Human-computer Interaction Perspective Research Articles

Driving Distraction Evaluation Model of In-Vehicle Infotainment Systems Based on Driving Performance and Visual Characteristics

With the rapid development of automotive electronic technology, increasingly car enterprises choose to carry touchscreen in-vehicle infotainment systems (IVISs) in smart cars. The integration of navigation, music, telephone, and other functions into touchscreen IVISs has greatly enriched the driving experience. However, the design of touchscreen IVISs, which lacks consideration of driver human–computer interaction leads to increased driving distraction. The current discussion is limited to evaluating the overall distractions of the secondary task, and there is a lack of research on classifying and summarizing the types of driving distractions. Therefore, this paper proposes a new method to evaluate the degree of driving distraction during the interaction with touchscreen IVISs based on driving performance and visual characteristics. A driving simulation environment was built to conduct psychological experiments on three types of driving distraction, namely visual, manual, and cognitive distraction, respectively, to obtain the impact of different types of driving distraction by using touchscreen IVISs. Combining the criteria importance through intercriteria correlation method with fuzzy comprehensive evaluation to establish a driving distraction evaluation method, we quantify the driving distraction caused by the touch screen IVIS. The results of this study indicate that the proposed driving distraction evaluation model by using driving performance and visual characteristics can effectively evaluate the degree of driving distraction caused by the touchscreen IVIS and provide reference and specification for IVIS safety design from a human–computer interaction perspective.

Co-making the future: crafting tomorrow with insights and perspectives from the China-U.S. young maker competition

AbstractThis research paper investigates the intersection of the maker movement and educational innovation, using the China-U.S. Young Maker Competition as a foundational example. It examines how maker education, fueled by hands-on learning and a curiosity-driven approach, can evolve and influence. The study explores the roles and impacts of Human-Computer Interaction (HCI), Design-Driven Innovation (DDI), and Cross-Cultural Perspectives (CCP) within maker education. It highlights HCI’s connection of technology with learning, DDI’s focus on user-centered solutions, and the significance of CCP in enhancing cultural collaboration, vital for fostering an innovative and creative future. This paper offers a detailed perspective on the current state and future potential of maker education. It proposes a roadmap for the coming decade, emphasizing collaborative learning and creative endeavors, all set within the engaging environment of the competition.

Human-computer Interaction Perspectives on Condition Monitoring and Fault Diagnosis of Gearbox in Doubly-Fed Wind Turbines: An Exploration with Artificial Intelligence Technology

Human-computer Interaction Perspectives on Condition Monitoring and Fault Diagnosis of Gearbox in Doubly-Fed Wind Turbines: An Exploration with Artificial Intelligence Technology

The advantage of videos over text to boost adolescents' lateral reading in a digital workshop

ABSTRACT Today, fostering media and information literacy (MIL) among citizens is essential for preserving democracy. The effectiveness of scalable interventions, particularly those employing lateral reading, a fact-checking heuristic, is well recognised. Our digital workshop, designed to model lateral reading from a user's perspective, has proven beneficial in educational settings and has garnered expert endorsement. Addressing recent scholarly calls to understand the underlying mechanisms of successful MIL interventions, our study is anchored in Cognitive Load Theory. We examine how different instructional modalities in our workshop influence engagement with lateral reading and how effectively it is executed. The study separates implicit text feedback and hands-on video instructions, previously combined, in a full-factorial design using a parallel-group RCT. We analysed the responses of 178 upper-secondary students in the online workshop and conducted a detailed video analysis of 30 students participating in a controlled environment at their schools. Our findings reveal that hands-on video instructions notably enhance both the engagement and effectiveness of the lateral reading heuristic. This study underscores the significance of a human-computer interaction perspective in designing more impactful media and information literacy interventions.

