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Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in learning processes, particularly for students with differing achievements. This paper explores the use of sequential pattern mining to address the evolution of student action patterns in Massive Private Online Courses (MPOCs) and compare these patterns between different achievement groups. The study was conducted with first-year undergraduate computer science students enrolled in a computer application course at a traditional open university in one of the Chinese provinces (N = 1375). The results showed the development of various action patterns in each phase of the course and the distinct action patterns for high-achieving and low-achieving students. The findings of study provide a new perspective for instructors and students to understand interaction patterns at the fine-grained level, and can help instructional designers develop learner-cantered courses and platforms to improve online learning.

Fractional-order derivative is attracting more and more attention of researchers in image processing because of its better property in restoring more texture than the total variation. To improve the performance of fractional-order variation model in image restoration, a truncated fractional-order variation model was proposed in Chan and Liang [Truncated fractional-order variation model for image restoration, J. Oper. Res. Soc. China]. In this paper, we propose a dual approach to solve this truncated fractional-order variation model on noise removal. The proposed algorithm is based on the dual approach proposed by Chambolle [An algorithm for total variation minimisation and applications, J. Math Imaging Vis. 20 (2004), pp. 89–97]. Conversely, the Chambolle's dual approach can be treated as a special case of the proposed algorithm with fractional order α = 1. The work of this paper modifies the result in Zhang et al. [Adaptive fractional-order multi-scale method for image denoising, J. Math. Imaging Vis. 43(1) (2012), pp. 39–49. Springer Netherlands 0924–9907, Computer Science, pp. 1–11, 2011], where the convergence is not analysed. Based on the truncation, the convergence of the proposed dual method can be analysed and the convergence criteria can be provided. In addition, the accuracy of the reconstruction is improved after the truncation is taken. [ABSTRACT FROM AUTHOR]

The study provides a quantitative and qualitative description of global research in the domain of quantum machine learning (QML) as a way to understand the status of global research in the subject at the global, national, institutional, and individual author level. The data for the study was sourced from the Scopus database for the period 1999-2020. The study analyzed global research output (1374 publications) and global citations (22434 citations) to measure research productivity and performance on metrics. In addition, the study carried out bibliometric mapping of the literature to visually represent network relationship between key countries, institutions, authors, and significant keyword in QML research. The study finds that the USA and China lead the world ranking in QML research, accounting for 32.46% and 22.56% share respectively in the global output. The top 25 global organizations and authors lead with 35.52% and 16.59% global share respectively. The study also tracks key research areas, key global players, most significant keywords, and most productive source journals. The study observes that QML research is gradually emerging as an interdisciplinary area of research in computer science, but the body of its literature that has appeared so far is very small and insignificant even though 22 years have passed since the appearance of its first publication. Certainly, QML as a research subject at present is at a nascent stage of its development. [ABSTRACT FROM AUTHOR]

The paper examines 12104 global publications on digital library research, as covered in Scopus database during 2007-16. Digital library research registered annual average growth rate of 7.83% and averaged 4.40 citations per paper. Digital library research is dominated by top 15 most productive countries accounting for 81.61% global publications share in 10 years during 2007-16. USA accounted for the highest global publications share (26.89%), followed by China (10.42%), etc. Computer Science accounts for the largest publication share (62.48%) in global digital library research, followed by Social Sciences and Engineering (30.86% and 19.75%), Mathematics (15.74%), etc. The top 20 most productive research organizations and productive authors contributed 13.64% and 6.90% global publication share respectively and 15.98% and 10.05% global citation share respectively during 2007-16. The top 30 journals contributed 35.15% share to the global journal output during 2007-16. [ABSTRACT FROM AUTHOR]

