Bibliografías temáticas / Approaches to learning

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Literatura académica sobre el tema "Approaches to learning"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Approaches to learning"

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Urhahne, Detlef. "Learning approaches." Educational Psychology 40, no. 5 (2020): 533–34. http://dx.doi.org/10.1080/01443410.2020.1755503.

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Wiltshire, Monica. "Approaches to learning." Early Years Educator 17, no. 11 (2016): 28–30. http://dx.doi.org/10.12968/eyed.2016.17.11.28.

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Shivaleela, Barawade, Ingole Nishikant, Dahiwele Akshay, and Kokati Drakshayini. "A Study of Learning Approaches in Undergraduate Medical Students." International Journal of Toxicological and Pharmacological Research 13, no. 1 (2023): 38–45. https://doi.org/10.5281/zenodo.11301924.

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<strong>Introduction:</strong>&nbsp;One among various methods adopted by students in the process of seeking knowledge is a learning approach. Learning approach of students will be of concern to the teachers and medical education experts.&nbsp;<strong>Methods:</strong>&nbsp;Total 155 second year MBBS students were included for study, out of which&nbsp; 143 students were participated in the study. A preformed proforma was prepared for the study which includes demographic details of the student and a R-SPQ-2F questionnaire. SPSS software was used to analysed the data. Outcome variables were descr
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Madeleine, Kapinga-Mutatayi, Mukendi waMpoyi Pierre, and Jan Elen. "Students Approaches to Learning: Towards a Context-specific Learning Approaches Instrument." International Journal of Higher Education 12, no. 3 (2023): 68. http://dx.doi.org/10.5430/ijhe.v12n3p68.

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Students' Approaches to Learning (SAL) are a critical determinant of learning outcomes and have been assessed around the world, from Asia to Africa, using the traditional questionnaires developed in the Western context. However, studies in Asia have challenged the traditional dichotomous view of SAL by supporting the presence of intermediate approaches, suggesting that the current view of SAL may not be universal. In response to the need for a broader understanding of SAL, a new instrument, the Approaches to Learning Questionnaire (ALQ), was developed during a pilot study. This instrument capt
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Jain, Migul. "Machine Learning and Deep Learning Approaches for Cybersecurity: A Review." International Journal of Science and Research (IJSR) 12, no. 10 (2023): 1706–10. http://dx.doi.org/10.21275/sr231023115126.

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Axatovna, Safina Farida. "LANGUAGE LEARNING AND LANGUAGE TEACHING APPROACHES." American Journal of Philological Sciences 4, no. 3 (2024): 43–45. http://dx.doi.org/10.37547/ajps/volume04issue03-08.

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The evolution of modern language teaching and learning can be traced back to the 20th century, a time when travel by land, sea, and air became more accessible to a larger portion of the population. Initially limited to Europe and North America, travel eventually expanded globally,allowing people from all continents to explore foreign lands. This accessibility marked a departure from the exclusive domain of pilgrims, explorers, and the wealthy, making foreign travel achievable for the majority in developed nations. Additionally, advancements such as the discovery of electricity and wireless com
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Franţuzan, Ludmila, Ina Grigor, and Cristina Straistari-Lungu. "Effective school learning: conceptual and methodological approaches." Univers Pedagogic 2, no. 66 (2020): 21–31. https://doi.org/10.5281/zenodo.4090444.

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This article examines and defines the concept of learning. The dimensions of the learning process are presented: the cognitive, emotional and social dimension and the contemporary models of learning are examined: associationist, constructivist, as information processing. It was found that the examined learning models explain the learning process from the perspective of cognitive and partially social dimensions, and the affective dimension is not addressed. So learning is approached as a specific process, only on the cognitive dimension, so it is necessary to make some changes in the educationa
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Duff, Angus, and Sam McKinstry. "Students' Approaches to Learning." Issues in Accounting Education 22, no. 2 (2007): 183–214. http://dx.doi.org/10.2308/iace.2007.22.2.183.

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This paper provides an overview of the students' approaches to learning (SAL) literature, including a review of the models, theories, and research instruments. SAL research has developed largely in the United Kingdom and Australasia, where its concepts are widely understood by academics. Yet little research using these ideas has been done in North America. To encourage American accounting educators to redress this imbalance, the paper describes the motivations for undertaking SAL research, describes conceptions of learning, and reviews a number of inventories developed by SAL scholars for appl
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Wasson, Barbara, and Paul A. Kirschner. "Learning Design: European Approaches." TechTrends 64, no. 6 (2020): 815–27. http://dx.doi.org/10.1007/s11528-020-00498-0.

