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Work-Based Learning (WBL) is a form of practical learning that is still rare, yet upcoming in academic education. It differs mainly from classical approaches because work experience forms a key curriculum element. To enable WBL, a cultural change in academic landscape seems required, which depends on views and support of academic staff.

The authors carried out a case study, in which the authors interviewed 20 Dutch science professors to examine their vision on the master track Science, Business and Policy (SBP), a WBL program offered for over 15 years.

Generally professors are positive about its added value and recommend the track, especially for students with career ambitions outside academia. WBL is perceived to have a positive contribution to academic level. Professors indicated that for academic skills development, compared with a traditional master's program, SBP is evaluated neutral to positive.

Altogether the current climate at the university of Groningen towards WBL seems predominantly positive. The educational change towards a solid inclusion of WBL in the regular curriculum seems supported by one of the key players, the professors. This track could thereby be an example for other WBL programs worldwide.

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

Computer-assisted instruction (CAI) has been used to combat reading challenges, namely reading accuracy and rate for learners with intellectual, developmental and learning disabilities (IDLD). Whilst most reading CAI effectiveness has been studied in English, other transparent languages have less evidence. This study provides a systematic review and meta-analysis of CAI effectiveness for transparent language reading for K-3 learners with IDLD.

This study systematically reviews academic peer-reviewed studies from 2010 to 2023 with either randomised controlled treatment (RCT) or single-case treatments. Articles were searched from the ACM Digital Library, Google Scholar, IEEE Xplore, ERIC, PsychINFO and Science Direct databases, references and systematic review articles. Reading component skills effect sizes were computed using the random effect sizes model.

11 RCT studies of reading CAI for transparent languages with 510 learners with IDLD were found. A random effect sizes (Cohen’s d) of CAI on individual reading component skills were d = 0.24, p-value = 0.063 and confidence interval (CI) 95% (−0.068–0.551) for phonics and phonemic awareness d = 0.41, p-value = 0.000 and CI 95% (0.175–0.644). Given an average intervention dosage of 1.8 h weekly for a maximum of 16 weeks, CAI had better retention with d = 1.13, p-value = 0.066 and CI 95%(−0.339–2.588). However, these results must be interpreted with a concern of only using published studies.

The study contributes to quantitative CAI effectiveness for transparent language reading components for learners with IDLD.

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

This study aims to co-develop a Frailty, Health and Care Needs Assessment (FHCNA) questionnaire for people experiencing homelessness and explore the feasibility of its use by non-clinical staff in homeless hostels.

The FHCNA, aimed at identifying frailty and other health and care priorities for people experiencing homelessness, was co-designed in workshops (online and in person) with homelessness and inclusion health staff. Its feasibility was tested by staff and their clients in two hostels, with pre- and post-study focus groups held with hostel staff to gain input and feedback.

The FHCNA was co-developed and then used to collect 74 pairs of resident and key worker inputted data (62% of eligible hostel residents). The mean age of clients was 48 years (range 22–82 years). High levels of unmet need were identified. Over half (53%) were identified as frail. Common concerns included difficulty walking (46%), frequent falls (43%), chronic pain (36%), mental health issues (57%) and dental concerns (50%). In total, 59% of clients reported difficulty in performing at least one basic activity of daily living, while only 14% had undergone a Care Act Assessment. Hostel staff found using the FHCNA to be feasible, acceptable and potentially useful in facilitating explorations of met and unmet health and social care needs of hostel clients. By identifying unmet needs, the FHCNA has the potential to support staff to advocate for access to health and social care support.

To the best of the authors’ knowledge, this is the first study to co-develop and feasibility test a questionnaire for use by non-clinically trained staff to identify frailty and other health and care needs of people experiencing homelessness in a hostel setting.

This study aims to address the growing importance of online health information (OHI) and the associated uncertainty. Although previous research has explored factors influencing the credibility of OHI, results have been inconsistent. Therefore, this study aims to identify the essential factors that influence the perceived credibility of OHI by conducting a meta-analysis of articles published from 2010 to 2022. The study also aims to examine the moderating effects of demographic characteristics, study design and the platforms where health information is located.

Based on the Prominence-Interpretation Theory (PIT), a meta-analysis of 25 empirical studies was conducted to explore 12 factors related to information content and source, social interaction, individual and media affordance. Moderators such as age, education level, gender of participants, sample size, platforms and research design were also examined.

