Relevant bibliographies by topics / Collective learning

Contents

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

Academic literature on the topic 'Collective learning'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 January 2023

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Journal articles on the topic "Collective learning"

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Backström, Tomas. "Collective learning." Learning Organization 11, no. 6 (December 2004): 466–77. http://dx.doi.org/10.1108/09696470410548827.

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Fu, Wai‐Ki, Hing‐Po Lo, and Derek S. Drew. "Collective learning, collective knowledge and learning networks in construction." Construction Management and Economics 24, no. 10 (October 2006): 1019–28. http://dx.doi.org/10.1080/01446190500228258.

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Vengerov, Alexander. "Collective Learning and Collective Intelligence Working Together." International Journal of Learning: Annual Review 18, no. 2 (2011): 45–56. http://dx.doi.org/10.18848/1447-9494/cgp/v18i02/47500.

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Zhang, Hanwang, Xindi Shang, Huanbo Luan, Meng Wang, and Tat-Seng Chua. "Learning from Collective Intelligence." ACM Transactions on Multimedia Computing, Communications, and Applications 13, no. 1 (January 17, 2017): 1–23. http://dx.doi.org/10.1145/2978656.

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Forsyth, Lachlan, and Lynette Schaverien. "Re-presenting collective learning." ACM SIGGROUP Bulletin 24, no. 3 (December 2003): 25–31. http://dx.doi.org/10.1145/1052829.1052836.

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Novikov, Dmitry A. "COLLECTIVE LEARNING-BY-DOING." IFAC Proceedings Volumes 45, no. 11 (2012): 408–12. http://dx.doi.org/10.3182/20120619-3-ru-2024.00002.

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Sitkin, Sim B. "SHAPING COLLECTIVE COGNITION AND BEHAVIOR THROUGH COLLECTIVE LEARNING." Academy of Management Proceedings 2000, no. 1 (August 2000): B1—B6. http://dx.doi.org/10.5465/apbpp.2000.5535126.

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Fadul, Jose A. "Collective Learning: Applying Distributed Cognition for Collective Intelligence." International Journal of Learning: Annual Review 16, no. 4 (2009): 211–20. http://dx.doi.org/10.18848/1447-9494/cgp/v16i04/46223.

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Schechter, Chen. "Toward Communal Negotiation of Meaning in Schools: Principals’ Perceptions of Collective Learning from Success." Teachers College Record: The Voice of Scholarship in Education 113, no. 11 (November 2011): 2415–59. http://dx.doi.org/10.1177/016146811111301107.

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Background In light of the growing complexity of schoolwork, it is important that faculty members move away from isolated learning toward a more collective type of thinking regarding teaching and learning issues. Purpose Whereas collective learning has mostly been approached from a deficit-based orientation (finding/solving problems and overcoming failures), this study examines principals’ perceptions (mindscapes) about the notion and strategy of collective learning from faculty members’ successful practices. Research Design The study employed a qualitative topic-oriented methodology to explor
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Flack, Andrea, and Dora Biro. "Collective learning in route navigation." Communicative & Integrative Biology 6, no. 6 (November 9, 2013): e26521. http://dx.doi.org/10.4161/cib.26521.

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Dissertations / Theses on the topic "Collective learning"

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Holmquist, Mats. "Collective Learning in Innovative Networks." Högskolan i Halmstad, Regionalt lärande och ledarskap (RELL), 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-21771.

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There are different forms for boundary-crossing learning in and between organizations. One growing form is network. This paper will present a study of collective learning in two innovative networks at the west coast of Sweden. One network is about regional health and growth, the other about leadership development among general directors. Representatives from different organizations meet to learn from each other’s practice. How does this learning take place? What supports and what prevents it? Does it have any effects in their own organizations? Data has been collected through questionnaires, o
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Xiong, Liang. "On Learning from Collective Data." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/560.

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In many machine learning problems and application domains, the data are naturally organized by groups. For example, a video sequence is a group of images, an image is a group of patches, a document is a group of paragraphs/words, and a community is a group of people. We call them the collective data. In this thesis, we study how and what we can learn from collective data. Usually, machine learning focuses on individual objects, each of which is described by a feature vector and studied as a point in some metric space. When approaching collective data, researchers often reduce the groups into v
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Wu, Zhichao. "Modelling collective learning in conceptual design." Thesis, University of Strathclyde, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405494.

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Wang, Xi. "Learning Collective Behavior in Multi-relational Networks." Doctoral diss., University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6379.

