Relevant bibliographies by topics / Contextual learning

Contents

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

Academic literature on the topic 'Contextual learning'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 June 2025

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Journal articles on the topic "Contextual learning"

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Usdarisman, Usdarisman, Debi Febianto, and Abdul Basit. "Pembelajaran Tematik Berbasis Kontekstual di Madrasah Ibtidaiyah Negeri 6 Kota Padang." Edu Cendikia: Jurnal Ilmiah Kependidikan 4, no. 03 (February 3, 2025): 1581–88. https://doi.org/10.47709/educendikia.v4i03.5450.

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This study aims to (1) describe the contextual-based thematic learning plan that is implemented in MIN 6 Kota Padang, (2) describe contextual contextual teaching-learning in MIN 6 Kota Padang, (3) describe contextual-based thematic learning evaluation in MIN 6 Kota Padang. Methods This study is a qualitative descriptive study that describes phenomena in the field without treatment. The object of this research is the students of grade V MIN 6 Kota Padang. Sources of data obtained from teachers and students of class V. In addition, learning tools are used when learning is implemented. The primary data collection techniques are observation, documentation, and interviews as research support techniques. The results showed that contextual thematic learning planning at MIN 6 Kota Padang was good enough and run as it should be. Implementing contextually thematic learning at MIN 6 Kota Padang is still not by the planning. The practice of a contextual approach to thematic learning is still less than optimal because teachers are less well-understood when applying a contextual-based thematic approach. Finally, the thematic learning evaluation is implemented using the assessment standards. Learning evaluation includes assessing student learning outcomes, which include aspects of attitude, knowledge, and skills.
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Md Amin, Zulkarnain, Nafisah Kamariah Md Kamaruddin, Norziha Che Him, and Ahmad Badruridzwanullah Zun. "Student’s Learning Style and Achievement after Being Taught Contextually." Environment-Behaviour Proceedings Journal 6, SI4 (July 31, 2021): 103–7. http://dx.doi.org/10.21834/ebpj.v6isi4.2908.

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Contextual learning combines examples taken from everyday experience. The purpose of this research is to identify whether learning contextually will improve students' achievement. A quasi-experimental design used. The engineering students were divided into contextual and non-contextual groups. The Neuro-Linguistics Programming (NLP) VAKD Preferred Representational Systems Test shows, majority of both groups use auditory digital learning styles. There is a significant difference at a significance level of .05, in the achievement test where the contextual groups performed better. The majority of the students in both groups are auditory digital learning styles, learning statistics contextually is an effective method for engineering students. Keywords: NLP VAKD, learning styles, statistics, contextual eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.2908
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Zafar, Aasim, and Syed Hamid Hasan. "Towards Contextual Mobile Learning." International Journal of Modern Education and Computer Science 6, no. 12 (December 8, 2014): 20–25. http://dx.doi.org/10.5815/ijmecs.2014.12.03.

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Temple, Paul, Mathieu Acher, Jean-Marc Jezequel, and Olivier Barais. "Learning Contextual-Variability Models." IEEE Software 34, no. 6 (November 2017): 64–70. http://dx.doi.org/10.1109/ms.2017.4121211.

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Kukulska-Hulme, Agnes, and Mike Sharples. "Mobile and contextual learning." ALT-J 17, no. 3 (November 2009): 159–60. http://dx.doi.org/10.1080/09687760903257608.

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Sitosanova, Ol'ga. "CONTEXTUAL LEARNING IN EDUCATION." Modern Technologies and Scientific and Technological Progress 2024, no. 1 (April 22, 2024): 311–12. http://dx.doi.org/10.36629/2686-9896-2024-1-311-312.

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As-Sa'idah, Millah Maryam, Ujang Dedih, and Maslani Maslani. "Effectiveness of Contextual Learning Models, Problem-Based Learning, and Learning Outcomes." Jurnal Inovasi Pendidikan Agama Islam (JIPAI) 2, no. 1 (November 26, 2022): 1–15. http://dx.doi.org/10.15575/jipai.v2i1.18786.

