检索结果-内蒙古大学图书馆

Disconfirmation effect on online reviews and learner satisfaction determinants in MOOCs

Education and Information Technologies 2023年第12期28卷 15497-15521页

作者： Wang, Wei Liu, Haiwang Wu, Yenchun Jim Goh, Mark College of Business Administration Huaqiao University Quanzhou China MBA Program in Southeast Asia National Taipei University of Education Taipei Taiwan Graduate Institute of Global Business and Strategy National Taiwan Normal University Taipei Taiwan The Logistics Institute-Asia Pacific NUS Business School National University of Singapore Singapore Singapore

In Massive Open Online Courses (MOOCs), learners can post both text comments and overall ratings regarding the courses. There is growing interest in assessing the consistency of online reviews and the determinants of learner satisfaction. This study analyses the disconfirmation effect between textual review topics and the determinants of learner satisfaction in MOOCs. The MOOCs are categorised under three disciplines - Social Science, Technical Science, and Humanities & Natural Science. A crawler was employed to collect the corpus, extracting 93,679 reviews of 5,214 online courses from a Chinese university MOOC platform ( *** ). Textual analytics was used in the topic extraction. The empirical results suggest a strong disconfirmation effect between textual reviews and the determinants of learner satisfaction, i.e., not all textual review topics affect the overall learner satisfaction. Compared with positive reviews, negative (and neutral) reviews have a stronger disconfirmation effect. Further, the antecedents of learner attention are course-discipline specific. The disconfirmation effect is course-discipline dependent, with the most prominent for Technical Science courses, and the least for Humanities & Natural Science courses. This study provides a framework to guide platform managers and course instructors in better course delivery and enhancing overall learner satisfaction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Extreme Climate Events in Southern Brazil Warn of Agricultural Collapse

SSRN

引用

SSRN 2024年

作者： Nóia Júnior, Rogério de Souza Christo, Bruno Fardim Pezzopane, José Eduardo Macedo LEPSE Univ Montpellier INRAE Institut Agro Montpellier Montpellier France UFSC Federal University of Santa Catarina Graduate Program in Administration Santa Catarina Florianópolis Brazil Department of Forestry and Wood Sciences Federal University of Espírito Santo Espírito Santo Jerônimo Monteiro Brazil

Southern Brazil, one of the world's largest grain-producing regions, is facing significant threats to its stability due to fluctuating seasonal weather patterns. In recent years, this region has experienced severe and unprecedented droughts, such as those observed in 2023, followed by extreme flooding events, including a notable incident in May 2024, where rainfall exceeded 500 mm within a few days. These climatic anomalies have resulted in exceptionally low grain yields, with unharvested soybean grains valued at approximately 45 billion BRL (about 8.3 billion USD). Future projections indicate a temperature increase of up to 3°C and heightened precipitation variability by 2100, which could further undermine grain production in the region. To mitigate these risks and safeguard future stability, it is crucial to implement comprehensive climate change adaptation and mitigation measures. © 2024, The Authors. All rights reserved.

关键词： Drought

来源：评论

学校读者我要写书评

暂无评论

Scrum to support application development project for online learning 8

Scrum to support application development project for online ...

引用

8th International Conference on Information Technology: IoT and Smart City, ICIT 2020

作者： Tjhin, Viany Utami Riantini, Regina Eka Kusumastuti, Dwi Listriana Ellynia, Ellynia BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Health Administration Program STIKES RS Husada Jakarta10730 Indonesia

ISBN: (纸本)9781450388559

Good health services require adequate human resources, especially nursing personnel during a pandemic. To produce quality human resources in the health sector, a quality learning process is needed in health education institutions. One of the steps that can be taken to achieve this is to transform online and mobile-based nursing education. Technological developments have changed the way applications developed. Application users have also experienced changes by prioritizing mobile-based applications. This change makes application developers look for new methods in developing applications that can be used effectively. This article presented a study that applies the principles of agile mobile application development. The agile methodology used in this study is SCRUM for application development. This study prepared a mobile-based learning application that will be used by nursing students. The development of this application uses an agile methodology. This paper discusses Scrum's use in developing mobile-based applications that will be used in the nursing department's learning environment. The requirements are deliberately modified to provoke changes to the software being developed. Our findings revealed that agile practices were capable of assisting mobile software development. The advantage of this method was the ease of managing the project. control, and speed of development. However, aspects of user interface and user experience, different development platforms, and user expectations still represented the challenges in developing mobile applications. © 2020 ACM.

