scholarly journals Raising the Dimensions and Variables for Searching as a Learning Process: A Systematic Mapping of the Literature

2020 ◽  
Author(s):  
Marcelo De Oliveira Costa Machado ◽  
Paulo Jose de Alcantara Gimenez ◽  
Sean Wolfgand Matsui Siqueira
Keyword(s):  
Learning Process ◽  
Search Engines ◽  
Research Area ◽  
Information Gathering ◽  
Educational Technologies ◽  
Search Process ◽  
Systematic Mapping ◽  
Learning Tasks ◽  
Factual Learning ◽  
Associated Variables

Search engines are great allies in our daily educational tasks. However, usually, these tools are prepared only for factual learning and are less effective when dealing with more complex learning tasks. Thus, in recent years, Searching as Learning (SAL) research area has been developing from proposals that target the main challenges involving learning during the search process. The effectiveness of educational technologies in providing appropriate instructions depends directly on the input information. Gathering information on what should be taken into account in a search as a learning process can support the development of specialized search engines to support learning. Therefore, we performed a systematic mapping of the literature in order to gather this information, raising the dimensions and their associated variables.

scholarly journals Global and Latin American female participation in evidence-based software engineering: a systematic mapping study

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Katia Romero Felizardo ◽  
Amanda Möhring Ramos ◽  
Claudia de O. Melo ◽  
Érica Ferreira de Souza ◽  
Nandamudi L. Vijaykumar ◽  
...  
Keyword(s):  
Software Engineering ◽  
Latin American ◽  
Gender Issue ◽  
Research Area ◽  
Systematic Mapping Study ◽  
Evidence Based ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Participation Of Women ◽  
New Generation

Abstract Context While the digital economy requires a new generation of technology for scientists and practitioners, the software engineering (SE) field faces a gender crisis. SE research is a global enterprise that requires the participation of both genders for the advancement of science and evidence-based practice. However, women across the world tend to be significantly underrepresented in such research, receiving less funding and less participation, frequently, than men as authors in research publications. Data about this phenomenon is still sparse and incomplete; particularly in evidence-based software engineering (EBSE), there are no studies that analyze the participation of women in this research area. Objective The objective of this work is to present the results of a systematic mapping study (SM) conducted to collect and evaluate evidence on female researchers who have contributed to the area of EBSE. Method Our SM was performed by manually searching studies in the major conferences and journals of EBSE. We identified 981 studies and 183 were authored/co-authored by women and, therefore, included. Results Contributions from women in secondary studies have globally increased over the years, but it is still concentrated in European countries. Additionally, collaboration among research groups is still fragile, based on a few women as a bridge. Latin American researchers contribute a great deal to the field, despite they do not collaborate as much within their region. Conclusions The findings from this study are expected to be aggregated to the existing knowledge with respect to women’s contribution to the EBSE area. We expect that our results bring up a reflection on the gender issue and motivate actions and policies to attract female researchers to this area.

scholarly journals THE RESEARCH DOMAIN OF PRODUCT-SERVICE SYSTEMS AND VOICE OF THE CUSTOMER: A SYSTEMATIC MAPPING

2021 ◽  
Vol 1 ◽  
pp. 3101-3110
Author(s):  
Carl Nils Konrad Toller ◽  
Marco Bertoni
Keyword(s):  
Research Area ◽  
Service Systems ◽  
Future Research ◽  
Systematic Mapping ◽  
Progressive Development ◽  
Development Cycle ◽  
Product Service ◽  
Product Service Systems ◽  
Research Domain ◽  
Voice Of The Customer

AbstractProduct-Service Systems (PSS) have emerged as a key concept to meet the societal and market trends of increasing customer needs through the entire life-cycle. Unfortunately, several companies are struggling with getting revenues from service investments and translating 'real needs' to design improvements. The demand of the designer to go beyond the Voice of the Customer (VoC) is evident. This paper aims to map the interventions proposed by research in the area of PSS and VoC. Using a systematic mapping approach, the research domain was analyzed with regards to context and interventions. The results show a progressive development in the research area with a focus on the specification and realization of needs. A gap exists in connecting the engineers with 'real needs' and integrating the customer as a natural part of the entire development cycle of a PSS. By performing a systematic mapping, future research can be more focused and hopefully increasing its impact.

scholarly journals Representing Deep Neural Networks Latent Space Geometries with Graphs

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 39
Author(s):  
Carlos Lassance ◽  
Vincent Gripon ◽  
Antonio Ortega
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Objective Function ◽  
Learning Process ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
The Core ◽  
Learning Tasks ◽  
Latent Space

