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Student persistence has long been a major challenge for open universities. Despite the evolution of open education, an overall high student attrition rate remains. This paper examines the changes and trends in factors related to student persistence in open universities. It reviews the empirical studies from the 1970s to the 2010s which reported factors influencing student persistence. The relevant studies were searched from databases, including Scopus, Web of Science, and Google Scholar. Among the 108 studies collected, a total of 284 factors influencing student persistence were identified. The factors were categorised into student factors, institutional factors, and environmental factors. Their changes and trends over the years were examined. The results show that student factors were the most frequently studied over the years examined, with the major categories being students' psychological attributes and outcomes. Institutional factors have been increasingly studied in recent decades, with the design and delivery of programmes and courses being the strongest category. Finally, environmental factors have been decreasingly examined, with factors related to students' family and work being the two main categories. Based on the results, the implications for developing intervention and retention strategies for student persistence in open universities are discussed.

In higher education, non-traditional students experience a range of challenges, from aspiration and access into university to academic progress and success in their degree. Most students either enter employment or further study after their degree. This paper focuses on the latter stages of the effort to widen student access and participation in higher education, with an exploratory study of the career preparation and readiness of 22 final-year undergraduates from non-traditional backgrounds in the UK. We explore how students prepare themselves and are prepared by their degree for life after university, with the focus on career preparations and employment. In particular, we discuss the challenges for these students to engage in opportunities such as work experiences and extracurricular activities, which have implications for their chances of success and social mobility. We conclude with recommendations for practice, especially for academic and professional staff.

Background: The analogy of the leaky pipeline has been used to describe STEM education, with lower student diversity from compulsory to post-compulsory education and beyond. Although extensive research has explored the views and experiences of school-aged children about STEM, fewer studies have examined the career intentions of STEM students at university, especially those from under-represented backgrounds (e.g., racial/ethnic minority, women and working class students). This paper draws on a large qualitative study that interviewed 110 under-represented STEM undergraduates in the UK. We focus on students' STEM career intentions and the likely directions of their post-degree trajectories, drawing on the lenses of science identity and Social Cognitive Career Theory. Results: Three pathways were identified. The first group plans to pursue a career in or from STEM. While social inequalities may persist, the potential impact of these challenges may be neutralised by the personal drive and passion of STEM career-oriented students, who seem committed to "drive into an STEM future." The second group stated intentions for non-STEM-related careers, leaving the STEM pipeline. The reasons students gave for their imminent departure from STEM are the better financial reward on offer in some non-STEM sectors, especially in finance and business, as well as wider social inequalities and stereotypes. The third group was undecided, those who are uncertain or unclear about their futures. Students described a general lack of direction or clear career pathway, from a complete lack of career ideas to an overload of options. Conclusions: We conclude with a reminder that the STEM pipeline is far from secured or equitable, despite apparent progress in participation and representation. We reiterate the importance of fostering a diverse, inclusive and supportive learning environment that maximises the participation, strengths and potential of all students, especially those from under-represented backgrounds. While it is not uncommon for STEM students to pursue careers outside of STEM, we need to be wary that those who exit the STEM pipeline are not "forced off the road" by social inequalities and exclusions.

Oral input has long been recognised as a key factor influencing second language acquisition in early childhood. Children rely heavily on oral input to learn new words and develop phonological awareness of a language. However, in the context of English teaching in Hong Kong kindergartens -- which feature diversity in language use in the classroom -- little work has been done on the oral input given to children. This study examined the English oral input of teachers in Hong Kong kindergarten classrooms. It investigated the amount and features of teachers' English oral input, and how the input affected the conditions for English language learning. Classroom observations were conducted monthly for three months with one native speaking (NS) and two non-native speaking (NNS) kindergarten teachers together with a total of 44 Chinese-speaking children. The research used the Oral Input Quality Observation Scheme developed for systematically collecting oral input and output data from the teachers and children respectively. The results show that the learning activities did not seem to be hindered by the different pronunciations of the NS and NNS teachers. However, the NS teacher tended to use a broader variety of vocabulary and a richer amount of English than the NNS teachers. Both the NS and NNS teachers demonstrated limitations in pedagogical skills in teaching the children English pronunciation. The implications of the results are discussed in relation to the context of English teaching in Hong Kong kindergartens.

