Enablers of the Use of Virtual Assistants by Students at a Nigerian University

Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers' perspective, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price/value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust, and personal innovativeness. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price/value, and perceived privacy risk were not significant factors in the users' intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies.

The rise in the use of virtual assistants such as Siri, Google Assistant, or Alexa among different sectors of society is facilitating access to information and services that were previously inconceivable due to the existing digital divide due to age. This situation allows especially the elderly to perform tasks much more easily and to access applications and services that could be a challenge for them with other digital user interfaces. With this in mind, the EMERITI project aims to improve the lives of the elderly through the use of virtual assistants in different case studies. In this sense, virtual voice assistants along with the use of Internet of Things (IoT) technologies can contribute to avoid sedentarism in the elderly; however, it is necessary to address the problem of proactivity presented by the virtual assistants available in the market. This article presents a solution that, through the use of activity monitoring smart bracelets, IoT devices and virtual voice assistants allow the elderly to monitor their daily physical activity simply by using their voice and therefore prevent them from sedentary patterns. Finally, this study presents the technical results obtained after the deployment of the proposed system and discusses the main advantages and the current challenges of the use of virtual assistants in applications to prevent sedentary lifestyles in the elderly.

This study examined the perceptions of caregivers of young childhood cancer survivors (YCCS) regarding the use of virtual assistant (VA) technology for health information seeking and care management. The study aim was to understand how VAs can support caregivers, especially those from underserved communities, in navigating health information related to cancer survivorship. A qualitative study design was employed, involving semi-structured interviews and focus groups with 10 caregivers of YCCS from metropolitan, rural, and Appalachian regions, recruited from a large pediatric academic medical center in the Midwest. A web-based VA prototype was tested with caregivers, who provided feedback on its usability, utility, and feasibility. Data were analyzed using thematic analysis to identify key themes related to caregivers' interactions with and perceptions of the VA technology. We identified four major themes: Interface and Interaction, User Experience, Content Relevance, and Trust. Caregivers expressed preferences for multimodal interactions (voice and text), particularly valuing flexibility based on context. They emphasized the need for accurate, relevant, and easily retrievable health information tailored to their child's needs. Trust and confidentiality were critical, with caregivers favoring VAs integrated with trusted healthcare systems. While VAs were perceived as valuable tools for reducing search fatigue and cognitive burden, caregivers highlighted the need for improved conversational depth, personalization, and empathetic response. VAs hold promise as support tools for caregivers of YCCS, particularly in underserved communities, by offering personalized, credible, and accessible health information. To maximize their potential, research and development efforts should focus on building trust-building, integrated, and personalized VAs. These enhancements can help VAs further ease caregiving tasks and support caregivers in managing complex health needs.

Abstract: The popularity of artificial intelligence (AI) technology has driven the creation of new strategies in online shopping, combining technological interaction and commercial transactions through the use of virtual assistants like ChatGPT. Although this technology is still in the exploration phase among consumers, several studies have attempted to uncover the factors influencing consumers' intention to use ChatGPT for product information search, such as performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habit, AI self-efficacy, perceived satisfaction, and social influence. However, findings remain inconsistent. This study aims to address this gap by analyzing the determinants of consumers’ intention to use ChatGPT as a source of shopping information. A total of 269 active ChatGPT users participated, and the data were analyzed using SPSS and PLS-SEM via SmartPLS. The results show that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habit, AI self-efficacy, and perceived satisfaction positively and significantly influence intention to use ChatGPT. Conversely, social influence shows no significant effect. This study contributes to marketing literature on AI usage in e-commerce and offers practical insights for marketing managers to design strategies that optimize ChatGPT to enhance consumer experience and promote AI adoption in the Indonesian market.

People in vulnerable positions who need support in their daily lives often face challenges in receiving timely access to care; for instance, due to disabilities or individual and situational vulnerabilities....

