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关键词： Computer programming   Gender   Monitoring accuracy   Prior experience   UMC progression  

摘要： This study investigated middle school students? computer science (CS) learning and monitoring accuracy in the Use-Modify-Create (UMC) progression. This study also examined the effects of prior experience and gender on CS learning and monitoring accuracy measured with sensitivity (proportion of confidence in correct answers) and specificity (proportion of uncertainty in incorrect answers). A total of 255 middle school students participated in this study. A one-group pretest-posttest design was used, and the data were analyzed using multilevel modeling and repeated-measures correlation tests. The results show a non-significant interaction effect of prior experience and gender on students? CS learning and monitoring accuracy. We found that gender significantly interacted with students? CS learning and monitoring accuracy, primarily specificity. In particular, UMC progression was able to reduce the gender gap in CS performance, and improved male monitoring accuracy. The results also showed a significant positive correlation between students? CS performance and sensitivity, and negative correlation with specificity. We discuss the results around the potential advantage of using a UMC progression strategy to reduce gender gaps in CS education, as well as the extent to which UMC can facilitate better instructional environments for serving students with a range of prior experiences.

关键词： Software   Project management   Computer science   Interviews   Encoding   Education   Data collection   Computer science students   software project management   student engagement   student’   s learning perception   student performance  

摘要： Contribution: This article presents a research for enhancing the computer science students' perception on the software project management subject. The main objective of this article is double. The first one is to redesign the current course by including new teaching and new learning methods that encourage students to learn the project management competences and skills. The second one is to analyze the satisfaction of the students regarding the new software project management course. The design of the new course has been based on the improvement proposals from the students, which were collected throughout a grounded theory (GT) study during two academic years. Background: Students must be motivated with both the technical and other transversal competencies provided by the different subjects in the computer science curricula. It is not easy to teach a management subject because students do not clearly find the relationship with their studies. However, it is widely accepted that computer science students need to be trained in project management to be able to work at full capacity in the industry. There is not much literature on how to increase the motivation of students in management subjects. Research Question: Which are the causes and consequences of a low level of interest for software project management in computer science studies? Methodology: Two different experiments were carried out. The first one consisted of determining, during two academic years, the main reasons why computer science students do not get to comprehend the need for such this subject in the curricula. From the GT results, a set of innovative actions were introduced in order to redesign the subject. In the second experiment, during the following two academic years, the satisfaction of the students regarding the changes introduced in the course was analyzed. Findings: The first finding was obtained from the GT study conducted. Four causes influencing students to do not give enough importance to s

关键词： Computational thinking   Engineering   Computer science   Higher education   Valuation methodologies   Pedagogical issues   Teaching/learning strategies   Structural equation modelling   Mathematics  

摘要： Since the end of the 20th century, the digitalization of society, including the educational systems, has been growing exponentially. At the same time, education systems have been evolving towards competency-based assessment. Likewise, at the beginning of this century, the idea of Computational Thinking was resurrected by J. Wing, for solving problems and designing systems using concepts of computer science. Today, we can see how all these questions are taking shape in a new competence, called Computational Thinking, related to others that already exist. In this paper, we have studied the skills of Computational Thinking in university students, focusing on abstraction and its possible relationship with other factors. Results conclude that the students fail in relation to abstraction and in algorithmic thinking. Although the ability of abstraction is not easy to measure, a linear regression analysis has been carried out in order to determine its possible study.

关键词： Tensors   Markov processes   Big Data   Prediction algorithms   Computational modeling   Predictive models   Computer science   Accurate services   big data   high-order dominant eigen decomposition (HODED)   multivariate Markov model   multimodal prediction   scalable tensor computations   tensor-train (TT)-based Einstein product  

摘要： By leveraging neoteric analytical techniques associated with big data, numerous new data-focused computation and service models have flourished in service computing systems. Accurate future predictions based on tensor-based multivariate Markov models can vigorously support enterprise decisions. However, the computation efficiency and quick response of tensor-based multimodal prediction approach are seriously restricted by the curse of dimensionality arising from high-order tensor. Therefore, to alleviate the problem, this paper focuses on proposing a tensor-train (TT)-based computation approach with its scalable implementation for high-order dominant eigen decomposition (HODED) in multivariate Markov models. First, we present a TT-based Einstein product directly based on decomposed TT cores and guarantee that the result remains TT format. Then, we put forward a scalable implementation for TT-based Einstein product in a distributed or parallel manner. Afterwards, we propose a scalable TT-based HODED (TT-HODED) algorithm and a multimodal accurate prediction algorithm. Furthermore, a TT-based big data processing and services framework is presented to provide accurate proactive services. Experimental results based on real-world GPS trajectory dataset demonstrate that TT-HODED algorithm can significantly improve the computation efficiency and reduce the running memory on the premise of guaranteeing the almost consistent prediction accuracy compared to the original HODED algorithm.