In the United Kingdom, a "good" undergraduate degree is understood to be a "first class" or an "upper second class," which is achieved by three-quarters of students. The need to distinguish oneself from others is ever more important in an increasingly crowded graduate market, although a first-class degree is most likely achieved by privileged students. Informed by Bourdieu's theory of habitus and capital, this study explores the educational experiences and trajectories of 30 final-year high-achieving nontraditional (HANT) students through in-depth interviews. These include working-class, minority ethnic, and/or mature students at university. We found that prior development in academic study skills and the desire to prove oneself, often in response to previous negative experiences, are key ingredients in academic success. Our HANT students also seem to find inspiration or support from significant others, an educational capital, although these resources are often by chance rather than by plan. Implications for policy and practice are suggested.

This study aims to examine the use of learning analytics in course evaluation within higher education institutions, in order to identify effective methodologies and best practices for leveraging data to improve educational effectiveness. Following the PRISMA guidelines, a systematic literature search was conducted in Scopus, yielding 34 relevant studies published between 2015 and 2024 for analysis. The results reveal six key categories of learning analytics applications: sentiment analysis, questionnaire analysis, engagement analysis, topic classification, predictive modelling, and performance analysis. The data sources for learning analytics applications primarily include questionnaires and learning management systems. While descriptive analysis was found to be the most commonly employed analytical technique, advanced techniques such as machine learning, artificial intelligence, and social network analysis are becoming more prominent. The studies addressed a wide range of elements associated with course evaluation, including course design, content quality, assignments, instructional strategies, workload, feedback mechanisms, and the integration of technology. These findings highlight the importance of adopting holistic approaches to capture the multifaceted nature of student experiences. This study also uncovers major limitations in the existing research, such as small sample sizes, potential biases due to the use of survey-based methods, and challenges in generalising findings across disciplines. These insights underscore the need for further research to enhance the methodologies used in course evaluations. This study contributes to advancing learning analytics practices and emphasises the importance of innovative approaches for evaluating and improving course effectiveness. [ABSTRACT FROM AUTHOR]

This article presents a review of the literature on smart learning in order to provide a comprehensive overview of its latest developments in research and practice. The review covered 90 studies published from 2010 to 2019, which were collected from three publication databases, namely Web of Science, Scopus and ProQuest. They were analysed for the patterns and trends in terms of publication years, sources of publication, countries or regions of publication, research purposes, research methods, educational levels of the studies, application domains, research issues, research participants, learning devices or tools, learning environments and learning features. Overall, the findings show that increasing global attention was given to smart learning from diverse disciplines and contexts of application. The results also reveal the areas which should be addressed in future work: development of pedagogies which make effective use of smart learning technologies in different learning environments; examination of smart learning to cope with learners' needs in informal contexts; in-depth analysis of how smart learning could be tailored to fit the characteristics of various application domains; and investigation of the views and perceptions of teachers on smart learning technologies, their readiness to use these technologies and their challenges and needs for support.

Purpose: This paper examines the pedagogical features of massive open online courses (MOOCs) for language learning--known as language MOOCs. The mainstream pedagogy of MOOCs typically involves the provision of short videos and reading materials for self-study; discussion forums, mostly for peer-to-peer interaction on course content; and machine-graded quizzes for self-assessment. For language learning, which has been conventionally understood as skill development, the pedagogical features of relevant MOOCs have yet to be comprehensively surveyed. Design/methodology/approach: This study surveyed a total of 123 language MOOCs from the major MOOC platforms. The pedagogical features shown in these courses were identified and categorised according to the types of course materials and learning activities as well as the participation of learners and instructors. Findings: English was the most common language taught in the courses. Over 80% of the courses took not more than six hours to complete. Most of these courses followed the typical approach of xMOOC delivery, with video watching, reading and auto-graded assessment being the most common learning activities. Less than half of the courses included discussion as part of learning, and instructors were involved in less than 30% of the discussion. Originality/value: The findings show that, despite the technological advances in course delivery, current language MOOCs do not differ substantially from conventional distance language learning. Yet, the utilisation of computer-assisted language learning technology and the massive student base of MOOCs for creating a virtual social community are opportunities for developing learners' language proficiency on this learning environment.

