Relevant bibliographies by topics / Learning-based resources

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Learning-based resources'

Author: Grafiati
Published: 7 September 2021
Last updated: 29 July 2025

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Journal articles on the topic "Learning-based resources"

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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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Dissertations / Theses on the topic "Learning-based resources"

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Henze, Nicola. "Adaptive hyperbooks: adaptation for project-based learning resources." [S.l. : s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=959579044.

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Nganji, Julius Tanyu. "Ontology-based personalisation of e-learning resources for disabled students." Thesis, University of Hull, 2015. http://hydra.hull.ac.uk/resources/hull:13604.

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Students with disabilities are often expected to use e-learning systems to access learning materials but most systems do not provide appropriate adaptation or personalisation to meet their needs. The difficulties related to inadaptability of current learning environments can now be resolved using semantic web technologies such as web ontologies which have been successfully used to drive e-learning personalisation. Nevertheless, e-learning personalisation for students with disabilities has mainly targeted those with single disabilities such as dyslexia or visual impairment, often neglecting tho
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Scholl, Philipp [Verfasser], Ralf [Akademischer Betreuer] Steinmetz, and Wolfgang [Akademischer Betreuer] Effelsberg. "Semantic and Structural Analysis of Web–based Learning Resources - Supporting Self–directed Resource–based Learning / Philipp Scholl. Betreuer: Ralf Steinmetz ; Wolfgang Effelsberg." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2011. http://d-nb.info/1105562719/34.

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Kiaian, Mousavy Sayyed Ali. "A learning based workflow scheduling approach on volatile cloud resources." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-282528.

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Workflows, originally from the business world, provide a systematic organization to an otherwise chaotic complex process. Therefore, they have become dominant and popular in scientific computation, where complex and broadscale data analysis and scientific automation are required. In recent years, demand for reliable algorithms for workflow optimization problems, mainly scheduling and resource provisioning have grown considerably. There are various algorithms and proposals to optimize these problems. However, most of these provisioning and algorithms do not account for reliability and robustnes
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Lemanski, Tomasz Marek. "Exploring models of work-based learning in the chemical and related industries." Thesis, University of Hull, 2013. http://hydra.hull.ac.uk/resources/hull:7086.

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The term work-based learning is widely used throughout the literature, academia and industry to describe a multiplicity of approaches by which one can learn through work. This thesis focuses on the rationale for conducting work-based learning and blended learning. Qualitative data was gathered from questionnaires with students and interviews with students, industry champions, course developers and employers. The results show that effective work-based learning is not the simple implementation of one single model or single tool, but rather a negotiated approach to the students’ learning which ta
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Sadik, Alaa M. "The design, implementation and evaluation of a web-based learning environment for distance education." Thesis, University of Hull, 2002. http://hydra.hull.ac.uk/resources/hull:8533.

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In this study, the need was emphasised to investigate the effects of using the Web in teaching students at a distance using a multi-level evaluation framework. A Web-based learning environment was designed, developed, implemented and evaluated for this purpose. Constructivist epistemology provided the basis for developing various components and developing problem-centred and interactive activities. Management, tutorial, interaction and support components were designed to work with each other to construct the learning environment, deliver course content, facilitate interaction and monitor stude
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Hammami, Seif Eddine. "Dynamic network resources optimization based on machine learning and cellular data mining." Thesis, Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0015/document.

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Les traces réelles de réseaux cellulaires représentent une mine d’information utile pour améliorer les performances des réseaux. Des traces comme les CDRs (Call detail records) contiennent des informations horodatées sur toutes les interactions des utilisateurs avec le réseau sont exploitées dans cette thèse. Nous avons proposé des nouvelles approches dans l’étude et l’analyse des problématiques des réseaux de télécommunications, qui sont basé sur les traces réelles et des algorithmes d’apprentissage automatique. En effet, un outil global d’analyse de données, pour la classification automatiqu
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Hammami, Seif Eddine. "Dynamic network resources optimization based on machine learning and cellular data mining." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0015.

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Les traces réelles de réseaux cellulaires représentent une mine d’information utile pour améliorer les performances des réseaux. Des traces comme les CDRs (Call detail records) contiennent des informations horodatées sur toutes les interactions des utilisateurs avec le réseau sont exploitées dans cette thèse. Nous avons proposé des nouvelles approches dans l’étude et l’analyse des problématiques des réseaux de télécommunications, qui sont basé sur les traces réelles et des algorithmes d’apprentissage automatique. En effet, un outil global d’analyse de données, pour la classification automatiqu
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Crause, Ewald. "The effect of using a computer-based exploration tool on children's career development learning." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1015020.

