Shaping User Research Articles

Factors Influencing User Favorability of Government Chatbots on Digital Government Interaction Platforms across Different Scenarios

This study investigates the direct and indirect influences of behavioral quality, social support, perceived system, emotional perception, and public expectation on user favorability regarding government chatbots in both government service and policy consultation contexts. The findings reveal that while behavioral quality, social support, and perceived system directly affect user favorability in both scenarios, public expectation uniquely impacts user favorability in policy consultation settings, but not in government service scenarios. Furthermore, the analysis indicates that social support, emotional perception, and public expectation all indirectly influence user favorability through their mediating effect on behavioral quality in both contexts. Notably, the significant distinction between the two scenarios is the presence of an indirect impact of perceived system on user favorability within policy consultation scenarios, which is absent in government service scenarios. This study sheds light on the intricate interplay of factors shaping user favorability with government chatbots, and provides valuable insights for improving user experiences and user favorability in different governmental service contexts.

Fostering CSR Sponsorship in China: A Conceptual Framework for Cultivating Sustainable Behavior among Ant Forest App Users via Internet Platforms

Ant Forest has emerged as a prominent pro-environment advocate, amassing a user base of 650 million individuals. However, the sustained engagement of its users is crucial for its enduring success. To ensure the continued viability of Ant Forest, it is imperative to foster and maintain users’ pro-environmental behaviors over an extended period. Central to Ant Forest’s appeal are its gamification features and interactive elements linked to CSR sponsorship. This study aims to investigate the potential of these distinctive characteristics within an Internet platform to enhance users’ awareness of sustainability issues and prolong their engagement. As part of a comprehensive inquiry into the role of Chinese Internet Platform Companies such as Ant Forest in shaping users’ attitudes and behaviors towards sustainability, this research endeavors to ascertain whether these platforms fulfill their responsibility in offsetting carbon emissions. The present findings are from a thorough desktop survey focusing on key themes related to the Ant Forest app, including the maintenance of users’ sustainable behavior and the enhancement of CSR sponsorship. Utilizing the EAGLE System, an online research platform, we meticulously documented the synthesis of literature reviews and adapted the findings for presentation. Our analysis identified CSR-linked sponsorship, the sustainability of Chinese Internet Platform Companies, users’ behavior, and users’ attitudes as potential independent variables. Furthermore, we identified the gamification mechanism and interactivity as moderator variables influencing users’ engagement with their responsibilities in carbon emissions offsetting. Notably, Chinese Internet platform companies have the potential to positively influence users’ attitudes and behaviors towards sustainability by integrating gamification, interactivity, and CSR-linked sponsorship into their platforms. Harnessing these features effectively may empower Internet platforms to instill sustainable habits among users, thereby laying the groundwork for a conceptual framework termed the Users’ Sustainable Awareness Model.

Charting a sustainable course: how normative factors shape intentions for Autonomous Rapid Transit commuting

With the continuous advancement of technology, transportation methods have undergone significant transformation, giving rise to innovative solutions like Autonomous Rapid Transit (ART). ART systems are designed to utilize hydrogen energy, serving as an efficient and eco-friendly power source. This not only addresses issues related to traffic congestion but also presents a promising solution to environmental challenges. However, the success of implementing such technologies to mitigate these challenges relies heavily on the support and acceptance of potential users. This study aims to explore the intention of users to adopt ART as a mode of transportation in the context of Sibu, Sarawak, Malaysia. This study conducted a comprehensive survey involving 350 respondents and employed Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse the data. The findings of this study reveal that several critical factors significantly influence the behavioural intention to use ART for commuting. Specifically, subjective norms, perceived behavioural control, and individual attitudes have a significant impact on the intention to embrace ART as a sustainable mode of transportation. However, the study also finds that personal norms do not exhibit a significant relationship with behavioural intention. This insight underscores the pivotal role of societal influences compared to individually internalized values in shaping user decision-making with regard to the adoption of ART for commuting. It is imperative for policymakers to take into account the perspectives and considerations of users when formulating policies related to the introduction and promotion of new public transportation modes where private transportation has traditionally been prevalent.