This paper presents a comprehensive survey of knowledge graphs in education. It covers the patterns and prospects of research in this area. A total of 48 relevant publications between 2011 and 2023 were collected from the Web of Science, Scopus, and ProQuest for review. The findings reveal a sharp increase in recent years in the body of research into educational knowledge graphs which was mainly conducted from institutions in China. Most of the relevant research work adopted a quantitative method, such as performance evaluation, user surveys, and controlled experiments, to assess the effectiveness of knowledge graph approaches. The findings also suggest that knowledge graph approaches were primarily researched and implemented in higher education institutions, with a focus on computer science, mathematics, and engineering. The most frequently addressed objectives included enhancing knowledge representation and providing personal learning recommendations, and the most common applications were concept instruction and educational recommendations. Diverse data resources, such as course materials, student learning behaviours, and online encyclopaedia, were processed to implement knowledge graph approaches in different scenarios. Relevant technical means employed for the implementation of knowledge graphs dealt with the purposes of building knowledge ontology, achieving recommendations, and creating knowledge graphs. Various pedagogies such as personalised learning and collaborative learning are supported by the knowledge graph approaches. The findings also identified key limitations in the relevant work, including insufficient information for knowledge graph construction, difficulty in extending applications across subject areas, the restricted scale and scope of data resources, and the lack of comprehensive user feedback and evaluation processes. [ABSTRACT FROM AUTHOR]

Low participation rates in the study of science, technology, engineering, and mathematics (STEM) post-16 are a matter of international concern. Existing evidence suggests children's science aspirations are largely formed within the critical 10 to 14 age period. This article reports on survey data from over 9,000 elementary school children in England (age 10/11) and qualitative data from 160 semi-structured interviews (92 children aged 10/11 and 78 parents), collected as part of an ongoing 5-year longitudinal study in the United Kingdom tracking children from 10 to 14. Drawing on the conceptual framework of Bourdieu, the article explores how the interplay of family habitus and capital can make science aspirations more "thinkable" for some (notably middle-class) children than others. It is argued that while family habitus is not deterministic (there is no straightforward alignment between family habitus, capital, and a child's science aspirations), social inequalities in the distribution of capital and differentially classed family habitus combine to produce uneven (classed, racialized) patterns in children's science aspirations and potential future participation. (Contains 4 notes and 1 table.)

