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Higher Education Institutions are expected to stimulate the innovation system and to contribute to the development of societies in a global perspective. Within this context, there is an increasing focus on internationalization. HEIs are developing institutional mechanisms to support internationalization while academics are expected to carry specific practices that allow them to improve the internationalization of knowledge production. At the same time, they are encouraged to engage with non-academic partners to co-produce and transfer knowledge, contributing, in this way, to economic and social development. Although there is some research on the impact of internationalization on academic entrepreneurship, studies on the effects in other dimensions of academic engagement with society are almost absent. This paper aims to fill this gap by analyzing the relationship between academics' internationalization practices and perceptions and the development of different types of academic engagement. Our analysis draws on quantitative analysis with data provided by an international survey (APIKS) and explores the Portuguese context. Findings show that the different practices and perspectives on internationalization impact differently on the way scientists engage. While there are positive effects of internationalization of research on engagement, the time academics stay abroad and the high focus on publishing in internationally high-rated journals may negatively affect academics' orientation towards the local community. This paper contributes to the debate on the role of the internationalization in the context of a knowledge-based society, considering different dimensions and a broad spectrum of knowledge-based engagement activities. [ABSTRACT FROM AUTHOR]

This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following data analyses: 1) predict students' gender based on their perception of complex thinking competency and sub-competencies from a 25 items questionnaire, 2) analyze models' performance during training and testing stages, and 3) study the models' prediction bias through a confusion matrix analysis. Our results confirm the hypothesis that the four machine learning models (Random Forest, Support Vector Machines, Multi-layer Perception, and One-Dimensional Convolutional Neural Network) can find sufficient differences in the eComplexity data to classify correctly up to 96.94% and 82.14% of the students' gender in the training and testing stage, respectively. The confusion matrix analysis revealed partiality in gender prediction among all machine learning models, even though we have applied an oversampling method to reduce the imbalance dataset. It showed that the most frequent error was to predict Male students as Female class. This paper provides empirical support for analyzing perception data through machine learning models in survey research. This work proposed a novel educational practice based on developing complex thinking competency and machine learning models to facilitate educational itineraries adapted to the training needs of each group to reduce social gaps existing due to gender. [ABSTRACT FROM AUTHOR]

In recent years, there has been a notable upswing in the realm of innovation and entrepreneurship education for Chinese students, leading to remarkable advancements. However, students' initiatives in this field fall short of the desired standards. The current evaluation index system is insufficient for meeting the developmental needs of colleges and universities. Therefore, exploring innovative approaches and implementing a comprehensive evaluation framework become crucial. This research analyzes the limitations of the current evaluation system, which focuses on curriculum, teaching materials, management, research output, student employment, entrepreneurship awareness, and participation. Unfortunately, this narrow approach has a significant impact on the quality of education in this field. To address this issue, this paper proposes a novel evaluation system for assessing students' innovation and entrepreneurship education by utilizing the capabilities of backpropagation (BP) neural network. We researched the conceptual framework, components, and learning process of BP neural network. Additionally, we provide a thorough description of the calculation process and structure of the BP neural network algorithm by facilitating stakeholders' understanding. Our study aims to strengthen the landscape of education by developing a culture of excellence. We developed a robust evaluation system with well-defined indexes calibrated to capture the essence of this education. Through precise training and analysis, we achieved remarkable results, with a maximum difference of 1.6% between the anticipated and actual output. This highlights the accuracy of our model in assessing teaching quality. We also thoroughly compared several kinds of assessment methods for the growth of students' entrepreneurial and innovative skills that have been presented in the literature. Based on the simulation results, we discovered that our model performs better as compared to the existing model. Based on the evidence, innovation and entrepreneurship education in Chinese institutions can be characterized as moderate. This finding lays the foundation for further advancements, fostering a future where educational excellence and entrepreneurial spirit thrive. [ABSTRACT FROM AUTHOR]

