International Journal of Educational Technology in Higher Education最新文献

In this study we measured the effect of COIL on intercultural competence development using a quasi-experimental design. Our sample consisted of 108 undergraduate students from two universities, one located in the Netherlands (NL) and one in the United States (US). Students' self-reported intercultural competence was measured using a pre-post survey which included the Cultural Intelligence Scale (CQS) and Multicultural Personality Questionnaire (MPQ). Qualitative data were collected to complement our quantitative findings and to give a deeper insight into the student experience. The data showed a significantly bigger increase in intercultural competence for the US experimental group compared to the US control group, supporting our hypothesis that COIL develops intercultural competence. This difference was not observed for the NL students, possibly due to the NL control group being exposed to other international input during the course.

Supplementary information: The online version contains supplementary material available at 10.1186/s41239-022-00373-3.

The influence of personality traits on educational outcomes has been widely recognized and studied. Research has explored its effects on factors such as student satisfaction, academic anxiety, and dishonesty, particularly during the COVID-19 pandemic. However, there has been a lack of studies comparing the learning behaviors and performance of students with different personality traits during the pre, during, and post-COVID-19 lockdown periods. This study fills this gap by analyzing the differences in academic metrics, such as class grades and assignment submissions, among students with varying personality traits during different lockdown periods. Our research, based on a dataset of 282 graduate students in the USA, identified correlations and patterns between lockdown periods, personality traits, and academic metrics. For example, the class grades and the rate of late submissions were affected by different lockdown periods. Students with lower degree in extraversion and agreeableness made less attempts in assignment submissions. These findings can assist educators in identifying impacted students and developing effective teaching strategies at early stage in future incidents.

Digital games are considered relevant in higher education due to their ability to foster authentic, active and experiential learning opportunities that are of importance in engineering education. However, as a relatively new pedagogical tool, there is the need to understand the perceptions of engineering students as well as to identify factors that influence their adoption of games for learning. So far, only a few studies have investigated the perceptions of higher education students towards learning games and even fewer for engineering students. To bridge this research gap, the current study utilises a mixed-method research design to identify factors that influence the adoption of digital learning games by engineering students as well as their overall perceptions of the use of games for engineering education. Results from the analysed quantitative and qualitative data suggest that engineering students value fun and engagement as well as relevance to the curriculum as factors that would influence their intentions to use digital games for engineering education. Students also showed openness to the use of digital games for learning, but resistance to their use for assessment. These findings have implications for the design of games and classroom deployment of games, as these provide insights to game designers and educators on the factors to consider in the design and classroom deployment of games, respectively.

This paper aims to evaluate and discuss the digital competence of academics at universities, to identify challenges and define recommendations for policy. This study was conducted through collaboration between the Joint Research Centre (JRC) of the European Commission and Metared of the Universia Foundation, surveying 30,407 participants who present the perceptions of their own digital competence levels. These self-reflections took place in universities in seven countries, namely Argentina, Brazil, Colombia, Chile, Peru, Mexico and Portugal, and used the Check-In tool, which consists of 22 questions based on the European Framework for the Digital Competence of Educators-or 'DigCompEdu' framework. A descriptive statistical analysis was performed, followed by a qualitative evaluation. Almost 70% of the academics have an average intermediate level of competence when the data is aggregated, with results varying in each DigCompEdu area according to the specific question asked. There is no significant difference between young and senior academics, as well as between men and women. The results present a discussion of whether the age and gender of educators and their work environment have an impact on their digital competence level, and at the same time highlights the areas in which educators perceive themselves to be most and least competent. It shows how the amount of institutional support that is offered affects the academics' perceptions of their level of digital competence. On the basis of the results, recommendations are presented for higher-education institutions, with the aim of supporting the professional development of their academics.

As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI prediction models focus on the development and optimization of the accuracy of AI algorithms rather than applying AI models to provide student with in-time and continuous feedback and improve the students' learning quality. To fill this gap, this research integrated an AI performance prediction model with learning analytics approaches with a goal to improve student learning effects in a collaborative learning context. Quasi-experimental research was conducted in an online engineering course to examine the differences of students' collaborative learning effect with and without the support of the integrated approach. Results showed that the integrated approach increased student engagement, improved collaborative learning performances, and strengthen student satisfactions about learning. This research made contributions to proposing an integrated approach of AI models and learning analytics (LA) feedback and providing paradigmatic implications for future development of AI-driven learning analytics.