The objective of this article was to verify how virtual assistants have contributed to the accessibility of students with ADHD in higher education. As a methodological procedure, we interviewed students with ADHD enrolled in undergraduate and graduate courses at higher education institutions. All those selected are from different Brazilian states and use virtual assistants for at least six months. The approach was carried out through social networks, after some posts by the selected ones about the use of virtual assistants and their diagnosis of ADHD. The in-depth interviews were structured around three axes: user profile, use of virtual assistants and use with an educational focus. The results highlight the importance of developing technologies already thinking about the accessibility requirement. We understand that access to different technologies can facilitate academic performance and the development of potential for students with ADHD.

Relevance. In the modern world, artificial intelligence (AI) is one of the fastest growing areas of information technology, which is increasingly penetrating into various spheres of human activity. In the context of public and municipal management, AI is a technology that is able to automate and optimize work processes, improve the quality of services provided to citizens, and increase the level of security and transparency of government work.The purpose is to analyze the possibilities and risks of using artificial intelligence in state and municipal management, as well as to determine the prospects for its development in this area.Objectives: to analyze the advantages of using artificial intelligence in state and municipal management; to study the risks and challenges associated with its implementation; to analyze trends in the development of artificial intelligence in this area, as well as to determine the prospects for its use.Methodology. Empirical, theoretical, statistical and graphical representation methods were used in the course of scientific research.Results. The study revealed the advantages of AI in public administration (improving efficiency, improving the quality of services, transparency, security); risks and challenges were studied (lack of infrastructure, risk of privacy violations, problems of transparency of algorithms, risk of discrimination); trends in the development of AI were analyzed (e-government, optimization of workflows, personalization of services, monitoring of social media, security); the prospects of using AI (smart cities, virtual assistants, hybrid systems, decision support, cooperation with business, international cooperation) have been identified.Conclusions. Artificial intelligence can significantly improve the efficiency and quality of public and municipal administration. However, for the successful implementation of AI, it is necessary to solve problems such as the lack of infrastructure and qualified specialists, ensuring data security, transparency of algorithms and compliance with the regulatory framework. To do this, it is necessary to conduct further research, develop integrated approaches and take into account world experience. The prospects for using AI include the creation of smart cities, the use of virtual assistants, hybrid systems, decision support systems, business cooperation and international cooperation.

Background. Technological innovations have become an important agent of social change, creating new socio-psychological meaning. In this context, G.M. Andreeva's idea that social psychology should help people adapt to changing environments remains relevant. Objectives. This paper aims to highlight the socio-psychological perspective on the role of innovative technologies in social change. We present two empirical studies that demonstrate emerging socio-psychological patterns in the context of open-source software development (study 1) and the use of virtual assistants (VA) for economic decision-making (study 2). Study Participants. Study (1): 900 posts from a collaborative development platform. Study (2): 200 users of the VA popular in Russia, residents of Russian cities with a population of more than 500,000 people. Methods. Study (1): Content analysis using large language models. Study (2): Quantitative online survey assessed users' perception of their VA and previously unknown VA across 15 characteristics, subjective trust levels, and economic trust through scenarios involving monetary transactions. Results. Study (1): A pre-configured GPT-4 turbo model with an instruction consisting of two examples achieved 56% accuracy in classification. Using a fine-tuned model of the previous generation, DeBERTa-v3-Small, increased the efficiency of classifying developer messages by up to 70%. This allowed the model to be used to encode developer interactions in order to identify the factors that contribute to effective collaboration. Study (2): Both forms of trust (declared and economic) are significantly related to components of social representations (SR) of VA. Individual components of these perceptions correlate with both declared and economic trust at the level of r > 0.3, p < 0.05. However, there is a difference in the strength of these relationships for familiar and unfamiliar VAs. An assumption can be made about the possible influence of the duration of use of VA on the strength of connections between SR and trust in VA. Thus, SR formed through interaction with VA contributes to a trusting attitude towards it and, accordingly, to decision-making processes involving its use. Conclusions. Socio-psychological knowledge about the changing socio-psychological meaning can form the foundation for the development of human-centered technologies. As a part of professional work, a developer can improve current tools for the creation, management, and optimization of collaborative activities. In everyday life, it is also important to establish a level of trust that is appropriate for the situation in which a Virtual Assistant is used.