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With the rapid expansion of the Internet and WWW, the problem of analyzing social media data has received an increasing amount of attention in the past decade. The boom in social media platforms offers many possibilities to study human collective behavior and interactions on an unprecedented scale. In the past, much work has been done on the problem of learning from networked data with homogeneous topologies, where instances are explicitly or implicitly inter-connected by a single type of relationship. In contrast to traditional content-only classification methods, relational learning succeeds
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Kim, Juho Ph D. Massachusetts Institute of Technology. "Learnersourcing : improving learning with collective learner activity." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101464.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages [199]-213).<br>Millions of learners today are watching videos on online platforms, such as Khan Academy, YouTube, Coursera, and edX, to take courses and master new skills. But existing video interfaces are not designed to sup
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Tödtling, Franz, Patrick Lehner, and Michaela Trippl. "Knowledge intensive industries, networks, and collective learning." Institut für Wirtschaftsgeographie, Abt. Stadt- und Regionalentwicklung, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/636/1/document.pdf.

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Knowledge has become a key source of competitiveness for advanced regions and nations, indicating a transformation of advanced capitalist economies towards "knowledge-based economies". Knowledge intensive sectors in production and in services have a lead in this respect, they can be considered as role models for the future. The innovation process, the mechanisms of knowledge exchange and the respective linkages in those industries differ quite markedly from those in other sectors. Clustering and local knowledge spillovers are frequently stated phenomena, although it is still unclear to what ex
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Richardson, Matthew. "Learning and inference in collective knowledge bases /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6926.

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Rhamachan, Molly. "Social movement learning: Collective,participatory learning within the jyoti jivanam movement of south Africa." University of the Western Cape, 2014. http://hdl.handle.net/11394/4401.

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Magister Educationis (Adult Learning and Global Change) - MEd(AL)<br>The purpose of this research paper is to explore and examine the nature of learning within the context of and situated within a social movement. Based on an exploratory qualitative study of learning within the Jyoti Jivanam Movement of South Africa, this research explores the nature and purpose/s of learning within a social movement. Accordingly, this study is guided by the research questions: How and why do adults learn as they collectively participate in social movements; and what factors facilitate, contribute, hinder and
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Gulcehre, Caglar. "Two Approaches For Collective Learning With Language Games." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613109/index.pdf.

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Recent studies in cognitive science indicate that language has an important social function. The structure and knowledge of language emerges from the processes of human communication together with the domain-general cognitive processes. Each individual of a community interacts socially with a limited number of peers. Nevertheless societies are characterized by their stunning global regularities. By dealing with the language as a complex adaptive system, we are able to analyze how languages change and evolve over time. Multi-agent computational simulations assist scientists from different disci
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Verri, Filipe Alves Neto. "Collective dynamics in complex networks for machine learning." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102018-113054/.

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Machine learning enables machines to learn automatically from data. In literature, graph-based methods have received increasing attention due to their ability to learn from both local and global information. In these methods, each data instance is represented by a vertex and is linked to other vertices according to a predefined affinity rule. However, they usually have unfeasible time cost for large problems. To overcome this problem, techniques can employ a heuristic to find suboptimal solutions in a feasible time. Early heuristic optimization methods exploit nature-inspired collective proces
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Books on the topic "Collective learning"

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Kassam, Tamiza A. Collective learning within nursing clinical groups. St. Catharines, Ont: Brock University, Faculty of Education, 2002.

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Steiner, Roy, and Duncan Hanks, eds. Harnessing the Power of Collective Learning. and Duncan Hanks.Description: New York, NY : Routledge, 2016.: Routledge, 2016. http://dx.doi.org/10.4324/9781315651248.

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Sanders, William R. Collective staff training in a virtual learning environment. Alexandria, Va: U.S. Army Research Institute for the Behavioral and Social Sciences, 2002.

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National Joint Committee on Learning Disabilities (U.S.), ed. Collective perspectives on issues affecting learning disabilities: Position papers and statements. Austin, Tex: Pro-Ed, 1994.

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Datta, Rukmini. Behind the scenes action: Learning from a collective process. New Delhi: Programme on Women's Economic Social and Cultural Rights, 2010.

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David, Keeble, and Wilkinson Frank, eds. High-technology clusters, networking, and collective learning in Europe. Aldershot , Hampshire, England: Ashgate, 2000.

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Rational herds: Economic models of social learning. Cambridge: Cambridge University Press, 2004.