The rise of the Internet and social media (i.e. reviews, forum discussions, blogs and social networks) constituted an interesting source to detect user opinion trends. This study examines the global publication output on opinion mining and sentiment analysis from documents published in 2000 to 2020. Bibliometric indicators on the trends, most cited papers, authors, institutions, countries, funding agencies and research subject areas were independently screened and analysed using bibliometrix package in R. A total of 7603 eligible documents were identified from 2000 to 2020. The total number of citations for all publications was 129,251, with an average of 17.0 citations per publication. About 14,629 authors wrote those documents with 1.93 authors per document and a collaboration index of 1.98. The most prolific author was Cambria Erik, with 47 publications and h-index of 42. The leading countries for research were China with n = 824, India with n = 576 and the United States with n = 244 publications. Lecture Notes in Computer Science proceedings was the top-ranked venue for publications with n = 434, h-index of 32 and 4598 total citation scores. National Natural Science Foundation of China was the top-ranked funding agency for research, and most of the publications were computer science (n = 6320) documents. The study provides an in-depth assessment of the landmark of the hot research topic and acknowledges the contribution of the most productive and active authors across different countries in the world. In addition, the findings could support the younger scholars in their future research direction and improve the efficiency in potential future research collaborations and projects. [ABSTRACT FROM AUTHOR]

Summary: Art painting is a very important major in China's education system. Under the background of the new era, the country vigorously promotes the modernization of education and the development of intelligence. Many subjects of teaching have been more mature and carried out intelligent teaching based on virtual reality technology. But throughout the art painting profession, the research on this aspect is almost blank. The main reason is that there are deep academic barriers between art painting and computer science. Therefore, this paper puts forward the application research of multi‐source information art painting fusion interactive 3D dynamic scene virtual reality technology. This paper deeply analyzes the needs of art painting and its teaching reform and believes that the existing virtual reality technology cannot adapt to the teaching environment of art painting. In view of the possible inaccurate calculation and other problems, this paper puts forward the optimization scheme. The core of the scheme is to use the information integration advantages of multi‐source information fusion to provide more comprehensive and complete object information for 3D modeling of virtual reality technology, so as to improve the imaging quality of virtual reality technology. In order to meet the requirement of high precision, the calculation method is optimized, the calculation steps are simplified, and the sensor selection is optimized again. This paper introduces the design principle and operation steps of the optimization method in detail. In order to further verify the actual effect of this method, comparative analysis method is used to test the comprehensive performance. In order to ensure the test quality, the median filtering algorithm and fuzzy algorithm are compared. Through the analysis and comparison of the data, the optimization method in this paper greatly improves the accuracy of calculation and the comprehensive performance is improved. [ABSTRACT FROM AUTHOR]

Purpose — The aims of this article are to describe the current status, usage, and acceptance of domestic preprint servers in mainland China by investigating three integrated preprint servers in mainland China. These are the Qiji e-print archive (Qiji), the Chinese Preprint Server (CPS), Chinese Science Papers Online (CSPO)., Design/methodology/approach — This research gives a quantitative analysis of the submission numbers to three preprint servers, the subject distribution and citations. An investigation of university websites and their policies was also carried out. Findings — Preprint submissions have a strong correlation with official promotion and policies. The preprints communication pattern in mainland China concentrates on the disciplines of physics, mathematics and computer science which reflects international preprint communication behaviour. As yet the domestic preprint servers in mainland China attract little attention from excellent scholars and have a low impact on scientific communication. Research limitations/implications — No author survey was conducted. Originality/value — This is the first paper to characterize the usage and acceptance of domestic preprint servers in mainland China using a quantitative method. [ABSTRACT FROM AUTHOR]