Commercial deep learning capabilities are available for many applications such as computer vision processing and intelligent chat bots. The Google Cloud Platform product Google Dialogflow provides lifelike conversational artificial intelligence (AI) using machine learning (ML) to generate natural conversations between computers and humans. This ML utilizes natural language understanding (NLU) to recognize a user's intent and extracts key information into a form of entities. We have developed a user-friendly application through understanding the hazardous material database, first aid safety guidelines and observing the process of first responders who access this information in the field. We created the Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL) virtual assistant using Dialogflow¹ and TensorFlow² paired with EasyOCR.3 The chatbot supports first responders by providing voice interaction which helps limit additional steps such as browsing through multiple categories when searching for information. Using feedback from our field interviews, the voice interface has been developed to enable the first responder to focus on the immediate emergency. With less distractions, the first responder is able to engage the incident more effectively. The partial hands-free TruePAL chatbot assistant improves the accessibility to the correct guidance by an average of 1.9 seconds compared to the widely used application, NIH WISER, which requires full attention to operate. We combined this intelligent chatbot with a separate visual processing capability to produce hazardous signage analysis and generate the proper guidance for first responders. With the evolving functionality of AI tools, the use of virtual assistants in first responder technology will be an advancement, benefiting the safety of both first responders and civilians.

Due to the increased use of Virtual Assistants (VAs) for various personal usage, the safety of VAs from various spoofing attacks is utmost important. To that effect, we investigate the significance of Delay-and-Sum (DAS) beamformer over state-of-the-art Minimum Variance Distortionless Response (MVDR) along with Teager Energy Operator (TEO)-based features for replay Spoof Speech Detection (SSD) on VAs. Conventional DAS method is known to suppress the additive noise component and retains the reverberation effect (i.e., an important acoustic cue for replay SSD). On the contrary, MVDR used for Distant Speech Recognition (DSR) suppresses the reverberation effect and additive noise. Hence, MVDR is not suitable choice for replay SSD, whereas DAS can be exploited for replay SSD in VAs. Furthermore, suppression of reverberation due to the DAS vs. MVDR beamformer is analyzed via TEO profile. The experimental validation is done on recently released Realistic Replay Attack Microphone-Array Speech Corpus (ReMASC) and its DAS vs. MVDR beamformed versions. Furthermore, Teager Energy Cepstral Coefficients (TECC) feature set is employed as it is recently shown to capture the characteristics of reverberation for replay SSD task. For performance comparison, Constant-Q Cepstral Coefficients (CQCC), Linear Frequency Cepstral Coefficients (LFCC), and Mel Frequency Cepstral Coefficients (MFCC) feature sets along with Gaussian Mixture Model (GMM) classifier are used. In particular, TECC-GMM SSD system on DAS gave relative reduction in %EER by 13.12% and 43.16% for Eval set as compared to the original ReMASC and its MVDR beamformed version, respectively. Finally, relative significance of TECC w.r.t. practical deployment is shown through latency analysis of various SSD systems for VAs.

Virtual assistants (VA) like Siri, Alexa, or Google Assistant are becoming household names - especially for families with young children. Scientific inquiry studying this user population and their intention to use VAs at home, however, remains scarce. By bridging the Technology Acceptance Model, Uses and Gratifications theory, and the first proposition of the Differential Susceptibility to Media Effects Model, this study disentangles (1) different types of families with (2) different motivations for (3) different forms of VA-usage (i.e., parent only, child only, co-use). Cross-sectional survey data (N = 305) from Dutch parents with at least one child between 3 and 8 years and a Google Assistant-powered smart speaker in their home show that (1) families mostly differ along parents' digital literacy skills, frequency of VA-use, trust in technology, and preferred degree of child media-mediation. (2) Hedonic motivation is key for parents to (3) co-use the VA together with their child(ren). New pathways for the methodological and theoretical study of technology use in families are highlighted. Developers can best anchor VA-application among families in aspects of enjoyment while scholars and policy makers might wish to consider additional meaningful intervention criteria for the future study and guidance of family VA-use practices. (197 words).

