Search results

This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms.

This paper describes a pedagogical approach that uses a data science framework the research team developed to assist teachers in providing data science instruction to elementary-aged students. Using phenomenological case study methodology, the authors use classroom observations, student focus groups, video recordings and artifacts to detail ways learners engage in data science practices and understand how they perceive their engagement during activities and learning.

Findings suggest student engagement in data science is enhanced when data problems are contextualized and connected to students’ lived experiences; data analysis and data-based decision-making is practiced in multiple ways; and students are given choices to communicate patterns, interpret graphs and tell data stories. The authors note challenges students experienced with data practices including conflict between inconsistencies in data patterns and lived experiences and focusing on data visualization appearances versus relationships between variables.

Data science instruction in elementary schools is an understudied, emerging and important area of data science education. Most elementary schools offer limited data science instruction; few elementary schools offer data science curriculum with embedded CT practices integrated across disciplines. This research assists elementary educators in fostering children's data science engagement and agency while developing their ability to reason, visualize and make decisions with data.

The advent of online live streaming platforms (OLSPs) and online health communities (OHCs) has expedited the integration of traditional medical services with Internet new media technology. Since the practice of physicians conducting live streaming is a relatively new phenomenon, the potential cross-platform effects of such physicians’ live streaming have not received adequate attention.

This study collected data from 616 physicians specializing in cardiology, obstetrics and gynecology and neurology between April and November 2022 on Live.Baidu.com and WeDoctor.com. It constructed a panel data set comprising a total of 4,928 observations over an 8-month period and validated the model using empirical analysis with the fixed-effects method.

We find evidence of cross-platform influence in online healthcare. Physicians’ live streaming behavior (whether live or not and the heat of their streams) on OLSPs positively impacts both their consultation and reputation on OHCs. Additionally, physicians’ ability positively moderates the relationships between live streaming heat and their performance (in terms of consultation volume and reputation) on OHCs. However, ability does not moderate the relationship between physicians’ live streaming status (live or not) and their performance (in terms of consultation and reputation) on OHCs. Furthermore, the attractive appearance of the physicians also significantly moderates the impact in a positive way.

This is one of the pioneering studies on physicians’ live streaming. The study offers vital guidance for physicians and patients utilizing dual platforms and holds significant reference value for platform operators (such as OLSPs and OHCs) aiming to optimize platform operations and for the government in policy formulation and industry regulation.

This study aims to examine the moment-to-moment (MTM) effects of in-consumption dynamic comments on consumers' responses to digital engagement and the underlying mechanisms involved, as well as the interactive role of advertisements embedded in short-form online video.

This study uses data extracted from 2,081 videos posted on the prominent Chinese online live platform, Bilibili. The hypotheses are tested using regression models and natural language processing.

The results indicate that the intensity of live comments at the beginning negatively affects users' digital engagement, while a corresponding increase in live comments at the end elicits a positive effect. A linear trend and peak difference in live comments intensity positively affect digital engagement, while the variability of live comment intensity exerts a negative effect. These MTM effects were driven by sentiments of live comments. Furthermore, in-video advertisements are likely to amplify the negative beginning effect on users' digital engagement and mitigate the negative variability of live comments.

This study is the first to examine the direct effects of MTM comments from the online temporal sequence perspective, differentiating the process- and performance-based engagement. The mechanism and interactive role of in-video advertisements were identified. These findings contribute to literature on interactive marketing and provide valuable guidance for influencer marketing.

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

In the actual livestreaming background, to obtain more income, some broadcasters will transform their original single role orientation into mixed one. This research study aims to conduct an empirical study on the influence of the broadcasters' role orientation transformation on the viewers' tipping behavior.

The authors collect data from Kuai, a leading online live streaming service provider in China. The dataset includes 175,701 live streaming data from 971 broadcasters in 7 months. To avoid unobservable factors, the authors adopt two difference-in-differences (DID) models to estimate the effect of two kinds of broadcaster's role orientation transformation on the broadcaster’s direct income separately. And the authors use the Heckman-type correction to solve broadcasters’ self-selected problem.

The authors evaluated that there is a U-shape relationship between the broadcasters' role orientation transformation and their direct income. The broadcasters' direct income experienced a sharp decline for a short period of time after transformation and followed by a rise after a period of adaptation. And for broadcasters with different genders and amounts of fans, the influence degree of role orientation transformation is various.

