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The author proposed a mobile learning model of pervasive animated games which allows college students to learn via games accessed through a smartphone. It can develop the process of field observation and self-reflection to enhance learning effectiveness, and the motivation, and attitude of students towards learning.

The author proposed a model for teaching via pervasive animated games. The author used SPSS software and Pearson's correlation coefficients to explore different mobile learning strategies and their relationship with learning attitudes and achievement. Participants were vocational technology college students, who each experienced animated games in individual and group learning settings.

The results found that the learning performance of students in the individual learning group was better than that of the group learning group. A higher level of digital experience was associated with better learning performance, and a more positive attitude towards using mobile phones was associated with better learning performance.

The learning method still has its limitations, the learner's digital information level, learning mode, learning attitudes will have an impact on the student playing teaching pervasive animation games. Therefore, improving student information level is one of the important topics of teaching pervasive animation games and mobile learning.

The author proposed a mobile learning strategy based on pervasive animated games. The result in the strategy of mobile learning shows that the level of students' digital experience and the overall design of animated games are important criteria for successful implementation.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Augmented reality (AR) and virtual reality (VR) are becoming increasingly interwoven into people's daily lives, with applications in fields such as science, engineering, medical, the arts, education, finance and business. While much study has been conducted in the field of VR and AR in a variety of areas, less attention has been paid to online education. The purpose of this research is to conduct a systematic review of studies on AR and VR, as well as its applications in many disciplines of education, with a special emphasis on online education.

The data were gathered from the SCOPUS database under the subject “Augmented and Virtual Reality Applications in Online Education.” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format has been used to summarize the available literature and research in academics throughout the world. First, systematic literature reviews and later bibliometric analysis were conducted for performance and science mapping analysis.

The research adds to the body of knowledge about the role of AR and VR in online education and its future prospects. AR and VR have demonstrated a substantial contribution to facilitating teaching in a variety of fields, including engineering, medicine, nursing and chemistry. Additionally, this research indicates that AR and VR can be utilized to teach various areas and specialties. Additionally, it can be used in other aspects of online education, such as admissions, industry visits, training, internationalization and specific courses for students with disabilities.

This research lays the framework for educational institutions, legislators and researchers to investigate additional applications of VR and AR. Though this research suggests some possible uses for AR and VR in the online education system, more applications can be integrated into the online education system to fully leverage the potential of AR and VR worldwide. AR and VR have the potential to be a very cost-effective method of delivering online education on a wide scale in the future.

The article explores the applicability of VR and AR in education using bibliometric analysis. This is one of the first studies to do an assessment of VR and AR, evaluating their strengths, drawbacks and current applications. Future application areas are also identified as a result of the investigation.

A makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a university library is vital, as it fosters innovation, interdisciplinary learning, practical skills, entrepreneurship and career readiness while transforming the library into a dynamic centre for hands-on education and collaboration. Nevertheless, the wide-ranging functions and uses of makerspace equipment can potentially lead to a situation where librarians are overwhelmed by their duties due to manpower constraints. Therefore, this study aims to develop a novel game-based augmented reality navigation system (GARNS) based on the Octalysis gamification framework and scaffolding theory to support makerspace user education, hoping to promote learners’ learning motivation and their immersive experience and to enhance the learning performance of makerspace user education.

With a true experimental research method, 24 grade 11 students from a high school in Keelung City, Taiwan, were recruited to participate in the experiment on makerspace user education. Among them, ten students were randomly assigned to the experimental group using the GARNS and the other seven students were randomly assigned to a control group using the Web navigation system. The remaining seven students were assigned to a second control group using the narrative guided tour with a librarian to conduct makerspace user education.

Analytical results show that learners can achieve significant learning effectiveness using the GARNS, Web navigation system or traditional narrative guided tour with a librarian for makerspace user education. There were no significant differences in learning effectiveness and motivation neither between the GARNS group and the narrative guided tour with a librarian group nor between the Web navigation system group and the narrative guided tour with a librarian group. However, there were significant differences in learning effectiveness and motivation in terms of the value and expectation dimensions of learning motivation between the GARNS group and the Web navigation system group, and the GARNS group was significantly better than the Web navigation system group.

The study’s practical implication on makerspace user education is to reduce the manpower of a university library with makerspace services by the proposed GARNS that can offer a practical solution to enhance the learning effectiveness and motivation of makerspace through immersive game-based autonomous learning. Additionally, the study’s theoretical contribution lies in its innovative combination of game-based learning and scaffolding theory, while its practical significance stems from its potential to revolutionize makerspace user education, enhance motivation and performance and influence the broader landscape of educational technology.

This study combines game-based learning with augmented reality tools to develop a novel GARNS, which provides an innovative and effective learning tool suitable for the characteristics of makerspace and contributes to promoting makerspace user education and diversified learning modes. Additionally, most interviewees believed that using GARNS for educating makerspace users could assist them in consistently evaluating, choosing and discovering educational tasks in a library makerspace. This study contributes to promoting the popularization of makerspace user education.

The post-pandemic recognises changes are required; universities need to rethink their e-servicescapes strategies by offering different approaches to enhance students’ learning. This study aims to draw on learning self-efficacy trajectories and propose a conceptual model for exploring the predictive validity of satisfaction. In addition, it explores the mediating role of e-servicescapes and the moderating relationship effect of mature and younger students.

Learning self-efficacies is incorporated into the design of the model in an attempt to understand student cognition. The influences of e-servicescape on adopting online preferences and satisfaction are also examined. The model was empirically validated by surveying 266 respondents. Structural equation modelling and multi-group analysis were used to analyse the data.