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Abstract Research on instructional and learning design is ‘booming’ in Europe, although there has been a move from a focus on content and the way to present it in a formal educational context (i.e., instruction), to a focus on complex learning, learning environments including the workplace, and access to learner data available in these environments. We even see the term ‘learning experience design’ (Neelen and Kirschner 2020) to describe the field. Furthermore, there is an effort to empower teachers (and even students) as designers of learning (including environments and new pedagogies), and t
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Albergaria-Almeida, Patrícia, José Joaquim Teixeira-Dias, Mariana Martinho, and Chinthaka Balasooriya. "Kolb’s Learning Styles and Approaches to Learning." International Journal of Knowledge Society Research 1, no. 3 (2010): 1–16. http://dx.doi.org/10.4018/jksr.2010070101.

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The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades.This study took place during the 1st semester of the school year 2009/2010. This research was carried out in a naturalistic setting, within the context of chemistry classes for 1st year science and engineering courses, at the University of Aveiro,
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Tesis sobre el tema "Approaches to learning"

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Potari, Despina. "Learning approaches in mathematics." Thesis, University of Edinburgh, 1987. http://hdl.handle.net/1842/12130.

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Hussein, Ahmed. "Deep learning based approaches for imitation learning." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3117.

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Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for intelligent applications. The goal of imitation learning is to describe the desired behaviour by providing demonstrations rather than instructions. This enables agents to learn complex behaviours with general learning methods that require minimal task specific information. However, imitation learning faces many challenges. The objective of this thesis
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Effraimidis, Dimitros. "Computation approaches for continuous reinforcement learning problems." Thesis, University of Westminster, 2016. https://westminsterresearch.westminster.ac.uk/item/q0y82/computation-approaches-for-continuous-reinforcement-learning-problems.

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Optimisation theory is at the heart of any control process, where we seek to control the behaviour of a system through a set of actions. Linear control problems have been extensively studied, and optimal control laws have been identified. But the world around us is highly non-linear and unpredictable. For these dynamic systems, which don’t possess the nice mathematical properties of the linear counterpart, the classic control theory breaks and other methods have to be employed. But nature thrives by optimising non-linear and over-complicated systems. Evolutionary Computing (EC) methods exploit
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Chang, Yu-Han Ph D. Massachusetts Institute of Technology. "Approaches to multi-agent learning." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33932.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Includes bibliographical references (leaves 165-171).<br>Systems involving multiple autonomous entities are becoming more and more prominent. Sensor networks, teams of robotic vehicles, and software agents are just a few examples. In order to design these systems, we need methods that allow our agents to autonomously learn and adapt to the changing environments they find themselves in. This thesis explores ideas from game theory, online prediction, and reinforcement learning,
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Flaherty, Drew. "Artistic approaches to machine learning." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/200191/1/Drew_Flaherty_Thesis.pdf.

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This research is about how Artificial Intelligence and Machine Learning may impact creative practice. The thesis looks at various implementations and models related to the subject from different cultural and technical viewpoints. The project also provides experimental creative outcomes from my personal practice along with a qualitative study into attitudes and perspectives from other creative practitioners.
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Yu, Kai. "Statistical Learning Approaches to Information Filtering." Diss., lmu, 2004. http://nbn-resolving.de/urn:nbn:de:bvb:19-25120.

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Kashima, Hisashi. "Machine learning approaches for structured data." 京都大学 (Kyoto University), 2007. http://hdl.handle.net/2433/135953.

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Chen, Zhe Haykin Simon S. "Stochastic approaches for correlation-based learning." *McMaster only, 2004.

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Boots, Byron. "Spectral Approaches to Learning Predictive Representations." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/131.

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A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must obtain an accurate environment model, and then plan to maximize reward. However, for complex domains, specifying a model by hand can be a time consuming process. This motivates an alternative approach: learning a model directly from observations. Unfortunately, learning algorithms often recover a model that is too inaccurate to support planning or too large and complex for planning to succeed; or, they require excessive prior domain knowledge
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Fu, I.-Ping P. "Student Approaches to Learning Chinese Vocabulary." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/25955.

