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Journal articles on the topic 'Learning-based resources'

Author: Grafiati

Published: 7 September 2021

Last updated: 29 July 2025

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1

Singh, Bhupinder, Amandeep Kaur, and Khushpreet Singh Brar. "Information literacy and learning styles: an overview of resource-based student-centred learning." Journal of Management Research and Analysis, 4, no. 3 (2017): 84–86. https://doi.org/10.18231/2394-2770.2017.0012.

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Information plays a very vital role in the economic and social development of a country. The article is deals with the ‘new approaches of Information Literacy and Learning Styles. Information Literacy (IL) has different meaning to different people and is known by different names: Library Orientation; Bibliographic Instruction; User Education; Information Skills Training. All the forms of IL are closely related to each other but information skills training and information literacy concentrated on cognitive and transferable skills such as problem solving, evaluation and communication skill

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Tinker, Robert. "Free Model-Based Learning Resources." i-manager's Journal of Educational Technology 1, no. 4 (2005): 20–22. http://dx.doi.org/10.26634/jet.1.4.913.

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Jia, Ligang. "Online Course Learning Resource Recommendation Based on Difficulty Matching." International Journal of Emerging Technologies in Learning (iJET) 17, no. 22 (2022): 156–69. http://dx.doi.org/10.3991/ijet.v17i22.35123.

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The current methods for online course learning resource recommendation tend to continuously push similar items to students. To make students more satisfied with the overall recommendation service, it is necessary to explore the recommendation methods for online course learning resources based on difficulty matching. Therefore, this paper devises an online course learning resource recommendation method based on difficulty matching. Firstly, an online course learning resource recommendation approach was developed based on the autoencoder, in the light of difficulty matching. The flowchart of lea

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Xu, Shuoyan. "Recommendation of Online Learning Resources for Personalized Fragmented Learning Based on Mobile Devices." International Journal of Emerging Technologies in Learning (iJET) 17, no. 03 (2022): 34–49. http://dx.doi.org/10.3991/ijet.v17i03.29427.

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Fragmented learning aims to fully utilize fragmented time slices to learn and accumulate fragmented knowledge. The current mobile online learning apps fail to fully consider the preferences, demands, and adaptability of users. The content and difficulty of the recommended resources are not in match with user features. Therefore, this paper explored the issue of the recommendation of personalized online learning resources for fragmented learning based on mobile devices. Firstly, the authors developed an architecture for the adaptive recommendation model of online learning resources, modeled the

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Yuan, Shuai, Qian Qi, Enliang Dai, and Yongfeng Liang. "Human Resource Planning and Configuration Based on Machine Learning." Computational Intelligence and Neuroscience 2022 (March 15, 2022): 1–6. http://dx.doi.org/10.1155/2022/3605722.

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Human resources are the core resources of an enterprise, and the demand forecasting plays a vital role in the allocation and optimization of human resources. Starting from the basic concepts of human resource forecasting, this paper employs the backpropagation neural network (BPNN) and radial basis function neural network (RBFNN) to analyze human resource needs and determine the key elements of the company’s human resource allocation through predictive models. With historical data as reference, the forecast value of current human resource demand is obtained through the two types of neural netw

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Li, Qiaolan. "A New Methodology for Clustering of Online Learning Resources Based on Students' Learning Styles." International Journal of Emerging Technologies in Learning (iJET) 18, no. 13 (2023): 234–49. http://dx.doi.org/10.3991/ijet.v18i13.41909.

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Recommending learning resources to students according to their respective learning style is conductive to improving learning efficiency, and the clustering and classification of learning resources conduce to reducing learning resource redundancy and duplication and increasing learning resource utilization. However, available methods of learning resource recommendation usually regard students’ learning styles as fixed and invariable, which apparently contradicts reality and may have a negative influence on students’ learning effect. In view of this matter, this paper aims to propose a novel met

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Li, Peng, Yuanru Cui, Qian Liu, et al. "LRDC: Learning Resource Diffusion Based on Credibility for Computer-Supported Collaborative Learning." Wireless Communications and Mobile Computing 2021 (November 30, 2021): 1–13. http://dx.doi.org/10.1155/2021/6646399.

