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The purpose of this case study is to determine the effectiveness of the UDL academy in terms of the number of UDL techniques used by faculty after participating in the academy and surveys to explore faculty perceptions of UDL.

This quantitative case study utilized faculty surveys about the UDL academy, class observations and review of course syllabi to determine the effectiveness of the UDL academy and explore the experience of implementing UDL.

The UDL initiative has been a positive and effective experience. Broadly, faculty have had positive perceptions of UDL implementations based on faculty surveys. The effectiveness of the UDL academy was demonstrated by the number of UDL techniques used by faculty increased significantly for faculty that participated in the UDL academy. The control group of faculty members did not increase the number of UDL techniques used based on class observations and a review of course syllabi.

This research is from one librarian's perspective since the librarian led the UDL initiative and is the sole librarian with faculty status currently at the institution. As a proponent of UDL, the librarian's perspective may be biased. Librarians can implement UDL to reduce educational barriers and support student success. Additionally, librarians can offer support to faculty in learning about UDL by offering a similar UDL academy.

Most faculty were able to incorporate UDL elements into their courses and responded positively to the concept of integrating UDL in the classroom, feeling that it helped improve their teaching. These results demonstrate that faculty can integrate UDL into higher education to use effective teaching strategies after participating in a UDL academy.

This paper is an original work describing a campus UDL initiative from a librarian's perspective.

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.

Eleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.

The findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.

This study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

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.

The purpose of this study is to examine the formation of sustainable development competencies (SDCs) in future primary school teachers during English for specific purposes classes, and to assess the correlation between English proficiency and the development of SDCs, including Collaboration, Strategic thinking, Critical thinking, Modelling sustainable behaviour, Systems thinking and Future thinking.

The research experiment involved the application of content and language integrated learning and facilitation methods in three higher education institutions in Ukraine. The students’ level of English language proficiency was assessed based on the results of the online Cambridge English Language Assessment test, while the level of SDC formation was measured using research methods adapted to the Ukrainian context.

The experiment revealed positive changes in the levels of SDCs and English language proficiency through integrated learning and the application of facilitation methods.

The study established a correlation between the level of English language proficiency and the formation of competencies, such as Collaboration, Strategic thinking, Critical thinking, Modelling sustainable behaviour, Systems thinking and Future thinking, all of which are vital for sustainable development.

The aim of this paper is to examine the existing literature circa 2010–2023 of introductory wine education involving sensory experience components in an objective, transparent and replicable manner. Sensory experience education normally involves the usage of the five senses (smell, taste, sight, feel and hearing) as means to demonstrate, scaffold and illuminate introductory-level wine curricula. This study identifies the methodologies used in existing in educational wine sensory experience literature, identifies the pedagogical utilities of current wine research and explores findings useful for wine educators.

This paper uses the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) for literature review reporting.

From the existing body of literature involving wine sensory experience in education (N = 20), five pedagogical utilities emerged from the dataset: wine sensory experience training (n = 7), wine sensory analysis techniques (n = 5), teaching environment (n = 5), wine and food pairing (n = 2) and psychological context (n = 1). Furthermore, experimental design is the preferred method (n = 14) of research related to wine sensory experience in education.

This study provides utility for wine educators at the college and university level and may provide perspective and tools for firms seeking consumer engagement through wine education.

To the researchers' knowledge, there are no literature reviews that explore wine sensory experience in education. Thus, the primary contributions of this study are threefold: identification of current gaps in wine education research, identification of future research questions and avenues of study, and resources for curriculum improvement of introductory wine courses.

This study aims to measure the global research landscape of the National Institute of Pharmaceutical Education and Research (NIPER) of India on a set of quantitative and qualitative metrics in terms of research output toward exploring research trends and give an overview of collaborative practices by researchers of NIPERs.

The present study has selected the Scopus database as a tool to retrieve potential publications of studied NIPERs during the last 12 years (2010–2021). NIPER-Mohali, NIPER-Hyderabad, NIPER-Ahmedabad, NIPER-Guwahati and NIPER-Kolkata have been selected for the study. The study has adopted a comprehensive search strategy to extract 3,926 publications data. VOS viewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The global scientific research output of NIPERs accrued 3,926 publications with an average of 327 publications per year. The retrieved publications fetched a total of 67,772 citations with an average citation impact of 17.26. There observed a steady growth of publications from 168 to 509 registered with an average growth rate of 18.44%. The mean relative growth rate and doubling time of research output are 0.26 and 2.94. The authorship patterns explore collaborative trends as most of the publications were published by multiple authors (99.39%). NIPERs have expanded their outreach to collaborate with the USA, Malaysia, Saudi Arabia, Australia and the UK to collaborate on research and regulatory reforms exhibits in the USA as a major contributor.

The present study is the first effort to evaluate the global research productivity of NIPERs and assess the current research trends on a set of quantitative and qualitative metrics to provide some insights into the complex dynamics of research productivity. The study’s outcome may help to identify the current research progress of NIPERs at the global level.

This article focuses on the assessment of entrepreneurship competence by selected vocational teachers in Italy. The exploratory research question addresses the extent to which entrepreneurship assessments are competence based, and the research seeks to identify fully fledged assessment programmes with both a formative and summative component, and the use of assessment rubrics. It also explores the extent to which entrepreneurship competence is referred to in school documentation and later assessed, and the tools and strategies used for such assessment.