The Relationship between Political Ideology and Social Media Echo Chambers

Purpose: The general purpose of this study was to explore the relationship between political ideology and social media echo chambers. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to political ideology and social media echo chambers. Preliminary empirical review revealed that echo chambers exist on social media platforms, with individuals predominantly exposed to information aligning with their political beliefs. Social Identity Theory and Selective Exposure Theory were instrumental in understanding how users' political affiliations influenced their interactions online, reinforcing echo chambers. These echo chambers, driven by users' desire for ingroup solidarity and selective exposure to like-minded content, posed challenges to democratic discourse and societal cohesion. The study emphasized the importance of addressing these challenges by promoting media literacy, critical thinking, and exposure to diverse viewpoints on social media platforms to foster a more inclusive and deliberative public sphere. Unique Contribution to Theory, Practice and Policy: The Social Identity theory, Selective Exposure theory and Dual Process theory may be used to anchor future studies on the relationship between political ideology and social media echo chambers. The study provided valuable recommendations that contributed to advancing theoretical understanding, informing practical interventions, and shaping policy responses to the challenges posed by echo chambers in contemporary political discourse. It emphasized the integration of social identity theory and selective exposure theory into theoretical frameworks, highlighting the psychological mechanisms driving the formation of echo chambers. Practically, the study underscored the importance of promoting media literacy and critical thinking skills among social media users, while suggesting that social media platforms play a pivotal role in shaping users' information environments. On the policy front, it emphasized the need for evidence-based interventions aimed at mitigating the adverse effects of echo chambers on democratic governance and societal cohesion.

Assessing the moderating effects of involvement on tourist attitudes and intentions through virtual reality applications

PurposeThis paper aims to evaluate the impact of various preview modes on tourist attitudes and intentions to visit a destination based on consumers’ level of involvement in travel decision-making.Design/methodology/approachThe study was conducted as a between-subjects one-factor [preview mode: static images vs 360-degree tour vs virtual reality (VR) mode] in a laboratory experiment setup to examine how consumers with different levels of involvement in travel decision-making respond to destination marketing toward three different preview modes.FindingsThe findings indicated that VR preview mode highly influences tourist attitudes and visit intentions toward a destination compared to static images and 360-degree tours. This effect is more significant among participants with higher levels of customer involvement. Finally, the results from the study offer empirical evidence of the effectiveness of VR in shaping user behavior compared to traditional preview modes.Research limitations/implicationsThe limitations are using a non-probability sampling method, a small sample size and affordable mobile-compatible VR headsets.Practical implicationsThis study offers empirical evidence on the effectiveness of VR in shaping tourist behavior compared to traditional preview modes. It helps destination marketers develop appropriate strategies for promoting tourist destinations.Originality/valueThe novelty of this paper lies in understanding the effectiveness of VR in shaping tourist behavior with different levels of customer involvement in travel decision-making.

AI recommendations’ impact on individual and social practices of Generation Z on social media: a comparative analysis between Estonia, Italy, and the Netherlands

Abstract Social media (SM) influence young adults’ communication practices. Artificial Intelligence (AI) is increasingly used for making recommendations on SM. Yet, its effects on different generations of SM users are unknown. SM can use AI recommendations to sort texts and prioritize them, shaping users’ online and offline experiences. Current literature primarily addresses technological or human-user perspectives, overlooking cognitive perspectives. This research aims to propose methods for mapping users’ interactions with AI recommendations (AiRS) and analyzes how embodied interactions mediated by a digital agent can lead to changes in social and cultural practices. For this, this work proposes a comparative analysis of central practices evoked by AI recommendations-mediated communication on SM among users in Italy, Estonia, and the Netherlands in the age category 18–26 years old. The data used in the comparative analysis was collected via semi-structured interviews and elaborated based on cognitive psychology and semiotics. This research highlights the contextual significance of AI recommendations as a mediator in creating new communication practices. Findings confirm that young adults often choose practices that would enhance their digital representations according to AiRS’ dominant patterns and categories. AiRS impacts individual interpretations and practices and can further affect social and cultural levels.

Security and Privacy Concerns in the Adoption of IoT Smart Homes: A User-Centric Analysis