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Historically the process of career development was thought of as occurring in adolescence and adulthood; however, the renewed emphasis on lifelong career development has led to a greater focus on the career developmental stage of childhood. The present research focused on the development and trialling of a research-based computerised career exploration tool, Growing-up: Children Building Careers™ (GCBC™) that can be used for early intervention in children‘s career development. The integration of developmental considerations within a career developmental context is of paramount importance, cons
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Rahman, M. Mostafizur. "Machine learning based data pre-processing for the purpose of medical data mining and decision support." Thesis, University of Hull, 2014. http://hydra.hull.ac.uk/resources/hull:10103.

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Building an accurate and reliable model for prediction for different application domains, is one of the most significant challenges in knowledge discovery and data mining. Sometimes, improved data quality is itself the goal of the analysis, usually to improve processes in a production database and the designing of decision support. As medicine moves forward there is a need for sophisticated decision support systems that make use of data mining to support more orthodox knowledge engineering and Health Informatics practice. However, the real-life medical data rarely complies with the requirement
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Books on the topic "Learning-based resources"

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R, Woods Donald. Problem based learning: resources to gain the most from PBL. 2nd ed. McMaster University, 1997.

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Ferrer, Elmer M. Learning and working together: Towards a community-based coastal resources management. Research and Extension for Development Office, College of Social Work and Community Development, University of the Philippines, 1992.

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NATO Advanced Research Workshop on Instructional Models in Computer-Based Learning Environments (1991 University of Twente). Instructional models in computer-based learning environments. Springer-Verlag, 1992.

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Ullrich, Carsten. Pedagogically founded courseware generation for web-based learning: An HTN-planning-based approach implemented in PAIGOS. Springer, 2008.

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Ullrich, Carsten. Pedagogically founded courseware generation for web-based learning: An HTN-planning-based approach implemented in PAIGOS. Springer, 2008.

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Wong, Rosalia. Web-based learning and teaching and its educational worth. Equilibrium Books, 2008.

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Kinch, Jeff. Learning together: Participatory tools for community engagement : Milne Bay community-based coastal and marine conservation program. Conservation International, 2002.

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Nicol, Jacqui. Directory of resources for computer based learning in land use and environmental sciences. 3rd ed. CTI Centre for Land Use and Environmental Sciences, University of Aberdeen, 1994.

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Cowles, Susan. Teaching and learning with Internet-based resources: A set of lesson plans and activities. National Institute for Literacy, 1997.

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National Institute for Literacy (U.S.), ed. Teaching and learning with Internet-based resources: A set of lesson plans and activities. National Institute for Literacy, 1997.

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Book chapters on the topic "Learning-based resources"

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Bohland, Mark A., and Stephanie O’Shaughnessy. "Other Teacher Resources." In Problem-Based Learning Mystery Disease. Routledge, 2021. http://dx.doi.org/10.4324/9781003236818-19.

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Purcell, Jeanne H., Deborah E. Burns, and Wellesley H. Purcell. "Finding and Managing Resources." In The Interest-Based Learning Coach. Routledge, 2021. http://dx.doi.org/10.4324/9781003238843-9.

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Mandanici, Marcella, Simone Spagnol, Luca Andrea Ludovico, Adriano Baratè, and Federico Avanzini. "Learning Theories and Technology-Based Learning Approaches." In Digital Music Learning Resources. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4206-0_2.

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Stanley, Todd. "Technology, Resources, and Classroom Environment." In Project-Based Learning for Gifted Students, 2nd ed. Routledge, 2021. http://dx.doi.org/10.4324/9781003237310-9.

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Gavrilova, Tatiana, Vladimir Gorovoy, and Elena Petrashen. "Learning Resources Organization Using Ontological Framework." In Advances in Web Based Learning – ICWL 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03426-8_20.

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Zhu, Hongming, Xiangfeng Luo, Zheng Xu, and Jun Zhang. "Association Link Network: An Incremental Web Resources Link Model for Learning Resources Management." In Advances in Web-Based Learning - ICWL 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25813-8_35.

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Yang, Haojin, Franka Grünewald, Matthias Bauer, and Christoph Meinel. "Lecture Video Browsing Using Multimodal Information Resources." In Advances in Web-Based Learning – ICWL 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41175-5_21.

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Wang, Jun, Junfu Xiang, and Kanji Uchino. "Topic-Specific Recommendation for Open Education Resources." In Advances in Web-Based Learning -- ICWL 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25515-6_7.

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Wang, Zhitao, Chengyao Chen, and Wenjie Li. "Information Diffusion Prediction Based on Social Representation Learning with Group Influence." In Chinese Language Resources. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38913-9_31.

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Kommers, Piet A. M., and Alcindo Ferreira. "(S)GML-based hypermedia: Generic resources for exploratory learning." In Instructional Models in Computer-Based Learning Environments. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-02840-7_21.

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Conference papers on the topic "Learning-based resources"

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Wang, Yan, Li Chen, and Caihua Qiu. "Deep Reinforcement Learning-based Recommendation System for Ideological and Political Curriculum Learning Resources." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10941307.