Main objective of this paper is investigating the role of transit station accessibility on intercity travel mode choices in contexts of a proposed High Speed Rail. The study area is the Quebec-Windsor corridor, which is the most important corridor in Canada and one of the most important corridors in North America. A web-based joint revealed preference--stated preference survey is used to collect data for empirical investigation. To contribute further to travel survey methods, an innovative social media based data collection approach is taken. As opposed to explicit sample frame-based sample selection approach, it applies a reverse procedure of open sample frame-based data collection. The web-based survey is spread through social media groups (that are open in sense that information of all individuals are not known explicitly) and the collected responses are screened to match with population distributions. Results prove the potential of such data collection approach in extracting representative samples of the population of concern. The collected dataset, which has close representation of the population, is used to estimate discrete mode choice model (Nested Logit model) of intercity mode choices. Empirical model reveals that intercity travellers are more concerned about access to and egress from transit stations than the main in-vehicle travel while selecting intercity travel modes. The result of this investigate imply that transit station accessibility should be given careful consideration for the success of any innovative travel mode, e.g., high speed rail. Key words: intercity travel, transit accessibility, high speed rail, nested logit model. Le present article vise principalement a etudier la maniere dont l'accessibilite des stations de transit influe sur le choix d'un mode de transport interurbain dans le cadre d'un projet de liaison ferroviaire a grande vitesse. La zone etudiee est le corridor Quebec-Windsor, corridor le plus important du Canada et l'un des plus importants d'Amerique du Nord. Une enquete en ligne portant a la fois sur les preferences revelees et sur les preferences declarees permet de recueillir des donnees a des fins d'etude empirique. Pour ameliorer davantage les methodes employees dans le cadre d'enquetes portant sur les deplacements des personnes, on adopte une approche innovante de recueil de donnees s'appuyant sur les medias sociaux. Contrairement aux methodes de selection d'echantillons fondees sur des bases de sondage clairement definies, cette approche suit un processus inverse de recueil de donnees axe sur une base de sondage ouverte. L'enquete en ligne est publiee sur differents reseaux sociaux en ligne (consideres comme'ouverts'dans la mesure ou les renseignements de l'ensemble des membres de ces groupes ne sont pas vraiment connus) et les reponses recueillies sont filtrees en fonction de la repartition de la population. Les resultats montrent qu'une telle methode de recueil de donnees permet d'extraire des echantillons representatifs de la population etudiee. L'ensemble de donnees recueillies, qui donne une vraie representation de la population, sert a evaluer le modele de choix discret de mode de transport (modele logit emboite) sur lequel sont bases les choix de mode de transport interurbain. Le modele empirique montre que les voyageurs interurbains sont plus l'acces aux stations de transit et la sortie de ces dernieres que par le deplacement principal a l'interieur d'un moyen de transport lorsqu'ils choisissent un mode de transport interurbain. Les resultats de la presente etude montrent qu'il est essentiel de prendre en consideration l'accessibilite aux stations de transit pour garantir le succes d'un mode de transport innovant, tel qu'une liaison ferroviaire a grande vitesse. [Traduit par la Redaction] Mots-cles: deplacement interurbain, accessibilite des stations de transit, liaison ferroviaire a grande vitesse, modele logit emboite., Introduction The continued economic growth and development of urban areas within Canada have created corridors of population, economic activity, and movement of individuals. The Quebec-Windsor corridor is one such corridor. [...]

This paper presents a longitudinal study analysing the literature on the hybrid and flexible mode of learning (HyFlex learning) in terms of its research and practice over the past decade. A total of 84 articles published between 2013 and 2022 were collected from Scopus for analysis, covering their changes in publication patterns, research issues, features of practices, benefits, and challenges, as well as the recommendations given in the articles along the years. The results show a sharp increase in publications since 2018. Relevant work was primarily carried out at the tertiary level of education, with an emphasis on issues in respect of teachers' and students' perceptions, experiences, and behaviours in HyFlex learning. Most of the practices were mediated by technologies, which were primarily used for course delivery, course management, and in-class/off-class communication. The recommendations made in the literature cover the roles of teachers and institutions as well as relevant support, which are noted to have an impact on the effective implementation of HyFlex learning. The findings contribute to providing an overview of the longitudinal development and current state of HyFlex learning as well as insights into its future development in both research and practice. [ABSTRACT FROM AUTHOR]

A new stepwise time-domain analysis technique for power electronics circuits is presented. At each simulation step the rate of change of each state variable is determined by the corresponding reactive element parasitic resistance and state value obtained after performing a modified nodal analysis (MNA). A quadratic state trajectory description for each reactive element is formulated. To ensure the correct topological operation of the power stage, the algorithm monitors the position and checks the validity of all switches, requiring no a priori knowledge of their switching relationships. All computations require simple algebraic manipulations of resistive networks only. An example of simulating the responses of a zero-voltage-transition PWM buck converter is illustrated. The results are favorably compared to the previous method using constant nodal voltage approximation, experimental measurements, and the commercial software - PSpice. Index Terms - Circuit simulations, power electronics, switching regulators.

This paper presents a dual-loop iteration algorithm for steady-state determination of current-programmed direct current to direct current (dc-dc) switching converters. The methodology starts with separating the gate signal from the feedback circuit to the power stage in order to convert a closed-loop configuration into an open-loop one. The first iteration loop applies the Newton's method together with a time-domain simulation technique to find the steady-state state variables when the transformed configuration is operating at a constant duty cycle. The second iteration loop is to find the steady-state duty cycle using the secant method. The algorithm includes all of the advantages of a previously developed time-domain simulation technique and solves the nonconvergence problem in the single-loop iteration method, due to the amplifying effect of poor guess values of the state variables on the duty cycle in the feedback path during the iteration. A current-programmed boost converter is illustrated. The performances of the single-loop and the proposed methods are compared. The theoretical results are verified with the experimental measurements. Index Terms - Circuit simulation, dc-dc power conversion, iterative methods, Jacobian matrices, power electronics, switched mode power supplies, switching circuits.