The advancement of Internet of Things (IoT) technologies has ushered in a new era of smart homes, promising convenience and automation. However, alongside these advancements, concerns regarding the security and privacy of Internet of Things smart homes have garnered significant attention. The study embarked on a user-centric analysis, delving into the intricacies of security and privacy concerns in the adoption of Internet of Things smart homes. The primary purpose of this research was to investigate the security and privacy concerns that users harbour when adopting Internet of Things smart home technologies. We used SMART-PLS version (4.0.9.6) as the data analysis tool, to examine the concerns and to gain a comprehensive understanding of their impact on adoption. The analysis was, rooted in quantitative research design and based on data gathered through an online questionnaire distributed to the target population of 325 participants. The research response rate was 92%. The hypotheses examined unveiled statistically significant relationships, culminating in results indicating an R<sup>2</sup> of 0.762. This implies that approximately 76.2% of the rationale behind individuals' decisions to either adopt or refrain from using IoT smart home devices, with a focus on security and privacy considerations, can be elucidated by our proposed Structural Equation Model. his model served as a comprehensive lens through which we dissected the intricate interplay of variables shaping user attitudes and behaviors. The study sheds light on the critical concerns of security and privacy within the IoT smart home domain. By leveraging quantitative analysis and a well-crafted Structural Equation Model, we offer valuable insights into the factors influencing user adoption decisions. The research contributes to the broader discourse IoT technology adoption and serves as a foundation for future studies and policy considerations in the ever-evolving landscape of smart homes.

Exploring User Attitudes Toward Online Behavioral Advertising: Insights into Trust, Transparency and Privacy

This study explores the dynamic relationship between user acceptance and Online Behavioral Advertising (OBA). It aims to unravel how trust, transparency, and privacy concerns shape user attitudes and behaviors in the realm of personalized advertising. Employing a mixed-methods approach, the research integrates quantitative data from online surveys with qualitative insights from semi-structured interviews. The findings reveal that trust in advertisers and perceived transparency play important roles in influencing user acceptance of OBA. Interestingly, while privacy concerns negatively impact trust, they paradoxically enhance perceptions of OBA's effectiveness. The study further explores the nuanced interaction between transparency and trust, indicating that their combined effect differs from their individual influences. These insights are vital for advertisers and policymakers, underscoring the need for strategies that prioritize user-centric values like transparency and trust while addressing privacy concerns. The research contributes to the broader discourse in digital marketing, offering guidelines for ethical and effective personalized advertising practices.
 
 Received: 1 December 2023 / Accepted: 15 February 2024 / Published: 5 March 2024

Exploring the Stimulus Organism Response (SOR) Framework that Shapes Impulse Buying in the Epoch of E-Wallets in the Philippines

In the progressing digital financial landscape of the Philippines, the surge in e-wallet applications has vastly captured the interest of Filipino users. As e-wallets restructure how consumers manage their finances, a crucial question emerges: Can they influence impulsive buying tendencies? Using the (S-O-R) framework, the study reconnoitered the factors that incite impulse buying, expanding prior models by integrating both intrinsic and extrinsic stimuli. A total of 828 active e-wallet users were gathered using homogenous purposive sampling. After employing a Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis, the results elucidated five significant stimuli (i.e., perceived risk, visual appeal, subjective norms, convenience, and monetary savings) in shaping user satisfaction and perceived enjoyment. Conversely, information quality demonstrated statistical significance only in association with satisfaction. Moreover, the study highlighted those three factors (i.e., perceived enjoyment, subjective norms, and monetary savings) that directly impact impulse buying. Ultimately, it accentuates the full mediating role of perceived enjoyment in linking visual appeal with impulsive buying whilst showcasing a partial mediation effect in the relationship between cost savings and impulsive buying. Edifice on these findings, e-wallet providers have a strategic outlook to further invest in the following: (a) user-centric design strategies, (b) process enhancement for seamless user experience, and (c) optimization of user education.

How Does Interactivity Shape Users' Continuance Intention of Intelligent Voice Assistants? Evidence from SEM and fsQCA.

With the rapid expansion in the use of intelligent voice assistants (IVAs) in people's daily lives, how to improve users' continuous intention is crucial for the sustainable development of intelligent voice technology. Utilizing the stimulus-organism-response (S-O-R) framework, we propose a theoretical model to examine how three dimensions of interactivity (ie, two-way communication, responsiveness, perceived control) impact individuals' affective reactions (ie, psychological ownership, subjective well-being) and continuance intention of IVAs and how that effect differs technology readiness. To validate the proposed model, 412 valid samples were collected in China and underwent analysis using a comprehensive approach that incorporated partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The findings from the PLS-SEM analysis indicate that three dimensions of interactivity have significant impacts on affective reactions to varying degrees, thus affecting users' continuance intention. Among these dimensions, responsiveness is the strongest predictor of affective reactions. Additionally, the impact of subjective well-being on continuance intention is stronger when users with high technology readiness. Finally, the results from fsQCA support the PLS-SEM findings and provide three configurations with different combinations of antecedents that sufficiently explain high continuance intention. Our findings reveal the internal mechanisms through which the three dimensions of interactivity impact users' continued usage of IVAs. This study is among the first to examine the effects of dimensions of interactivity on behavioral intentions, utilizing both symmetric (PLS-SEM) and asymmetric (fsQCA) methodologies to identify the most significant dimensions of interactivity and determine sufficient combinations of dimensions to predict users' intention to continue using IVAs. These findings offer valuable and fresh insights for both theoretical understanding and practical application.