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Computer-supported collaborative learning (CSCL) is a learning strategy that gathers students together on campus through mobile application software on intelligent handheld devices to carry out creative exploration learning activities and social interaction learning activities. Learning resource diffusion is a very important constituent part of CSCL mobile software. However, learners will receive or forward a large number of learning resources such that short video, images, or short audio which will increase the energy consumption of forwarding nodes and reduce the message delivery success rat

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Gong, Lin, Zi Jian Zhang, and Jian Xie. "Multi Strategies-Based Resources Recommendation in Learning Team." Advanced Materials Research 1006-1007 (August 2014): 1187–93. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.1187.

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Learning team has become an important foundation for collaborative work. In a team, according to the knowledge of members and task requirements, how to recommend learning resources to the appropriate team member is a key factor of success. This paper firstly reviewed related methods and concepts in knowledge management and recommendation. Then, it constructed different models for task, knowledge, team member and learning resource. The two strategies of resources recommendation were proposed. One was based on similarity measurement and another is based on knowledge background and experience of

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Lu, Jingxuan, YangKwon Jeong, and Jiaqi Xue. "Design and Implementation of a Learning Resource Recommendation System based on User Habits Based on GNN." Frontiers in Computing and Intelligent Systems 4, no. 3 (2023): 62–65. http://dx.doi.org/10.54097/fcis.v4i3.11135.

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This project aims to design and implement a learning resource recommendation system based on Graph Neural Networks (GNN). The system utilizes user learning habits as a foundation to provide personalized learning resource recommendations. By collecting and preprocessing user learning history data, and constructing a user-resource relationship graph, the GNN model is used to learn the representation vectors of users and resources. Combined with user habit features, appropriate recommendation algorithms are employed to recommend learning resources that align with their interests and habits.

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Mrs., K.S.Saraswathi Devi. "Federated Learning-Based Resource Allocation for Cloud-Edge Computing." IJAPR Journal UGC Indexed & Care Listed 7, no. 1 (2022): 120–25. https://doi.org/10.5281/zenodo.8311909.

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<strong>Cloud-edge computing is a promising paradigm that can address the challenges of latency, bandwidth, and privacy in cloud computing. However, the edge nodes have limited resources, so it is important to allocate resources efficiently. This paper proposes a federated learning-based resource allocation framework for cloud-edge computing. The proposed framework consists of three main components: a federated learning algorithm, a resource allocation algorithm, and a secure communication protocol. The federated learning algorithm is responsible for training a machine learning model without s

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Shi, Weiwei, and Qiuzuo Li. "Human Resources Balanced Allocation Method Based on Deep Learning Algorithm." Scientific Programming 2021 (September 23, 2021): 1–9. http://dx.doi.org/10.1155/2021/4681959.

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At present, the economics and social developments show the characteristics of diversification, and the focus of social enterprise management is driven by the allocation of human resources. Human resource allocation is a way of appropriate allocation and reasonable placement of human resources. It means that, under the guidance of science, human resources can maintain the best combination with other resources at any time. Nevertheless, the irregularities in management teams and the balanced differences of talent quality have a great effect on the balanced development of an enterprise. Based on

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Amirah Mohd Fisal, Farah, Azlina Abdul Aziz, and Nur Ehsan Mohd Said. "Field Experts’ Evaluation of a Web-based Academic Vocabulary Learning Resource for ESL Pre-university Learners." Arab World English Journal 15, no. 1 (2024): 368–83. http://dx.doi.org/10.24093/awej/vol15no1.23.

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Evaluating web-based learning resources during the development process before implementation with target learners is essential to ensure their efficacy. This study examines field experts’ perceptions of a web-based academic vocabulary learning resource developed by the authors for ESL pre-university learners. The main aim is to evaluate the resource’s technical, design, content, and pedagogy aspects, following Kartal and Uzun’s (2010) criteria for good language learning websites. A questionnaire survey was distributed to six field experts from various Malaysian tertiary education institutions

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Bourkoukou, Outmane, and Omar Achbarou. "Weighting based approach for learning resources recommendations." JOIV : International Journal on Informatics Visualization 2, no. 3 (2018): 104. http://dx.doi.org/10.30630/joiv.2.3.124.