The results of this study show learning self-efficacies has no significant influence on satisfaction. Yet, they showed a significant influence on e-servicescapes. E-servicescapes positively influenced satisfaction and preference for adopting online learning. E-servicescapes also had a mediating effect between self-efficacy to complete a course and satisfaction, as well as self-efficacy to interact with instructors and satisfaction. It had a negative suppressed effect on social interaction.

The research makes the following contributions. Firstly, the conceptualised model identifies an association between learning self-efficacies and e-servicescapes, suggesting universities as service providers can maximise the value offerings of their customer assets. Secondly, e-servicescapes demonstrate a full mediating effect between self-efficacies and satisfaction, indicating that if universities are to compete successfully in dynamic markets, they should co-create value in their e-servicescapes domain to increase satisfaction. Thirdly, the study recognises the need for a hybrid system of both face-to-face and online delivery because the multi-group analysis shows mature age preference for online learning is required to make this transformation successful.

The purpose of this study is to discuss how organizations can drive organizational performance through human capital (HC) investment through systematic thinking.

This study analyzes three companies from various industries, adopts systems thinking and uses three leading indicators from the balanced scorecard framework to explore the effects of strategic orientations for HC on innovation ecosystems and organizational performance.

In terms of academic contributions, this study broadly verifies the innovation ecosystem model for organizations and reveals that customer-oriented, internal process-oriented and innovation learning-oriented HC strategies reinforce the pathways in organizational innovation ecosystems, thereby enriching the literature on innovation ecosystems.

In terms of practical contributions, this study provides a novel HC-based perspective on developmental dynamics and details the relationships among each aspect of the innovation ecosystem and HC strategies.

The proposed architecture and strategic frameworks provide a reference for corporations to implement strategic orientations of HC, drive operations in organizational innovation ecosystems and improve organizational performance.

The purpose of this study is to investigate the effect of using mobile devices as an instructional tool on teachers' creativity and to promote their usage as instructional tools in educational settings. The research also studies the perceptions of teachers on the effect of using mobile devices as an instructional tool on their creativity and what features of mobile devices are believed to help in terms of enhancing their creativity.

This qualitative inquiry used an interpretive phenomenological analysis (IPA) method for inspecting the professional capabilities of Pakistan's primary and secondary school teachers. Data were gathered from nine individuals through interviews. Three themes regarding creativity emerged from the study data.

It is found that the use of mobile devices as a teaching tool significantly increases teachers' creativity by enabling them to manifest their creativity and explore different pedagogical vistas in which they can use a wide variety of instructional resources and tools. Using mobile devices as a teaching tool improved three skills: motivation, self-confidence and communication skills. Mobile applications, cameras and portability of these devices are among the features that teachers considered to have encouraged their creativity.

Finding the obstacles and difficulties teachers have while utilizing these tools to demonstrate their creativity may be valuable for future studies. First, because respondents were teachers from elementary and secondary classes, the population was not entirely homogenous, even though they had adequate help. Second, only semi-structured interviews were utilized for data gathering in this study. Further data collection methods, including observational research or participant-written reflective diaries, are thought to have been preferred.

For future research, it may be interesting to determine whether the results of this study can be applied to other demographic groups. Based on this study, it is also recommended to conduct a quantitative study to know teachers' perceptions of the impact of these devices on creativity, since these studies can have promising results for teachers.

Through the use of various materials, tools and activities, these devices provide several distinctive teaching alternatives. Because of this, using it as a teaching tool gives teachers the ability to tailor courses to a range of learner types. Additionally, having easy access to a multitude of online resources and the capacity to interact with others helped in ideation. The teachers experienced feelings of motivation, self-confidence and a desire to impart information, all of which are traits of creative teachers. Based on the findings of this study, we may now think about using mobile devices in the classroom to encourage teachers' creativity.

The outcomes of this research indicated that teachers' creativity is strongly influenced by their use of mobile devices as instructional tools. This paper advances the understanding of teachers’ creativity by highlighting their lived experiences. This study is novel because it highlights how these devices have the potential to be used as instructional tools, which has not been highlighted by any study so far.

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques.

Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability.

There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains.

The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers.

As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians.

This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

The purpose of this study is to identify the knowledge gap and future opportunities for developing mobile recommender system in tourism sector that lead to comfortable, targeted and attractive tourism. A recommender system improves the traditional classification algorithms and has incorporated many advanced machine learning algorithms.

Design of this application followed a smart, hybrid and context-aware recommender system, which includes various recommender systems. With the recommender system's help, useful management for time and budget is obtained for tourists, since they usually have financial and time constraints for selecting the point of interests (POIs) and so more purposeful trip planned with decreased traffic and air pollution.

The finding of this research showed that the inclusion of additional information about the item, user, circumstances, objects or conditions and the environment could significantly impact recommendation quality and information and communications technology has become one part of the tourism value chain.

The application consists of (1) registration: with/without social media accounts, (2) user information: country, gender, age and his/her specific interests, (3) context data: available time, alert, price, spend time, weather, location, transportation.

The study’s social implications include connecting the app and registration through social media to a more social relationship, with its textual reviews, or user review as user-generated content for increasing accuracy.

The originality of this research work lies on introducing a new content- and knowledge-based algorithm for POI recommendations. An “Alert” context emphasizing on safety, supplies and essential infrastructure is considered as a novel context for this application.