Exploring how non-clinical factors in childbirth care shape users’ experiences in public health facilities in rural Chiapas, Mexico: a qualitative study using the WHO health systems responsiveness framework

IntroductionMany Mexicans face barriers to receive delivery care from qualified professionals, especially indigenous and poor sectors of the population, which represent most of the population in the state of Chiapas. When access to institutional delivery care is an option, experiences with childbirth care are often poor. This underscores the need for evidence to improve the quality of services from the user’s perspective. The present study was conceived with the objective of understanding how non-clinical aspects of care shape women’s birthing experiences in public health institutions in Chiapas.MethodsWe conducted an exploratory qualitative study. Data collection consisted in 20 semi-structured interviews to women who had delivered in a public health facility in Chiapas during the last six months prior to the interview. For the design of the interview guide we used the WHO health system responsiveness framework, which focus on the performance of the health system in terms of the extent to which it delivers services according to the “universally legitimate expectations of individuals” and focuses on the non-financial and non-clinical qualities of care. The resulting data were analyzed using thematic analysis methodology.ResultsWe identified a total of 16 themes from the data, framed in eight categories which followed the eight domains of the WHO health systems responsiveness framework: Choice of the provider and the facility, prompt attention, quality of basic amenities, access to social support, respectful treatment, privacy, involvement in decisions, and communication. We shed light on the barriers women face in receiving prompt care, aspects of health facilities that impact women’s comfort, the relevance of being provided with adequate food and drink during institutional delivery, how accompaniment contributes positively to the birthing experience, the aspects of childbirth that women find important to decide on, and how providers’ interpersonal behaviors affect the birthing experience.ConclusionsWe have identified non-clinical aspects of childbirth care that are important to the user experience and that are not being satisfactorily addressed by public health institutions in Chiapas. This evidence constitutes a necessary first step towards the design of strategies to improve the responsiveness of the Chiapas health system in childbirth care.

Enhancing User Experience With a Generative AI Chatbot

With the rapid evolution of artificial intelligence (AI), this study aims to examine the interplay among the perceived usability, perceived enjoyment, perceived responsiveness, and intention to continue using ChatGPT. Structural equation modeling (SEM) was used to investigate our proposed model. We recruited 446 ChatGPT users through an online survey conducted on the Connect platform, powered by CloudResearch. Perceived usability (β = 0.254) and enjoyment (β = 0.438) significantly influence satisfaction with ChatGPT. However, perceived responsiveness is not significantly related to perceived attachment or satisfaction. Furthermore, we established that perceived attachment (β = 0.405) and satisfaction (β = 0.447) are pivotal in shaping users’ intentions to continue using ChatGPT, providing insights into human–AI interactions. The practical implications of our findings suggest that generative AI chatbots should be crafted with a focus on enjoyable, user-centered interfaces that foster long-term user satisfaction and engagement. AI developers should design AI conversation flows and chatbot personas to optimize the user experience.

AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students-an integrated analysis utilizing UTAUT and ECM models.

This study is centered on investigating the acceptance and utilization of AI Chatbot technology among graduate students in China and its implications for higher education. Employing a fusion of the UTAUT (Unified Theory of Acceptance and Use of Technology) model and the ECM (Expectation-Confirmation Model), the research seeks to pinpoint the pivotal factors influencing students' attitudes, satisfaction, and behavioral intentions regarding AI Chatbots. The study constructs a model comprising seven substantial predictors aimed at precisely foreseeing users' intentions and behavior with AI Chatbots. Collected from 373 students enrolled in various universities across China, the self-reported data is subject to analysis using the partial-least squares method of structural equation modeling to confirm the model's reliability and validity. The findings validate seven out of the eleven proposed hypotheses, underscoring the influential role of ECM constructs, particularly "Confirmation" and "Satisfaction," outweighing the impact of UTAUT constructs on users' behavior. Specifically, users' perceived confirmation significantly influences their satisfaction and subsequent intention to continue using AI Chatbots. Additionally, "Personal innovativeness" emerges as a critical determinant shaping users' behavioral intention. This research emphasizes the need for further exploration of AI tool adoption in educational settings and encourages continued investigation of their potential in teaching and learning environments.