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Zhang, Yuanwei, and Haixia Cui. "Optimization of Air Network Resources Based on Deep Reinforcement Learning." In 2024 4th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE). IEEE, 2024. http://dx.doi.org/10.1109/mlise62164.2024.10674492.

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Dhote, Sunita, Chandan Vichoray, Vishakha Mankar, and Rajas Dhote. "STEM-Based AR Physics Assisted Resources in Smart Learning System." In 2024 International Conference on Emerging Research in Computational Science (ICERCS). IEEE, 2024. https://doi.org/10.1109/icercs63125.2024.10895695.

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Mondal, Sonali, and Lalnunthari. "Reinforcement Learning-Based Adaptive Utilization of Resources in Cloud Networks." In 2025 International Conference on Intelligent Control, Computing and Communications (IC3). IEEE, 2025. https://doi.org/10.1109/ic363308.2025.10957566.

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Chen, Xuedong. "Dynamic scheduling algorithm for container resources based on reinforcement learning." In International Conference on Machine Vision and Deep Learning (MVDL 2025), edited by Chengzhong Xu and Dickson K. W. Chiu. SPIE, 2025. https://doi.org/10.1117/12.3071443.

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Shi, Hui. "Intelligent Recommendation Algorithm for Online Learning Resources Based on Recommendation System." In 2025 Asia-Europe Conference on Cybersecurity, Internet of Things and Soft Computing (CITSC). IEEE, 2025. https://doi.org/10.1109/citsc64390.2025.00106.

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Alanssari, Ali Ihsan, Jawad Radhi Rustum Al-Assal, Ahmad Hussein Hassan, Hussain Myassar, and Rozhgar Khorsheed Mahmud. "Integrating Smart Learning-Based Digital Resources for Teaching Contemporary and Modern." In 2024 International Conference on Emerging Research in Computational Science (ICERCS). IEEE, 2024. https://doi.org/10.1109/icercs63125.2024.10894955.

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Xu, Li. "Research on Optimal Allocation of Educational Resources Based on Deep Learning." In 2025 4th International Symposium on Computer Applications and Information Technology (ISCAIT). IEEE, 2025. https://doi.org/10.1109/iscait64916.2025.11010300.

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Gao, Xian, Peixiong He, Yi Zhou, and Xiao Qin. "Limited Resources Usage of Deep-Learning-Based IoT Devices in Healthcare." In 2024 IEEE 2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings). IEEE, 2024. https://doi.org/10.1109/aibthings63359.2024.10863456.

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"Designing Mini-Games for Micro-Learning: Open Educational Resources on Cultural Risks in Multi-Cultural Organisations." In 13th EuropeanConference on Game Based Learning. ACI, 2020. http://dx.doi.org/10.34190/gbl.20.013.

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Reports on the topic "Learning-based resources"

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Iwatani, Emi, Barbara Means, Maria R. Romero, and Mai Chou Vang. Deepening Science Engagement With Challenge Based Learning: Research Report. Digital Promise, 2020. http://dx.doi.org/10.51388/20.500.12265/93.

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Learn about the Challenge Based Science Learning Project and its larger implications for the fields of Next Generation Science Learning and Open Educational Resources. The project involved 18 middle school teachers and five administrators from three U.S. school districts partnering with instructional coaches and learning sciences researchers from Digital Promise to address an ambitious educational challenge: How might we deepen engagement and learning of middle school science in our schools and beyond?
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Gavryliuk, Olga. Comparison of available cloud-based learning technologies for the preparation of Bachelor of Statistics. RVV TSDPU im. V. Vynnychenka, 2019. https://doi.org/10.33407/lib.naes.id/eprint/717067.

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In the article the conceptual-terminological apparatus of the research is presented, such concepts as cloud technologies, cloud services, technologies of training, cloud-oriented learning technologies, competence, professional competence are considered. The advantages of cloud technologies, which consist of the dynamism of the provision of computing resources and software-hardware, the ability to customize it to personal usage needs. Besides, access to multi-sectoral e-learning resources may be provided on a specially set cloud server or placed on other electronic data carriers that are access
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Valko, Nataliia V., Viacheslav V. Osadchyi, and Vladyslav S. Kruhlyk. Cloud resources use for students' project activities. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4444.

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The modern educational system proclaims learning aimed at acquiring practical skills and based on the activity approach. Educational research projects are the necessary component of curricula in physics, computer science, biology and chemistry. There is a problem of specialized equipment and facilities using for the implementation of such projects in distance learning. Therefore, the issue of cloud resources using for distance learning organization in robotics is relevant. The article presents a brief overview of the current state of projects development in Ukrainian schools and approaches use
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Neroda, Tetyana V., Lidia V. Slipchyshyn, and Ivan O. Muzyka. Adaptive toolkit of branch-oriented workshop environment for enlargement the cloud-based e-learning media platform. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4449.