Results suggest that all factors, except social support, have significant effects on the credibility of OHI. Among them, argument quality had the strongest correlation with credibility and individual factors were also found to be relevant. Moderating effects indicate that social support was significantly moderated by age and education level. Different sample sizes may lead to variations in the role of social endorsement, while personal involvement was moderated by sample size, platform and study design.

This study enriches the application of PIT in the health domain and provides guidance for scholars to expand the scope of research on factors influencing OHI credibility.

To reveal the emotions and information needs expressed by Chinese parents of children with autism spectrum disorder (ASD) in an online forum, and their relationship.

The 10,062 data were from “Yi Lin”, China’s largest online forum for ASD. Open coding identified parents’ emotions and information needs, and a chi-squared test explored the correlation.

First, parents’ emotions were categorized into four themes: emotions about coping with their child’s care, emotions about the parents’ own behavior, emotions about social support with other parents and emotions about anticipating the future. Parents’ overall emotions were negative (72.47%), while the tendency of emotions varied among the four themes. Second, five information needs topics were expressed: intervention and training of ASD, parenting experiences, schooling issues, social interaction and support and future development. Different information needs topics contained different themes of emotions. Third, the tendency of emotions and expression of information needs were significantly correlated. Negative emotions had a statistically significant correlation in expression of information needs.

This study reveals the relationship between the emotions and information needs expressed by parents of children with ASD. The ASD forum could develop emotional support modules and functions for parents and facilitate emotional communication between parents.

In the digital age, emerging technologies have affected every industry. Information and communications technology and digital technologies have transformed traditional supply chains into smart and more resilient ones, enabling effective management of challenges. Given the importance of the two topics, namely sustainable supply chain management and Industry 4.0 in supply chain management, on the one hand, and the dearth of theoretical research performed in this area on the other, this study aims to propose a conceptual model on a sustainable digital supply chain management in manufacturing companies.

This study utilized a qualitative approach. First, an in-depth review of the relevant literature was done. Then, following a multi-grounded theory methodology, relevant data were gathered by reviewing 92 papers and conducting nine semi-structured interviews with industry experts. These data were analyzed using the MAXQDA software.

A total of 41 concepts, ten sub-components and three main components (dimensions) were extracted, and the proposed conceptual model was presented. Finally, based on this conceptual model, three propositions were suggested.

Considering that the present study was performed in the context of Iranian manufacturing companies, caution should be exercised in relation to the generalizability of the obtained results. Also, due to the problems in the digital technology infrastructure and the limited use of these technologies by manufacturing companies (emphasized by the interviewees), this study focused on the theoretical dimension of using digital technologies by these companies.

The proposed comprehensive model can help academicians as well as practitioners to focus better and explore the variables and constructs of the model, paving the way toward successful implementation of digital technologies in the manufacturing supply chain.

To the best knowledge of the authors, this study is among the first of its kind which presents a holistic and comprehensive digital supply chain model aimed at guiding companies to consider sustainability from all the main dimensions and their relevant indicators.

The purpose of the current study is to assess Omani teachers’ performance on tasks related to the stages of engineering design. To achieve this, data from an engineering design test was used, and demographic variables that are correlated with this performance were identified.

This descriptive study employed a cross-sectional design and the collection of quantitative data. A sample of preservice science teachers from Sultan Qaboos University (SQU) (n = 70) participated in this study.

Findings showed low and moderate levels of proficiency related to the stages of engineering design. Differences between males and females in terms of performance on engineering design tasks were found, with females scoring higher overall on the assessment. Biology preservice teachers scored higher than teachers from the other two majors (physics and chemistry) in two subscales. There were also differences between teachers studying in the Bachelor of Science (BSc) program and the teacher qualification diploma (TQD) program.

This study provides an overview, in an Arab setting, of preservice science teachers’ proficiency with engineering design process (EDP) tasks. It is hoped that the results may lead to improved instruction in science teacher training programs in similar contexts. Additionally, this research demonstrates how EDP competency relates to preservice teacher gender, major and preparation program. Findings from this study will contribute to the growing body of research investigating the strengths and shortcomings of teacher education programs in relation to science, technology, engineering and mathematics (STEM) education.