Research on user response in virtual reality environment based on visualization and clustering

As the feasibility of virtual reality (VR) therapies is gradually being validated, understanding users' physiological and emotional responses to different VR environments is crucial for optimizing VR experiences and improving user engagement. This study aims to introduce machine learning models to analyze user responses to VR environments and identify user groups with similar physiological and emotional characteristics. This study employs visualization tools and clustering models to explore the role of various factors in shaping user experience. K-Means modeling helps the research team understand users' physiological and emotional responses to VR environments. The Principal Component Analysis (PCA) dimensionality reduction algorithm makes the model visualization easier to understand and implement. This study is conducted on a virtual reality experience dataset and produced many nuanced users experience results. The results of the experiments show that there is an apparent disparity in the experience of VR among users of different age groups. It also shows that different user groups have different levels of suitability for VR. Targeted improvements to VR can provide suggestions for people with different needs. This study has significant implications for analyzing and understanding the emotional responses and preferences of VR users and driving the personalization of VR products.

Exploiting social capital for improving personalized recommendations in online social networks

This article presents a novel approach to enhancing personalized recommendations in online social networks by exploiting the concept of Social Capital. Recognizing the challenges posed by information overload on platforms like Twitter, the proposed method integrates user interactions and features on social media with the concept of Social Capital to generate more relevant recommendations. The model incorporates a multifaceted analysis of user data, including the user’s reputation, influence, and engagement strength, alongside tweets’ recency, diversity, and context scores, to calculate a comprehensive Social Capital Score for each recommendation. An extensive offline evaluation of the model demonstrates its effectiveness in improving the personalization and relevance of recommendations. The findings highlight the significant role of incorporating Social Capital in recommender systems, contributing to a more engaging and informative user experience on social media platforms. This study provides valuable insights into the potential benefits and limitations of this approach, advancing the field of recommender systems and enhancing our understanding of the role of social capital in shaping user behavior and preferences.

Unveiling the Dynamics of Modern Web Design: Trends, User Engagement, and the Essence of UI/UX

In the ever-evolving digital landscape, the role of web design transcends mere aesthetics, becoming a linchpin in shaping user experiences. 'Unveiling the Dynamics of Modern Web Design' embarks on a journey beyond fleeting trends, delving into the foundational principles of user engagement and the core essence of UI/UX. This exploration recognizes web design as a dynamic language-communicating, engaging, and adapting. From deciphering trend language to unraveling user interaction psychology, the narrative unfolds the driving force behind impactful digital experiences. It's an invitation to comprehend how design choices resonate, forge memorable interactions, and elevate the digital journey. Keywords: Web design, UI/UX, user engagement, digital experiences, design trends, brand identity, adaptability, innovation, user-centric approach, visual aesthetics, functionality, accessibility, digital presence, competitive edge, user satisfaction, business success, design evolution

The co-construction and emotion management of hope within psychosis services.

There is a growing acknowledgement of the salience of hope for mental health service-users, in influencing care outcomes and recovery. Understandings of the processes through which hopes are co-constructed, alongside specific conceptualisations of experiences of hoping, remain limited however. This qualitative study explored how a range of stakeholders experienced and dealt with uncertainty within three purposively selected psychosis services in southern England. In this article we focus particularly on the co-construction of hope within participants' narratives and how this emotion work shaped experiences of hoping. In-depth interviews (n = 23) with service-users, professionals, managers and other stakeholders were analysed following a phenomenological approach. Hope was spontaneously identified by participants as a fundamental mechanism through which service-users and professionals managed uncertainty when vulnerable. Professionals were influential in shaping users' hopes, both intentionally and unwittingly, while some professionals also referred to managing their own hopes and those of colleagues. Such management of expectations and emotions enabled motivation and coping amidst uncertainty, for users and professionals, but also entailed difficulties where hope was undermined, exaggerated, or involved tensions between desires and expectations. Whereas, hope is usually reflected in the caring studies literature as distinctly positive, our findings point to a more ambivalent understanding of hope, as reflected in the accounts of both service-users and professionals where elevated hopes were described as unrealistic and harmful, to the well-being of professionals as well as of service-users. It is concluded that a greater awareness within care contexts of how hopes are co-constructed by professionals and service-users, explicitly and implicitly, can assist in improving health care and healthcare outcomes.

