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Questionnaire studies of knowledge, attitude and practice (KAP) are effective research in the field of health, which have many shortcomings. The purpose of this research is to propose an automatic questionnaire-free method based on deep learning techniques to address the shortcomings of common methods. Next, the aim of this research is to use the proposed method with public comments on Twitter to get the gaps in KAP of people regarding COVID-19.

In this paper, two models are proposed to achieve the mentioned purposes, the first one for attitude and the other for people’s knowledge and practice. First, the authors collect some tweets from Twitter and label them. After that, the authors preprocess the collected textual data. Then, the text representation vector for each tweet is extracted using BERT-BiGRU or XLNet-GRU. Finally, for the knowledge and practice problem, a multi-label classifier with 16 classes representing health guidelines is proposed. Also, for the attitude problem, a multi-class classifier with three classes (positive, negative and neutral) is proposed.

Labeling quality has a direct relationship with the performance of the final model, the authors calculated the inter-rater reliability using the Krippendorf alpha coefficient, which shows the reliability of the assessment in both problems. In the problem of knowledge and practice, 87% and in the problem of people’s attitude, 95% agreement was reached. The high agreement obtained indicates the reliability of the dataset and warrants the assessment. The proposed models in both problems were evaluated with some metrics, which shows that both proposed models perform better than the common methods. Our analyses for KAP are more efficient than questionnaire methods. Our method has solved many shortcomings of questionnaires, the most important of which is increasing the speed of evaluation, increasing the studied population and receiving reliable opinions to get accurate results.

Our research is based on social network datasets. This data cannot provide the possibility to discover the public information of users definitively. Addressing this limitation can have a lot of complexity and little certainty, so in this research, the authors presented our final analysis independent of the public information of users.

Combining recurrent neural networks with methods based on the attention mechanism improves the performance of the model and solves the need for large training data. Also, using these methods is effective in the process of improving the implementation of KAP research and eliminating its shortcomings. These results can be used in other text processing tasks and cause their improvement. The results of the analysis on the attitude, practice and knowledge of people regarding the health guidelines lead to the effective planning and implementation of health decisions and interventions and required training by health institutions. The results of this research show the effective relationship between attitude, practice and knowledge. People are better at following health guidelines than being aware of COVID-19. Despite many tensions during the epidemic, most people still discuss the issue with a positive attitude.

To the best of our knowledge, so far, no text processing-based method has been proposed to perform KAP research. Also, our method benefits from the most valuable data of today’s era (i.e. social networks), which is the expression of people’s experiences, facts and free opinions. Therefore, our final analysis provides more realistic results.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

This study was based on situated learning, by combining mobile learning and augmented reality, so that students could not only access information content in a real environment but also obtain such information via augmented reality, to support mobile learning.

The research included development of an augmented reality system combined with situational learning, used by students to learn about campus plants as part of the college life technology curriculum. Students took part in mobile learning, and an investigation was conducted into the computer learning behaviour of notebook users. College students were used as the experimental subjects. Data were collected using questionnaire surveys and were evaluated in order to identify the behavioural intentions of learners in outdoor learning activities.

The questionnaire survey covered environmental interactivity, system quality and textbook content. It was found that learners who used mobile learning augmented reality (MLAR) generally managed to browse all the contents of the textbook at each learning location, without spending too much time looking for information, and learners could quickly integrate this into the learning situation. Learners who used MLAR had a strong motivation to study plants at the learning site because they wanted to use the augmented reality technology to observe virtual plant models. Learners who used MLAR in their field learning liked using augmented reality for further learning, for example, using a magic wand to interact with the technology.

This study adopted a new approach to deliver elements of the life technology curriculum, integrating augmented reality into mobile learning. All participating students gave positive reviews of six aspects of the proposed system: their behavioural intentions, cognitive usefulness, cognitive ease of use, environmental interactivity, system quality and textbook content.

This study explores the utilization of simulation tools for building performance assessments among design professionals in Ghana.

A quantitative approach was used to obtain responses from 104 design professionals in Ghana through a structured questionnaire. The questionnaire was generated through a critical review of the related literature on the subject matter. Data from respondents were analyzed through descriptive and inferential statistics.

Results from the analysis indicated that design professionals in Ghana possessed a low level of awareness of the simulation tools used for building performance assessments. Subsequently, the findings also revealed that the design professionals' level of usage of the simulation tools was low.