Impact of user engagement on virtual reality behavioral response from the human–computer interaction perspective toward a service context: A hybrid statistics and machine learning approach

Owing to recent uncertainty in the service sector, new attractive ways, such as virtual reality, have been adopted by online sites to provide products and services to individual users in the tourism context. Based on human–computer interaction user engagement and the domain segmentation innovativeness theory, we develop and test a theoretical framework to examine the impact of key user engagement drivers on in-person tour intentions as behavioral responses using the partial least squares structural equation model and a neural network with activation function analysis as the new two-stage approach. According to a survey sample of visitors' responses as the case, the results demonstrate that a) user engagement, including aesthetic appeal, focused attention, perceived usability, and reward experience, improves attitudes toward virtual reality; b) product-possessing innovativeness positively moderates the relationships between attitude toward virtual reality and in-person tour intentions; c) information-possessing innovativeness negatively moderates the relationships between the attitude toward virtual reality and in-person tour intentions; d) focused attention and reward experience show both linear high performance and nonlinear importance; and e) activation function analysis could further improve the accuracy of prediction.

The Effects of Experienced Utility and PEEIM on the Purchase Intention of Cross-Border E-Commerce

Due to the rapid development of the internet, cross-border e-commerce (CBEC) is gaining popularity. With CBEC, consumers from different countries can overcome the limits of languages and currencies to buy desired products directly. However, compared to domestic e-commerce, CBEC confronts significant challenges, such as risky distribution channels, dependency on third-party logistics, customs clearance, etc. Therefore, multi-faceted efforts are needed to promote CBEC. Traditional studies probe CBEC through a logistics and operational perspective; this study bridges a research gap by stressing a human–computer interaction perspective. Under the premise that technical infrastructure keeps improving, consumers’ expectations of switching to CBEC has been an essential issue. Specifically, this study develops a theoretical model that emphasizes website cues as experienced utility and the perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as decision utility to investigate their effects on the purchase intention of CBEC. This study applied Smart PLS 3.0 to verify the research model with 300 valid responses from online questionnaires. Research findings confirmed the proposed model. Practical strategies for promoting CEBC were suggested accordingly.

The effects of non-fungible token platform affordances on customer loyalty: A Buyer–Creator duality perspective

Prior academic research on non-fungible tokens (NFTs), an application of blockchain technology in the metaverse environment, has focused primarily on the market demand side (i.e., buyers), with limited attention given to the supply side (i.e., creators). To address this gap, we seek to understand creators' and buyers’ perceptions of platform affordances that can aid NFT platforms in developing functions that address the needs and expectations of both parties. To do this, we draw on affordance theory and psychological contract theory and use a mixed-methods approach consisting of text mining, structural equation modeling, and importance-performance map analysis. The results show that platform affordances (transaction, aesthetics, status, and user interface affordance) facilitate the creation of psychological contracts, which in turn promotes customer loyalty. Moreover, the relationships identified differ between creators and buyers. Overall, these results point to the value of using a user-centric human–computer interaction perspective to study emerging blockchain-based systems. They can inform design principles and guidelines for NFT platforms to effectively support creator–buyer interactions, transactions, and relationships through enhanced affordances and user-centric experience. This study advances knowledge of design in the nascent NFT domain relevant to the cross-disciplinary human–computer interaction community.

What is critical for human-centered AI at work? - Toward an interdisciplinary theory.

Human-centered artificial intelligence (HCAI) has gained momentum in the scientific discourse but still lacks clarity. In particular, disciplinary differences regarding the scope of HCAI have become apparent and were criticized, calling for a systematic mapping of conceptualizations-especially with regard to the work context. This article compares how human factors and ergonomics (HFE), psychology, human-computer interaction (HCI), information science, and adult education view HCAI and discusses their normative, theoretical, and methodological approaches toward HCAI, as well as the implications for research and practice. It will be argued that an interdisciplinary approach is critical for developing, transferring, and implementing HCAI at work. Additionally, it will be shown that the presented disciplines are well-suited for conceptualizing HCAI and bringing it into practice since they are united in one aspect: they all place the human being in the center of their theory and research. Many critical aspects for successful HCAI, as well as minimum fields of action, were further identified, such as human capability and controllability (HFE perspective), autonomy and trust (psychology and HCI perspective), learning and teaching designs across target groups (adult education perspective), as much as information behavior and information literacy (information science perspective). As such, the article lays the ground for a theory of human-centered interdisciplinary AI, i.e., the Synergistic Human-AI Symbiosis Theory (SHAST), whose conceptual framework and founding pillars will be introduced.