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This study aims to determine the effectiveness of contextual, problem-based learning and conventional learning models on student learning outcomes. The method used is quantitative with a comparative design. The object of this research is the learning outcomes of the seventh-grade students of MTs YPPS Sukamiskin. Class VII A consists of 32 students using a contextual model, class VII B has 34 students using a problem-based learning model, and class VII C has 32 students using a conventional one. Testing the data using the one-way ANOVA test which was analyzed by the SPSS version 20 application. The results of the normality test study, data using contextual learning models, problem-based learning and conventional normal distribution, and other evidence are indicated by the distribution of points on the Q-Q diagram on a diagonal line. While the results of the homogeneity test, the variance data is not homogeneous, this is indicated by the sig value of more than 0.05, namely 0.013. The conclusion from the results of this study is that the use of contextual learning models is more effective than problem-based and contextual learning models. This is evidenced by the average result (mean) using the contextual model is 81.5625, while the average result of the problem based learning model is 61.1765 and the average result of the conventional model is 57.5000.Penelitian ini berujuan untuk mengetahui efektivitas model pembelajaran contextual, problem based learning dan konvensional terhadap hasil belajar siswa. Metode yang digunakan kuantitatif dengan desain komparatif. Objek dalam penelitian ini adalah hasil belajar siswa kelas VII MTs YPPS Sukamiskin. Kelas VII A berjumlah 32 menggunakan model contextual, kelas VII B berjumlah 34 siswa menggunakan model problem-based learning dan kelas VII C berjumlah 32 siswa menggunakan konvensional. Pengujian data menggunakan uji ANOVA satu jalur yang dianalisis oleh aplikasi SPSS versi 20. Hasil penelitian uji normalitas, data yang menggunakan model pembelajaran contextual, problem-based learning dan konvensional berdistibusi normal dan bukti lain ditujukan oleh sebaran titik-titik pada diagram Q-Q berada pada garis diagonal. Sedangkan pada hasil uji homogenitas, data variansi nya tidak homogen hal ini ditujukan oleh nilai sig lebih dari 0,05 yaitu 0,013. Kesimpulan dari hasil penelitian ini adalah penggunaan model pembelajaran contextual lebih efektif dibanding dengan model problem-based learning dan contextual. Hal tersebut dibuktikan hasil rata-rata (mean) dengan penggunaan model contextual adalah 81,5625, sedangkan hasil rata-rata model problem-based learning adalah 61,1765 dan hasil rata-rata model konvensional adalah 57,5000.
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Lengyel, Gabor, Máté Lengyel, and József Fiser. "Contextual learning and inference in perceptual learning." Journal of Vision 22, no. 14 (December 5, 2022): 3999. http://dx.doi.org/10.1167/jov.22.14.3999.

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Maisyaroh, Maisyaroh, Pardomuan Sitompul, and Asmin Asmin. "Development of GeoGebra-Assisted Learning Media Using Contextual Learning to Enhance Mathematical Critical Thinking and Independent Learning." Jurnal Perspektif 9, no. 2 (May 26, 2025): 258. https://doi.org/10.15575/jp.v9i2.358.

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This study aims to obtain valid, practical, and effective GeoGebra-assisted contextual learning media to improve mathematical critical thinking skills and learning independence of grade VIII students. Assess the mathematical critical thinking skills of grade VIII students after using GeoGebra-assisted contextual learning media. Calculate the learning independence of grade VIII students after using GeoGebra-assisted contextual learning media. ADDIE development research is used. Results of the study: Valid, practical, and successful GeoGebra-assisted contextual learning media improve students' mathematical critical thinking skills and learning independence. Students who learn through contextual LKPD and GeoGebra show a significant increase in their critical thinking skills and mathematical independence
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Zhakypova, Zarina, and Chinara Sydykova. "THE IMPORTANCE OF USING CONTEXTUAL LEARNING AS AN EFFECTIVE TEACHING METHOD." Alatoo Academic Studies 21, no. 3 (September 30, 2021): 144–53. http://dx.doi.org/10.17015/aas.2021.213.16.

