Search results

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

This paper aims to attempt to provide an overview of the copyright legal framework for audiovisual resources in Europe and Greece, how Audiovisual (AV) content is currently licensed by Greek providers and how licenses or copyright exceptions enable its reuse. The motivation for this work was the development of an aggregation service for audiovisual resources in Greece, the Open AudioVisual Archives (OAVA) platform.

Copyright licenses and exceptions in the European Union and in Greek Legislation have been thoroughly reviewed along with the reuse of content, based on the terms of Fair Use, Rights Statements and Creative Commons. Licensing issues for the most well-known aggregation services, such as Europeana, Digital Public Library of America, Trove, Digital New Zealand and the National Digital Library of India, have also been studied and considered. Audiovisual content providers in Greece have been recorded, and their licensing preferences have been analyzed. Pearson’s chi-square test was applied to test the relationship between the provider’s type, resources’ genre and licenses used.

Despite the abundance of copyright legislation in the European Union and in Greece, audiovisual content providers in Greece seem to ignore it or find it difficult to choose the right license. More than half of them choose to publish their resources on popular audiovisual platforms using the default licensing option provided. Creative Commons licenses are preferred for audiovisual content that falls into the following categories: open courses (almost exclusively) and interviews and digital collection/research projects (about half of the content).

This paper examines audiovisual content aggregation, in the EU and Greece, from a legal point of view. To the best of the authors’ knowledge, it is the first attempt to record and analyze the licensing preferences of Greek AV content providers.

The purpose of this study is to explore the perceptions of teachers’ and undergraduate students concerning the provision of written corrective feedback (WCF) in Saudi EFL writing classrooms in the form of a case study.

The sample consisted of three teachers and five students, whose views on WCF were recorded via individual semi-structured interviews to gather qualitative data.

The results revealed some divergent viewpoints between students and teachers and among peers in both groups.

By offering the best WCF practice and considering students' interests, this research is important for improving the pedagogical approaches used by EFL instructors for teaching writing to university learners. It will, therefore, have more of an impact on EFL writing instruction.

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.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

The purpose of this study is to gain insight into the dynamics and considerations of professionals regarding the sharing of tacit, personal knowledge in their practice.

Adopting a social-constructivist ontology, the qualitative design deploys semi-structured interviews and focus groups. Data were coded, and analysed through interrelating and reasoning.

Personal knowledge is difficult to share precisely, but can be shared to some extent using reflection and stories. Knowledge also provides a position and professional agency, emphasising boundaries and impacting the decisions on interaction and sharing. As such, professional commitment is vulnerable and contextual and, by extension, material becomes part of this interplay of professional practice and collaborative development.

Findings imply that exchange and use of knowledge and material present in organisations are impacted by individual professionals’ autonomy and decisions, which consequently impact on employees’ practice. This calls for research that focuses on individual factors such as autonomy, professionalism and attitudes in addition to organisational and facilitative matters.

Stimulating professional commitment and interpersonal learning is a matter of valuing personal knowledge and practice to avoid protectionism, boundaries and segregated agency. Management and professionals should consider how and why individuals exchange their personal knowledge, paying attention to social structures and individuals’ voices and objectives in forming communities.

This study combines the concept of tacit knowledge with the younger field of practice theory. By connecting personal knowledge to practice, it extends agency to the material world and offers a more individual perspective to knowledge sharing in and between entities.

This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

This paper aims to explore consumer perception of “brand voice” authenticity, brand authenticity and brand attitude when the source of text is disclosed as either artificial intelligence (AI)-generated or human-written.

A 3 × 3 experimental design using Adidas marketing texts disclosed as either “AI” or “human”, or not disclosed was applied to data gathered online from 624 English-speaking students.

Text disclosed as AI-generated is not perceived as less authentic than that disclosed as human-written. No negative effect on brand voice authenticity and brand attitude results if an AI-source is disclosed.

Findings offer brand managers the potential for cost and time savings but emphasise the strong effect of AI technology on perceived brand authenticity and brand attitude.

Results show that brands can afford to be transparent in disclosing the use of AI to support brand voice as communicated in product description or specification or in chatbot text.