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This research focuses on the strategies that native English speakers use as they learn to speak and write Chinese vocabulary words in the first year of an elementary Chinese class. The main research question was: what strategies do native English-speaking beginning learners of Chinese use to learn Chinese vocabulary words in their speaking and writing? The study was conducted at a medium-sized comprehensive university in the Southeastern U.S. The study drew from concepts and theories in second language acquisition and psycholinguistic studies. A random sampling of four students was select
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Libros sobre el tema "Approaches to learning"

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Stobie, Tristian D. Approaches to learning. European Council of International Schools., 1997.

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Staveley-Taylor, Helen. Further approaches to learning. Films for the Humanities & Sciences, 2003.

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Harteis, Christian, David Gijbels, and Eva Kyndt, eds. Research Approaches on Workplace Learning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89582-2.

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Cutting, Roger, and Rowena Passy, eds. Contemporary Approaches to Outdoor Learning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85095-1.

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Touretzky, David, ed. Connectionist Approaches to Language Learning. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4008-3.

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Kueker, David W., and Carl H. Smith, eds. Learning and Geometry: Computational Approaches. Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-4088-4.

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Touretzky, David. Connectionist Approaches to Language Learning. Springer US, 1991.

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Kim, Reid D., Hresko Wayne P, and Swanson H. Lee 1947-, eds. Cognitive approaches to learning disabilities. 3rd ed. Pro-Ed, 1996.

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1943-, Kueker D. W., and Smith Carl H. 1950-, eds. Learning and geometry: Computational approaches. Birkhäuser, 1996.

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S, Touretzky David, ed. Connectionist approaches to language learning. Kluwer Academic Publishers, 1991.

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Capítulos de libros sobre el tema "Approaches to learning"

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Singh, Nirbhay N., Diane E. D. Deitz, and Judy Singh. "Behavioral Approaches." In Learning Disabilities. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4613-9133-3_13.

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Kim, Rina, and Lillie R. Albert. "Methodological Approaches." In Mathematics Teaching and Learning. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13542-7_3.

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Hengst, Bernhard. "Hierarchical Approaches." In Adaptation, Learning, and Optimization. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27645-3_9.

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Daelemans, Walter. "Machine Learning Approaches." In Text, Speech and Language Technology. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9273-4_17.

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Savin-Baden, Maggi, and David Burden. "Approaches to Learning." In The Metaverse for Learning and Education. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003413875-3.

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Yang, Ching-Chi, and Lih-Yuan Deng. "Statistical Learning Approaches." In Dimensionality Reduction in Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05371-9_8.

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Venugopal, Deepak, and Max Garzon. "Machine Learning Approaches." In Dimensionality Reduction in Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05371-9_9.

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Abbott, Tina. "Social learning approaches." In Social and Personality Development. Routledge, 2021. http://dx.doi.org/10.4324/9781003209300-6.

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Liu, Han, Alexander Gegov, and Mihaela Cocea. "Ensemble Learning Approaches." In Studies in Big Data. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23696-4_6.

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Misra, Pradeep Kumar. "Approaches to Learning." In Learning and Teaching for Teachers. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3077-4_2.

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Actas de conferencias sobre el tema "Approaches to learning"

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T, Dhakshnamoorthi, Giriraj M, Gokul S, and Vanitha K. "Novel Learning Approaches for Feature Representation and Classification Using Learning Approaches." In 2024 International Conference on Data Science and Network Security (ICDSNS). IEEE, 2024. http://dx.doi.org/10.1109/icdsns62112.2024.10690856.

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AlShaikh-Hasan, Mohammad, and Gheorghita Ghinea. "Predicting Student Performance Using Deep Learning and Machine Learning Techniques." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013240.

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Amer, Waleed, Ola Nasir, Ala Hamarsheh, Ali Mahmoud Ali, Amani Abu Zaid, and Walaa Shtayah. "A Comparative Study of Machine Learning and Deep Learning for Disaster Prediction." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013546.

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Mintii, Iryna. "Approaches to the Blended Learning Organisation." In International Conference on History, Theory and Methodology of Learning. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0012647500003737.

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Abbassi, Faten, Yousra Hlaoui, and Faouzi Ben Charrada. "Machine Learning for Ontology Alignment." In 20th International Conference on Evaluation of Novel Approaches to Software Engineering. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013425700003928.

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Siandri, Elpida, Zoi Kasapi, Efthimia Mavridou, Eleni Vrochidou, and George A. Papakostas. "Machine Learning in Employee Attrition." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013566.

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Dhrir, Hanen, Maha Charfeddine, and Habib Kammoun. "Advancing Network Anomaly Detection Using Deep Learning and Federated Learning in an Interconnected Environment." In 20th International Conference on Evaluation of Novel Approaches to Software Engineering. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013134100003928.