Deep Learning (DL) has attracted a lot of attention for its ability to reach state-of-the-art performance in many machine learning tasks. The core principle of DL methods consists of training composite architectures in an end-to-end fashion, where inputs are associated with outputs trained to optimize an objective function. Because of their compositional nature, DL architectures naturally exhibit several intermediate representations of the inputs, which belong to so-called latent spaces. When treated individually, these intermediate representations are most of the time unconstrained during the learning process, as it is unclear which properties should be favored. However, when processing a batch of inputs concurrently, the corresponding set of intermediate representations exhibit relations (what we call a geometry) on which desired properties can be sought. In this work, we show that it is possible to introduce constraints on these latent geometries to address various problems. In more detail, we propose to represent geometries by constructing similarity graphs from the intermediate representations obtained when processing a batch of inputs. By constraining these Latent Geometry Graphs (LGGs), we address the three following problems: (i) reproducing the behavior of a teacher architecture is achieved by mimicking its geometry, (ii) designing efficient embeddings for classification is achieved by targeting specific geometries, and (iii) robustness to deviations on inputs is achieved via enforcing smooth variation of geometry between consecutive latent spaces. Using standard vision benchmarks, we demonstrate the ability of the proposed geometry-based methods in solving the considered problems.

scholarly journals Digitization and Visualization of Folk Dances in Cultural Heritage: A Review

Inventions ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 72 ◽  
Author(s):  
Iris Kico ◽  
Nikos Grammalidis ◽  
Yiannis Christidis ◽  
Fotis Liarokapis
Keyword(s):  
Performance Evaluation ◽  
Cultural Heritage ◽  
Computer Science ◽  
Learning Process ◽  
Research Area ◽  
Active Research ◽  
Active Research Area

According to UNESCO, cultural heritage does not only include monuments and collections of objects, but also contains traditions or living expressions inherited from our ancestors and passed to our descendants. Folk dances represent part of cultural heritage and their preservation for the next generations appears of major importance. Digitization and visualization of folk dances form an increasingly active research area in computer science. In parallel to the rapidly advancing technologies, new ways for learning folk dances are explored, making the digitization and visualization of assorted folk dances for learning purposes using different equipment possible. Along with challenges and limitations, solutions that can assist the learning process and provide the user with meaningful feedback are proposed. In this paper, an overview of the techniques used for the recording of dance moves is presented. The different ways of visualization and giving the feedback to the user are reviewed as well as ways of performance evaluation. This paper reviews advances in digitization and visualization of folk dances from 2000 to 2018.

scholarly journals National followers in the students use of educational technologies instruction of interests

2021 ◽  
Vol 7 (3) ◽  
pp. 152-157
Author(s):  
Shomirzayev Shomirzayev
Keyword(s):  
Critical Thinking ◽  
Collaborative Learning ◽  
Learning Process ◽  
Creative Thinking ◽  
Independent Learning ◽  
Educational Technologies

This article discusses how to use the craft of national crafts. More importantly, the role of the teacher in the learning process is determined by the fact that the learners are helped by independent learning. In addition to teaching the readers not only the knowledge they have, they also understand their role in teaching independent, creative thinking, critical thinking about their personality and knowledge, analyzing information, identifying what needs to be done, drawing conclusions, and teaching their own ideas. The main purpose of collaborative learning is to work on a common problem and focus on the problem.

scholarly journals Promoting Learners` Autonomy Through Individualized Learning

2007 ◽  
Vol 1 (2) ◽  
pp. 105
Author(s):  
Endang Fauziati
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Classroom Practices ◽  
Learning Goals ◽  
Integrated Learning ◽  
Individualized Learning ◽  
Learning Tasks ◽  
Practical Guidance ◽  
Teaching Learning

Article basically tries to explore the concept of individualized learning applicable in teaching learning process which can enhance learners’ autonomy and provides a brief practical guidance on how to put this concept into classroom practices. There are at least five underlying assumptions of learning based on this concept, namely: different learning styles, a variety of sources, teacher as facilitator, integrated learning tasks, and different learning goals. It can be concluded that classroom practices designed based on these concepts can improve learners’ autonomy, such as grouping, projects or tasks, and discussion.

The Role Of Interactive Educational Technologies In Improving The Effectiveness Of Music Education

2020 ◽  
Vol 02 (12) ◽  
pp. 205-208
Author(s):  
Toshmatov Gulomjon ◽  
◽  
Goziyev Jobirkhan ◽  
Keyword(s):  
Music Education ◽  
Learning Process ◽  
Music Teachers ◽  
Interactive Learning ◽  
Learning Technologies ◽  
Educational Technologies

In this article the authors discuss the role of interactive and educational technologies and their effectiveness in the process of teaching for music teachers. Furthermore, the article gives information about concepts and information on the content, purpose and application of interactive learning technologies in the learning process.