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This article is about why is important using contextual teaching in learning process. The concept of contextual teaching in learning emphasizes the full student’s activity both physically and mentally. Contextual learning considers that learning is not a memorizing activity, considering facts, but a process of experience in life. Contextual teaching and learning imply that learning becomes meaningful to learners by connecting to the real world. It is based on the diverse skills, interests, experiences and cultures of learners. Education can be used to change human behavior. It can enhance one’s ability to perform verbally, quantitatively and analytically. In this regard, we consider the strengths and weaknesses of this method and analyze whether it is worth using the Contextual method in teaching. The article provides interpretations of the term context by different scientists and its efficiency in all branches of science
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Dissertations / Theses on the topic "Contextual learning"

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Morin, Johanne. "Learning relational cliches with contextual generalization." Thesis, University of Ottawa (Canada), 1999. http://hdl.handle.net/10393/8773.

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Inductive logic programming (ILP) is concerned with the problem of inducing concepts represented as logic programs (or Horn clauses) from examples. Top-down inductive learners such as FOIL (Quinlan 1990; Cameron-Jones et al. 1993) learn Horn clauses adding one literal at a time using a hill-climbing search. These learners suffer from local plateaus, where the selection of a conjunction of literals, rather than a single literal, would improve the accuracy of the clause. The problem becomes the search for combinations of literals rather than just single literals. A mechanism to search efficiently through the space of combinations of literals is needed. The FOCL system (Pazzani et al. 1991) solved this problem by giving the concept learner hand-made "relational cliches" which are combinations of literals to consider while learning. The problem is that these cliches are hard to derive and often specific to a domain. So, it would be desirable to learn them automatically. As a part of this thesis, an inductive learner called CLUSE (Cliches Learned and USEd) has been developed that learns combinations of literals called relational cliches. The underlying idea is to learn cliches from examples of a concept and to use them with a hill-climbing learner to escape local plateaus. Cliches are learned from a concept in one domain and used to learn concepts within the same domain as well as across domains. Assuming that cliches are learned and used in the same domain, literals used to express different concepts overlap. Consequently cliches learned from one concept should provide appropriate lookahead to learn concepts in the same domain. On the other hand, these cliches probably have few literals in common with concepts across domains, hence the need for more general cliches. To solve this, CLUSE learns two kinds of cliches: Domain Dependent Cliches expressed as a conjunction of literals specific to a domain, and Domain Independent Cliches where literals have variable predicate symbols. CLUSE is a bottom-up inductive relational learner based on Relative Least General Generalization (RLGG). To remedy the inefficiency and the overgeneralization problems of RLGG, a modified version of RLGG has been developed that exploits the context in which LGG is applied. The modified RLGG is called Contextual Least General Generalization (CLGG). Empirical experiments with CLUSE reveal that cliches learned with CLUSE provide appropriate lookahead to escape local plateaus of a hill-climbing learner both within and across domains. For the purpose of the evaluation, FOIL has been extended to learn concepts with or without cliches. In two domains of application, cliches have proven to be useful. One domain is the real-life application defining structures for the finite element methods (FEM). The other domain is the synthetic domain of blocks, which offers a wide variety of problems (or concepts). Other domains of application such as drug design, text categorization, and detecting traffic problems are also discussed.
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Morin, Johanne. "Learning relational clichés with contextual generalization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0015/NQ46535.pdf.

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Martin, Susanna Marie. "Mobile contextual data for hands-on learning." Thesis, University of Bath, 2013. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607144.