Realtime Recognition of Dynamic Hand Gestures in Practical Applications

Dynamic hand gesture acting as a semaphoric gesture is a practical and intuitive mid-air gesture interface. Nowadays benefiting from the development of deep convolutional networks, the gesture recognition has already achieved a high accuracy, however, when performing a dynamic hand gesture such as gestures of direction commands, some unintentional actions are easily misrecognized due to the similarity of the hand poses. This hinders the application of dynamic hand gestures and cannot be solved by just improving the accuracy of the applied algorithm on public datasets, thus it is necessary to study such problems from the perspective of human-computer interaction. In this article, two methods are proposed to avoid misrecognition by introducing activation delay and using asymmetric gesture design. First the temporal process of a dynamic hand gesture is decomposed and redefined, then a realtime dynamic hand gesture recognition system is built through a two-dimensional convolutional neural network. In order to investigate the influence of activation delay and asymmetric gesture design on system performance, a user study is conducted and experimental results show that the two proposed methods can effectively avoid misrecognition. The two methods proposed in this article can provide valuable guidance for researchers when designing realtime recognition system in practical applications.

Passenger non-driving related tasks detection using a light weight neural network based on human prior knowledge and soft-hard feature constraints

Many evidences prove that the development of autonomous cars increases the probability of motion sickness when passengers perform non-driving related tasks. Making the autonomous cars know what the passenger is doing is necessary to adjustment optimal strategy of vehicle motion style and alleviate motion sickness used the human–machine interaction method automatically. For autonomous cars, passengers’ non-drive related task detecting is a non-main task, and it is necessary to reduce the occupation of computing resources, the current study did not address this issue. Therefore, we have choose several types of behaviors based on current motion sickness research literature to improve motion sickness from a human–computer interaction perspective and build a dataset, then, a lightweight model for the detection of passenger non-driving related tasks is proposed. In order to reduce computational load, feature redundancies and improve the accuracy, the soft-hard features constraints method is proposed based on the human prior knowledge. We annotated the key features regions of the images and make the network learn the labeled regions used a two-layer feature constraint structure, which allow the model to learn labeled features earlier, and the label smooth regularization method is used to improve the robustness. The proposed model used the windowed attention mechanism to calculate the importance of each neuron in the feature map and reduce the number of parameters. Finally, we used a visualization method visualize features related to passenger tasks. The results show that the proposed model has an accuracy of 0.9710 with 2.5 M Params, and 1.15G FLOPs, compared with other models, the proposed lightweight model has the highest accuracy.

Where Am I Now? Modelling Disorientation in Pan-Scalar Maps

Disorientation is a common feeling for all users of zoomable multi-scale maps, even for those with good orientation and spatial skills. We make the assumption that this problem is mainly due to the desert fog effect, documented in human–computer interaction within multi-scale zoomable environments. Starting with a collection of reported experiences of disorientation, this paper explores this notion from the spatial cognition, philosophical and human–computer interaction perspectives and proposes a model of disorientation in the exploration of multi-scale maps. We argue that disorientation is a problem of reconciliation between the current map view and the mental map of the user, where landmarks visible on the map or memorised in the mental map play a key role. The causes for failed reconciliation are discussed and illustrated by our collected experiences of disorientation.

Understanding the customer experience in human-computer interaction: a systematic literature review.