关键词： User interfaces

来源：评论

学校读者我要写书评

暂无评论

An empirical model for branding oriented by the environmental sustainability of the Amazon Rainforest: a hybrid structural equation modeling with fsQCA approach

引用

Discover Analytics 2024年第1期2卷 1-21页

作者： Santos, Luiz Diego Vidal Holanda, Francisco Sandro Rodrigues Pedrotti, Alceu de Medeiros, Raphael Mario Bastos de Santana Oliveira, Catuxe Varjão Villwock, Ana Paula Schervinski Graduate Program in Intellectual Property Science Universidade Federal de Sergipe-UFS São Cristóvão Brasil Agronomy Engineering Department Universidade Federal de Sergipe-UFS São Cristóvão Brasil Administration Department Universidade da Amazônia Manaus Brasil Computer Science Department Instituto Federal de Sergipe-UFS Lagarto Brasil

Utilizing the Theory of Planned Behavior, a meaningful connection between an organization and its consumers can be established, transcending mere appearances and delving into emotions, relationships, and brand experiences. In line with these principles, this study aims to present an empirical model grounded in factual evidence derived from the perspectives of entrepreneurs and consumers of environmentally sustainable brands in the Brazilian Amazon. The proposed model adopts a mixed-modeling approach, utilizing data analysis techniques such as fuzzy-set qualitative comparative analysis (fsQCA). Two independent data sets were collected: one from 8 companies operating in the Amazon rainforest and another from 535 potential consumers. By analyzing these datasets, consumer motivations for the consumption of sustainable brands, entrepreneurial practices, and the role of traditional communities and the forest environment in shaping brand perceptions were identified. The results reveal that, from the consumer’s perspective, the key factors influencing a positive inclination to purchase sustainable brands include the brand’s engagement with traditional com munities, perceived product quality, brand innovation, and a transparently communicated positioning strategy. These constructs form the core components of the main solution. This article provides valuable information for entrepreneurs operating sustainable brands in tropical forests as well as for policymakers in community-based entrepreneurship. It is also of interest to researchers and individuals involved in brand management as a strategy for empowering small businesses engaged in sustainable practices and community collaboration. The study’s findings and recommendations have the potential to foster more sustainable and socially responsible business practices, thereby enhancing local economies and contributing to environmental preservation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

引用

2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

来源：评论

学校读者我要写书评

暂无评论

Gc-Red: Graph Convolution-Based Recurrent Encoder-Decoder for Anomaly Diagnoses in Multivariate Time-Series Data

SSRN

引用

SSRN 2023年

作者： Kim, Yejin Jeon, Daeseong Park, HyeRim Lee, Changyong Lee, Junghye Ulsan44919 Korea Republic of Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Seoul National University Seoul08826 Korea Republic of Department of Public Administration Korea University Seoul02841 Korea Republic of Technology Management Economics and Policy Program Graduate School of Engineering Practice Seoul National University Seoul08826 Korea Republic of

Detecting anomalies in multivariate time-series data is an important task in various real-world industries, but doing so is non-trivial because both the temporal dependency within the time series and correlations between multiple time series must be considered. Previous studies have only addressed one issue, resulting in limited performance. To address this, we propose a graph convolution-based recurrent encoder-decoder, called GC-RED. The model incorporates intra-dependencies and inter-correlations using a graph-construction process and an encoding-decoding process that encodes the graph with an attention-enhanced graph convolutional LSTM and then restores it. Anomaly detection and root cause identification are performed based on the reconstruction error. Considering that anomalies with various durations can occur in actual situations, the model includes a vanilla model reflecting single scales and a model reflecting multiple scales. The feasibility and usefulness of GC-RED are demonstrated by intensive experiments on several benchmark and real-world datasets with comparisons to other competitive methods. © 2023, The Authors. All rights reserved.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Mobile Learning as Tool for Implementation of Blended Learning in Nursing Education 2021

Mobile Learning as Tool for Implementation of Blended Learni...

引用

2021 The 9th International Conference on Information Technology: IoT and Smart City

作者： Dwi Listriana Kusumastuti Viany Utami Tjhin Regina Eka Riantini Enni Juliani Information Systems Department School of Information Systems Bina Nusantara University Indonesia BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Indonesia Management Department BINUS Business School of Undergraduate Program Bina Nusantara University Indonesia Health Administration Program STIKES RS Husada Indonesia

ISBN: (纸本)9781450384971

This research focuses on the development of mobile learning applications in nursing education in Indonesia. Using the BeeDa application, which is a learning application for nursing students as a complement to blended learning. Blended learning is an integration between classroom learning, online learning and mobile learning. BeeDa facilitates students in accessing learning resources easily, anytime and anywhere. This study describes the design and implementation stages related to the development of BeeDa. Experimental data were collected using a questionnaire to nursing students. The evaluation results show that the BeeDa application is easy to use and useful in supporting learning, so it has the potential to improve learning achievement.