This case study is part of a larger European research project promoted by Cedefop; in Italy it focused on six selected vocational IVET and CVET programmes and apprenticeship schemes. It used a wide range of instruments to ensure triangulation and multiple perspectives: analysed policy documents and undertook online interviews with experts and policy makers. At VET providers' premises it deployed: analysis of school documents; observations of learning environments; interviews and focus groups with (in schools) teachers, directors and vice directors, learners and alumni (in companies) instructors, company tutors and employers, apprentices and alumni.

Assessment tasks were rarely embedded within fully fledged assessment programmes involving both formative and summative tasks, and assessment rubric for grading. Most of the time, entrepreneurship programmes lacked self-assessment, peer assessment and structured feedback and did not involve learners in the assessment process. Some instructors coached the students, but undertook no clear formative assessment. These findings suggest institutions have a testing culture with regard to assessment, at the level of both policy and practice. In most cases, entrepreneurship competence was not directly assessed, and learning outcomes were only loosely related to entrepreneurship.

One limitation concerned the selection of the VET providers: these were chosen not on a casual basis, but because they ran programmes that were relevant to the development of entrepreneurship competence.

At the policy level, there is a need for new guidelines on competence development and assessment in VET, guidelines that are more aligned with educational research on competence development. To ensure the development of entrepreneurship competence, educators need in-service training and a community of practice.

So far, the literature has concentrated on entrepreneurship education at the tertiary level. Little is known about how VET instructors assess entrepreneurship competence. This study updates the picture of policy and practice in Italy, illustrating how entrepreneurship competence is developed in selected IVET and CVET programmes and apprenticeships.

This paper aims to propose an innovative method for deploying a personalized instructor-created software-aided assessment system, that will disrupt traditional learning environments by allowing students to confidentially and with indirect supervision from the instructor, assess their knowledge and ability to achieve the course outcomes.

Through empirical evaluation in real-world educational settings, the authors examine the impact of augmenting human activity in the classroom with an innovative software platform to transform the learning process.

Findings indicate that this software-aided assessment system effectively augments human interactivity by providing timely instructor-designed feedback to increase knowledge retention and skillsets.

This study has shown that incorporating disruptive innovation through the use of software-aided assessment systems increases the effectiveness of the faculty in the classroom and enhances student learning and retention. Thus, a transformative software-aided assessment system design that incorporates artificial intelligence into the learning pathway should be pursued. These software-aided assessments are disruptive innovation as they are formative, frequent and require little direct involvement from the instructor.

To the best of the authors’ knowledge, this study is the first of its kind to incorporate artificial intelligence into the assessment process by analyzing results of pilot programs at several universities. The results demonstrate how using software-aided transformative assessments in various courses have helped instructors assess students’ preparedness and track their learning progress. These software-aided systems are the first step in bringing disruptive innovation to the classroom as these software-aided assessment instruments rapidly assess learners’ knowledge and skills based on short, easily created, multiple-choice tests, with little direct engagement from the faculty.

This paper investigated the possibilities of implementing inclusive education in the tertiary-level language classrooms and suggests new teaching methodologies adhering to the guidelines of multicultural education (MCE) framework. It explored how Indian teachers fostered social inclusivity in ESP (English for Specific Purposes) classrooms and documented the methods used by the language teachers to sustain a socially inclusive environment in the classroom.

This qualitative study undertaken with 17 faculty members using online interviews and surveys as tools revealed the challenges faced by the teachers.

The results have implications towards teacher training as there is a clear dearth of teacher strategies to foster an equitable and inclusive learning environment inside the classroom.

Classrooms are the sources of values and perspectives, and teachers are responsible for providing equal opportunities to students who are otherwise marginalised in society.

Inclusive education aims at providing equal opportunities to people despite the differences in terms of race, class, caste, region, religion, gender, sexuality, ethnicity and disabilities. India being a multilingual and multicultural country, inculcating values in students to enable them to reflect beyond these differences becomes important.

The study showcases the social impact (online attention) of funded research compared to nonfunded for the BRICS nations. The key themes achieving online attention across the funded and nonfunded publications have also been identified.

A total of 1,507,931 articles published across the BRICS nations for a period of three (03) years were downloaded from the Clarivate Analytics' InCites database of Web of Science (WoS). “Funding Acknowledgement Analysis (FAA)” was used to identify the funded and nonfunded publications. The altmetric score of the top highly cited (1%) publications was gauged from the largest altmetric data provider, “Altmetric.com”, using the DOI of each publication. One-way ANOVA test was used to know the impact of funding on the mentions (altmetrics) across different data sources covered by Altmetric.com. The highly predominant keywords (hotspots) have been mapped using bibliometric software, “VOSviewer”.

The mentions across all the altmetric sources for funded research are higher compared to nonfunded research for all nations. It indicates the altmetric advantage for funded research, as funded publications are more discussed, tweeted, shared and have more readers and citations; thus, acquiring more social impact/online attention compared to nonfunded publications. The difference in means for funded and nonfunded publications varies across various altmetric sources and nations. Further, the authors’ keyword analysis reveals the prominence of the respective nation names in publications of the BRICS.

The study showcases the utility of indexing the funding information and whether research funding increases social impact return (online attention). It presents altmetrics as an important impact assessment and evaluation framework indicator, adding one more dimension to the research performance. The linking of funding information with the altmetric score can be used to assess the online attention and multi-flavoured impact of a particular funding programme and source/agency of a nation so that necessary strategies would be framed to improve the reach and impact of funded research. It identifies countries that achieve significant online attention for their funded publications compared to nonfunded ones, along with the key themes that can be utilised to frame research and investment plans.

The study represents the social impact of funded research compared to nonfunded across the BRICS nations.