This project implements an assistive robotic platform in a mathematics high school class to support the professor's teaching process while analyzing its performance by using a gamification approach and the Octalysis framework. The results obtained from this study evaluated both the platform usability and the general class perception from the students and the professors involved in the experimentation. This paper demonstrates that the implementation of a robotic platform as a supportive tool for the professor improves the class' dynamism and the cooperative behavior of the students, by following the Octalysis approach. Finally, the results helped to determine a better role assignment for future cases where the professor implements a robotic platform during class, leaving the theoretical explanations and class control to the professor, and giving the robot the role of enhancing the activities and review exercises. [ABSTRACT FROM AUTHOR]

The popularisation of higher education supports UNESCO's aim of developing inclusive and equitable quality education to achieve the fourth Sustainable Development Goal. However, the effect of popularising higher education on economic growth and poverty alleviation remains unexplored. Therefore, this study investigated the effects of higher education and adult education within populations (popularisation of higher education) on economic growth (gross domestic product; GDP) and the poverty line using panel data from 38 countries. OLS and quantile regression were performed using data for the period 1995–2021 extracted from the OECD and World Bank databases. The results showed that the population segments with higher education had a significantly positive impact on GDP growth. Moreover, an increased proportion of the population with higher education, of working age, was found to be a contributing factor to GDP growth. Popularising higher education also played a positive role during the initial stage of social and economic development. This study also highlighted that popularising higher education play a key role to influence a country's educational development and scientific and technological innovation drives the deepening of a country's economy. It suggested that both national and local governments worldwide should pay much attention to the popularisation degree of higher education to greatly improve the innovative ability of talents and scientific and technological innovation in higher education for both the economic growth and poverty alleviation. [ABSTRACT FROM AUTHOR]

This article examines the purposeful introduction of the pedagogy of student-centred education (SCE) in one educational institution in the United Arab Emirates (UAE) to consider its cultural compatibility. The study was undertaken in the largest higher education (HE) institution in the country where a key element of the institution's two strategic plans over a nine-year period was to blend traditional and innovative teaching methods, including student centred approaches, into programmes of study. Interpretative phenomenological analysis is used to analyse the perspectives of seven non-citizen, Western teachers, as they recontextualise their practice. Drawing on Heidegger, the study explores the philosophical nature and significance of place as a way of thinking about the world. Findings revealed aspects of the teachers' student-centred practice are challenging; the universal value of SCE is understood in relative rather than absolute terms with an overall need to diversify universal imaginings of pedagogy. Centralised curricula, high stakes final assessments and individualised performance management models ultimately determined learning experiences, leaving little room for any sustained inquiry into the recontextualisation of SCE. The study concludes that pedagogy is inescapably situated: practiced in terms of place orientated thinking. Transformation necessitates an epistemic institution where change is a public endeavour and teachers are positioned inside participatory processes with possibilities to renegotiate, rearticulate and resignify pedagogy. [ABSTRACT FROM AUTHOR]

In the digitally empowered society, increased internet utilization leads to potential harm to the youth through cyberbullying on various social networking platforms. The cyberbullying stats keep on rising each year, leading to detrimental consequences. In response to this online threat, the Indian Government launched different helplines, especially for the children and women who need assistance, various complaint boxes, cyber cells, and made strict legal provisions to curb online offenses. This research evaluates the relevant initiatives. Additionally, a survey is conducted to get insights into cyberbullying in higher education institutions, discussing multiple factors responsible for youth and adolescents being cyberbullied and a few measures to combat it in universities/colleges. [ABSTRACT FROM AUTHOR]

