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Continuous advances in digital technology and business models digitalization have decisively altered the entrepreneurial landscape redefining the aims and the requirements of entrepreneurial education to suit the new digital reality in entrepreneurship. The purpose of this study is to shed light in a neglected niche in the intersection between digital entrepreneurship (DE) and entrepreneurship education and outline DE education as field of research. Given that the interdisciplinary growth of DE research outpaces instructional designs in terms of required knowledge and skills, it is important to document how entrepreneurship education responds to the ongoing integration of emerging digital technologies with the entrepreneurial process. Moreover, the introduction of a DE education conceptual framework would facilitate the discussion on theoretical and practical implications and promote new conceptualizations in future research, new educational approaches and new curriculum designs.

A concept-driven, semi-structured developmental literature review methodology, based on grounded theory and reinforced with increased systemization, was used for the identification and analysis of peer-reviewed articles. Previous literature reviews were used to define the search keywords. The articles from three databases were carefully selected, based on protocol and strict eligibility criteria. The papers in the final set were classified in four primary dimensions, synthesized from several sub-streams of research. Each sub-stream highlighting a different view of DE education emerged through open, axial and selective coding of articles. The combined perspectives of these dimensions resulted in a new DE conceptual framework.

Thematic interrelation between the studies examined, revealed an ample view of the various schools of thought in the research field, offering also a better understanding on how entrepreneurial education addresses the practical requirements of digital entrepreneurship. A four dimensional conceptual framework produced highlights pedagogy and learning, success factors and barriers, behavioral approach and ecosystems as the current trends of research. Also, directions for future research are proposed.

The classification framework proposed can serve as a roadmap for entrepreneurship educators seeking efficient pedagogical practices focused on the transfer of knowledge and training on the new skills required by DE and motivate future researchers aiming to propose novel educational interventions.

Although digital entrepreneurship research has gained significant momentum in recent years, little attention is paid to its increased educational requirements. The body of knowledge develops in an uncontrolled and fragmented manner, and the systematic study of the field from an educational perspective was missing. This study offers a representative picture of the topic, highlights current trends of research, synthesizes literature from different disciplinary origins, provides linkages between unconnected streams of research and points out research gaps. Finally, it proposes a conceptual framework to circumscribe DE education as a field of study and serve as a basis to help future research move forward.

This study probed the impact of using learning technologies (LT) on developing Yemeni English as a foreign language (EFL) students' autonomy and creativity toward English language learning. Also, the research gauged if LT impacts learners' autonomy and creativity across gender and university-type variables.

The study utilized a valid and reliable questionnaire, comprising 20 close-ended items, which was administered to 109 Yemeni EFL undergraduate students.

The researchers found that LT positively impacts learners' creativity and autonomy, with mean scores of 4.09 and 3.86, respectively. Furthermore, the results showed a medium correlation between creativity and autonomy with a correlation coefficient of r = 0.63 at a probability of Sig = 0.00. Likewise, the results revealed that LT impacted female learners' creativity more significantly than their male counterparts (Sig = 0.047). Nevertheless, no significant differences were found pertaining to the impact of LT on students' autonomy across public and private universities (Sig = 0.213).

EFL teachers are advised to encourage their students' autonomy and creativity throughout their lifelong learning journey in order to adapt to the ever-changing demands of the world.

This study investigates the impact of learning technology on Yemeni EFL students' autonomy and creativity.

The COVID-19 pandemic has created a significant disruption in the educational systems worldwide. Some institutions opted for emergency remote education due to the need to cancel in-person activities. The aims of this paper were to evaluate the use of asynchronous methodology in health sciences education, determine whether asynchronous methodology was sacrificing overall student satisfaction, and investigate whether satisfaction improved as the program develops.

Initially, there was phase 1 that corresponded to four weeks of activities. Each professor produced a video lesson, and after each video lesson, a weekly educational activity was made available. Next, phase 2 was implemented using the same methodology, however lasting six weeks. Three questionnaires were developed, and a Likert scale was administered to verify the students’ level of satisfaction. Data were analyzed using frequency distributions, mean values, standard deviation and confidence interval. The normality of the sum data (total of the questionnaires) was tested using the Kolmogorov–Smirnov test.

