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The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

This systematic review paper aims to examine extant empirical research involving educational technology during COVID-19 to provide an aggregated analysis of how the pandemic has influenced educational technology research.

Using a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic review and an integrative review methodology, 50 primary research studies were selected from ten top-ranked educational research journals. These studies were reviewed regarding research purposes, methodologies, instruments, educational level, geographical distribution, and findings of the studies.

The findings reveal four emerging themes: influencing factors, effectiveness, challenges and teachers. The majority of the studies focused on higher education. Quantitative research design based on a questionnaire was the most adopted method of investigation by researchers.

Search parameters focused on the top 10 journals in the field of educational technology. Although this provides a level of quality, it narrowed the search.

For practitioners and researchers, this study provides a summary of the field to better understand what knowledge we have gained on the use of educational technology to enable a more agile, knowledgeable response to education in future emergencies.

This systematic review is unique in examining how the pandemic has influenced educational technology research. It also provides insight into gaps in the research that future researchers can use as a springboard to enable a more knowledge and a more agile approach to future emergencies.

This study aims to enhance the understanding of the current research landscape regarding the utilisation of telepresence robots (TPRs) in education.

The bibliometric and thematic analysis of research publications on TPRs was conducted using papers in the Scopus database up to 2023. The final analysis focused on 53 papers that adhered to the selection criteria. A qualitative analysis was performed on this set of papers.

The analysis found a rising trend in TPR publications, mostly from the USA as conference papers and journal articles. However, these publications lacked technology integration frameworks, acceptance models and specific learning design models. TPRs have proven effective in various learning environments, fostering accessible education, better communication, engagement and social presence. TPRs can bridge geographical gaps, facilitate knowledge sharing and promote collaboration. Obstacles to implementation include technical, physical, social and emotional challenges. Publications were grouped into four thematic categories: didactic methods of using TPRs, TPRs for educational inclusivity, TPR as a teacher mediator and challenges in using TPRs. Despite the significant potential of TPRs, their broader adoption in education is still facing challenges.

This research solely analysed research papers in the Scopus database, limiting TPR publications with the keywords “telepresence robots”, “learning”, “teaching” and “education”, excluding studies with different other keywords.

This study enhances understanding of TPR research in education, highlighting its pedagogical implications. It identifies a gap in the inclusion of technology integration frameworks, acceptance models and learning design models, indicating a need for further research and development.

The use of augmented reality (AR) and experiential learning go hand in hand. Although AR learning opportunities have been well discussed, there is limited empirical research on the use of AR within higher education settings. Drawing from the uses and gratifications theory (U&GT), this study aims to explore the use of AR for learning satisfaction and student engagement, while also examining differences in learning styles.

This study used experiments with higher education students in the UK to explore the use of AR as part of the learning experience. Data from 173 students who experienced AR as part of their learning experience were analysed using partial least square analysis.

The authors found that hedonic, utilitarian, sensual and modality gratifications influence AR learning satisfaction and student engagement. Furthermore, the authors found differences between active and passive learners with regards to utilitarian (information seeking, personalisation) and sensual gratifications (immersion, presence) and effects on learning satisfaction.

This study developed and validated a U&GT framework incorporating different learning styles rooted in Kolb’s learning cycle. Findings provide important implications for the use of commercial AR applications as part of the learning experience within higher education settings.

The effect of e-learning success relies on the learning management system and its effectiveness provided to the learners. As a result, higher education institutions (HEIs) are expanding using various e-learning platforms and focusing on system and information quality. This study adopts the ISS (information system success) model to assess students' perception of e-learning system success (e-LSS).

A quantitative research approach was used to analyse 151 students' perceptions collected from HEIs in Oman. The survey instrument was built on prior research related to DeLone and McLean’s ISS model, and expert opinion was involved for validation. The snowball sampling method was used to collect the data, and participants' anonymity and confidentiality were maintained as part of the ethical process. The reliability of data was tested using Cronbach's alpha analysis. A statistical tool like correlation was used to examine the relationship between the study variables (system quality, information quality, user satisfaction and e-LSS).

This study’s results revealed that students positively perceived system usage, and users' satisfaction with e-learning systems (e-LSs) was high. Moreover, the correlation results indicated that the system and information quality aspects of e-learning significantly influence e-LSS.

The study results on students' perspective towards e-learning information systems can be advantageous to HEIs and various stakeholders like policymakers, and e-learning platforms. It may support and assist the HEIs and corporate firms in deciding on e-learning platforms for students and learners, respectively. Moreover, the consolidated findings will contribute to the existing literature on e-learning success factors from students’ perspectives.

This study examines the students' perception of e-LSS in Oman HEIs and advocates prospects for further in-depth study and analysis.

Mobile learning has seen tremendous growth over the years. Like any other software application, usability is one of the key concerns in its successful implementation. There is a lack of study that provides a comprehensive overview of usability testing of mobile learning applications. Motivated by this a mapping study is conducted.

