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The purpose of this study was to develop the augmented reality (AR) educational program combined with the instructional guidance for supportive learning, which enhanced the thinking process cooperative discussion and problem-solving skills in chemistry subject.

The method used the quasi-experimental research design. Of the 45 students who attended this experiment, only 25 with low achievement qualified in operating the AR learning system of saponification and transesterification environment (ARLS-STE) system.

These results confirmed that the AR educational program could have increased substantial benefits in improvements of students’ knowledge and the ability of the thinking process for the participants with the lowest score. In semi-structured interviews, most of participants enjoyed manipulating the ARLS-STE system, which was realistic, motived and interesting for learning science subjects.

The low-achieving students have often been known with a low learning capability, and they lack in developing constructional knowledge, despite being keen for learning. Regarding educational concerns for this population, providing orientated learning and supportive materials could increase their learning effects. Virtual worlds are an efficient learning tool in educational setting. The AR can offer visual concepts and physical interaction for students with low achievement in learning. Thus, this study investigates the acceptability of an educational program designed in the ARLS-STE, which involves the learning effects of academic knowledge and the capability of thinking process for students with low achievement. The ARLS-STE system was developed for this proposal, based upon the marker-based AR technologies combined with hands-on manipulation.

This study aims to investigate the advancement of place attachment within the bicycle tourism context. Specifically, this study seeks to ascertain whether the four attributes of bicycle tourism (tourism attractions, accessibility, amenities and complementary services) and enduring involvement can serve as predictors of tourists’ place attachment. Also, the research endeavors to examine the positive effects generated by the four attributes of bicycle tourism on enduring involvement. Additionally, the mediating role that enduring involvement plays in attribute–place attachment relationships will be clarified.

The final 547 samples are collected from five WeChat cycling groups in Shanghai, and the partial least squares structural equation modeling approach is used to analyze the data.

The results show that each of the four attributes has a positive impact on place attachment. Moreover, tourism attractions, accessibility and amenities can be the drivers of enduring involvement. Enduring involvement mediates the tourism attractions–place attachment relationship, the accessibility–place attachment relationship, as well as the amenities–place attachment relationship.

This paper, to the best of the author’s knowledge, pioneeringly introduces the concept of enduring involvement and place attachment into bicycle tourism research, and the findings contribute to providing practical implications for destination managers and government policymakers.

This is innovative work with a comprehensive and creative research framework for place attachment.

This paper aims to explore the latest study of the emerging data-driven approach in the area of FinTech. This paper attempts to provide comprehensive comparisons, including the advantages and disadvantages of different data-driven algorithms applied to FinTech. This paper also attempts to point out the future directions of data-driven approaches in the FinTech domain.

This paper explores and summarizes the latest data-driven approaches and algorithms applied in FinTech to the following categories: risk management, data privacy protection, portfolio management, and sentiment analysis.

This paper details out comparison between different existed works in FinTech with traditional data analytics techniques and the latest development. The framework for the analysis process is developed, and insights regarding the implementation, regulation and workforce development are provided in this area.

To the best of the authors’ knowledge, this paper is first to consider broad aspects of data-driven approaches in the application of FinTech industry to explore the potential, challenges and limitations of this area. This study provides a valuable reference for both the current and future participants.

The purpose of this study is to analyse Peruvian cuisine in the context of visitors’ overall experience, focusing on the loyalty of tourists in terms of gastronomy, their satisfaction with the destination, and the overall image.

Data were obtained from tourists who visited Lima (Peru). Structural equation modeling was used to verify the hypothesized relationships.

The results obtained confirm that satisfaction and appreciation, such as quality, have a positive influence on tourists’ loyalty and, therefore, they recommend and express their desire to come back to this destination. The traditional gastronomy of Lima stands out as a prominent factor on overall experience.

This paper helps the managers of cities in their decisions to improve the satisfaction and seek loyalty of those who visit a city, emphasizes the role of gastronomy.

The results obtained in this research can be used for the establishment of new strategies for the promotion of the destination in terms of tourism and traditional food.

The gastronomy in Lima, (Peru) is recognized worldwide, as well as a stimulus for tourism because it increases the number of visits to the destination. Several studies carried out in these types of destinations have shown the existence of a relationship between gastronomy, overall experience, satisfaction and loyalty. However, there are no previous studies carried out in Lima that sustain this relationship. This work makes a contribution that completes the academic literature on the study of the emotional bonds between Peruvian gastronomy and the tourist who visits it and its behaviour.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.