Although the students pointed out that the asynchronous methodology facilitated access to the content and considered this methodology satisfactory, they expressed a reduced level of satisfaction regarding emergency remote education in general when data from the first weeks were compared to those of the previous weeks. It is clear that students became increasingly discouraged and tired over time, which motivated the institution to shift into a combination of synchronous and asynchronous methodology to improve student learning.

Teaching in the field of health care encompasses difficult competencies that sometimes are impossible to be learned remotely, so there is a need to examine and evaluate properly the remote education in this area. With careful planning, educational institutions can evaluate their experiences during the pandemic, allowing those involved to highlight strengths and identify weaknesses to better prepare for future needs to improve remote education.

This paper aimed to determine the self- and co-regulation influences on the community of inquiry (CoI) for collaborative online learning.

A quantitative survey was used on a sample of (N = 626) enrolled postgraduate students in a South African Open Distance and e-Learning (ODeL) university. The measuring instruments were the CoI and the shared metacognitive surveys. Correlation and multiple regression analyses were used to determine the association and influence of self- and co-regulation on the CoI.

The results indicated that self- and co-regulation related to the CoI (teaching, cognitive and social) presences. In addition, the results revealed that self- and co-regulation influence the CoI presences. Self-regulation had the highest influence on teaching and cognitive presence, while co-regulation influenced social presence.

The study’s convenience sampling method from a single university limited the applicability of the findings to other online learning environments.

Higher educational teachers who encourage student self- and co-regulation may enhance their online teaching, cognitive and social presence when studying online. The research’s findings may be valuable to teachers to enable them to provide a more collaborative and interactive online learning environment and promote productive online communities.

This study contributes to the body of knowledge about the relationship between teaching, social and cognitive presence and self- and co-regulation within the CoI framework. Furthermore, there has also been limited research focussing on the dynamics of shared metacognition within the CoI framework in an ODeL context.

Crowd logistics is a rising phenomenon in last-mile delivery that integrates technological applications and sources a large number of participants to do logistical activities, achieving sustainable shipping in urban environments. However, up until now, there has been limited literature in this field. This research aims to investigate the extrinsic and intrinsic factors that impact the participative behaviour of driver-partners in crowd logistics.

An integrated model is developed based on motivation theory, incorporating attitude as a contributor to both extrinsic and intrinsic motivations. A questionnaire was constructed and distributed to collect data from 303 respondents who are existing or potential driver-partners in Vietnam.

Our findings confirm (1) the influence of monetary rewards on extrinsic motivation and (2) the power of self-efficacy, trust and sense of belonging on intrinsic motivation. Further, we find that attitude positively impacts extrinsic motivation, whereas there is no effect between attitude and intrinsic motivation. Both extrinsic and intrinsic motivations are demonstrated to significantly influence driver-partners' participative intentions. Additionally, a positive association is found between extrinsic and intrinsic motivations.

Findings from this study theoretically enrich the literature on crowd logistics, especially on the supply side, and empirically contribute to implications that are valuable to crowd logistics firms on driver-partner recruitment and business strategy development.

This paper aims to clarify the effect of discount discrepancy (DD) on consumers’ purchase intention (PI). The authors propose, test and provide evidence and explanations about the moderation of justification in the relation between consumers’ perceived DD and PI.

The authors conducted three experimental studies with a 2 × 2 factorial design, focusing on consumers’ processing of price discounts. Participants were informed that this study aimed to gather opinions on fashion, clothing and retail sales promotions. They accessed the questionnaire via Qualtrics. Each participant took part in only one study. The experimental conditions were manipulated through scenarios.

Study 1 tested and supported the moderation of justification on the effect of DD on PI. Study 2 tested and supported the moderation of the type of justification for the effect of DD on PI. Study 3 confirmed the findings in Study 2 and revealed the more effective type of justification.

The authors focused on a typically hedonic product category (fashion clothing). Further research should include a wider variety of goods and services, which could lead to different explanations or generalizations.

Sales promotions must refrain from generating DD between the initial price discount and the subsequent smaller discounts. Practitioners must evaluate the gains of an initial, more considerable percentage discount to attract consumers to the store and sell them other products versus the cost of losing sales because of DD. Management should recognize the importance of giving the correct justification for perceived DD, aligning the firm’s justification with the consumer’s motivation to buy the product.

The authors offer subsidies for effective consumer protection policies.

