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1 – 10 of over 4000Siti Hajar Hussein, Suhal Kusairi and Fathilah Ismail
This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism…
Abstract
Purpose
This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.
Design/methodology/approach
This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.
Findings
This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.
Research limitations/implications
The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.
Originality/value
Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.
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Jorge Sanabria-Z and Pamela Geraldine Olivo
The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth…
Abstract
Purpose
The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.
Design/methodology/approach
The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.
Findings
This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.
Originality/value
This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.
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Barbara Fedock, Armando Paladino, Liston Bailey and Belinda Moses
The purpose of this paper is to examine how robotics program developers perceived the role of emulation of human ethics when programming robots for use in educational settings. A…
Abstract
Purpose
The purpose of this paper is to examine how robotics program developers perceived the role of emulation of human ethics when programming robots for use in educational settings. A purposive sampling of online robotics program developer professional sites which focused on the role of emulation of human ethics used when programming robots for use in educational settings was included in the study. Content related to robotics program developers’ perceptions on educational uses of robots and ethics were analyzed.
Design/methodology/approach
The design for this study was a qualitative summative content analysis. The researchers analyzed keywords related to a phenomenon. The phenomenon was the emulation of human ethics programmed in robots. Articles selected to be analyzed in this study were published by robotics program developers who focused on robots and ethics in the education. All articles analyzed in this study were posted online, and the public has complete access to the studies.
Findings
Robotics program developers viewed the importance of situational human ethics interpretations and implementations. To facilitate flexibility, robotics program developers programmed robots to search computer-based ethics related research, frameworks and case studies. Robotics program developers acknowledged the importance of human ethics, but they felt more flexibility was needed in the role of how classroom human ethical models were created, developed and used. Some robotic program developers expressed questions and concerns about the implementations of flexible robot ethical accountability levels and behaviors in the educational setting. Robotics program developers argued that educational robots were not designed or programmed to emulate human ethics.
Research limitations/implications
One limitation of the study was 32 online, public articles written by robotics program designers analyzed through qualitative content analysis to find themes and patterns. In qualitative content analysis studies, findings may not be as generalizable as in quantitative studies. Another limitation was only a limited number of articles written by robotics programs existed which addressed robotics and emulation of human ethics in the educational setting.
Practical implications
The significance of this study is the need for a renewed global initiative in education to promote debates, research and on-going collaboration with scientific leaders on ethics and programming robots. The implication for education leaders is to provide ongoing professional development on the role of ethics in education and to create best practices for using robots in education to promote increased student learning and enhance the teaching process.
Social implications
The implications of this study are global. All cultures will be affected by the robotics’ shift in how students are taught ethical decision making in the educational setting. Robotics program developers will create computational educational moral models which will replace archetypal educational ethics frameworks. Because robotics program developers do not classify robots as human, educators, parents and communities will continue to question the use of robots in educational settings, and they will challenge robotics ethical dilemmas, moral standards and computational findings. The examination of robotics program developers’ perspectives through different lens may help close the gap and establish a new understanding among all stakeholders.
Originality/value
Four university doctoral faculty members conducted this content analysis study. After discussions on robotics and educational ethics, the researchers discovered a gap in the literature on the use of robots in the educational setting and the emulation of human ethics in robots. Therefore, to explore the implications for educators, the researchers formed a group to research the topic to learn more about the topic. No personal gains resulted from the study. All research was original. All cultures will be affected by the robotics’ shift in how students are taught ethical decision making in the educational setting. Robotics program developers will create computational educational moral models which will replace archetypal educational ethics frameworks. Because robotics program developers do not classify robots as human, educators, parents and communities will continue to question the use of robots in educational settings, and they will challenge robotics ethical dilemmas, moral standards, and computational findings. The examination of robotics program developers’ perspectives through different lens may help close the gap and establish a new understanding among all stakeholders.
