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Academic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning post-COVID-19, an understanding of student cheating dynamics is essential for developing effective strategies to combat academic dishonesty in the rapidly changing educational landscape.

This study explored academic integrity and reasons for dishonesty from the perspective of health sciences students at a South African University of Technology (UOT) via the Fraud Diamond. To gain an in-depth understanding of the topic, a qualitative method was employed, and data were collected via focus group discussions with nine student class representatives. These data were analysed thematically using the Clarke and Braun approach.

Cheating during online assessment was common and innovative, with students manipulating others and exploiting friendships to facilitate dishonest practices. Student motivations for dishonesty included a lack of consequences and pressure due to a lack of time management, engagement and preparation.

This study underscores the need for institutions to adopt an adaptable, multi-faceted approach that addresses student cheating opportunity, motivation and normalisation of dishonest practices whilst strengthening academic integrity policies and enforcement thereof.

The findings contribute valuable insights into the ongoing academic integrity crisis in higher education in the South African context.

The current study examined several aspects of validity evidence for the Faculty Readiness to Teaching Online (FRTO) scale.

Data were collected from 307 faculty in higher education. Construct validity was evidenced through an exploratory factor analysis and a reliability coefficient. Differential validity was explored using the differential item functioning analysis to explore potential bias in items due to gender and age. In addition, convergent validity was tested by correlating FRTO with years of teaching online, the primary modality of instruction and whether there is required training in online teaching by the institution.

The findings from validation showed that new factors emerged and also demonstrated differences based on instructors gender and age, as well as based on teaching experience and primary modality of teaching.

The findings confirmed the previous study's results (Martin et al., 2019) and provided some modifications to the instrument. The factor structure did not conform to the original four factors proposed in the instrument; instead, the newly loaded factors were course design and facilitation, course technologies, course expectations and resources and time management. The revised instrument can be presented and discussed at online teaching professional development programs to help faculty understand the core competencies they need to better instruct students.

During the COVID-19 pandemic, the importance of digital infrastructure in higher education surged. This study aims to analyze how a country’s digital capabilities influence pedagogical transitions in business schools and compare the impacts between digitally advanced and advancing countries.

The authors applied the job demands–resources model and the IMD World Digital Competition Ranking 2021 to analyze the impact of nations’ digital capabilities on the pedagogical transitions experienced by 121 business faculty members from 20 nations. The countries were categorized into digitally advanced countries and advancing countries. The snowball sampling method was used to gather data through an online survey consisting of 24 items. SPSS was used to statistically analyze the data in two stages using paired t-test and group comparison.

Significant shifts between face-to-face and online lectures occurred in both groups. Advanced countries witnessed positive shifts in discussions, presentations, oral assessment, independent learning opportunities, online teaching methods, technical support and faculties’ readiness, whereas advancing countries mainly noted alterations in professional development and communication technologies.

This study offers insights into optimizing digital capabilities and enhancing business schools’ readiness for effective pedagogical shifts during crises. Both the theoretical contribution and the findings will benefit national education policies, higher education institution leaders, scholars and educators.

This study aims to develop a model for readiness measurement and to study readiness levels for online testing of undergraduate students in Thailand’s distance education programs.

In total, 870 undergraduate students enrolled in the 2022 academic year of a Thai university were sampled for the study. The samples were divided into two groups: Group 1 comprised 432 students who underwent exploratory factor analysis (EFA) and Group 2 comprised 438 students who underwent second-order confirmatory factor analysis (CFA). Both were multi-stage random samples. Descriptive statistics, item-total correlations (ITCs), coefficient correlations, EFA and second-order CFA were used.

The readiness for the online testing model comprised 5 factors and 33 indicators. These included self-efficacy (SE) in utilizing technology (nine indicators), self-directed learning (SL) for readiness testing (six indicators), adequacy of technology (AT) for testing (five indicators), acceptance of online testing (AC) (seven indicators) and readiness training for testing (six indicators). The model was congruent with empirical data, and the survey results indicated that students were highly prepared at the “high” level.

This study disclosed several factors and indicators involved in the readiness for online testing. The university may use these findings in preparing its students for online testing for better achievement.

These findings may serve as a framework for the analysis of the readiness issues for online testing of undergraduate students and also offer guidance to the universities preparing to offer online testing.

The purpose of this paper is threefold: first, to examine the influence of the quality of online classes on student satisfaction and student loyalty; second, to explore the mediating role of student participation between online classes and student satisfaction; third, to examine the mediating role of student satisfaction between online classes and student loyalty.

The primary data is collected from the postgraduate students in Jammu and Kashmir, India. A descriptive research design was applied to collect the primary data via Google questionnaire with the COVID-19 pandemic in mind to maintain social distance.

The result reveals that online classes and student participation positively affect student satisfaction. Student participation is a partial mediator between online classes and student satisfaction, with 0.393 Variance Accounted For (VAF). In comparison, it is a full mediator between online classes and student loyalty with 0.96 VAF.

The current study was restricted to postgraduate students, while future research could include research scholars, graduate students, and others. Only government institutions in Jammu and Kashmir were employed for the present study. The study may eventually be expanded to include private universities and more states.

The suggested approach can help teachers, students, policymakers and administrators. The study emphasizes the crucial elements of student engagement and happiness, which must be prioritized to improve online teaching and learning effectiveness and win over students' loyalty.