A new iterative technique for steady-state analysis of pulsewidth modulated (PWM) dc/dc switching regulators is presented. The methodology is based on transforming the closed-loop regulator into an open-loop configuration. The steady-state solution is solved by two iteration loops. The first loop is to find the steady-state state variables when the converter is at a fixed duty cycle. The circuit waveforms are obtained by a stepwise time-domain simulation method, which is based on using stepwise quadratic formulation of the circuit state variables with progressive analysis of the switches' states. The second iteration loop is to determine the steady-state duty cycle of the PWM modulator output, using an explicit 'fictitious' ramp offset value as the error index. This two-loop iteration approach lessens the occurrence of the nonconvergence problem that is sometimes found in the single-loop iteration method. Furthermore, the advantages of this method include the following: 1) substantial improvement in speeding up the convergence to steady-state solution; 2) simplicity in requiring simple algebraic manipulations; 3) generality in determining valid topology without prior knowledge of the regulator operation; and 4) directness in determining the switching instants. Several examples illustrating the computational efficiency and the accuracy are presented and are verified with the available literature. Index Terms - Circuits simulation, power electronics.

A general-oriented time-domain simulation algorithm for power electronic circuits is presented. The methodology is based on stepwise quadratic formulation of circuit state variable trajectory with progressive analysis of switches' operation. At each simulation step, the circuit topology is transformed into a purely resistive network which is analyzed by the modified nodal analysis (MNA) technique. The rate of change of each state variable is determined by its parasitic resistance and instantaneous value. The trajectory of each state variable and switch branch voltage is expressed by a quadratic description. A simple and efficient method is used to determine the switching instants of circuit topologies. The prominent features of this approach include: 1) its simplicity in solving resistive network only throughout the analysis without dealing with any complicated Laplace-transformed equation or differential formula; 2) its generality in determining valid circuit topology without prior understanding of the switching relationships; 3) its directness in calculating the switching instants; and 4) its inherent consideration of the parasitic resistance of each reactive element in the analysis. Two examples illustrating the generality and computational efficiency of the proposed algorithm are presented. The simulated results are favorably compared to the method used in available literature and the commercial software, PSpice. Index Terms - Circuit simulation, power electronics, switching regulators.

A new general-oriented time-domain simulation technique for power electronic systems is developed. The algorithm is based on stepwise quadratic extrapolations on the branch voltages across each reactive element, together with progressive validation of the switches' operation. The power of this new technique lies in its simplicity in solving purely resistive networks for each topological configuration, generality in requiring no a priori understanding of the switching relationships and sequence of operations, inclusion of the effects of the parasitic elements, effectiveness of using computer memory, and ease of implementation on a desktop computer. Several examples illustrating the generality and computational efficiency of this new approach are presented and verified with experimental measurements and other available literature. Index Terms - Circuit simulation, power electronics.

This article presents a review of the literature on smart learning in order to provide a comprehensive overview of its latest developments in research and practice. The review covered 90 studies published from 2010 to 2019, which were collected from three publication databases, namely Web of Science, Scopus and ProQuest. They were analysed for the patterns and trends in terms of publication years, sources of publication, countries or regions of publication, research purposes, research methods, educational levels of the studies, application domains, research issues, research participants, learning devices or tools, learning environments and learning features. Overall, the findings show that increasing global attention was given to smart learning from diverse disciplines and contexts of application. The results also reveal the areas which should be addressed in future work: development of pedagogies which make effective use of smart learning technologies in different learning environments; examination of smart learning to cope with learners' needs in informal contexts; in-depth analysis of how smart learning could be tailored to fit the characteristics of various application domains; and investigation of the views and perceptions of teachers on smart learning technologies, their readiness to use these technologies and their challenges and needs for support. [ABSTRACT FROM AUTHOR]