeling the Interaction with Conversational Agents

Intelligent conversational agents have become widespread. Inspired by conversations in natural language, they present different degrees of intelligence and autonomy, bringing challenges for Human-Computer Interaction (HCI). One such challenge concerns design languages for modeling user-agent interaction. We focus here on MoLIC, a design-phase dialogue model based on Semiotic Engineering theory devised to represent user-system interactions as conversations. We performed two case studies with MoLIC interaction diagrams representing two conversational agents – the ANA chatbot and Samsung Bixby. We examined how the interactive aspects of these agents could be expressed in MoLIC. Although it was possible to express the general interaction, our results showed limitations related to the language expressiveness or its inadequacy to represent these systems. We identified limitations in the applicability of MoLIC in modeling and pondered on how to extend or adapt it; directing the HCI community to issues and initiatives that can help design and model these technologies.