Exploring Generation Z's Perspective on Twitter as a News Discovery Platform: Insights from @CNNIndonesia Followers

This qualitative descriptive research aims to explore how Generation Z perceives the use of Twitter, particularly the @CNNIndonesia news account, as a platform for news discovery. Employing purposive sampling, in-depth interviews, and observations, the study reveals that followers retain knowledge obtained from @CNNIndonesia, emphasizing the critical role of perception indicators in influencing their attitudes. The informants express a preference for @CNNIndonesia, citing its reliability and alignment with their information needs. The results underscore the significance of perception in shaping user behavior on Twitter as a news source. Highlights : Digital Information Consumption: Explore how Generation Z consumes and retains news information through the Twitter platform, specifically focusing on the @CNNIndonesia account. Perception Indicators: Investigate the key indicators shaping the perceptions of Generation Z followers towards @CNNIndonesia as a reliable and preferred news source. User Behavior Influence: Highlight the significance of perception in influencing the behavior of Generation Z users on Twitter as they seek and engage with news content. Keywords: Generation Z, Twitter, News Discovery, @CNNIndonesia, Perceptions

Social Media and Radicalization: An Affordance Approach for Cross-Platform Comparison

To accentuate which platform characteristics particularly foster radicalization and extremist dynamics, this contribution investigates the affordances of social media as delineated in contemporary literature, conducting a platform comparison encompassing Telegram, WhatsApp, and X (formerly Twitter). Based on a scoping review, 17 affordances identified from studies researching radicalization dynamics on social media were extracted and categorized. The most frequently mentioned affordances—anonymity, visibility, and collectivity—were then further analyzed concerning their contribution to radicalization and the radicalization potential of these specific platforms. The platform-comparative affordance discussion shows that, although in principle each of the three compared platforms can foster an environment conducive to radicalization depending on user intention and context or use, the specific characteristics of each platform necessitate a nuanced consideration. On one hand, it is imperative to discern affordances differentially along various dimensions when assessing their implications (e.g., internal vs. external visibility). On the other hand, it is beneficial to consider which affordances emerge from the actualization of other affordances. For instance, collectivity can result from the interplay of several affordances, such as interactivity and anonymity, and can be referred to as a meta-affordance. Furthermore, the analysis shows that platform branding and self-presentation not only affect platform architecture and affordances but also shape users’ perceptions of the platform, thereby influencing the actualization of affordances. This was particularly noted in the literature for Telegram and increasingly for X. Specific assertions, nevertheless, are hindered by the conceptual diffusion of the affordance approach and a lack of empirical analyses directly and systematically examining platform affordances in conjunction with radicalization dynamics.

Factors Affecting English Foreign Language (EFL) Learners’ Acceptance of Content-Based Language Application for Language Learning

In recent years, investigating factors affecting learners’ acceptance has gained prominence. However, little is known about the effect of behavioural intention, and interactivity and engagement as mediating variables, particularly in the use of technology-based content application for language learning. This study explored the relationships among variables on learners’ acceptance of Content-Based Language Application (CBLA). The Unified Theory of Acceptance and Use of Technology (UTAUT) construct reveals a strong correlation with both self-efficacy and attitude. Performance expectancy demonstrates a positive correlation with attitudes, indicating that learners’ beliefs about favourable outcomes and performance in language learning influence their attitudes positively. Social influence exhibits a critical correlation with behavioural intention, highlighting the role of social factors in shaping learners’ intentions to engage in language learning activities. Effort expectancy shows a positive direct correlation with self-efficacy and attitude. Social influence significantly affects self-efficacy and attitude, and these effects are mediated by behavioural intention, as well as interactivity and engagement. These findings underscore the important role of social factors in shaping learners’ self-efficacy beliefs and attitudes, which in turn influence their behavioural intentions. Facilitating conditions have a substantial direct effect on behaviour, while interactivity and engagement act as mediators in the relationship between facilitating conditions and self-efficacy and attitude, highlighting their significance in shaping users’ attitudes and intentions to adopt and use content-based language application. Future research can investigate the suitability of the suggested model in other linguistic settings for broader applicability of the results. In light of the ever-evolving nature of technology and language learning, longitudinal studies could offer valuable insights into the lasting effects and stability of the observed relationships over an extended period.