Microteaching techniques have been used for teacher training since the mid 1960s. Despite its usefulness, as affirmed by pre-service teachers, in-service teachers, and graduate teaching assistants (GTAs), there are numerous criticisms on the shortcomings of microteaching activities. Specifically, it (a) oversimplifies the classroom learning and teaching nature, (b) encourages skill modelling on one or only few technique(s) demonstrated during training sessions, (c) involves costly human and technical resources for implementation, and most critically, (d) fails to provide instant and reusable feedback to improve classroom teaching skills. Addressing the inadequacies of traditional microteaching practice, this paper proposes an Extreme-Teaching-2 (XT[superscript 2]) framework based on the computer science literature. Originating from Extreme Programming (XP) methodology, XT[superscript 2] preserves the agility on teaching-feedback-teaching cycles with heavy peer and instructor involvement. With strong technological support, XT[superscript 2] allows specific, personalized, incremental, and constructive formative feedback to be given by peers and instructors during and after two classroom observation sessions. Through the XT[superscript 2] framework, teacher candidates are able to reuse feedback instantly (feedforward) and rapidly improve (a) confidence in identifying their weaknesses and strengths, (b) and their facilitating skills, while the administrative workload on instructors is significantly reduced.

Purpose: The declining participation of young American females in computing fields negatively impacts diversity in the computing-related workforce. While computing in China is also dominated by men, career prospects are positively perceived by Chinese women. The purpose of this paper is to investigate both countries' female gender perceptions toward computing and two influencing psychological factors, computer anxiety and computer self-efficacy (CSE). To better understand American females' perception toward computing, these factors are compared to those of Chinese women. Design/methodology/approach: The paper tried to understand gender perception toward computing, which is believed to be one factor influencing female participation in computing. The paper examined 137 American female students and 145 Chinese female students. All students were non-IT-related business majors. The survey contained the following scales: gender typing scale, CSE scale, and computer anxiety rating scale. The paper used the model comparison technique in structural equation modeling to develop the proposed model demonstrating the relationship among the three psychological factors. Findings: It is found that American females perceive that computing is for females, but Chinese females perceive that computing is for both males and females. Computer anxiety has a direct influence on gender perception toward computing for both groups. CSE, however, does not have a direct influence on gender perception toward computing for both groups. CSE also has a direct relationship with computer anxiety. The extent to which each factor influences other factors is different between both groups and this reveals interesting implications. Social implications: The authors believe that to properly encourage female participation in computing, it is important to emphasize two areas in education. In order to lower computer anxiety and increase CSE, educators need to promote basic computer skills and provide a fundamental knowledge of computers and information technologies. A more positive perception by females could be created through a stronger awareness of female roles in computing. Classroom discussions including more examples of positive female role models in computing is necessary. Female professionals need to support each other and encourage young females to pursue computing-related education fields and careers. Originality/value: There is an important need to understand the decline of American female participation in computing. Few researchers have investigated gender perception toward computing with computer anxiety and CSE. Furthermore, a model explaining the relationship of the three factors previously had not been presented. This paper not only investigated how computer anxiety and CSE influences gender perception toward computing, but also compared these results between American and Chinese females. A suggested guideline to improve gender perception of American females was developed. (Contains 1 note, 6 tables, and 2 figures.)

Purpose: The purpose of this paper is to consider the under-representation of women in computing, information technology (IT) and information systems in most Western countries. This under-representation can only be detrimental to society. Design/methodology/approach: The authors discuss recently published studies on the under-representation of women in this field, and the lack of career progression for women, particularly in positions of senior responsibility. The results of a survey conducted in the UK, Greece, Malaysia and China are presented, and similarities as well as differences are identified. Malaysia and China are included as the under-representation is much less in the Asian countries. Findings: The authors identify the main reasons for the under-representation and lack of career progression, and study the effect of national culture on the formation of strategy and of practice in the four countries. Research limitations/implications: The survey respondents are mainly female students studying computing/IT at degree level. In the next phase of the research, the survey will include both male and female students, lecturers and employees within the IT sector. The research will be extended into a longitudinal study, in order to monitor trends. Originality/value: The UK Government is currently undertaking a number of initiatives to improve the representation of women in information and communication technologies. For those initiatives to be successful, the cultural issues identified in the paper need to be considered. (Contains 7 tables.)