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This study aims to adopt cloud technology and develop a “cloud bookcase system” to make it possible to provide consistent mobile reading experiences to allow readers to use all kinds of mobile devices to read e-books.

This study implements a cloud bookcase and uses four indicators (system quality, information quality, service quality, user satisfaction) to evaluate the system for reading e-books.

After completing the system, the authors used a questionnaire to evaluate the system. The results show that the quality can meet the needs and satisfaction of users. Subsequent interviews with some of the participants also reveal the biggest concerns of readers include library policy, resources and system quality.

System quality, information quality, service quality and satisfaction are adopted as the indicators to assess the ratings from people using mobile devices to read e-books on the cloud bookcase system developed in this study to evaluate whether the cloud bookcase system is a successful information system as well as the relations between mobile device factors and user ratings. The results indicate that the ratings from more than half of the readers for the system, as shown in the various indicators, achieve more than 60%. From the interview results, the results show that some participants also reveal there is still room for improvement in some areas.

This study implements a cloud bookcase and there are three contributions: (1) the cloud bookcase system developed in this study based on related theories proves able to meet the needs of users, (2) this system had high ratings for all four indicators, (3) the interview responses reveal that most people regard system quality as the most important, and some of the people value some of the items more, including library policy, readers' interests and more resources, especially the number of e-books available.

To support achieving sustainable development goals (SDGs), we integrated science, technology, engineering and math (STEM) and extended reality technologies into an artificial intelligence (AI) learning activity. We developed Feature City to facilitate students' learning of AI concepts. This study aimed to explore students' learning outcomes and behaviors when using Feature City.

Junior high school students were the subjects who used Feature City in an AI learning activity. The learning activity consisted of 90-min sessions once per week for five weeks. Before the learning activity, the teacher clarified the learning objectives and administered a pretest. The teacher then instructed the students on the features, supervised learning and unsupervised learning units. After the learning activity, the teacher conducted a posttest. We analyzed the students' prior knowledge and learning performance by evaluating their pretest and posttest results and observing their learning behaviors in the AI learning activity.

(1) Students used Feature City to learn AI concepts to improve their learning outcomes. (2) Female students learned more effectively with Feature City than male students. (3) Male students were more likely than female students to complete the learning tasks in Feature City the first time they used it.

Within SDGs, this study used STEM and extended reality technologies to develop Feature City to engage students in learning about AI. The study examined how much Feature City improved students' learning outcomes and explored the differences in their learning outcomes and behaviors. The results showed that students' use of Feature City helped to improve their learning outcomes. Female students achieved better learning outcomes than their male counterparts. Male students initially exhibited a behavioral pattern of seeking clarification and error analysis when learning AI education, more so than their female counterparts. The findings can help teachers adjust AI education appropriately to match the tutorial content with students' AI learning needs.

Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development.

The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software.

AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy.

The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.

The purpose of this paper is to introduce an affective computing-based method of identifying sleeping beauties and their princes in five educational technology journals.

This study develops an information technology-based methodology to analyze sleeping beauties in the field of educational technology. The authors seek to determine the characteristics of studies which trigger the awakening of sleeping beauties (called “princes”). The keywords and Hirsch index (H-index) are used as two essential analysis indicators.

Between 2000 and 2015, these five journals included 7,864 articles with a total of 77,700 citations and 24,312 keywords. This study identified articles as being in deep sleep (75.7 percent), less deep sleep (14.7 percent), and awakening (5.5 percent) states. According to the analytical results, 431 of 7,864 articles are qualified as “sleeping beauties.” Of the 431 sleeping beauties identified, 232 articles were awakened by trend princes, while 286 were awakened by H-index princes. A total of 128 sleeping beauties were awakened by both prince types. Besides, impact factors (IFs) of journals do not have a significant effect on the number of sleeping articles.

There are two main research limitations in this study. The first one is the amount of target journals. Only five well-known educational technology journals are analyzed in this research. There may be more valuable sleeping publications in other journals not been found. The second limitation is that the authors merely pick up the lead author of citing papers as the indicator to determine the H-index prince. The contributions of the rest of authors are not taken are not taken into consideration. These limitations should be further studied.

To the knowledge, this study is the first one reporting the identification of sleeping beauty and princes in educational technology field. Furthermore, the authors devise an informational method to determine sleeping publications, sleeping beauty, and princes. A systematic analysis of five well-known journals in the field of educational technology field confirms the existence of “sleeping beauties.” It is reported that improvements to a journal’s IF are positively correlated to increased numbers of sleeping beauties being awakened. To reduce the number of such articles, or to reduce the overall sleeping duration, journal editors should not only seek to raise the journal’s IF, but also strategically select keywords for maximum visibility, and promote articles to high H-index authors.