The study tested the conceptual framework of an integrated approach connecting online classes, student participation, student satisfaction and student loyalty. The study was conducted during the COVID-19 pandemic lockdown period, as it was the need of the hour to come out of such a crisis in the future. The present study can also provide a roadmap for transformation from physical to virtual classrooms.

The widespread uptake of digital technology tools for online teaching and learning reached its peak during the nationwide lockdown triggered by the COVID-19 pandemic. It transformed the higher education institutions (HEIs) marketplace both in developed and developing countries. However, in this process of digital transformation, several HEIs, specifically from developing countries, faced major challenges. That threatened to affect their sustainability and performance. In this vein, this study conducts a bibliometric review to map the challenges during the COVID-19 pandemic and suggest strategies for HEIs to cope with post-pandemic situations in the future.

This comprehensive review encompasses 343 papers published between 2020 and 2023, employing a systematic approach that combines bibliometrics and content analysis to thoroughly evaluate the articles.

The investigation revealed a lack of published work addressing the specific challenges faced by the faculty members affecting their well-being. The study underscores the importance of e-learning technology adoption for higher education sustainability by compelling both students and teachers to rely heavily on social media platforms to maintain social presence and facilitate remote learning. The reduced interpersonal interaction during the pandemic has had negative consequences for academic engagement and professional advancement for both educators and students.

This has implications for policymakers and the management of HEIs, as it may prove useful in reenvisioning and redesigning future curricula. The paper concludes by developing a sustainable learning framework using a blended approach. Additionally, we also provide directions for future research to scholars.

This study has implications for policymakers and HEI management to rethink the delivery of future courses with a focus on education and institute sustainability. Finally, the research also proposes a hybrid learning framework for sustainability and forms a robust foundation for scholars in future research.

This study aims to address the growing importance of online health information (OHI) and the associated uncertainty. Although previous research has explored factors influencing the credibility of OHI, results have been inconsistent. Therefore, this study aims to identify the essential factors that influence the perceived credibility of OHI by conducting a meta-analysis of articles published from 2010 to 2022. The study also aims to examine the moderating effects of demographic characteristics, study design and the platforms where health information is located.

Based on the Prominence-Interpretation Theory (PIT), a meta-analysis of 25 empirical studies was conducted to explore 12 factors related to information content and source, social interaction, individual and media affordance. Moderators such as age, education level, gender of participants, sample size, platforms and research design were also examined.

Results suggest that all factors, except social support, have significant effects on the credibility of OHI. Among them, argument quality had the strongest correlation with credibility and individual factors were also found to be relevant. Moderating effects indicate that social support was significantly moderated by age and education level. Different sample sizes may lead to variations in the role of social endorsement, while personal involvement was moderated by sample size, platform and study design.

This study enriches the application of PIT in the health domain and provides guidance for scholars to expand the scope of research on factors influencing OHI credibility.

This study aims to describe the m-learning experience of school students and teachers during the COVID-19 pandemic and explores the factors influencing the continuance intention of m-learning.

Semistructured interviews of 24 students and 09 teachers of schools in national capital territory (NCT) Delhi, India were conducted over 03 months and transcribed verbatim. A hermeneutic phenomenological design was used to interpret the text and bring out the “lived experiences” of m-learning.

The following 15 themes or factors influencing continuance intention emerged through the hermeneutic circle: (1) actual usage, (2) attitude, (3) context, (4) extrinsic motivation, (5) facilitating conditions, (6) intrinsic motivation, (7) perceived compatibility, (8) perceived content quality, (9) perceived mobile app quality, (10) perceived teaching quality, (11) perceived usefulness, (12) satisfaction, (13) self-efficacy, (14) self-management of learning and (15) social influence.

The study offers insightful recommendations for school administrators, mobile device developers and app designers. In addition, suggestions for effectively using m-learning during disasters such as COVID-19 have been provided. Several future research directions, including a nuanced understanding of m-assessment and online discussions, are suggested to enhance the literature on m-learning continuance.

The study enriches the literature on m-learning continuance. A qualitative approach has been used to identify relevant factors influencing m-learning continuance intention among secondary and higher secondary level (Grades 9 to 12) school students and teachers in India. In addition, a conceptual framework of the relationships among the factors has been proposed. Further, an analysis of the lived experiences of m-learning during the COVID-19 pandemic indicated several issues and challenges in using m-learning during disasters.

This study aimed to review the different types of academic integrity violations reported in the literature between 2013 and 2023. Moreover, this study investigated the causes of these violations and recommends approaches and measures that can be implemented to minimise academic integrity violations in the era of artificial intelligence (AI).

We reviewed 27 articles published between 2013 and 2023 from the Scopus database. We followed the reporting guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to select, filter, and report relevant studies that met the research objectives.

The study revealed that various individual, institutional, social, cultural, and technological factors contribute to academic integrity violations. To minimise this issue, higher education institutions should offer brief academic integrity tutorial courses to all first-year students to enhance their knowledge of academic integrity. Moreover, academic honour codes should be regularly reviewed and updated, and technological tools should be implemented to detect AI-generated third-party assignments submitted by students. Furthermore, higher education institutions should frequently conduct training and workshops to educate students on the consequences of violating academic integrity.

This study contributes to existing literature. It highlights the wider societal implications of academic integrity violations such as their influence on workforce readiness and ethical standards in professional environments.

This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.