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This work seeks to support scholars interested in non-face-to-face modalities of higher education in making decisions about the use of digital and educational technologies (DET) to promote educational transformation (ET) in the context of their organizations. This organizational change deals with the implementation of technology-based flexible educational practices, focused on helping students develop competencies of interest for their personal and professional growth. With this in mind, in 2018 we identified and followed six leading higher education institutions on three continents that, for years, have carried out educational innovation experiences with the support of technology. Two of the analyzed experiences make use of eLearning, another of bLearning, and the others combine eLearning and bLearning as a complement to the face-to-face modality. The meta-analysis of the cases, carried out in 2019, followed suggestions from (Stake in The art of case study research, Sage Publications Inc., 1995) as well as from qualitative research that seeks to understand what is behind the cases from three dimensions: education, technology, organization. For each one, we determined what they do, how they do it, and what success factors must be considered. As the data was collected before the 2020 pandemic and this issue produced structural imbalances in society and in higher education, it was considered pertinent, at the end of 2020, to check the pulse of the ET mediated with DET in three of the six institutions studied. The purpose was to refine the findings of the meta-analysis and learn from the decisions made in the situation of forced change in environments, means, and strategies to continue providing quality higher education. [ABSTRACT FROM AUTHOR]

Recent trends in educational technology have led to emergence of methods such as teaching analytics (TA) in understanding and management of the teaching–learning processes. Didactically, teaching analytics is one of the promising and emerging methods within the Education domain that have proved to be useful, towards scholastic ways to make use of substantial pieces of evidence drawn from educational data to improve the teaching–learning processes and quality of performance. For this purpose, this study proposed an educational process and data mining plus machine learning (EPDM + ML) model applied to contextually analyze the teachers' performances and recommendations based on data derived from students' evaluation of teaching (SET). The EPDM + ML model was designed and implemented based on amalgamation of the Text mining and Machine learning technologies that builds on the descriptive decision theory, which studies the rationality behind decisions the learners are disposed to make based on the textual data quantification and statistical analysis. To this effect, the study determines pedagogical factors that influences the students' recommendations for their teachers, what role the sentiment and emotions expressed by the students in the SET play in the way they evaluate the teachers by taking into account the gender of the teachers. This includes how to automatically predict what a student's recommendation for the teachers may be based on information about the students' gender, average sentiment, and emotional valence they have shown in the SET. Practically, we applied the Text mining technique to extract the different sentiments and emotions (intensities of the comments) expressed by the students in the SET, and then utilized the quantified data (average sentiment and emotional valence) to conduct an analysis of covariance and Kruskal Wallis Test to determine the influential factors, as well as, how the students' recommendation for the teachers differ by considering the gender constructs, respectively. While a large proportion of the comments that we analyzed (n = 85,378) was classified to be neutral and predominantly interpreted to be positive in nature considering the sentiments (76.4%), and emotional valence (88.2%) expressed by the students. The results of our analysis shows that for the students' comments which contain some kind of positive or negative sentiment (23.6%) and emotional valence (11.8%); that females students recommended the teachers taking into account the sentiments (p =.000). While the males appear to be slightly borderline in terms of emotions (p =.056) and sentiment (p =.077). Also, the EPDM + ML model showed to be a good predictor and efficient method in determining what the students' recommendation scores for the teachers would be, going by the high and acceptable values of the precision (1.00), recall (1.00), specificity (1.00), accuracy (1.00), F1-score (1.00) and zero error-rate (0.00) which we validated using the k-fold cross-validation method, with 63.6% of optimal k-values observed. In theory, we note that not only does the proposed method (EPDM + ML) proves to be useful towards effective analysis of SET and its implications within the educational domain. But can be utilized to determine prominent factors that influences the students' evaluation and recommendation of the teachers, as well as helps provide solutions to the ever-increasingly need to advance and support the teaching–learning processes and/or students' learning experiences in a rapidly changing educational environment or ecosystem. [ABSTRACT FROM AUTHOR]