A systematic mapping study was conducted using 51 papers retrieved from the Scopus database published between 2005 and 2022 that reported on usability testing of mobile learning applications.

The key findings suggest that research is expected to expand in the near future. User-based testing is the commonly used method, while data are collected mainly through questionnaires, observation and interviews. Testing is mainly conducted in a controlled environment.

The study provides (1) an evidence-based discussion on usability testing of mobile learning applications, (2) an up-to-date map on state of the art on usability testing of mobile learning applications and (3) providing direction for further research to scientifically strengthen the field.

This study aims to examine the relationships between organizational learning capabilities, open innovation and firm performance (FP) in the context of small and medium enterprises (SMEs) in the emerging economies.

Data collected from 384 manufacturing SMEs operating across the seven emirates of the UAE were statistically analyzed using SmartPLS 3 to examine the hypotheses of this study.

The results show that organizational learning capabilities positively influences both inbound and outbound dimensions of open innovation (OI). Inbound open innovation (IP) practice positively impacted both market effectiveness and profitability, while outbound open innovation (OP) practice only affected profitability. Findings further confirmed the mediating role of IP practice on the relationships of organizational learning capabilities with market effectiveness and profitability. In contrast, OP practice did not mediate the relationships of organizational learning capabilities with market effectiveness and profitability.

To the best of the authors knowledge, this is among the first study contributing to the extant innovation literature in terms of investigations into the significant and complex interrelations of organizational learning capabilities, OI and FP in a single study, demonstrating various theoretical implications in the context of manufacturing SMEs in emerging countries. Overall, the findings of this study confirmed that the owners/managers of the UAE’s manufacturing SMEs need to be acquainted with the need of creating a working environment fostering organizational learning processes and capabilities to enhance IP and OP activities, thereby improving their market effectiveness and profitability.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether gamification and personalization as environmental stimuli to learners’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs) and, in turn, their learning outcomes in MOOCs.

Sample data for this study were collected from learners who had experience in taking gamified MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 331 usable questionnaires were analyzed using structural equation modeling.

This study demonstrated that learners’ perceived gamification and personalization in MOOCs positively influenced their cognitive LE and emotional LE elicited by MOOCs, which jointly explained their LP in MOOCs and, in turn, enhanced their learning outcomes. The results support all proposed hypotheses and the research model, respectively, explaining 82.3% and 65.1% of the variance in learners’ LP in MOOCs and learning outcomes.

This study uses the S-O-R model as a theoretical base to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is influenced by gamification and personalization. Noteworthily, while the S-O-R model has been extensively used in prior studies, there is a dearth of evidence on the antecedents of learners’ learning outcomes in the context of MOOCs, which is very scarce in the S-O-R view. Hence, this study enriches the research for MOOCs adoption and learning outcomes into an invaluable context.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from medical professionals at six university-/medical university-affiliated hospitals in Taiwan. A total of 600 questionnaires were distributed, and 309 (51.5%) usable questionnaires were analyzed using structural equation modeling in this study.

This study certified that medical professionals’ perceived MR, HSI and HHI in MOOCs positively affected their emotional LE, cognitive LE and social LE elicited by MOOCs, which together explained their LP in MOOCs. The results support all proposed hypotheses and the research model accounts for 84.1% of the variance in medical professionals’ LP in MOOCs.

This study uses the S-O-R model as a theoretical base to construct medical professionals’ LP in MOOCs as a series of the psychological process, which is affected by MR and interaction (i.e. HSI and HHI). Noteworthily, three psychological constructs, emotional LE, cognitive LE and social LE, are adopted to represent medical professionals’ organisms of MOOCs adoption. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies using the S-O-R model and psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context, and this study’s contribution on the application of capturing psychological constructs for completely explaining three types of technological features as external stimuli to medical professionals’ LP in MOOCs is well-documented.

The lockdown of schools to control the spread of Coronavirus Disease 2019 (COVID-19) has adversely affected elementary and secondary school students in China. However, little evidence is available that documents their perceptions toward the use of e-learning under the pandemic context. This study aims to explore (1) the underlying determinants influencing the students' intentions to continue e-learning and (2) the role that the COVID-19 pandemic plays in this decision. This study extends the expectation–confirmation model (ECM) through a mixed-methods study.

This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China. This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China.

In Phase 1, the results reveal that students' most concern elements in the COVID-19 pandemic are user perceptions toward e-learning and threat perceptions of COVID-19. In Phase 2, the results reveal that perceived usefulness and attitude are the most significant factors in students' intention to continue. The perceived threat of COVID-19 indirectly influences their intention to continue.

The study extends the ECM with a mixed-methods study to understand students' perceptions toward e-learning during the COVID-19 pandemic. This study can be helpful in related studies in the context of COVID-19-related diseases or other novel scenarios.