Practically, the establishment of this study informs design stakeholders, educational institutions and researchers in Ghana. For design professionals, these findings will focus on enhancing their use of simulation tools for evaluating building performance in Ghana. For educational institutions, these findings will enable them to implement the necessary strategies for incorporating the concept of building performance simulation into their curriculum in order to boost awareness and utilization. Finally, researchers will also use the study's findings to identify any research gaps for future studies.

The findings from this study pioneer knowledge on an under-investigated topic within the Ghanaian construction industry. It also provides insight into the developing state-of-the-art technology employed in the built environment.

In this study, the authors propose a confirmatory factor analysis (CFA) to create a tenable measurement model and identify the factors that have the potential to enhance awareness of pro-environmental measures. The successful implementation of demand response (DR) programs and their required infrastructure is significant for moving towards green energy communities and a better environment for living. Not only can renewable energy capacities contribute to this desideratum, but also electricity consumers who, until the last decade, have played a passive role.

To answer these questions, a complex data set of 243 post-trial questions created by the Irish CER are analyzed using first-order and hierarchical CFA models with several SAS procedures (PROC CALIS, MIANALYZE). The questionnaire was launched to over 3,000 electricity consumers from Ireland that were participants to a trial program after the installation of smart metering systems and implementation of DR programs.

The effect of five latent factors – positive attitude, negative attitude, perceived impact of own actions, price- and incentive-DR programs – is measured. With a bi-factor CFA measurement model, the authors assess that they significantly influence the electricity consumers' awareness.

However, these findings have to be backed up by relevant information and simulations showing consumers benefits in exchange to their efforts. They have research implications on the design of the business models and DR programs pointing out the importance of benefits and fairness of value sharing mechanisms within energy communities.

Thus, the electricity consumers may change their consumption behavior as they positively perceive the implementation of DR programs.

This paper fulfills an identified need to study post-trial questionnaire and reveal latent factors that make electricity consumer change their behavior.

This research aimed to define the factors that may impact the effectiveness of online architectural education during COVID-19 and to examine the degree of students' and instructors' satisfaction with these factors among Jordanian governmental universities. Further, the research examines the relationships/interrelationships between the degree of their satisfaction with these factors and the students' and instructors' age, gender, education level, home size, and family size.

Different research methods were used to achieve the research purposes, including semi-structured interviews, online questionnaires and reviewing recent literature. This research used descriptive statistics and Pearson product-moment correlation coefficient (Pearson r) to analyze the data.

This research found that online architectural education during COVID-19 was stressful. It was ineffective in teaching practical architectural courses like design and negatively affected the architectural learning process and outcomes. In contrast, the online teaching of architectural theoretical courses was reliable and convenient if the students and instructors had intentional, sufficient technological and appropriate resources. Online architectural education negatively affected the students' design ability and skills, peer review, intended learning outcomes (ILOs) achievements, the quality of feedback, workload, interaction mode, participation, collaboration, productivity and increased cheating on online exams. The home environment was unsuitable for online architectural education. Family interventions, privacy, home size and family size significantly influence online architectural education's effectiveness.

Students' and instructors' satisfaction determines the continuity of using online teaching mode, which depends on information quality, system quality, service quality, perceived ease of use, perceived usefulness, achieved intended learning outcomes, cognitive absorption, skills, motivation, engagement, implementing resources and strategies and positive emotions as hope and enjoyment. Students' and instructors' satisfaction reflects how they view their learning experience, which is crucial in assessing the effectiveness of online education quality that focuses on the context, input, process and product, which is still not clearly understood, particularly for developing countries.

Based on the stimulus-organism-response theory, this research constructs the influence of the stimulus factors of the live-streaming shopping environment on consumers' psychological situation. It then produces the research model of impulsive purchase intention.

In this study, the online questionnaire survey method was used to survey users who participated in live-streaming shopping, and a total of 335 valid questionnaires were collected. Then SPSS and SmartPLS were used for data empirical evaluation and hypotheses test.

Research results show that demand, convenience, interactivity, and playfulness are positively stimulating consumers' perceived enjoyment. And their perceived enjoyment directly drives their intention of impulsive purchase.

The choice of the live streaming platform, the design of the interactive interface, and the design of the shopping process are all factors that the streamer must carefully consider. The results of this study can be used as a reference for the development of live-streaming shopping and provide the industry with an understanding of the main factors that affect users' live streaming and impulsive purchases to plan an effective live streaming platform and content.

“E-commerce live streaming” is regarded as the latest trend of e-commerce, and impulse buying is regarded as a key factor in the success of transactions. This research has developed factors that influence impulsive purchases after watching live streaming based on the SOR theory.