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Personalized e-learning systems based on recommender systems refines enormous amount of data and provides suggestions on learning resources which is appealing to the learner. Although, the recommender systems depends on content based approach or collaborative filtering technique to make recommendations, these methods suffers from cold start and data sparsity problems. To overcome the limitations of the aforementioned problems, a weight based approach is proposed for better performance. The main criterion for building a personalized recommender system is to exploit useful content and provide be

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Mahfuzi, Ahmad. "Utilization of Environment-Based PAI Learning Resources." Journal of Social Science 4, no. 3 (2023): 777–84. http://dx.doi.org/10.46799/jss.v4i3.574.

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    In the current context, learning activities have been greatly facilitated by the existence of various kinds of learning resources that can be used as a reference for exploring knowledge in order to improve and enrich our insights so that we can respond to the challenges of globalization. And one of the learning resources that can be utilized by humans is the environment. The environment is one source of learning that has a broad scope. And basically, all types of environment, around children can be used to optimize educational activities as long as they are relevant

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Furqon, Miftahul. "Film-Based Resources in Asynchronous Online Learning." EDULANGUE 3, no. 1 (2020): 17–28. http://dx.doi.org/10.20414/edulangue.v3i1.2009.

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Juxtaposed with other teaching and learning media, film-based resources in English Language teaching are succinctly beneficial to support students to learn English skills. Films facilitate students to learn English integrally, not in an isolated way. Responding to today’s trend in which the teaching and learning process is converted from offline to an online system, it is crucial to ease students to be independent learners. This paper is aimed to justify how filmbased resources can support student’s learning independence in asynchronous online learning. Specifically, the writer focuses on revi

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Zhou, Lijuan, Feifei Zhang, Shudong Zhang, and Min Xu. "Study on the Personalized Learning Model of Learner-Learning Resource Matching." International Journal of Information and Education Technology 11, no. 3 (2021): 143–47. http://dx.doi.org/10.18178/ijiet.2021.11.3.1503.

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With the development of service integration technology, online learning platforms have gathered a large number of learning resources, causing learners to get lost in a variety of course information and it is difficult to obtain learning resources that match their own needs. The proposal of personalized learning gives the problem a direction to solve. However, current personalized learning resource recommendation services facing problems such as excessive candidate resources, sparse history and cold starts. In addition, the learning resources provided also show problems of "difficult or easy, u

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Xiao, Yang, Guoli Yang, and Xijun Zhang. "A New Learning Resource Retrieval Method Based on Multi-knowledge Association Mining." International Journal of Emerging Technologies in Learning (iJET) 18, no. 04 (2023): 104–19. http://dx.doi.org/10.3991/ijet.v18i04.38243.

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Ever since the human society has entered the era of big data, the quantity and type of digital learning resources on the Internet are increasing exponentially, and the requirement of students for learning resource retrieval is on the rise. However, the existing methods of learning resource retrieval generally overlook the overall knowledge systems that the students have already possessed, so it’s impossible for them to predict the students’ learning path or perform deviation adjustment. In view of these issues, this paper aims to study a new learning resource retrieval method based on multi-kn

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Wannapiroon, Panita, Prachyanun Nilsook, Nutthapat Kaewrattanapat, Naphong Wannapiroon, and Wera Supa. "The Virtual Learning Resource Center for the Digital Manpower." International Education Studies 14, no. 9 (2021): 28. http://dx.doi.org/10.5539/ies.v14n9p28.

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This research aims to develop the models of Virtual Learning Resource Center (VLRC) for the digital manpower. The results of the research are that: 1) The VLRC development process consists of 5 steps: requirements analysis, planning and designing, prototyping and testing, implementing and monitoring, and evaluation and reporting. 2) The VLRC for the digital manpower consists of two models: 2.1) the physical learning resource, which is a physical space that the learner can actually touch. It can be divided into 5 categories: location-based learning resources, human-based learning resources, mat

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Trisnani, Novy, and Wulan Tri Puji Utami. "Ethnomathematics-Based Learning Tools." International Journal of Elementary Education 5, no. 4 (2021): 593. http://dx.doi.org/10.23887/ijee.v5i4.40574.