In a programming course, students often need tutors' assistance to complete learning activities, as they lack enough background knowledge to complete tasks. A further problem is that without individual tutoring, the knowledge gap between students increases. Therefore, the authors have proposed an instant response learning supplement tool (IRLST) to support students' learning, in order to facilitate students' independent problem-solving skills.

The authors divided the students into two groups according to their learning styles: verbal and visual. The IRLST was used to collect and analyze the information on their usage and provide supplementary resources to facilitate their learning. The proposed system also analyzed the student usage, background knowledge and exam scores to assess their academic performance.

According to the results of statistical analysis, students' learning performance improved significantly, especially low-scoring students. Moreover, as compiler messages were not recognized, students tended to identify the same problems. Thus, it is suggested that teachers not only should focus on improving the students' syntax but also strengthening their background knowledge and debugging skills.

There are two main limitations in this study: (1) as most of the students were in the visual learning group, the size of the groups was impacted, thus it was not possible to establish a control group; (2) one specific version of the IRLST system did not send reliable advice or supplementary content occasionally.

The IRLST developed in this study can be used to provide immediate supplementary resources to help students overcoming programming problems and developing problem-solving skills.

The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas.

Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future.

It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law.

First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation.

This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.

The purpose of this study, we present a robot used in education. Influenced by the epoch of revolutionary digital technology, the methodology of education has gone boundless. The robot programming sustainability and ability to solve problems is one an important skill that coding students require to learn programming. This educational have been integrated into curriculum instruction in clubs.

Robotics education has been regarded as a potential approach to enhance students' Science, technology, engineering, and mathematics learning competencies. The popular platform of robots diversifies educational practices by its advantages of reorganizational and logical forms. In this paper, we focus on the effects of applying blended instructional approaches to robot education on students' programming sustainability and ability.

The students of department of mechanical engineering at the University in Taipei city, who participate elective educational robot courses, prove through surveys that the problem-based leaning method with robot programming can effectively enhance students' interests and learning motivations in learning new knowledge and promote students' designing skills for a sustainable society.

In this paper, the authors focus on the effects of applying blended instructional approaches to robot education on students' programming sustainability and ability.

The aim of this paper is to improve the service quality of digital libraries (DLs) through an evaluation model for DLs' user interfaces. This evaluation model can provide a useful reference for existing DLs or relevant research.

Relevant literature was synthesized, an evaluation framework was established, and the Fuzzy AHP was employed to investigate the evaluation model for DLs' user interfaces, obtain the relative weights for the importance of the evaluation criteria, and establish the priority ranking for the criteria of DLs' user interfaces.

The top five criteria are ease of use, searching, language, presentation, and design, respectively. For users, an interface should be intuitive. Good interface presentation and design are critical when users evaluate a digital library.

All of the students, teachers and experts considered that the presentation and design of DL user interfaces were what users had had contact with in the very beginning, and they were critical influential factors in DL user interfaces. Furthermore, ease-of-use and searching were fundamental interface functions, as well as important evaluation criteria. Interfaces should also provide interactive functions to improve interaction, while tailor-made services should be taken into account to establish an excellent interface in order to meet each user's need.

The evaluation model for DLs' user interfaces employed in this study will help developers of DL user interfaces discover the criteria that they should aim for as a reference, perform comprehensive criteria evaluation according to their actual needs, and employ top criteria for evaluation.

The purpose of this paper is, based on leisure constraints and means-end theories, to identify the e-leisure constraints of using the video-sharing websites/apps; demonstrate how means-end theory can be used to reveal the differences between high- and low-leisure constraints in an e-leisure environment; and provide designers and marketers with valuable insights for developing e-leisure products and e-marketing strategies.

Both qualitative and quantitative approaches are employed to collect data. By eliminating three participants whose age range did not meet our criterion (15 to 24 years old), 57 one-on-one in-depth interviews were then content analyzed to design the survey questionnaire. A total of 514 valid samples were collected for hierarchical value map (HVM) construction.

By comparing the full HVM vs the e-leisure constraints HVM, the analytical results indicate that the importance of attributes, consequences and values for the young people using video-sharing websites/apps is quite different. “Unable to resume the video after leaving the screen,” “creating playlist,” “providing movies” and “location restrictions” are extremely important features that influence the willingness of such users with high e-leisure constraints to participate in e-leisure activities. By understanding the differences between these two HVMs, it is possible to provide marketers or designers with valuable insights for website/app design and marketing strategies.

This study only focused on young people’s perceptions of video-sharing websites/apps, so the findings are limited to those aged between 15 and 24 years old. Since managers today are challenged to design effective strategies that can meet target users’ demands across different ages with different economic, social and sub-cultural groups, future research may consider gathering a wider age range of respondents in order to obtain more robust results.

This is the first paper integrating leisure constraints theory and means-end theory to understand young people’s cognitive structure of using video-sharing websites/apps, especially when they encounter e-leisure constraints.