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A, Lambert Judith, ed. Collective learning for transformational change: A guide to collaborative action. New York: Routledge, 2013.

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The emergence of artificial cognition: An introduction to collective learning. Singapore: World Scientific, 1993.

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Kafker, Frank A. The encyclopedists as a group: A collective biography of the authors of the Encyclopédie. Oxford: Voltaire Foundation, 1996.

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Book chapters on the topic "Collective learning"

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Hu, Angang. "Collective Learning." In China’s Collective Presidency, 73–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55279-3_5.

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Garavan, Thomas N., and Ronan Carbery. "Collective Learning." In Encyclopedia of the Sciences of Learning, 646–49. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_136.

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Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Collective Classification." In Encyclopedia of Machine Learning, 189–93. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_140.

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Hager, Paul, and Mary C. Johnsson. "Collective Learning Practice." In Professional and Practice-based Learning, 249–65. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4774-6_16.

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Hayes, John. "Facilitating collective learning." In The Theory and Practice of Change Management, 501–14. London: Macmillan Education UK, 2018. http://dx.doi.org/10.1057/978-1-352-00132-7_33.

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Boreham, Nick. "Competence as Collective Process." In Vocational Learning, 77–91. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1539-4_5.

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Namata, Galileo, Prithviraj Sen, Mustafa Bilgic, and Lise Getoor. "Collective Classification." In Encyclopedia of Machine Learning and Data Mining, 1–7. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-7502-7_44-1.

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Namata, Galileo, Prithviraj Sen, Mustafa Bilgic, and Lise Getoor. "Collective Classification." In Encyclopedia of Machine Learning and Data Mining, 238–42. Boston, MA: Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_44.

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Xynogala, Lydia. "Learning from Loutraki." In Architecture and Collective Life, 182–94. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003118985-19.

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Hayes, John. "Individual and collective learning." In The Theory and Practice of Change Management, 487–511. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-28902-5_29.

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Conference papers on the topic "Collective learning"

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Mittrick, Mark R., John Richardson, Mark Dennison, Theron Trout, Eric Heilman, and Timothy Hanratty. "Investigating immersive collective intelligence." In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, edited by Tien Pham. SPIE, 2019. http://dx.doi.org/10.1117/12.2519364.

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Chan, Rosanna Y. Y., Morris S. Y. Jong, Eric T. H. Luk, and Xueqi Zhang. "Dynamic Collective Mobile Gaming." In 2013 IEEE 13th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2013. http://dx.doi.org/10.1109/icalt.2013.145.

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Singh, Ajit P., and Geoffrey J. Gordon. "Relational learning via collective matrix factorization." In the 14th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1401969.

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Choi, Wongun, Khuram Shahid, and Silvio Savarese. "Learning context for collective activity recognition." In 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2011. http://dx.doi.org/10.1109/cvpr.2011.5995707.

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Liu, Zixuan, Michael Crosscombe, and Jonathan Lawry. "Imprecise Fusion Operators for Collective Learning." In The 2021 Conference on Artificial Life. Cambridge, MA: MIT Press, 2021. http://dx.doi.org/10.1162/isal_a_00407.

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Gea, Miguel, Rosana Montes Soldado, and Vanesa Gamiz. "Collective intelligence and online learning communities." In 2011 International Conference on Information Society (i-Society). IEEE, 2011. http://dx.doi.org/10.1109/i-society18435.2011.5978461.

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Dongwon Lee, Jaejeung Kim, and Howon Lee. "Collective intelligence based Collaborative Learning platform." In 2010 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2010. http://dx.doi.org/10.1109/ictc.2010.5674754.

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Chen, Xiaoyu, Jiangchao Yao, Yanfeng Wang, and Ya Zhang. "Online Learning Algorithm for Collective LDA." In 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). IEEE, 2015. http://dx.doi.org/10.1109/icmla.2015.177.

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Meza, Jaime, Oswaldo Ortiz, Ester Simó, and Joseph M. Monguet. "MEASURING THE COLLECTIVE INTELLIGENCE EDUCATION INDEX." In International Conference on Education and New Learning Technologies. IATED, 2017. http://dx.doi.org/10.21125/edulearn.2017.1647.

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Brennan, Riordan, and Debbie Perouli. "Generating and Evaluating Collective Concept Maps." In LAK22: 12th International Learning Analytics and Knowledge Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3506860.3506918.

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Reports on the topic "Collective learning"

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Singh, Ajit P., and Geoffrey J. Gordon. Relational Learning via Collective Matrix Factorization. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada486804.

