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Considering the potential of Collaborative International Online Learning (COIL) for cross-boundaries interacting and collaborating effectively, this study aims to explore the intercultural awareness of pre-service language teachers after participating in a COIL project.

Following a quantitative research approach and an exploratory cross-sectional method, the authors administered a 13-item questionnaire to unveil the perceptions of 64 future language teachers from Spain after their online experience with counterparts from the USA.

Participants consider that COIL may have enhanced their intercultural and global awareness and equipped them with valuable skills and knowledge for the future, being women more positive than men. Moreover, the results also suggest that those participants who have not traveled abroad consider COIL to be a good opportunity to compensate for the lack of knowledge or experience with other cultures resulting from not having had the opportunity to visit other countries.

COIL needs to be seen as a powerful tool to promote global learning, intercultural understanding and the development of skills among students that will be vital for success in today’s interconnected world. Nevertheless, universities and teacher training centers need to rethink the preparation of future teachers for the increasing demands to prepare students for the requirements of the global world, and to do so, they need to consider that COIL may offer them significant benefits.

This work offers an interesting exploration of teachers’ attitudes toward COIL, providing insights into the potential of online collaboration for developing intercultural awareness.

Computer-Assisted Learning in Pediatrics Program (CLIPP) and National Board of Medical Examiners Pediatric Subject Examination (NBMEPSE) are used to assess students’ performance during pediatric clerkship. International Foundations of Medicine (IFOM) assessment is organized by NBME and taken before graduation. This study explores the ability of CLIPP assessment to predict students’ performance in their NBMEPSE and IFOM examinations.

This cross-sectional study assessed correlation of students’ CLIPP, NBMEPSE and IFOM scores. Students’ perceptions regarding NBMEPSE and CLIPP were collected in a self-administered survey.

Out of the 381 students enrolled, scores of CLIPP, NBME and IFOM examinations did not show any significant difference between genders. Correlation between CLIPP and NBMEPSE scores was positive in both junior (r = 0.72) and senior (r = 0.46) clerkships, with a statistically significant relationship between them in a univariate model. Similarly, there was a statistically significant relationship between CLIPP and IFOM scores. In an adjusted multiple linear regression model that included gender, CLIPP scores were significantly associated with NBME and IFOM scores. Male gender was a significant predictor in this model. Results of survey reflected students’ satisfaction with both NBMEPSE and CLIPP examinations.

Although students did not perceive a positive relationship between their performances in CLIPP and NBMEPSE examinations, this study demonstrates predictive value of formative CLIPP examination scores for their future performance in both summative NBMEPSE and IFOM. Therefore, students with poor performance in CLIPP are likely to benefit from feedback and remediation in preparation for summative assessments.

While most language departments of the university offer service-learning (SL) subjects based on language teaching, such as “Teaching Chinese as a Second Language in Local Schools” and “Serving the Community through Teaching English,” this paper aims to argue that teaching students to teach language(s) is yet to be the best strategy to serve the service recipients.

SL is widely understood as an experiential learning pedagogy that integrates academic focus, reflection and community service and is shown to be impactful. In Hong Kong, the first university that has made SL a graduation requirement is the Hong Kong Polytechnic University (the University). Considering this, new SL courses have proliferated over the past decade. Adopting a narrative inquiry approach, this paper examines personal narratives from a new SL subject aiming to raise awareness of refugees in Hong Kong. The data includes students’ reflective journals, co-created personal narratives and podcasts and semi-structured interviews.

This paper finds that crafting and recording narratives of shared experiences deepens cultural understanding, cultivates empathy and facilitates language learning in a genuine setting.

Ultimately, this paper advocates a well-designed SL that combines language, content and technology as a powerful, transformational experience for both college students and service recipients.

This paper focuses on a brand new SL course, “Storytelling for Understanding: Refugee Children in Hong Kong,” offered in Semester 1, 2022–2023. The subject was developed by the two authors from a language division affiliated to the University. The deliverables were podcast recordings, co-authored and co-edited by the students and the children.

We aimed to identify factors that influence student engagement in distance learning.

The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.

The components of the students’ attitude toward remote classes learning conditions are: satisfaction with teachers’ approach, attitude to distance learning, the system of students’ values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student’s sex, level of studies and the first five extracted PCs. Student’s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.

The research result suggests that in addition to students’ system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers’ attitude is one of the three most important factors that influence student engagement during the distance learning process.

The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.

The literature mainly concentrates on the relationships between externally oriented digital transformation (ExtDT), big data analytics capability (BDAC) and business model innovation (BMI) from an intra-organizational perspective. However, it is acknowledged that the external environment shapes the firm's strategy and affects innovation outcomes. Embracing an external environment perspective, the authors aim to fill this gap. The authors develop and test a moderated mediation model linking ExtDT to BMI. Drawing on the dynamic capabilities view, the authors' model posits that the effect of ExtDT on BMI is mediated by BDAC, while environmental hostility (EH) moderates these relationships.

The authors adopt a quantitative approach based on bootstrapped partial least square-path modeling (PLS-PM) to analyze a sample of 200 Italian data-driven SMEs.

The results highlight that ExtDT and BDAC positively affect BMI. The findings also indicate that ExtDT is an antecedent of BMI that is less disruptive than BDAC. The authors also obtain that ExtDT solely does not lead to BDAC. Interestingly, the effect of BDAC on BMI increases when EH moderates the relationship.

Analyzing the relationships between ExtDT, BDAC and BMI from an external environment perspective is an underexplored area of research. The authors contribute to this topic by evaluating how EH interacts with ExtDT and BDAC toward BMI.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.