The lack of practice to develop language skills is the main problem in learning foreign languages. The aim of the research is to establish methodological strategies with virtual assistants, for elementary school students through innovative and interactive classes, to develop the macro skills of the English language. The methodological design of this study is based on a mixed qualitative-quantitative approach, with the participation of an expert on "Virtual assistants in the English language", five teachers from the English area and 57 elementary school students from a private school in Ecuador. The data collected from the teachers made it possible to identify the main problems that students have when it comes to developing macro skills in the English language. With the support of the education expert, a strategy was designed using virtual assistants. The personal assistant Alexa, with great programming flexibility, was selected, applying a strategy focused on four macro skills: listening, reading, speaking, and writing. Each activity was aimed to reinforcing each skill according to students’ level at school. For example, for speech skills, students had to engage in a dialogue with Alexa through a game of questions and answers. For listening skills, Alexa would tell a story to determine the level of comprehension. For reading skills, the students were given a reading from which they were asked questions that Alexa could answer and through this the students developed writing skills according to the questions they answered. After the intervention, a post test was applied and it was shown that there was an improvement in the development of skills. It was concluded that the interactive classes motivated the participation of all students. For future work, we intend to carry out a longitudinal study with the use of virtual assistants and a comparison between other devices.

The rapid advancement of technology has revolutionized the field of education, providing new opportunities for enhancing the learning experience. This paper explores the implementation of virtual assistant technology and virtual office management in the context of education to improve teaching and learning processes. Additionally, virtual office management facilitates streamlined document sharing, project collaboration, and group discussions, promoting teamwork and enhancing the overall learning process. This paper investigates various case studies and pilot programs where educational institutions have successfully implemented virtual assistant technology and virtual office management systems. The impact of these technologies on student engagement, academic performance, and administrative efficiency are examined. Knowledge of virtual office management and virtual assistant applications (average value) increase from 4.5 for pre test to 9.5 for post test. The use of virtual assistants in improving the quality of learning from 45% before training to 100% after training. The use of virtual office management in improving the quality of learning from 40 % before training to 90% after training. Furthermore, the challenges faced during implementation and strategies for overcoming them are discussed.

Purpose of ReviewWith the rising cost of cardiovascular clinical trials, there is interest in determining whether new technologies can increase cost effectiveness. This review focuses on current and potential uses of voice-based technologies, including virtual assistants, in cardiovascular clinical trials.Recent FindingsNumerous potential uses for voice-based technologies have begun to emerge within cardiovascular medicine. Voice biomarkers, subtle changes in speech parameters, have emerged as a potential tool to diagnose and monitor many cardiovascular conditions, including heart failure, coronary artery disease, and pulmonary hypertension. With the increasing use of virtual assistants, numerous pilot studies have examined whether these devices can supplement initiatives to promote transitional care, physical activity, smoking cessation, and medication adherence with promising initial results. Additionally, these devices have demonstrated the ability to streamline data collection by administering questionnaires accurately and reliably. With the use of these technologies, there are several challenges that must be addressed before wider implementation including respecting patient privacy, maintaining regulatory standards, acceptance by patients and healthcare providers, determining the validity of voice-based biomarkers and endpoints, and increased accessibility.SummaryVoice technology represents a novel and promising tool for cardiovascular clinical trials; however, research is still required to understand how it can be best harnessed.

In recent years the use of virtual assistants has been extended in a large number of applications to provide comfort to the user. This article proposes the development of an IoT (Internet of Things) environment to control an industrial process through voice commands using these devices, where the operator can interact and control the process using his voice. In the first part, a review of works where virtual assistants are used for automation and control processes is made, then the proposed architecture is presented, where we detail the protocols and media used. Next, the development of the system and the validations carried out in an industrial environment are presented, considering its own characteristics. Finally, we detail the conclusions of the project focused on minimizing access times to a control interface, and the growing use of these technologies at different levels of the automation pyramid considering its benefits and limitations