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Sanders, William R. Collective Staff Training in a Virtual Learning Environment. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada400495.

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McGilvray, David H., Bruce C. Leibrecht, and Karen J. Lockaby. Measuring Learning and Performance in Collective Training Exercises. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada479614.

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Elliott, Kerry, Hilary Hollingsworth, Aiden Thornton, Liz Gillies, and Katherine Henderson. School leadership that cultivates collective efficacy: Emerging insights 2022. Australian Council for Educational Research, November 2022. http://dx.doi.org/10.37517/978-1-74286-694-9.

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The work of the Menzies School Leadership Incubator suggests we need a new approach to leadership that supports school leaders to better manage transformational change and deepen collaborative capacity necessary to cultivate collective efficacy to improve student learning outcomes. This paper provides a description of the work of the Menzies School Leadership Incubator (“the Incubator’) and insights generated so far. The Incubator has identified five leadership domains which underpin the leadership of Collective Efficacy: Understanding Collective Efficacy; Systems Leadership; Change Leadership
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Howard, Jo, Evert-jan Quak, and Jim Woodhill. A Practical Approach for Supporting Learning in Development Organisations. Institute of Development Studies, September 2022. http://dx.doi.org/10.19088/k4d.2022.120.

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The Knowledge, Evidence and Learning for Development (K4D) Programme, which started in 2016, comes to an end in September 2022. K4D is a programme funded by and for the UK Government’s Foreign, Commonwealth and Development Office (initially with the Department for International Development, DFID, which was merged with the FCO in 2020). To reflect on the processes and approaches of learning that K4D enabled over the years, a special Working Paper series will be published. One important pillar of the programme was to facilitate learning processes through learning journeys. A total of 33 learning
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Young, Stephen, Jessica Diaz, Bert De Coutere, and Holly Downs. Leadership Development in the Flow of Work: Leveraging Technology to Accelerate Learning. Center for Creative Leadership, 2022. http://dx.doi.org/10.35613/ccl.2022.2047.

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"A recent industry trend survey of CEOs found that only 11% of organizations report having a strong enough bench to fill leadership roles (Rhyne, 2021). As such, effective leadership development is an imperative for any high-performing organization. Rather than focusing time, money, and energy on only a small subset of “high-potential” employees, organizations can realize the full potential of their entire workforce by providing tech-enabled leadership development to leaders at all levels. This paper shares the following insights for Chief Learning Officers interested in leveraging evidence-ba
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Shaw, Jackie, Masa Amir, Tessa Lewin, Jean Kemitare, Awa Diop, Olga Kithumbu, Danai Mupotsa, and Stella Odiase. Contextualising Healing Justice as a Feminist Organising Framework in Africa. Institute of Development Studies, August 2022. http://dx.doi.org/10.19088/ids.2022.063.

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Healing justice is a political organising framework that aims to address the systemic causes of injustice experienced by marginalised peoples due to the harmful impacts of oppressive histories, intergenerational trauma, and structural violence. It recognises that these damaging factors generate collective trauma, which manifests in negative physical, mental–emotional, and spiritual effects in activists and in the functioning of their movements. Healing justice integrates collective healing in political organising processes, and is contextualised as appropriate to situational needs. This provid
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Eblie Trudel, Lesley. Leveraging Collective Efficacy in The Dangerous Space Between Good Intentions and Meaningful Interventions: A Study on the Use of School Suspensions in Manitoba; A Review of Literature for Manitoba Education and Early Childhood Learning. University of Winnipeg, December 2022. http://dx.doi.org/10.36939/ir.202212191117.

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Tumer, Kagan. Coordinating Learning Agents for Active Information Collection. Fort Belvoir, VA: Defense Technical Information Center, June 2011. http://dx.doi.org/10.21236/ada563864.

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Lavrentieva, Olena O., Lina M. Rybalko, Oleh O. Tsys, and Aleksandr D. Uchitel. Theoretical and methodical aspects of the organization of students’ independent study activities together with the use of ICT and tools. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3244.

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In the article the possibilities and classification of ICTs and tools that can be used in organizing students’ independent study activities of higher education institutions has been explored. It is determined the students’ independent study activities is individual, group, collective activity and is implemented within the process of education under the condition of no pedagogy’s direct involvement. It complies with the requirements of the curriculum and syllabus and is aimed at students’ acquisition of some social experiences in line with the learning objectives of vocational training. The ana
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