关键词： Feature extraction   Task analysis   Measurement   Visualization   Computer science   Training   Neural networks   Vehicle re-identification   convolutional neural network   attention   multi-view  

摘要： Vehicle Re-Identification (Re-ID) is a challenging vision task mainly because the appearance of a vehicle varies dramatically under different viewpoints. Moreover, different vehicles with the same model and color commonly show similar appearance, thus are hard to be distinguished. To alleviate negative effects of viewpoint variance, we design a multi-view branch network where each branch learns a viewpoint-specific feature without parameter sharing. Being able to focus on a limited range of viewpoints, this viewpoint-specific feature performs substantially better than the general feature learned by an uniform network. To further differentiate visually similar vehicles, we strengthen the discriminative power on their subtle local differences by introducing a spatial attention model into each feature learning branch. The multi-view feature learning and spatial attention learning compose our neural network architecture, which is trained end to end with the softmax loss and triplet loss, respectively. We evaluate our methods on two large vehicle Re-ID datasets, i.e., VehicleID and VeRi-776, respectively. Extensive experiments show that our methods achieve promising performance. For example, we achieve mAP accuracy of 76.78% and 72.53% on VehicleID and VeRi-776 dataset respectively, substantially better than current state-of-the art.

关键词： Epidemiology   Computer science   Extract   Transform   Load   Observational study   Research methods  

摘要： The use of primary care electronic health records for research is abundant. The benefits gained from utilising such records lies in their size, longitudinal data collection and data quality. However, the use of such data to undertake high quality epidemiological studies, can lead to significant challenges particularly in dealing with misclassification, variation in coding and the significant effort required to pre-process the data in a meaningful format for statistical analysis. In this paper, we describe a methodology to aid with the extraction and processing of such databases, delivered by a novel software programme;the "Data extraction for epidemiological research" (DExtER). The basis of DExtER relies on principles of extract, transform and load processes. The tool initially provides the ability for the healthcare dataset to be extracted, then transformed in a format whereby data is normalised, converted and reformatted. DExtER has a user interface designed to obtain data extracts specific to each research question and observational study design. There are facilities to input the requirements for;eligible study period, definition of exposed and unexposed groups, outcome measures and important baseline covariates. To date the tool has been utilised and validated in a multitude of settings. There have been over 35 peer-reviewed publications using the tool, and DExtER has been implemented as a validated public health surveillance tool for obtaining accurate statistics on epidemiology of key morbidities. Future direction of this work will be the application of the framework to linked as well as international datasets and the development of standardised methods for conducting electronic pre-processing and extraction from datasets for research purposes.

关键词： blended learning   mobile learning   COVID-19   physics education   performance learning   educational innovation   higher education  

摘要： The COVID-19 pandemic has modified and diversified the ways that students receive education. During confinements, complex courses integrating previous knowledge must be carefully designed and implemented to effectively replace the elements present in face-to-face learning to improve the students' experience. This work assesses the implementation of a digital-learning physics course for computer science students in a skill-based education program in higher education. The assessment was useful for the institution to evaluate if the digital strategy implemented in the course fulfilled the original premises and objectives. The analyses performed provide useful knowledge of theoretical and operational actions applied in this methodology that could be adapted to similar courses for the younger generations in this university. COVID-19 confinement will continue in Mexico in 2021. This assessment resulted in a positive evaluation of the digital strategy being followed, which can be continued while the contingency lasts. Three teachers came together to design math, physics, and computational sciences content for various sections of a physics course. The analysis was developed and implemented according to an institutional digital delivery model for the COVID-19 pandemic. Elements related to attendance, digital access, performance distribution by gender, activity types, and the course learning sections were considered. The analysis was performed with some techniques found in the literature for small groups, complemented when necessary by standard statistical tests to discern meaningful trends. A primary goal was to assess skill-based learning in the course delivered digitally due to the COVID-19 confinement. Furthermore, additional issues concerning the learning dynamics were searched, reported, and analyzed. Finally, the outcomes of an institutional exit survey collecting students' opinions supported certain observed behaviors. The analysis produced meaningful evidence that th

摘要： Donald Knuth on the best way to recognize the history of computer science.

关键词： Bibliometrics   Disaster management   Market research   Databases   Information and communication technology   Computer science   Economics   Disaster Management   Information and Communication Technologies (ICT)   Scopus   VOSviewer  

摘要： The advancements in information and communication technologies have propelled the efforts of various nations toward a disaster-ready society. This progression has even conceived a new term called as smart disaster management (SDM). This profound interest and popularity of SDM among the nations in recent years has led to a considerable number of research publications in this domain. Henceforth, the high relevance and growth of research require the overall study of the structure and development in this field, which can be well understood through quantitative approaches. This article presents a bidimensional scientometric study of SDM research from the perspective of various categories of disasters and research areas. This study is based on an extensive bibliographic data of the period 2009-2018 retrieved from Scopus. It exhibits various empirical approaches to study the evolution, status quo, and output of SDM research. This article provides extensive insights into the publication patterns, citation patterns, and keywords co-occurrence analysis for technological trends of the SDM research. This scientometric study identifies significant categories, research areas, nations, and institutions for SDM research from various perspectives. In whole, this article presents an overall and better understanding of various patterns, trends, and other factors as the foundation for the future research directives and collaborations in the domain of SDM research.