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The application of the learning from the home system (BDR) and the implementation of social distancing require teachers to develop mathematics learning resources by utilizing an environment close to students' daily lives. However, there are still many teachers who have difficulty developing learning resources that are suitable for students to apply. This study aimed to design a good, practical, and efficient ethnomathematical-based learning device by utilizing Pawon (kitchen) as a learning resource. Learning tools are designed by modifying the Borg and Gall development procedures, namely explo

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Peng, Zhiping, Delong Cui, Jinglong Zuo, and Weiwei Lin. "Research on Cloud Computing Resources Provisioning Based on Reinforcement Learning." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/916418.

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As one of the core issues for cloud computing, resource management adopts virtualization technology to shield the underlying resource heterogeneity and complexity which makes the massive distributed resources form a unified giant resource pool. It can achieve efficient resource provisioning by using the rational implementing resource management methods and techniques. Therefore, how to manage cloud computing resources effectively becomes a challenging research topic. By analyzing the executing progress of a user job in the cloud computing environment, we proposed a novel resource provisioning

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Zhou, Zhenfang. "A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation." International Journal of Emerging Technologies in Learning (iJET) 16, no. 09 (2021): 219. http://dx.doi.org/10.3991/ijet.v16i09.22745.

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Mature online English learning platforms should provide students with necessary learning resources, ensure efficient access to learning projects, and offer the optimal learning experience. However, the traditional recommendation methods for English learning resources cannot satisfy the in-depth learning demand of students. To solve the problem, this paper designs a resource recommendation algorithm for online English learning systems based on learning ability evaluation. Firstly, the workflow of the designed algorithm was introduced, and a four-layer test system was developed for students’ Eng

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Hajar, Siti. "Learning Polyhedrons Based On It." Mathematics Education Journal 2, no. 1 (2018): 1. http://dx.doi.org/10.22219/mej.v2i1.5799.

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Learning resources and media play very important roles in learningactivities in the classroom. Various learning resources complemented withinteractional media will encourage the learners to be more active in theclassroom. The objective of this present research is to analyze whatlearning resources and media are used by the teacher in learningpolyhedrons. This research was conducted in MTs N Malang 1. Themethods of data collection were observations and interviews. To obtain thedata, the researcher made observations during learning activities and thencompared the data from the observations and th

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Li, Fangfang. "Retrieval and Recommendation of English Learning Resources Based on Knowledge Correlation." International Journal of Emerging Technologies in Learning (iJET) 17, no. 16 (2022): 59–72. http://dx.doi.org/10.3991/ijet.v17i16.33763.

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 The design of retrieval and recommendation method of personalized learning resources based on students’ cognition level of professional knowledge and the correlation degree of the knowledge is of certain practical significance. In reality, students’ learning preferences and needs will change with the passing of time and the upgrading of learning stages, so giving learning resource recommendations without considering the time series features of students’ needs for learning resources cannot guarantee students' learning efficiency or the effect of personal knowledge system perfection. To s

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Wang, Xuebin, Zhengzhou Zhu, Jiaqi Yu, Ruofei Zhu, DeQi Li, and Qun Guo. "A learning resource recommendation algorithm based on online learning sequential behavior." International Journal of Wavelets, Multiresolution and Information Processing 17, no. 02 (2019): 1940001. http://dx.doi.org/10.1142/s0219691319400010.

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The accuracy of learning resource recommendation is crucial to realizing precise teaching and personalized learning. We propose a novel collaborative filtering recommendation algorithm based on the student’s online learning sequential behavior to improve the accuracy of learning resources recommendation. First, we extract the student’s learning events from his/her online learning process. Then each student’s learning events are selected as the basic analysis unit to extract the feature sequential behavior sequence that represents the student’s learning behavioral characteristics. Then the extr

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Yang, Hui, Jia Jun Liu, and Xiao Bao Zhang. "Web Based Learning System Modeling Research." Applied Mechanics and Materials 389 (August 2013): 974–78. http://dx.doi.org/10.4028/www.scientific.net/amm.389.974.

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Based on being a modeling process of the network learning system essentially, it has three elements of learning environment, learning, learning activities, and three dimensions of conceptual model, physical model and logical model. From the method aspect, it has analytical method, theoretical basis, model design; from logical view, it has branch learning resource, learning control management and students' interaction layer. Focus on the analysis of the learning system model of learning resources and learning system modeling.