关键词： nursing education blended learning online learning mobile learning

来源：评论

学校读者我要写书评

暂无评论

Systematic literature review of human–machine collaboration in organizations using bibliometric analysis

引用

Management Decision 2023年第10期61卷 2920-2944页

作者： Jia-Min Li Tung-Ju Wu Yenchun Jim Wu Mark Goh School of Business Administration Northeastern University Shenyang China School of Management Harbin Institute of Technology Harbin China MBA Program in Southeast Asia National Taipei University of Education Taipei Taiwan Graduate Institute of Global Business and Strategy National Taiwan Normal University Taipei Taiwan NUS Business School and TLI-AP National University of Singapore Singapore Singapore

Purpose This study aims to systematically map the state of work on human–machine collaboration in organizations using bibliometric analysis. Design/methodology/approach The authors used a systematic literature review to survey 111 articles on human–machine collaboration published in leading journals to categorize the theories used and to construct a framework of human–machine collaboration in organizations. A bibliometric analysis is applied to statistically evaluate the published materials and measure the influence of the publications using co-citation, coupling and keyword analyses. Findings The results inform that the research on human–machine collaboration in the organizational field is targeted at four aspects: performance, innovation, human resource management and information technology (IT). Originality/value This work is the first exploratory piece to assess the extent and depth of research on human–machine collaboration.

关键词： Human-machine collaboration Systematic review Bibliometric analysis Literature review

来源：评论

学校读者我要写书评

暂无评论

The Role of Trust Transfer in Facilitating Stickiness Behavior in Live Streaming: A Socio-technical Perspective

The Role of Trust Transfer in Facilitating Stickiness Behavi...

引用

International Conference on Information Management and Technology (ICIMTech)

作者： Wen-Kuo Chen Fatih Yanbegi Andri Dayarana K. Silalahi Pantas H. Silaban Ixora Javanisa Eunike Serhan Demirci Department of Money and Banking National Kaohsiung University of Science and Technology Kaoshiung Taiwan Department of Business Administration Chaoyang University of Technology Taichung Taiwan Graduate School Master of Management Program University of HKBP Nommensen Medan Indonesia Department of Marketing and Logistics Management Chaoyang University of Technology Taichung Taiwan

In recent years, research on live streaming has developed rapidly among scholars. Especially scholars are increasingly interested in understanding consumer behaviors regarding purchasing behavior on live streaming platforms, which is classified as transactional behavior. A separate consideration is a non-transactional behavior, as there are currently many live-streaming platforms that are not only used for sales activities but also to broadcast games, cooking, and eating activities, which do not focus on consumer behavior in live-streaming activities. This study investigates consumers' non-transactional behavior (e.g., stickiness behavior) on live streaming platforms using socio-technical theory and trust transfer. This study tested the hypothesis on 285 Indonesian participants participating in various live-streaming activities across various platforms. Data analysis was performed using a structural equation modeling approach using Smart-PLS 4.0 software. In the study, interactivity and visualization significantly impacted cognitive trust more than affective trust. Although cognitive trust significantly impacts affective trust, it will also similarly impact consumers when they already possess it. The study also confirms that both types of trust increase stickiness behaviors. This is primarily because building cognitive trust is a priority for trust transfer. Therefore, it can increase stickiness behavior and affective trust, which, in this study, evolve significant managerial implications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Association between Prefrontal fNIRS signals during Cognitive tasks and College scholastic ability test (CSAT) scores: Analysis using a quantum annealing approach

arXiv

引用

arXiv 2024年

作者： Kim, Yeaju Choi, Junggu Kim, Bora Park, Yongwan Cha, Jihyun Choi, Jongkwan Han, Sanghoon Yonsei Graduate Program in Cognitive Science Yonsei University Seoul03722 Korea Republic of Department of Counselling Honam University Gwangju62399 Korea Republic of Department of Business Administration Gyeongsang National University Jinju52828 Korea Republic of OBELAB Inc. Seoul06211 Korea Republic of Department of Psychology Yonsei University Seoul03722 Korea Republic of

Background: Academic achievement is a critical measure of intellectual ability, prompting extensive research into cognitive tasks as potential predictors. Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIRS), offer insights into brain hemodynamics, allowing understanding of the link between cognitive performance and academic achievement. Herein, we explored the association between cognitive tasks and academic achievement by analyzing prefrontal fNIRS signals. Methods: A novel quantum annealer (QA) feature selection algorithm was applied to fNIRS data to identify cognitive tasks correlated with CSAT scores. Twelve features (signal mean, median, variance, peak, number of peaks, sum of peaks, slope, minimum, kurtosis, skewness, standard deviation, and root mean square) were extracted from fNIRS signals at two time windows (10- and 60-second) to compare results from various feature variable conditions. The feature selection results from the QA-based and XGBoost regressor algorithms were compared to validate the former's performance. In a three-step validation process using multiple linear regression models, correlation coefficients between the feature variables and the CSAT scores, model fitness (adjusted R2), and model prediction error (RMSE) values were calculated. Results: The quantum annealer demonstrated comparable performance to classical machine learning models, and specific cognitive tasks, including verbal fluency, recognition, and the Corsi block tapping task, were correlated with academic achievement. Group analyses revealed stronger associations between Tower of London and N-back tasks with higher CSAT scores. Conclusions: Quantum annealing algorithms have significant potential in feature selection using fNIRS data, and represents a novel research approach. Future studies should explore predictors of academic achievement and cognitive ability. © 2024, CC BY-NC-SA.

关键词： Infrared devices

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：