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Gavin Baxter and Thomas Hainey
This article aims to explore student views from a UK higher educational institution about the concept of remote online higher educational delivery. Students were asked about…
Abstract
Purpose
This article aims to explore student views from a UK higher educational institution about the concept of remote online higher educational delivery. Students were asked about opinions towards working remotely and the psychological impact this had upon students and students' studies. The research provided students with the opportunity to reflect upon whether the practice of delivering education remotely continues to provide students with a beneficial student learning experience.
Design/methodology/approach
The research adopted a case study methodology utilising a mixed methods approach via questionnaire-based research. In total, 894 students completed the questionnaire. The aim of the research was to obtain a wide breadth of student opinion from multidisciplinary backgrounds to ascertain whether students' learning experience differed per subject area.
Findings
The research identified some interesting findings, namely that certain participants considered that learning remotely online was beneficial for instant feedback, supported motivation and fostered communities of practice. Negative perspectives related to feeling isolated, unmotivated and a preference towards face-to-face (F2F) delivery. One of the main areas of conflict identified from this study is that the aspect of engagement can impact students' online learning both positively and negatively.
Originality/value
The study provides an in-depth multidisciplinary student tertiary perspective relating to online remote learning. The findings from this study can be useful for educators to reflect upon and inform educational policy in relation to how best to facilitate and support the student learning experience off-campus.
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Bargavi Ravichandran and Kavitha Shanmugam
This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption…
Abstract
Purpose
This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.
Design/methodology/approach
The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.
Findings
Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.
Research limitations/implications
A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.
Originality/value
The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.
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Jaime Rivera and Víctor Alarcón
This study aims to propose and test a model of educational quality in marketing-management by incorporating resource-capability variables that are linked to learning outcomes for…
Abstract
Purpose
This study aims to propose and test a model of educational quality in marketing-management by incorporating resource-capability variables that are linked to learning outcomes for students and the competitive positioning of universities.
Design/methodology/approach
Drawing on the resource-dependence theory, this study develops a comprehensive model for measuring educational quality. A sample comprising Spanish university teachers has been used to test the hypothesised relationships by using a two-stage least squares regression analysis while controlling for the possible effect of the public/private nature of the university.
Findings
The results validate the model and show that educational capabilities are reliable variables for predicting the educational quality of marketing-management programmes at Spanish universities.
Research limitations/implications
Similar to all educational research studies, certain problems have been acknowledged with respect to the data and the theoretical constructs that are used in the study. Future studies can replicate this study’s model by using more direct objective measures of the theoretical constructs and extend the study to other countries with different educational contexts.
Practical implications
The results provide guidance to marketing teachers at a university in designing high-quality marketing-management educational programmes and in developing self-diagnostic tools that can determine a university’s likelihood of competitive success.
Originality/value
This study is one of the few studies to apply the resource-dependence theory to the analysis of the variables associated with the quality of marketing-management education. In doing so, the study presents original multiitem scales to improve the measurement of model constructs.
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Fabrizia Sarto, Sara Saggese, Riccardo Viganò and Marianna Mauro
The purpose of this paper is to provide insights into the implications of board human capital heterogeneity for company innovation by focusing on the educational and the…
Abstract
Purpose
The purpose of this paper is to provide insights into the implications of board human capital heterogeneity for company innovation by focusing on the educational and the functional background of directors. Moreover, it examines the moderating effect of the CEO expertise-overlap within the innovation domain on the relationship between board human capital heterogeneity and firm innovation.
Design/methodology/approach
The hypotheses are tested through a set of ordinary least squares regressions on a unique dataset of 149 Italian high-tech companies observed between 2012 and 2015.
Findings
Findings show that the educational and the functional background heterogeneity of directors increase both the innovation input and output. However, results highlight that these relationships are negatively moderated by the CEO expertise-overlap within the innovation domain.
Practical implications
The paper emphasizes the importance of appointing directors with different and specific educational and functional backgrounds to foster the company innovation.