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Han, Xiaolu. "Recommendation Algorithm of Web-Based Learning Resources considering Timeliness and Popularity." Advances in Multimedia 2022 (October 7, 2022): 1–6. http://dx.doi.org/10.1155/2022/2584890.

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The optimized learner evaluation matrix and similarity model are essential methods to deal with the challenges of “data sparsity” and “cold start” in the process of learning resource recommendation on the online learning platform. Accordingly, an improved collaborative filtering algorithm (TRCP) is proposed to improve the accuracy of learning resource recommendation. The TRCP algorithm generates the learner evaluation matrix for recommended projects by classifying learning resources. It comprehensively considers the influence of learners’ online learning behavior, learning time, and popularity

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Wang, Xu. "Research on Online Education Resources Recommendation Based on Deep Learning." Computational Intelligence and Neuroscience 2022 (September 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/3674271.

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For the problem of knowledge overload in the process of online learning and the traditional algorithm’s poor recommendation accuracy and real-time performance in the massive educational resources, a deep learning-based recommendation model for online educational resources is proposed. First, attribute features of learners and learning resources are extracted, and then text features of learning resources are extracted, and attention fusion of features at multiple different scales is performed using a multiscale fusion strategy. Finally, the fused features are used as input to the multilayer per

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Nazil Iqdami, Muhammad. "Resource Based Learning for Teaching and Learning English in Digital Environments." Register Journal 9, no. 2 (2016): 187. http://dx.doi.org/10.18326/rgt.v9i2.187-226.

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This paper presents a conceptual framework on the implementation of Resource Based Learning (RBL) in English as a Foreign Language (EFL) class. Resource based learning emerges as the proponent of constructivism as well as a response to the rapid development of information and communication technology (ICT) and its influence in education. Digital technologies pose potential opportunities in changing the face of education. The affordances of digital technologies empower more student-centered learning and more accessible educational information. Teaching English for foreign learners is dynamic an

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Nazil Iqdami, Muhammad. "Resource Based Learning for Teaching and Learning English in Digital Environments." Register Journal 9, no. 2 (2016): 187. http://dx.doi.org/10.18326/rgt.v9i2.701.

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This paper presents a conceptual framework on the implementation of Resource Based Learning (RBL) in English as a Foreign Language (EFL) class. Resource based learning emerges as the proponent of constructivism as well as a response to the rapid development of information and communication technology (ICT) and its influence in education. Digital technologies pose potential opportunities in changing the face of education. The affordances of digital technologies empower more student-centered learning and more accessible educational information. Teaching English for foreign learners is dynamic an

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Hao, Cuiping, and Ting Yang. "Deep Collaborative Online Learning Resource Recommendation Based on Attention Mechanism." Scientific Programming 2022 (March 24, 2022): 1–10. http://dx.doi.org/10.1155/2022/3199134.

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In view of the lack of hierarchical and systematic resource recommendation caused by rich online learning resources and many learning platforms, an attention-based ADCF online learning resource recommendation model is proposed by introducing the attention mechanism into a deep collaborative DCF model. Experimental results show that the proposed ADCF model enables an accurate recommendation of online learning resources, reaching 0.626 and 0.339 on the HR and NDCG metrics, respectively, compared to the DCF models before improved, up by 1.31% and 1.25%, and the proposed ADCF models by 1.79%, 2.17

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Li, Jinlong, and Zhe Zhou. "Design of Human Resource Management System Based on Deep Learning." Computational Intelligence and Neuroscience 2022 (July 20, 2022): 1–9. http://dx.doi.org/10.1155/2022/9122881.

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With the advent of the Internet era, the frequency and proportion of candidates obtaining recruitment information through the Internet is getting higher and higher, and the amount of human resources information such as talent information and postinformation has also increased unprecedentedly, which makes human resources services face the problem of information overload. At the same time, deep learning has achieved great success in a series of fields such as computer vision, natural language processing, and semantic recognition in recent years. However, there are few related works in the field

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Ming, Li. "A Deep Learning-Based Framework for Human Resource Recommendation." Wireless Communications and Mobile Computing 2022 (July 22, 2022): 1–12. http://dx.doi.org/10.1155/2022/2377143.