Research has shown that learners' stress and mental distress are linked to poorer academic outcomes. A better understanding of stress and mental distress experiences during study could foster more nuanced course and intervention design which additionally teaches learners how to navigate through to protect their academic performance. The current study draws on data collected via validated self-reported questionnaires completed by final year undergraduate students (n = 318) at a large distance education university. We examined how common features of stress, depression and anxiety link to each other using a network analysis of reported symptoms. The results included findings demonstrating the symptoms with the greatest relative importance to the network. Specifically, these included the stress symptom 'I found it difficult to relax' and the depression symptom 'I was unable to become enthusiastic about anything'. The findings could help institutions design interventions that directly correspond to common features of students' stress and distress experiences.

This research addresses an identified need to further understand digital literacies (DL) and whether undergraduate students view DL as being important in their lives and in their learning. Using a cross-sectional survey sent to a stratified random sample of 2500 undergraduates representative of the overall student population at a medium-sized Canadian undergraduate university (survey response rate of 19.8%, N = 496), we explored the relationships between social media and digital literacies, particularly in different disciplinary contexts. We also explored the ways in which students report using social media in their university learning, showing that students value social media for collaboration, discussion, information finding and sharing, and practise activities related to their learning. Additionally, we examined the importance students place on DL, and how they perceive and rate their own abilities with digital literacies across three domains: procedural and technical, cognitive, and sociocultural. Findings illustrate an observable gap between the high importance that students place on digital literacies (including DL for social media) in their learning and their lives and the lack of coverage students reported receiving about these topics in their undergraduate education. Based on the study's findings, we discuss the specific ways that those in the higher education community can address this gap by engaging with and fostering development of digital literacies within specific disciplinary and professional contexts, and in interdisciplinary or transdisciplinary learning settings across the curriculum.

Educational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions' scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and  appropriate investments.

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Micro-credentials are gaining traction as viable vehicles for rapid upskilling of the workforce in the twenty-first century and potential pathways for gaining employment for some students. The primary purpose of the current systematic review was to understand the current conceptions and discourses of micro-credentials in higher education and to identify the opportunities and challenges in adopting micro-credentials in higher education. The review also aimed to develop a need-driven micro-credentials framework that demonstrates the value of micro-credentials to stakeholders, i.e., learners, higher education institutions, employers, and government agencies. Key findings revealed that there are various stakeholders' needs and expectations. The learner wants short, practical, and up-to-date courses for their chosen career path, education institutions emphasise accreditation for building trust, employers want clarity regarding the competencies gained through micro-credentials, and government bodies expect higher graduate employability with lower tuition fees. Key findings revealed that implementing micro-credentials can be disruptive in the higher education sector and present several challenges. However, these challenges are likely to be mitigated by increased collaboration among stakeholders. The review has revealed several outstanding research questions critical for the success of micro-credentials as significant pathways to supplement traditional degree programmes. The research presented in the article has implications for policy development to guide the implementation of micro-credentials in the higher education sector.

This study explores a student-centered teaching method in postgraduate courses. Teacher-centered classroom teaching cannot fully stimulate learning initiative and enthusiasm of students. Student-centered means that students actively learn and construct knowledge by participating in teaching activities. This study presents a student-centered online-offline hybrid teaching method, which adopts student-centered case-based teaching and online-offline case discussion in the postgraduate courses of computer science. The latest engineering cases are integrated into teaching and a case library is constructed. Taking the digital image processing course as an example, student-centered teaching allows students to choose what to learn and how to learn. Case-based teaching makes students better understand the application of theory of knowledge. It can introduce multiple perspectives, promote understanding and reflection on problems, and help students develop higher-level thinking, analysis, and synthesis skills. This study explores online-offline case discussion method in the student-centered teaching and proposes the principles of case design of postgraduate courses. Revised Bloom's taxonomy is used for teaching assessment. The actual teaching effect shows that student-centered case-based teaching and online-offline case discussion have achieved better teaching effect.