The advancements of technology have allowed digital transformation to reach all productive sectors, including the education sector and its members. This transformation is linked to emerging technologies, the digitalization of processes and resources, and the demand for users to upgrade to the latest technological updates. This research aims to analyze digital transformation and media literacy publications that impact higher education. Its purpose is to identify the types of research and topics they address and explore the scope of digital transformation in higher education institutions. The systematic mapping method was used to analyze 298 articles published in two databases, Scopus and Web of Science (WoS). Inclusion and exclusion criteria were applied to select the articles that could be included in this research. The results show that the largest proportion of articles were found in Scopus, and used both qualitative and quantitative empirical research methods, followed by theoretical-conceptual methods and, to a lesser extent, mixed methods. Likewise, the publications originated in five continents, and the Journal of Adolescent and Adult Literacy had the largest number of publications, with 14. Forty-two percent of the studies were classified in the strategy category, with the most mentioned topic being digital pedagogies. This research provides a perspective on digital transformation studies in higher education institutions and their internalization approaches. This research may be of value to trainers, students, decision-makers, and researchers interested in transformation, educommunication, and educational innovation. [ABSTRACT FROM AUTHOR]

Innovation in higher education teaching is essential to respond to global challenges and actively improve teaching (e.g. through new technologies), necessitating the implementation of educational reform programmes that fund educational innovations. Although currently deployed strategies frequently promote networks between innovators to diffuse educational innovations, little is known about the efficiency of these networks or whether they promote innovation diffusion. This study investigates a network comprising 88 higher education teachers who received funding for their educational innovations in a German university. We collected longitudinal data by asking higher education teachers from whom they adopted innovative teaching ideas and requesting self-reports on innovative teaching climate. Our findings show that the teachers' social network had a smaller path length and more clustering than might be expected by chance. This observation might indicate that the examined educational innovation network exhibits a small-world property and allows efficient exchange of ideas among the teachers. In line with our hypotheses, the network's initial tendency toward hierarchy and homophily decreased over time in response to strategies and network interventions. In summary, this study provides initial empirical support that educational reform programmes can create efficient educational innovation networks, facilitating innovation diffusion and promoting change in higher education teaching. [ABSTRACT FROM AUTHOR]

Transformational leadership, a type of leadership commonly promoted within higher education, has been shown to positively affect performance, collaborative behavior, and goal accomplishment. Such skills may correlate with the level of job responsibility one has been given and the technical, human, and conceptual skills needed for one to be successful. This study sought to bridge a research gap by exploring correlations between transformational leadership and skills-approach leadership with an exploration of the role of gender within perceptions. An unexpected result based on gender was found: As females achieve higher roles within the Land-Grant University System, the perception of their transformational leadership decreases while that of males increases. Transformational leadership and skills-approach leadership is discussed within the context of gender. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has disrupted many areas of the human and organizational ventures worldwide. This includes new innovative technologies and strategies being developed by educators to foster the rapid learning-recovery and reinstatement of the stakeholders (e.g., teachers and students). Indeed, the main challenge for educators has been on what appropriate steps should be taken to prevent learning loss for the students; ranging from how to provide efficient learning tools/curriculum that ensures continuity of learning, to provision of methods that incorporate coping mechanisms and acceleration of education in general. For several higher educational institutions (HEIs), technology-mediated education has become an integral part of the modern teaching/learning instruction amidst the Covid-19 pandemic, when digital technologies have consequently become an inevitable and indispensable part of learning. To this effect, this study defines a hybrid educational model (HyFlex + Tec) used to enable virtual and in-person education in the HEIs. Practically, the study utilized data usage report from Massive Open Online Courses (MOOCs) and Emotions and Experience Survey questionnaire in a higher education setting for its experiments. To this end, we applied an Exponential Linear trend model and Forecasting method to determine overall progress and statistics for the learners during the Covid-19 pandemic, and subsequently performed a Text Mining and Univariate Analysis of Variance (ANOVA) to determine effects and significant differences that the teaching–learning experiences for the teachers and students have on their energy (learning motivation) levels. From the results, we note that the hybrid learning model supports continuity of education/learning for teachers and students during the Covid-19 pandemic. The study also discusses its innovative importance for future monitoring (tracking) of learning experiences and emotional well-being for the stakeholders in leu (aftermath) of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]