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Recently, small- and medium-scale organizations have gained favorable responses due to the dramatic economic growth in China. This rise is due to international collaborations and social-economic growth by providing good quality and quantity services. However, when compared with other developing countries, small- and medium-scale organizations in China face many restrictions considering size and contributions. Few organizations are still facing a challenge because of the difficulties and lesser quality and also with lack of human resources. The prime objective of this study is to identify the c

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Yang, Xi, Zhihan Zhou, and Yu Xiao. "Research on Students’ Adaptive Learning System Based on Deep Learning Model." Scientific Programming 2021 (December 16, 2021): 1–13. http://dx.doi.org/10.1155/2021/6593438.

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With the rapid development of deep learning in recent years, recommendation algorithm combined with deep learning model has become an important direction in the field of recommendation in the future. Personalized learning resource recommendation is the main way to realize students’ adaptation to the learning system. Based on the in-depth learning mode, students’ online learning action data are obtained, and further learning analysis technology is used to construct students’ special learning mode and provide suitable learning resources. The traditional method of introducing learning resources m

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Tsai, Shih-Ting, Hsin-Yi Huang, and Teng-Wen Chang. "Developing a Motion Infographic-Based Learning System for Effective Learning." Education Sciences 10, no. 9 (2020): 247. http://dx.doi.org/10.3390/educsci10090247.

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The motion infographic system combines the characteristics of continuous images and the simplification of information, which can make up for the disadvantages of content in static images, and may have the advantage of deepening the impression of infographics. As Taiwan’s elementary school resource classes (elementary school pupils with mild disabilities or learning challenges) do not yet have exclusive learning content, resource class teachers prepare their own teaching content, but they cannot integrate existing learning lists and network resources. Therefore, this study designed and develope

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Liu, Ze, Jingzhao Zhou, Xiaoyang Yang, Zechuan Zhao, and Yang Lv. "Research on Water Resource Modeling Based on Machine Learning Technologies." Water 16, no. 3 (2024): 472. http://dx.doi.org/10.3390/w16030472.

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Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific basis for water resource management, protection, and planning. Traditional hydrological observation methods, often reliant on experience and statistical methods, are time-consuming and labor-intensive, frequently resulting in predictions of limited accuracy. However, machine learning technologies enhance the efficiency and sustainability of water r

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Tang, Yan. "Distance Learning Classroom Communication System Based on Cloud Computing." Applied Mechanics and Materials 644-650 (September 2014): 1813–16. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1813.

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The centralized model of B / S structure is adopted in the current distance education learning classroom, there are some drawbacks of this model, like the resource duplication, crowded user access, poor system scalability and so on. Adoption of cloud computing technology can collect all the distance learning classroom resources to build a "cloud" platform, students can easily access the resources they need by using different terminal devices locally. By analyzing the meaning of cloud computing, application mode and characteristics of cloud computing, the building contents and methods of distan

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M. R. M., Veeramanickam, Ciro Rodriguez, Carlos Navarro Depaz, et al. "Machine Learning Based Recommendation System for Web-Search Learning." Telecom 4, no. 1 (2023): 118–34. http://dx.doi.org/10.3390/telecom4010008.

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Nowadays, e-learning and web-based learning are the most integrated new learning methods in schools, colleges, and higher educational institutions. The recent web-search-based learning methodological approach has helped online users (learners) to search for the required topics from the available online resources. The learners extracted knowledge from textual, video, and image formats through web searching. This research analyzes the learner’s significant attention to searching for the required information online and develops a new recommendation system using machine learning (ML) to perform th

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Yun, Hong-Won. "Storing Method of Learning Resources based on Cluster for e-Learning." Journal of the Korea Contents Association 7, no. 1 (2007): 155–60. http://dx.doi.org/10.5392/jkca.2007.7.1.155.

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Ali, Sarhadi. "LEARNING AUTOMATA BASED METHOD FOR GRID COMPUTING RESOURCE VALUATION WITH RESOURCE SUITABILITY CRITERIA." International Journal of Grid Computing & Applications (IJGCA) 2, no. 4 (2011): 1/9. https://doi.org/10.5121/ijgca.2011.2401.

