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Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

To know the digital competence of rural teachers to carry out the tutoring process with members of the educational community through digital resources (teacher-student, teacher-families and teacher-teaching team). As specific objectives, gender, teaching specialties, interaction between gender*teaching speciality, and significant predictors were analysed.

The research was quantitative, with a non-experimental, cross-sectional, descriptive and inferential design.

The results showed an explorer-expert teacher, where the generalist teachers had a superior competence compared to the rest of the specialties. Gender and teaching speciality were significant predictors in the communication that the teacher has with all the agents involved, while the interaction of both predictors was only significant between the teacher-teaching team and teacher-families.

Another issue worth considering relates to the development of the classification tree for the use of digital resources in tutorial action. Due to lack of space, the proposal has focused on gender and particular subjects, but it would be interesting to focus on the dimensions of the instrument with regard to tutorial action with the different agents (students, teaching staff and families).

After reviewing the literature, the authors can conclude that very little quantitative research is focused on the level of self-perception of digital competence of teachers in rural schools. Furthermore, the teaching speciality of teachers has up until now hardly been taken into account as a variable that can determine the levels of digital competence. Not many studies have analysed the use of digital resources to communicate with the different members of the educational community.

The aim of this research is to assess the influence of the underlying service quality variable, usually related to university students' perception of the educational experience. Another aspect analysed in this work is the development of a procedure to determine which variables are more significant to assess students' satisfaction.

In order to achieve both goals, a twofold methodology was approached. In the first phase of research, an assessment of the service quality was performed with data gathered from 580 students in a process involving the adaptation of the SERVQUAL scale through a multi-objective optimization methodology. In the second phase of research, results obtained from students were compared with those obtained from the teaching staff at the university.

Results from the analysis revealed the most significant service quality dimensions from the students' viewpoint according to the scores that they provided. Comparison of the results with the teaching staff showed noticeable differences when assessing academic quality.

Significant conclusions can be drawn from the theoretical review of the empirical evidences obtained through this study helping with the practical design and implementation of quality strategies in higher education especially in regard to university education.

The study explores diverse and critical understandings of “international” in a higher education curriculum context, situated in a curriculum review of a postgraduate taught programme entitled “International Education” at a university located in England. Our study problematises and decentres some dominant, normalised notions of “international”, exploring critical possibilities of engaging with the term for higher education internationalisation.

We examined a set of programme curriculum documents and conducted a survey exploring teaching staff’s uses and interpretations of “international” in their design and delivery of course units. Through a thematic analysis of the dataset, we identify what “international” might mean or how it may be missing across the curriculum.

Our findings suggest a locally-developed conceptualisation of “international” beyond the normalised interpretation of “international” as the inclusion or comparison of multiple nations, and different, other countries around the global world. More diverse, critical understandings of the term have been considered, including international as intercultural, competences, ethics, languages and methods. The study provides an example approach to reflective scholarship that programmes can undergo in order to develop clarity, depth and purposefulness into internationalisation as enacted in a local curriculum context.

The study provides a first step towards establishing clearer guidelines on internationalising the curriculum by higher education institutions and individual programmes in order to challenge a superficial engagement of “international” within internationalisation. It exemplifies a starting point for making purposeful steps away from normalised notions and assumptions of international education and facilitates development towards its critical, ethically-grounded opportunities.

The COVID-19 pandemic has dramatically transformed higher education policy and practices across the globe, including Bangladesh. Higher education institutions (HEIs) were forced to deliver teaching and learning online. This chapter discusses the impact of the COVID-19 pandemic on teaching and learning practice in higher education in Bangladesh and highlights the cultural transformation of policy and practice. In addition, it proposes future directions on how to be prepared and addresses the challenges of emergencies and draws implications of the findings beyond the national context. In the beginning of the pandemic, most universities in Bangladesh had to initially shut down their operations without offering any alternatives. However, a number of universities gradually rolled out some online teaching and learning activities as the lockdowns kept extending. A large portion of the HEIs struggled to continue their online teaching and learning due to the lack of resources, i.e., devices, technological skills and training, lack of policy, negative mindset, poor network infrastructure, and high cost of internet. This unprecedented situation ushered in by the pandemic showed the lack of preparedness and below-par capacity to respond to emergencies for the continuation of higher education in Bangladesh. Furthermore, it highlighted that improving the higher education sector requires tremendous effort from the government, researchers, policymakers, practitioners, the universities, and other industries directly or indirectly related to the sector.

The study aims to qualitatively analyze how faculty can mobilize the intellectual capital of higher education institutions (HEIs), comprising human, structural and relational capital to enable the education and learning of individuals with intellectual and developmental disabilities.