This paper aims to employ social cognitive theory (SCT) as a theoretical framework to investigate the influencing factors affecting the knowledge transfer effectiveness of construction workers in China. The mediating role of their knowledge transfer willingness is also assessed.

A questionnaire on knowledge transfer among Chinese construction workers is designed and subsequently analyzed by structural equation modeling (SEM), with a total sample of 288 construction workers.

The SEM results show that the knowledge self-efficiency, blood and geographic relationships, and trust relationship promote knowledge transfer willingness and positively influence the knowledge transfer effectiveness of construction workers. However, the effect of organizational culture on knowledge transfer willingness and effectiveness is nonsignificant.

The results are conducive to managers and governments formulating strategies to optimize the learning mechanism of construction workers and facilitate their obtaining of resources from the project, thus easing skill shortages and promoting the transformation of construction workers into industrial workers.

This paper innovatively proposes blood and geographic relationships as research variables, expanding their scope. Furthermore, SCT is applied to enable future research to better understand individual knowledge transfer behavior from both personal and environmental perspectives.

With the goal to indicate the importance of human–nature connection in designing workplaces, the authors investigated the effects of direct and indirect biophilic indicators on the well-being and performance of employees of an organization. The main question is what is the effect of biophilic components on the well-being and performance of employees.

To answer the research questions, the authors designed and validated an instrument to evaluate correlation between biophilic components with well-being and performance. The participants include 160 employees of one organization. For the data analysis, both descriptive statistical and inferential statistics were used. Pearson's correlation test and ANOVA were conducted to explain the relationship between variables.

The results indicated that biophilic components have significant positive relationships with the well-being of the employees, but no significant relationship was found between biophilic components and the performance of the employees. Using the ANOVA test, biophilic indicators that have a positive and significant effect on the well-being and performance of employees were determined. The natural scenery and warm colors has significant positive effects on social well-being, and the usage of natural landscape posters in the working rooms has a positive and significant relationship with psychological well-being. The natural lighting has a positive and significant relationship with the employees' counterproductive work behavior.

Most of the questionnaires of this research were filled electronically because of the health protocols during pandemic. Almost 70% of the organization's employees had less than 5 years of work experience, which can be considered one of the interfering factors. In addition, the authors only used the questionnaire as a tool for collecting information in this study. There are other forms of information that can be explored through observations, interviews or experiments. Another limitation of this study is the lack of significant diversity in the investigated environments. Finally, the numbers of male and female participants of this study were not equal. The authors suggest studying both genders with an almost equal ratio so that the differences and needs of both groups can be understood.

The designed questionnaire is a validated instrument that can be used by other researchers to evaluate the biophilic design of workplace. These findings can also be useful for managers, companies and organizations in making decisions to improve the working environment and increase the well-being and performance of their employees.

The social effects of biophilic design in the workplace are significant as well. The use of biophilic components can foster a sense of connection between employees and their workplace, creating a positive social environment that supports collaboration and communication. Additionally, a biophilic workplace can promote a positive company culture that values the health and well-being of its employees, which can contribute to employee retention and satisfaction.

In this study, to determine the effects of the biophilic indicators on dimensions of employees' well-being and performance, an instrument is designed and validated.

In online shopping, there is often a risk due to the inability to check the products. As a result, it can reduce the impact of factors affecting the intention to buy online, which is a significant point in e-commerce. The purpose of this research is to investigate the impact of the evidence and the perceived usefulness of a store site on the existing risk and online participation of customers for online shopping.

The statistical population of this research is people who have had the experience of online shopping at the Digikala store. The research method was descriptive-survey and the samples were randomly selected. A questionnaire was also used to collect information. Structural and statistical analysis of the model was done by SmartPLS3 software.

In this research, the authors found that the perceived usefulness (benefits of the site) has a favorable effect on the online participation of customers. It can also reduce the risk of online shopping. This research suggests good ways to increase sales to those who have a store site. The present research provides useful findings for those who sell their products online.

This research specifically examines the interaction of customers with sellers and can be a help for progress in e-commerce. In this study, perceived risk and participation as mediating variables, information and perceived usefulness on the site as independent variables and online shopping intention a dependent variables. This research was done about Digikala's online store. The results were obtained with the participation of customers in completing the questionnaire. Then the theoretical model and the background of the research are examined and then the hypotheses are evaluated according to the statistical results and finally, the research results and limitations are stated.