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The ways of providing comprehensive efficiency increase in communication facilities of the academic space are given with regard to stipulated methods of managing distributed network resources. Selected the user interfaces types are distinguished according to user actions in the studied subject area, which made it possible to justify and hierarchically organize the categories of adaptive toolkit of the branch- oriented workshop environment by the classes of components declared in the project, which are closely related to the scheme of learning experiment and are basic means for simulating trans
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Попель, Майя Володимирівна, Світлана Вікторівна Шокалюк, and Марія Павлівна Шишкіна. The Learning Technique of the SageMathCloud Use for Students Collaboration Support. CEUR Workshop Proceedings, 2017. http://dx.doi.org/10.31812/0564/1076.

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The article describes the advisable ways of the cloud-based systems use to support students’ collaboration in the process of math disciplines learning. The SageMathCloud-based component that aggregates electronic resources for several math disciplines training is introduced. The learning technique of the SageMathCloud use in the process of educational staff training is proposed. The expediency of this technique implementation for more active take up of innovative approaches, forms and methods of math training with the use of the cloud-based tools is substantiated. The experimental results of t
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Papadakis, Stamatios, Арнольд Юхимович Ків, Hennadiy M. Kravtsov, et al. Revolutionizing education: using computer simulation and cloud-based smart technology to facilitate successful open learning. Криворізький державний педагогічний університет, 2023. http://dx.doi.org/10.31812/123456789/7375.

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The article presents the proceedings of two workshops: Cloud-based Smart Technologies for Open Education Workshop (CSTOE 2022) and Illia O. Teplytskyi Workshop on Computer Simulation in Education (CoSinE 2022) held in Kyiv, Ukraine, on December 22, 2022. The CoSinE workshop focuses on computer simulation in education, including topics such as computer simulation in STEM education, AI in education, and modeling systems in education. The CSTOE workshop deals with cloud-based learning resources, platforms, and infrastructures, with topics including personalized learning and research environment d
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Darling-Hammond, Kia, and Linda Darling-Hammond. The civil rights road to deeper learning. Learning Policy Institute, 2022. http://dx.doi.org/10.54300/462.143.

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This brief describes the key civil rights foundations that have been—and continue to be—essential to paving a path toward possibilities for deeper learning for all: those that secure safe communities, adequate school resources, inclusive environments, well-prepared teachers, and access to quality curriculum. It identifies the evidence-based policies and practices that can ensure that every student has access to a high-quality education focused on meaningful learning.
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Fusco, Judi, Sarah DiMaria, Beverly Yeadon, Janet Kolodner, and Alison Shell. Assessment During Collaborative Learning. Digital Promise, 2025. https://doi.org/10.51388/20.500.12265/252.

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Abstract:
This primer explores assessment during collaborative learning, shifting the focus from traditional summative evaluation to ongoing formative assessment for learning. It addresses key questions regarding what should be assessed, individual knowledge, group dynamics, collaborative skills, or both; and how assessments can be designed to align with learning objectives. The document outlines effective practices for incorporating self- and peer-assessment to empower students and provides guidance on delivering meaningful feedback. It discusses the importance of balancing individual and group assessm
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Gavryliuk, Olga. The use of cloud-based learning technologies to shape the professional competencies of future bachelors of statistics: a conceptual terminology research tool. National Pedagogical Dragomanov University, 2019. https://doi.org/10.33407/lib.naes.id/eprint/715382.

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In the article the conceptual-terminological apparatus of the research is presented, such concepts as cloud technologies, cloud services, technologies of training, cloud-oriented learning technologies, competence, professional competence are considered. The advantages of cloud technologies, which consist of the dynamism of the provision of computing resources and software-hardware, the ability to customize it to personal usage needs. Besides, access to multi-sectoral e-learning resources may be provided on a specially set cloud server or placed on other electronic data carriers that are access
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Chuulu, Yvonne M., Smith K. Bweupe, Ing’utu A. Kalumiana, Barbara M. Kasonde, and Mathews Musonda. Increasing Access to Open Schooling through an e-Learning Intervention: A Case Study from Zambia. Edited by Tony Mays. Commonwealth of Learning (COL), 2023. http://dx.doi.org/10.56059/11599/5223.

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During 2019–21, the Ministry of General Education in Zambia piloted an open and innovative schooling (OIS) programme. It used an e-learning model that involved developing and sharing curriculum-based open educational resources (OER) to supplement other teaching and learning processes. The resources could be accessed through both online and offline means. The programme was implemented in 15 centres that supported distance learners and five schools where traditional face-to-face learning took place. A tracer study was conducted among learners, teachers and head teachers who participated in the p
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