Drawing upon the extant literature, the researcher conducted a qualitative study through written, in-depth interviews with a sample of 40 academic staff/faculty members having prior experience in teaching individuals with intellectual and developmental disabilities. The data was collected through a set of questions formulated as key questions, to be asked to all participants for their responses.

Results of the analysis demonstrated that intellectual capital’s contribution to higher education of individuals with intellectual and developmental disabilities can be best understood in terms of its three components/dimensions. Accordingly, three main themes, with each comprising two sub-themes were uncovered. The first theme, leveraging human capital comprised: faculty acumen and faculty training as sub-themes; the second theme, resourcing structural capital comprised: tangible and intangible structural capital as sub-themes; and the third theme, nurturing relational capital comprised: in-class engagement and the second is ex-class connection as sub-themes.

The paper collects data from 40 faculty having prior experience in teaching individuals with intellectual and developmental disabilities to explore and reveal a completely new perspective of looking at intellectual capital as a means of providing accessible and inclusive higher education to differently-abled students, making them a part of the mainstream.

This paper explores stakeholder perceptions on the nature and extent of sustainability reporting on the websites of technical universities (TUs) in Ghana.

The authors collected data from the websites of the 10 TUs in Ghana and interviewed the stakeholders of the TUs. In analyzing the data, the authors used thematic analysis for the interview responses. The authors also adopted the global reporting initiative (GRI) guidelines and campus sustainability assessment tools for the presentation and analysis of the sustainability disclosures on the websites of the TUs.

The authors found that due to weak institutional coercions, there were limited disclosures on the websites of the TUs, which aimed at gaining stakeholders' legitimacy; the disclosures were more focused on organizational profile, governance and educational aspects of sustainability. To a large extent, while some external stakeholders such as parents, regulators and alumni appear to be less interested in the disclosures on the TU's websites, internal stakeholders such as employees (teaching and non-teaching staff) and students who frequently visited the TU's websites perceived limited reporting and were not impressed with the extent of sustainability disclosures on these websites.

The findings of this study are intended to assist policy-makers in the educational sector to appreciate the importance of sustainability reporting on their websites. The results of this study will assist higher educational institutions (HEIs) in increasing the success rate of sustainability implementation by overcoming the lack of sustainability disclosures on their websites. Thus, the results of this study have implications for sustainability implementations, particularly those in emerging economies and policy-makers of universities worldwide.

This study could provide two significant values. First, to the best of the authors’ knowledge, no other study has explored stakeholder perceptions of sustainability reporting in implementing sustainability within the education sector. Second, the results were arrived at by combining stakeholder consultations with content analyses, which could be a good guideline for sustainability implementation in the educational sector of developing countries.

This study aims to explore first-year engineering students’ perceptions of the engineering librarian as an instructor in multimodal environments related to Information Literacy (IL) topics, teaching strategy, content evaluation, organising, planning and support.

A quantitative approach was used through a survey instrument based on an online questionnaire. Questions were adopted and modified from a lecturer evaluation survey. A simple random sampling technique was used to collect data from first-year cohorts of engineering students in 2020 and 2022.

Respondents perception of the engineering librarian as an instructor in multimodal learning environment was good. Findings revealed students’ learning experiences were aligned with IL instruction even though the environment changed from blended to online. However, an emerging theme that continuously appeared was a lack of access to technology.

These findings may help in developing and strengthening the teaching identity of academic librarians as instructors in multimodal learning environments.

To the best of the author’s knowledge, this study is novel in that it evaluates the teaching abilities of an academic librarian in multimodal environments through the lens of students.

Saudi Arabia (SA) is amongst the few countries with a significant foreign workforce who are employed in the higher education sector. More specifically, 39% of SA's academic staff members are foreign nationals and 63% of that proportion occupy professorial positions. Drawing from a workforce localisation perspective, the study was framed as an exploration of equity and social justice amongst Saudi nationals and foreign nationals in a university work setting. The authors employ the lens of how human resource development (HRD) opportunities are administered.

Following the choice of an exploratory qualitative study, the authors employed a multi-case study approach where each of the six universities represented a unit of analysis.

The authors found that nationality differences influenced access to HRD opportunities. These differences are reinforced by practices associated with procedural processes, managerial discretion and selective restrictions in accessing HRD opportunities.

The findings have both practical and social implications, specifically for the SA government's strategic vision of developing local human capabilities.

The workforce localisation agenda within the higher education sector has both a compounding effect on local human capital and supports SA's 2030 Vision and human capital target. Nonetheless, perceived inequity and injustice in accessing HRD opportunities by foreign nationals potentially undermine morale, academic quality standards and research performance, which impacts the development of future human capital and the ‘Saudization’ goals.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.