In recent years, there has been an increasing interest in customer experience (CX) and its relation to the human-computer interaction (HCI) field. The CX is different depending on the domain in which it is studied, and therefore its dimensions may vary. This research presents an extensive review of 122 studies related to CX definitions and dimensions that have been proposed in different domains, including an analysis from an HCI perspective. The guidelines proposed by Kitchenham & Charters (2007) were used, complementing the review with a snowballing approach. We identified 71 CX definitions (where 14 definitions highlight HCI aspects), 81-dimensional proposals (where 24 proposals contain HCI aspects), and 39 application domains (where 18 domains cover topics related to HCI). However, we did not find CX definitions or dimensions directly focused on HCI. Based on the results, a novel CX definition and dimensions-focused on the HCI area-are proposed and activities that the authors should perform when proposing new CX dimensions in domains related to HCI are suggested, i.e., domains that involve the interaction of a user (or customer) with a software product. Implications for future practice focus on facilitating the understanding of the CX concept and its relationship with HCI; recognizing the key CX dimensions for different domains and how they relate to HCI dimensions; and helping in the creation of new CX dimensions by suggesting activities that can be performed. The results show that there are opportunities for HCI/CX researchers and practitioners to propose new dimensions of CX for a domain related to HCI, develop instruments that allow the evaluation of CX from an HCI point of view, and perform reviews on a particular domain relevant to HCI but less studied.

The occurrence mechanism of short video indulgence from the perspective of human-computer interaction

The occurrence mechanism of short video indulgence from the perspective of human-computer interaction

A Survey of Citizen Science Gaming Experiences

Citizen science games (CSGs) are a valuable means for motivating citizen science participation. However, many CSGs still suffer from the recruitment and retention issues of traditional citizen science projects, despite much prior literature on what motivates CSG players. In this study, we take a Human-Computer Interaction (HCI) perspective to explore in what ways CSGs are still failing to provide motivating play experiences for players. Using Qualitative Content Analysis, we conducted and analyzed an online survey of 185 players from 9 citizen science games. This survey contributes insights to the current state of CSG experiences and next steps for developers to address these issues. We found that major concerns included scientific communication, instructional design, user interface and controls, task quality, and software issues.

A Study on the Construction of Translation Curriculum System for English Majors from the Perspective of Human-Computer Interaction

This paper proposes a collaborative human-computer interaction recommendation model for English major translation courses to address the problems of poor course recommendation and lack of robustness to noisy data in traditional recommendation models for English major translation courses. First, a new data enhancement method is proposed for the bipartite graph structure. Then, the enhanced data is fed into a graph convolutional neural network for node feature extraction to obtain node representations of users and items. A recommendation supervision task and an auxiliary task for contrast learning are constructed for joint optimization. The human-computer interaction model of the knowledge graph is designed, and the dialogue entities are embedded in the knowledge graph ripple network to obtain potentially interesting content for students. Finally, the student interaction content and node representations are combined to obtain the optimal translation course recommendation. The experimental results indicate that the proposed model in this work is capable of producing higher-quality English major course recommendations and beats other current models. This model is suitable for English primary translation course content recommendation and helps to improve students’ translation ability.

New Qualitative Perspective in Human-Computer Interaction: Designing Mobile English for STEM.

The emerging field of human–computer interaction (HCI) opens up more opportunities for technology integration in language learning. Technology creates more workforces in the Science, Technology, Engineering, Mathematics (STEM) field, yet the number of STEM pursuers is declining due to poor command of the English language. There is a gap in English vocabulary for STEM, which needs a novel solution from the perspective of HCI. This study aims to explore the needs of STEM learners in creating an English language competency mobile module. The methodology used is through a qualitative study. Seven STEM learners, 17 years old, participated in semi-structured interviews. The results from the interview are divided into four main themes: (1) the importance of learning English, (2) problems of learners, (3) strategies of English language learning, and (4) learners' readiness in using a mobile app. This study is significant for mobile app designers, English language teachers, and course designers as the input will provide an overview of the STEM learners' needs in the English language. Plus, designing a mobile app from the learners' perspectives gives more effectiveness to HCI, rendering success to second language acquisition. Future work can design and develop a mobile app to enhance STEM learners' English language competency based on the learners' perspectives.

