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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.

Globally “non-urgent” health care services were ceased in response to the 2020 outbreak of COVID-19, until 2021, when restrictions were lifted. In the UK, this included speech and language therapy services. The implications of COVID-19 restrictions have not been explored. This study aimed to examine the impact of the UK’s COVID-19 response on speech and language therapy services.

An online survey of the practice of speech and language therapists (SLTs) in the UK was undertaken. This explored SLTs’ perceptions of the demand for their services at a time when COVID-19 restrictions had been lifted, compared with before the onset of the pandemic. The analysis was completed using descriptive statistics and content analysis.

Respondents were mostly employed by the UK’s National Health Service (NHS) or the private sector. Many participants reported that demands on their service had increased compared with before the onset of the pandemic. The need to address the backlog of cases arising from shutdowns was the main reason for this. Contributing factors included staffing issues and redeployment. Service users were consequently waiting longer for NHS therapy. Private therapy providers reported increased demand, which they directly attributed to these NHS challenges.

This presents the only focused account of the impact of the national response to COVID-19 on speech and language therapy services in the UK. It has been identified that services continue to face significant challenges, which indicate a two-tier system is emerging. Healthcare system leaders must work with service managers and clinicians to create solutions and prevent the system from being overwhelmed.

Key to transnational higher education (HE) cooperation is building trust to allow for seamless recognition of studies. Building on the Tuning Educational Structures initiative (2001) and lessons learnt from the Organisation for Economic Cooperation and Development (OECD)-Assessment of Learning Outcomes in Higher Education (AHELO) feasibility study, this paper offers a sophisticated approach developed by the European Union (EU)-co-financed project Measuring and Comparing Achievements of Learning Outcomes in Europe (CALOHEE). These evidence the quality and relevance of learning by applying transparent and reliable indicators at the overarching and disciplinary levels. The model results allow for transnational diagnostic assessments to identify the strength and weaknesses of degree programmes.

The materials presented have been developed from 2016 to 2023, applying a bottom-up approach involving approximately 150 academics from 20+ European countries, reflecting the full spectrum of academic fields. Based on intensive face-to-face debate and consultation of stakeholders and anchored in academic literature and wide experience.

As a result, general (overarching) state-of-the-art reference frameworks have been prepared for the associated degree, bachelor, master and doctorate, as well as aligned qualifications reference frameworks and more detailed learning outcomes/assessment frameworks for 11 subject areas, offering a sound basis for quality assurance. As a follow-up, actual assessment formats for five academic fields have been developed to allow for measuring the actual level of learning at the institutional level from a comparative perspective.

Frameworks as well as assessment models and items are highly innovative, content-wise as in the strategy of development, involving renown academics finding common ground. Its value is not limited to Europe but has global significance. The model developed, is also relevant for micro-credentials in defining levels of mastery.

The purpose of this study is to generate knowledge about assessment methods in blended business education, which have become increasingly important to establish sustainable assessment practices that support knowledge acquisition for undergraduate students in business administration at a Colombian university.

For the analysis, a two groups comparison was performed using a nonequivalent control group design with a sample of 420 students. As this study wants to find insights to improve the knowledge on assessment topics in marketing research (MR) education, it was focused on the students from the business administration program. This study also uses individual scores from the state test as prior cognitive scores and the high school classification provided by the National Ministry of Education in Colombia (2012).

It was found that the variables that best predict performance on the MR course examinations were the mathematics skills and reading comprehension scores on the state test. The study also showed a better performance of female students on both assessment methods. There were no significant differences between the assessment methods or among the high school levels.

One of the limitations of this study is the limited number of items on the tests. Additionally, the authors recommend conducting an analysis of the differences between the testing items to provide a detailed explanation of students’ performance when comparing computer-based testing and paper-and-pencil testing.

Further design of teaching material and assessments online and offline, based on local and regional marketing problems, is suggested. As the current text and readings are more oriented to the English-speaking contexts, most of the problems presented are oriented to multinational companies and brands.

Insights into the skills required for future jobs provide valuable guidance (World Economic Forum, 2020). Essential skills for emerging roles, like data scientists, can find robust support within the MR course. To further enrich in-class and online exercises with Excel and SPSS, Colombian educators can leverage data sets obtained from sources like the national statistics office and international market intelligence databases available through the university’s library, including Passport and Statista. Engaging with authentic data sets provides students with a more profound understanding of practical applications in MR.

This approach facilitates the identification of key variables, such as assessment and cognitive abilities in math and reading, which predict students’ knowledge acquisition in MR. It not only offers insights into the relevant factors influencing learning in MR but also provides valuable feedback. Additionally, it suggests potential avenues for future research in this field.