ANN softmax

2021 ◽  
Vol 15 (1) ◽  
pp. 1-10
Author(s):  
Kang Zhao ◽  
Liuyihan Song ◽  
Yingya Zhang ◽  
Pan Pan ◽  
Yinghui Xu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Training Sample ◽  
Locality Sensitive Hashing ◽  
Search Process ◽  
Inverted File ◽  
Deep Model ◽  
Learning Tasks ◽  
Improve Accuracy ◽  
Small Set ◽  
Kernel Design

Thanks to the popularity of GPU and the growth of its computational power, more and more deep learning tasks, such as face recognition, image retrieval and word embedding, can take advantage of extreme classification to improve accuracy. However, it remains a big challenge to train a deep model with millions of classes efficiently due to the huge memory and computation consumption in the last layer. By sampling a small set of classes to avoid the total classes calculation, sampling-based approaches have been proved to be an effective solution. But most of them suffer from the following two issues: i) the important classes are ignored or only partly sampled, such as the methods using random sampling scheme or retrieval techniques of low recall (e.g., locality-sensitive hashing), resulting in the degradation of accuracy; ii) inefficient implementation owing to incompatibility with GPU, like selective softmax. It uses hashing forest to help select classes, but the search process is implemented in CPU. To address the above issues, we propose a new sampling-based softmax called ANN Softmax in this paper. Specifically, we employ binary quantization with inverted file system to improve the recall of important classes. With the help of dedicated kernel design, it can be totally parallelized in mainstream training framework. Then, we find the size of important classes that are recalled by each training sample has a great impact on the final accuracy, so we introduce sample grouping optimization to well approximate the full classes training. Experimental evaluations on two tasks (Embedding Learning and Classification) and ten datasets (e.g., MegaFace, ImageNet, SKU datasets) demonstrate our proposed method maintains the same precision as Full Softmax for different loss objectives, including cross entropy loss, ArcFace, CosFace and D-Softmax loss, with only 1/10 sampled classes, which outperforms the state-of-the-art techniques. Moreover, we implement ANN Soft-max in a complete GPU pipeline that can accelerate the training more than 4.3X. Equipped our method with a 256 GPUs cluster, the time of training a classifier of 300 million classes on our SKU-300M dataset can be reduced to ten days.

Learning Behavioral Differences Among Students and Ethical Issues in a University Cloud Classroom System

2018 ◽  
pp. 183-214 ◽  
Author(s):  
Zhi Liu ◽  
Hai Liu ◽  
Hao Zhang ◽  
Sannyuya Liu
Keyword(s):  
Learning Process ◽  
Liberal Arts ◽  
Sequential Analysis ◽  
User Study ◽  
Ethical Issues ◽  
Evidence Based ◽  
Behavioral Differences ◽  
Self Monitoring ◽  
Learning Tasks ◽  
The Individual

In a private learning environment, each learner's interactions with course contents are treasured clues for educators to understand the individual and collective learning process. To provide educators with evidence-based insights, this chapter intends to adopt sequential analysis method to unfold learning behavioral differences among different groups of students (grade, subject, and registration type) in a university cloud classroom system. Experimental results indicate that sophomores undertake more learning tasks than other grades. There are significant differences in task-related and self-monitoring behaviors between liberal arts and science learners. Registered learners have higher participation levels than non-registered ones. Meanwhile, a user study aiming to analyze students' learning feelings indicates that a fraction of students have dishonest behaviors for achieving a good online performance. Finally, this study discusses behavioral ethical issues emerged in cloud classroom, which deserve the attention of educators for regulating and optimizing the online learning process of students.

scholarly journals Enhancing the performance of search engines based heap based data file and hash based indexing file

2018 ◽  
Vol 7 (2.7) ◽  
pp. 372
Author(s):  
Dr Jkr Sastry ◽  
Chandu Sai Chittibomma ◽  
Thulasi Manohara Reddy Alla
Keyword(s):  
Search Engines ◽  
Data File ◽  
Search Process ◽  
Indexing Method ◽  
Storage Area ◽  
The Web

WEB clients use the WEB for searching the content that they are looking for through inputting keywords or snippets as input to the search engines. Search Engines follows a process to collect the content and provide the same as output in terms of URL links. Sometimes enormous time is taken to fetch the content fetched especially when it goes into number of display pages. Locating the content among the number of pages of URLS displayed is complex. Proper indexing method will help in reducing the number of display pages and enhances the seed of processing and result into reducing the size of index space.In this paper a non-clustered indexing method based on hash based indexing and when the data is stored as a heap file is presented that helps the entire search process quite fast requiring very less storage area. 

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