Originality/value
The paper fills a gap in the literature as it has devoted limited attention to the performance implications of board human capital heterogeneity in the high-tech industry where knowledge and skills are the primary sources of value. Moreover, the paper integrates the research on the CEO-board interface by shedding light on how the CEO expertise within the innovation domain affects the contribution of heterogeneous boards to company innovation.
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Mara Soncin and Marta Cannistrà
This study aims to investigate the organisational structure to exploit data analytics in the educational sector. The paper proposes three different organisational configurations…
Abstract
Purpose
This study aims to investigate the organisational structure to exploit data analytics in the educational sector. The paper proposes three different organisational configurations, which describe the connections among educational actors in a national system. The ultimate goal is to provide insights about alternative organisational settings for the adoption of data analytics in education.
Design/methodology/approach
The paper is based on a participant observation approach applied in the Italian educational system. The study is based on four research projects that involved teachers, school principals and governmental organisations over the period 2017–2020.
Findings
As a result, the centralised, the decentralised and the network-based configurations are presented and discussed according to three organisational dimensions of analysis (organisational layers, roles and data management). The network-based configuration suggests the presence of a network educational data scientist that may represent a concrete solution to foster more efficient and effective use of educational data analytics.
Originality/value
The value of this study relies on its systemic approach to educational data analytics from an organisational perspective, which unfolds the roles of schools and central administration. The analysis of the alternative organisational configuration allows moving a step forward towards a structured, effective and efficient system for the use of data in the educational sector.
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Shahrokh Nikou and Ilia Maslov
During the COVID-19 pandemic, educational institutions were forced to shut down, causing massive disruption of the education system. This paper aims to determine the critical…
Abstract
Purpose
During the COVID-19 pandemic, educational institutions were forced to shut down, causing massive disruption of the education system. This paper aims to determine the critical factors for the intention to participate in e-learning during COVID-19.
Design/methodology/approach
Data were collected by surveying 131 university students and structural equation modelling technique using PLS-SEM was employed to analysis the data.
Findings
The results showed that the COVID-19 related factors such as perceived challenges and COVID-19 awareness not only directly impact students' intention but also such effects are mediated through perceived usefulness and perceived ease of use of e-learning systems. However, the results showed that the educational institution's preparedness does not directly impact the intention of students to participate in e-learning during COVID-19. The results also showed that the gender and length of the use of e-learning systems impact students' e-learning systems use.
Originality/value
These results demonstrated that, regardless of how well the educational institutions are prepared to promote the use of e-learning systems, other COVID-19-related challenges play a crucial role in forming the intention of students to participate in e-learning during the COVID-19 pandemic. Theoretical and practical implications are provided.
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Choo Jun Tan, Ting Yee Lim, Chin Wei Bong and Teik Kooi Liew
The purpose of this paper is to propose a soft computing model based on multi-objective evolutionary algorithm (MOEA), namely, modified micro genetic algorithm (MmGA) coupled with…
Abstract
Purpose
The purpose of this paper is to propose a soft computing model based on multi-objective evolutionary algorithm (MOEA), namely, modified micro genetic algorithm (MmGA) coupled with a decision tree (DT)-based classifier, in classifying and optimising the students’ online interaction activities as classifier of student achievement. Subsequently, the results are transformed into useful information that may help educator in designing better learning instructions geared towards higher student achievement.
Design/methodology/approach
A soft computing model based on MOEA is proposed. It is tested on benchmark data pertaining to student activities and achievement obtained from the University of California at Irvine machine learning repository. Additional, a real-world case study in a distance learning institution, namely, Wawasan Open University in Malaysia has been conducted. The case study involves a total of 46 courses collected over 24 consecutive weeks with students across the entire regions in Malaysia and worldwide.
Findings
The proposed model obtains high classification accuracy rates at reduced number of features used. These results are transformed into useful information for the educational institution in our case study in an effort to improve student achievement. Whether benchmark or real-world case study, the proposed model successfully reduced the number features used by at least 48 per cent while achieving higher classification accuracy.
Originality/value
A soft computing model based on MOEA, namely, MmGA coupled with a DT-based classifier, in handling educational data is proposed.
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