By studying the influence of justification on the effect of DD on PI, the authors propose a mechanism that would reduce the negative effect of DD on consumers’ PI.

Digital learning systems are crucial for education and data collected can analyse students learning performances to improve support. The purpose of this study is to design and build an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet.

A Learning Box has been build based on minicomputer and a web learning management system (LMS). This study presents different options to create such a system and discusses various approaches for data syncing. The structure of the final setup is a Moodle (Modular Object Oriented Developmental Learning Environment) LMS on a Raspberry Pi which provides a Wi-Fi hotspot. The authors worked with lecturers from X University who work in remote Northern Territory regions to test this and provide feedback. This study also considered suitable data collection and techniques that can be used to analyse the available data to support learning analysis by the staff. This research focuses on building an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet. Digital learning systems are crucial for education, and data collected can analyse students learning performances to improve support.

The resultant system has been tested in various scenarios to ensure it is robust when students’ submissions are collected. Furthermore, issues around student familiarity and ability to use online systems have been considered due to early feedback.

Monitoring asynchronous collaborative learning systems through analytics can assist students learning in their own time. Learning Hubs can be easily set up and maintained using micro-computers now easily available. A phone interface is sufficient for learning when video and audio submissions are supported in the LMS.

This study shows digital learning can be implemented in an offline environment by using a Raspberry Pi as LMS server. Offline collaborative learning in remote communities can be achieved by applying asynchronized data syncing techniques. Also asynchronized data syncing can be reliably achieved by using change logs and incremental syncing technique.

Focus on audio and video submission allows engagement in higher education by students with lower literacy but higher practice skills. Curriculum that clearly supports the level of learning required for a job needs to be developed, and the assumption that literacy is part of the skilled job in the workplace needs to be removed.

To the best of the authors’ knowledge, this is the first remote asynchronous collaborative LMS environment that has been implemented. This provides the hardware and software for opportunities to share learning remotely. Material to support low literacy students is also included.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

This paper aims to provide a literature review on the cloud-based platforms for the education sectors. The several aspects of cloud computing adoption in education, remote/distance learning and the application of cloud-based design and manufacturing (CBDM) have been studied and theorised.

A four-step methodology was adopted to analyse and categorise the papers obtained through various search engines. Out of 429 research articles, 72 papers were shortlisted for the detailed analysis.

Many factors that influence cloud computing technology adoption in the education sector have been identified in this paper. The research findings on several research items have been tabulated and discussed. Based on the theoretical research done on cloud computing for education, cloud computing for remote/distance learning and CBDM, cloud computing could enhance the educational systems in mainly developing countries and improve the scope for remote/distance learning.

This study is limited to papers published only in the past decade from 2011 to 2020. Besides, this review was unable to include journal articles published in different languages. Nevertheless, for the effective teaching and learning process, this paper could help understand the importance and improve the process of adopting cloud computing concepts in educational universities and platforms.

This study is a novel one as a research review constituting cloud computing applications in education and extended for remote/distance learning and CBDM, which have not been studied in the existing knowledge base.

The massive expansion of digital platform has been responsible for the widespread progressive engagement created amongst learners and educators. The practice of requiring student feedback on online learning services ensures that teacher education continues to advance its strategic approach to online learning. This paper aims to examine the level of accessibility and adaptability of digital technology with particular focus on Malaysia, by elaborating the value of superior learning service and practical adaptability of online learning during the pandemic era.

This study was conducted using qualitative approach of data collection, namely via structured interview. The listed respondents included 30 higher learners who participated in the study by providing feedback on the issues encountered during the research process.

The findings revealed that the strategic enhancement of digital accessibility continued with digital adaptability to sources of learning services would contribute to advancing achievement of digital learning pathway.

Increasing accessibility to digital platforms in digital learning system can help to shape the digital environment. Digital expansion can create unlimited boundaries for online knowledge acquisition.

The social implication refers to acquiring the abilities developed through online engagement with peers by actualising and exploring information together with continuous inter-connectedness of sharing pathway in online platform. The instructor would need to give a proportional gateway to make learners experience the digital environment for future education.

This study aims to assess the value of developing accessibility of digital technology for students' online learning services during the pandemic and beyond. A well-structured plan would enable digital learning capabilities and mutual accessibility amongst learners. This can allow digital abilities to be transformed into collaborative teamwork amongst learners.