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Al-E'mari, Salam, Yousef Sanjalawe, Waleed Awwad, Hamzah Alqudah, and Mohammed Aladaileh. "Hybrid Transfer Learning and Deep Learning for Cloud Intrusion Detection Using Bio-Inspired Optimization." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11012952.

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Rathore, Saurabh Pratap Singh, Shristi Chamoli, Roy T P, Ajith Sundaram, Neeraj Varshney, and Vinod Sharma. "Deep Learning Approaches for Natural Language Understanding." In 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). IEEE, 2025. https://doi.org/10.1109/iatmsi64286.2025.10984753.

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Yıldız, Serdar, Abbas Memiş, and Songül Varlı. "An Ensemble Learning Based Nuclei Segmentation: Using Base Deep Learning Models with Different Loss Functions." In 2024 8th International Symposium on Innovative Approaches in Smart Technologies (ISAS). IEEE, 2024. https://doi.org/10.1109/isas64331.2024.10845426.

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Informes sobre el tema "Approaches to learning"

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Tucker, Jennifer S. Mobile Learning Approaches for U.S. Army Training. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada528742.

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Villavicencio, Xuzel, and Caitlin Coflan. Hybrid learning International experiences with multimodal approaches. EdTech Hub, 2022. http://dx.doi.org/10.53832/edtechhub.0112.

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Gress, Gabriel. Understanding machine learning approaches for partial differential equations. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1669073.

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Esen, Berivan, and Jonathan Wentworth. Remote sensing and machine learning. Parliamentary Office of Science and Technology, 2020. http://dx.doi.org/10.58248/pn628.

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There is increasing interest in using machine learning to automatically analyse remote sensing data and increase our understanding of complex environmental systems. While there are benefits from this approach, there are also some barriers to its use. This POSTnote examines the value of these approaches, and the technical and ethical challenges for wider implementation.
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Bhagavatula, Vijayakumar. Advanced Signal Processing and Machine Learning Approaches for EEG Analysis. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada535204.

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Tillett, Will, and Oliver Jones. ‘Improving Rural Sanitation in Challenging Contexts’ Sanitation Learning Hub Learning Brief 8. The Sanitation Learning Hub, Institute of Development Studies, 2021. http://dx.doi.org/10.19088/slh.2021.006.

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Of the two billion people worldwide lacking access to at least basic sanitation, seven out of ten live in rural areas. Progress has been made on increasing rural sanitation and access levels are rising, but barriers remain in reaching the ‘last mile’ or some 10 to 20 per cent of the population who live in the most challenging contexts. The factors affecting the ability of households to construct and use toilets, as well as the challenges sanitation programmes face in reaching specific groups, are highly diverse. Applying one-size fits all approaches has been proven not to work; therefore, we n
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Näslund-Hadley, Emma. Acceleration of Education and Learning. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005072.

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In Latin America and the Caribbean (LAC), significant proportions of students struggle to attain basic competencies in reading and mathematics. To address this issue, traditional practices like grade repetition are prevalent, leading to delayed access to grade-level education and overcrowded classrooms. However, emerging research challenges the effectiveness of this approach. Instead, an innovative solution gaining traction is Accelerated Learning, rooted in neuroscience and psychology. It emphasizes learner-centered pedagogy, socioemotional development, and collaboration with families. EdTech
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Christie, Lorna. Interpretable machine learning. Parliamentary Office of Science and Technology, 2020. http://dx.doi.org/10.58248/pn633.

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Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that in some cases it may not be possible to explain completely how its outputs have been produced. This POSTnote gives an overview of ML and its role in decision-making. It examines the challenges of understanding how a complex ML system has reached its output, and some of the technical approaches to making ML easier to interpret. It also gives a brief overview
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Wheeler, Travis. Machine learning approaches for integrating multi-omics data to expand microbiome annotation. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2331432.

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Kaffenberger, Michelle, Jason Silberstein, and Marla Spivack. Evaluating Systems: Three Approaches for Analyzing Education Systems and Informing Action. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-rise-wp_2022/093.

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While conventional interventions and evaluations address the symptoms of the learning crisis, there is growing acknowledgement that widespread and sustained learning improvements will require systems approaches that diagnose and address the root causes of low learning. This paper presents and applies three methods to evaluate education systems and inform how to improve system coherence for learning. First, we use learning trajectories to evaluate the dynamics of children’s learning in 22 low- and middle-income countries. Second, we present a set of principles called the ALIGNS principles and s
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