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<strong>Abstract </strong> In economic Grid environments, the producers (resource owners) and consumers (resource users) have different goals, objectives, strategies, and supply-and-demand patterns. Mechanism based on economic models is an effective approach to solve the problem of grid resources management. Grid resource valuation and allocation is one of the fundamental problems in grid resource management. The essence of this problem is how to allocate and valuation resources for achieving the goal of a highly efficient utilization of resources in response to current resource valuations. Pr

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Choi, Joung-Min, Jihyeon Kim, HyunKyung Choo, Chaelin Park, and Heejoon Chae. "Machine Learning-based Agricultural Genetic Resources Analysis Platform." KIISE Transactions on Computing Practices 28, no. 1 (2022): 57–62. http://dx.doi.org/10.5626/ktcp.2022.28.1.57.

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Lengkong, Naijan. "Development of Historical Learning Resources Based on Novel." American Journal of Educational Research 6, no. 3 (2018): 258–61. http://dx.doi.org/10.12691/education-6-3-12.

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Chang, Chen-Chi, Ay Jong, and Fu-Chang Huang. "Using Electronic Resources to Support Problem-Based Learning." Journal of Educational Computing Research 46, no. 2 (2012): 195–206. http://dx.doi.org/10.2190/ec.46.2.e.

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Headmaster, Geoffrey Howarth. "Book Reviews : Resources Based Learning for School Governors." Educational Management & Administration 13, no. 3 (1985): 220–22. http://dx.doi.org/10.1177/174114328501300314.

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Shu, Jiangbo, Xiaoxuan Shen, Hai Liu, Baolin Yi, and Zhaoli Zhang. "A content-based recommendation algorithm for learning resources." Multimedia Systems 24, no. 2 (2017): 163–73. http://dx.doi.org/10.1007/s00530-017-0539-8.

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Polly, Drew. "Teachers' learning while constructing technology-based instructional resources." British Journal of Educational Technology 42, no. 6 (2011): 950–61. http://dx.doi.org/10.1111/j.1467-8535.2010.01161.x.

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Boehnstedt, Doreen. "Semantic tagging for managing web-based learning resources." ACM SIGMultimedia Records 3, no. 3 (2011): 13–14. http://dx.doi.org/10.1145/2069210.2069212.

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Allen, Rodney F. "Bibliographic Resources for School-Based Community Service Learning." Social Studies 88, no. 5 (1997): 220–24. http://dx.doi.org/10.1080/00377999709603782.

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Messnarz, Richard, Damjan Ekert, Michael Reiner, and Gearoid O'Suilleabhain. "Human resources based improvement strategies-the learning factor." Software Process: Improvement and Practice 13, no. 4 (2008): 355–62. http://dx.doi.org/10.1002/spip.397.

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Cheng, Wen-wen, Su-ching Lin, and Ming-sui Wu. "Evaluating Self-access Learning in Online Resource-based Context." Journal of Social Science Studies 3, no. 1 (2015): 168. http://dx.doi.org/10.5296/jsss.v3i1.8238.

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<p>For the past two decades, language center in almost every university in Taiwan has attempted to implement the notion of independent learning through online learning resources. To many student learners, the easy and inexpensive access of Internet has made innumerable learning resources provided by language centers available for self-access language learning. However, whether students have cultivated self-access learning ability through appropriate learning practices online is the main point that school authorities are eager to find out. In order to know the effectiveness of self-access

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Derkach, T. M. "ICT-based assessment of cognitive load in chemistry learning." Journal of Physics: Conference Series 2288, no. 1 (2022): 012016. http://dx.doi.org/10.1088/1742-6596/2288/1/012016.

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Abstract The article is devoted to studying and preventing an excessive increase in the cognitive load of university students studying chemistry using various electronic resources. The experiment involved 49 third-year students of the Faculty of Chemistry who studied organic chemistry. A homemade software was developed to measure the level of cognitive load using the secondary problem method. Cognitive load levels were studied depending on the types of used electronic resources. The studied resource types are texts of different levels of complexity, audio and visual materials in different comb

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