This paper provides a fresh usage of the regulatory engagement theory in the brand new information communication technology. And it also explores the boundary effect of the participating object's self-factors in the regulatory engagement theory. Besides, this paper expands the research of livestreaming into natural background. Such results also provide operable suggestions for the livestream platform, the broadcaster himself and the enterprises who want to employ some broadcasters to recommend their products.

Drawing upon the authors’ experiences as minoritised academic scholars within leadership roles of a Black, Asian, Minority Ethnic (BAME) Network in the United Kingdom (UK) academe, the authors explored the research question “In what ways do racially minoritised academics use coping techniques and strategies to counter racism and inequality in the higher education environment”.

The authors used a collective autoethnography approach accompanied by storytelling, underpinned by a qualitative interpretative process, supported by inductive, data-driven theorising. The authors’ approach is supplemented by the usage of content analysis (Schrieier, 2012) to analyse the data and generate findings.

The research findings specifically highlight (1) collectivism, solidarity and belonging, (2) knowledge expansion and critical consciousness, (3) disarming approaches and emotional labour, (4) resistance through setting boundaries and (5) intersectionality and BAME men allyship, as specific approaches for taking forward anti-racism.

Autoethnographic research has encountered challenges around verification, transparency and veracity of data, and issues have been debated due to its subjective nature (see Jones, 2010; Keeler, 2019; Méndez, 2013). Additional complications arise regarding neutrality and objectivity associated with the researchers' identities and experiences being represented in autoethnographic accounts. The authors acknowledge that the accounts provided are subjective, and have influenced the research process and product.

Research on the experiences of minoritised academics leading staff equality networks constitutes a research gap. This article offers an original analysis through outlining the authors’ lived experiences in leadership positions of a BAME Network and hope to other minoritised employees undertaking anti-racist work.

It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.

The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).

The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.

Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.

This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.

Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.

The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

This study aims to investigate the effects of interaction in agricultural product live rooms, including personalization, responsiveness, and entertainment, on consumers’ purchase intention.

The SOR model has been applied to formulate hypotheses. This study is based on an online survey conducted with a sample of 433 valid questionnaires from Chinese consumers on the TikTok agricultural products live platform. A partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses.

The findings indicate that (1) interactions (personalization, responsiveness, and entertainment) in the agricultural products live room have a positive effect on perceived values (utilitarian value, symbolic value, and entertainment value); (2) utilitarian value positively affects purchase intention and mediates the effects of personalization and entertainment interactions on purchase intention, respectively; (3) entertainment value positively influences purchase intention and mediates the influence of entertainment interaction on purchase intention.

This study offers theoretical insights into live marketing of agricultural products and practical implications for practitioners of agricultural products in live streaming commerce.

This paper argues that through information and communication technology (ICT) adoption, the youth will be engaged in all nodes of the agricultural value chains, thereby improving the level of employment and reducing post-harvest losses. The study examines the determinants of ICT adoption among the youth. In addition, it estimates the impact of ICT adoption on youth employment in agriculture towards the actualisation of the Sustainable Development Goals (SDGs), particularly SDG-8, to promote inclusive and sustainable economic growth, productive employment and decent work for all.

The study engages data from Wave 4 (2018/2019) of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The logit regression, the propensity score matching and the inverse probability weighted regression adjustment are used as the estimation techniques.

The study underscores that educational level, access to electricity, location, age and income are significant determinants of ICT adoption among the youth. The findings also show that the youth's average weekly engagement in agricultural activities is about 24 h. In addition, the result reveals that ICT adoption can increase youth agricultural employment by approximately 21%. The mean difference indicates that those with access to ICT participate in agricultural activities more than their counterparts without ICT access by 29.46%.

One of the limitations of the study is that some of the variables such as insecurity, social protection/safety nets, that may have a significant influence on youth agricultural participation where not included in the model due to data constraint. As a recommendation for further studies, given data availability, such variables should be considered when examining youth-agricultural employment nexus.

Since ICT adoption has a significant impact on agricultural employment, this study proposes improved infrastructure facilities such as reliable power supply, lowering the cost of mobile and data subscriptions and better education facilities should be prioritised at all localities. This will enable the youth to embrace agriculture and help improve their socioeconomic welfare and livelihood.

Using Wave 4 of the LSMS-ISA, logit regression, propensity score matching and the inverse probability weighted regression adjustment, makes this study one of the very few to examine the impact of ICT adoption on agricultural employment among the youth in Nigeria. It implies that this study has provided empirical evidence and expanded the frontiers of knowledge on the extent to which ICT adoption influences youth agricultural employment in Nigeria.