Effects of Prior Experience on the User Experience of News Aggregation App’s Features—Evidence from a Behavioral Experiment

News aggregator apps have become one of the major channels for acquiring information for the Chinese. The number of users is increasing but literature on the user experience (UX) of these apps from the perspective of human-computer interaction remains dearth. In study 1, a completely randomized between-participant experiment with prior experience of news aggregator apps (with prior experience vs. without prior experience) as the independent variable was conducted to investigate its effects on the UX of news aggregator app’s functions, including browsing news, searching news, watching short videos, interacting with news, personalized page setup and online shopping. UX was operationalized as perceived usefulness, ease of use, and satisfaction. Results indicated that the experienced users perceived lower levels of usefulness when they used the app to browse news, watch short videos, interact with news and set up the page than inexperienced users. Experienced users also perceived lower levels of ease of use when watching short videos. In addition, veteran users reported lower satisfaction levels when browsing the news. To explore the reason behind this phenomenon, a sentiment analysis (study 2) was conducted on the reports submitted by participants in the experienced group during the training sessions. It was found that the experienced group overall reported negative sentiment scores, and the results indicated positive trends of correlation between the sentiment score and the UX. The current research provides a more nuanced understanding of the effect of prior experience on the UX of news aggregator apps.

Establishing a blockchain online travel agency with a human–computer interaction perspective

以人机交互视角建立区块链在线旅行社研究目的本研究旨在在线旅行社 (B-OTA) 的设计中融入创新技术（即区块链）。通过专家访谈了解了区块链旅行的方便性和用户打造的住宿平台, 从而加快了原型系统设计。我们进一步通过可用性测试验证原型系统设计并提高其参考能力。研究设计/方法/途径进行了 B-OTA 的快速原型设计通过德尔菲法和文献汇编。设计验证可用性测试是使用修改后的系统评估进行的方法。通过收集受试者的建议对原型系统进行改进。研究发现本研究将有助于B-OTAs及相关领域的发展技术。通过可用性测试, 我们验证了创建一个熟悉的用户的操作环境可以减少用户对陌生技术的恐惧。我们的研究结果为未来的 B-OTA 研究人员和从业者提供了设计相关的指南。研究原创性/价值除了使用的区块链相关技术之外, 很少有研究报告了 B-OTA 的经验和界面设计。这项研究指出, 正如许多 HCI 相关论文所指出的, 成功的界面设计基本的先决条件是在使用过程中更清晰地定义用户需求。用户体验和用户界面设计应该提供良好的用户体验。

Adoption of e-government by Indonesian state universities: An application of Technology Acceptance Model

E-government is the use of internet platforms to deliver governmental services to citizens with the goal of improving government efficiency, transparency, and participation. This study aims to find out what factors determine the rate at which public university in Indonesians accept e-government services. This study uses the Technology Acceptance Model (TAM). TAM is a traditional model of technology diffusion that is an essential conceptual criterion. It drives acceptance consisting of perceived usefulness and perceived ease of use. The results of this paper back up the original TAM hypothesis. Based on the data collected and analyzed, the study concludes that three influencing factors, namely perceived usefulness (PU), perceived ease of use (PEU), and perceived risk (PR), are significantly related to the intention to use e-commerce government. However, trust and social influence do not significantly affect the intention to use e-government services. This paper has significant implications for policymakers and government officials who want to see the growth of e-government usage in Indonesia. When attempting to market a new online system from the perspective of human-computer interaction, it becomes evident that designers must consider how users perceive the risks.

Antecedents of Trust in Mobile-Health Applications: A Human-Computer Interaction Perspective for the Egyptian Users

Antecedents of Trust in Mobile-Health Applications: A Human-Computer Interaction Perspective for the Egyptian Users