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This thesis investigates whether the use of hand-held technology affects motivation and learning in science. An innovative mixed methods approach was used to provide new insights into an emerging area of research. First, two pilot observational studies were conducted, which aimed to establish how a school currently uses hand held dataloggers, and gain further insight into how learners respond to this technology. This was followed by a primarily quantitative experiment that was concerned with the role of data ownership and the impact of ‘seams’ on the transformation process of the collected data. The results indicated that a hands-on experience increased confidence among students in explaining their own data, as opposed to data collected by someone else. A third study was designed to compare how student motivation and learning were affected when carrying out the same inquiry task either with or without the support of dataloggers. The results revealed no difference in accuracy or motivation for learning. The final, fourth, study was a longitudinal study designed in collaboration with a secondary science teacher, comparing three conditions: the inclusion of cameras to support student reflection, the inclusion of both cameras and the use of dataloggers to support teaching, and a control condition where the lessons were not changed. This study found that inclusion of dataloggers into modules led to increased assessment scores, while the use of cameras indicated that students are adept at taking relevant photos, and did not suffer from an extensive novelty effect. The results highlighted the importance of using a range of methods and tools for teaching students. The thesis concludes with recommendations and future research ideas, including exploring how data is visualised and the role of physical context. Of key importance is that future work is conducted in collaboration with educators in the wild.
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Smyth, A. "Ageing and implicit learning : explorations in contextual cuing." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19559/.

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Research in cognitive ageing has found that while older adults show reductions in performance on standard explicit memory tasks, implicit memory performance remains relatively stable. Such findings are often used to support the popular dual-systems account of human learning and memory, which organizes these types of cognition into distinct implicit and explicit systems. In contrast to previous studies, we found that healthy older adults show learning impairments on an implicit contextual cuing task when compared to younger adults, in addition to expected poor performance on an explicit generation test. To examine the possibility that slower overall response speed may account for the implicit deficit, younger adults’ response times were artificially increased by altering the display properties so as to match those of older adults. Learning in younger participants remained intact under these conditions. Similarly, when display properties were altered to produce faster responses in older participants, their learning continued to be impaired. These results reveal that implicit processing is not immune to the effects of ageing, and that these deficits cannot be attributed solely to older adults’ slower overall response speed. In a further series of experiments using younger participants, we examined the claim that implicit knowledge is not accessible to awareness in contextual cuing. When the number of trials used in an explicit generation test was increased, we found that contextual cuing information was consciously retrievable. These results suggest that the shorter tests used previously were not statistically powerful enough to detect a true effect. Furthermore, when concurrent implicit and explicit tests were used, learning did not precede awareness. Collectively, these findings suggest that awareness may be a necessary concomitant of contextual cuing in older adults, and provide further evidence that learning and memory should not be divided on the basis of consciousness.
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Alnuaim, A. "Designing and evaluating a contextual mobile learning application to support situated learning." Thesis, University of the West of England, Bristol, 2015. http://eprints.uwe.ac.uk/25274/.

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This research emerged from seeking to identify ways of getting Human-Computer Interaction Design students into real world environments, similar to those in which they will eventually be designing, thus maximising their ability to identify opportunities for innovation. In helping students learn how to become proficient and innovative designers and developers, it is crucial that their ‘out of the classroom’ experience of the environments in which their designs will be used, augments and extends in-class learning. The aim of this research is to investigate firstly, a blended learning model for students in higher education using mobile technology for situated learning and, secondly, the process of designing a mobile learning app within this blended learning model. This app was designed, by the author, to support students in a design task and to develop their independent learning and critical thinking skills, as part of their Human-Computer Interaction coursework. The first stage in designing the system was to conduct a comprehensive contextual inquiry to understand specific student and staff needs in the envisaged scenario. In addition, this research explores the challenges in implementing and deploying such an app in the learning context. A number of evaluations were conducted to assess the design, usability and effectiveness of the app, which we have called sLearn. The results show an improvement in scores and quality of assessed work completed with the support of the sLearn app and a positive response from students regarding its usability and pedagogic utility. The promising results show that the app has helped students in developing critical thinking and independent learning skills. The research also considers the challenges of conducting an ecologically valid study of such interventions in a higher education setting. There were issues discovered in regards to the context of use such as usability of interface elements and feeling self-conscious in using the app in a public place. The model was tested with two other student cohorts: User Experience and Engineering students, to further investigate best practice in deploying mobile learning in higher education and examine the suitability of this learning model for different disciplines. These trials suggest that the model is indeed suitable and, the engineering study in particular has demonstrated that it has the potential to support the learning in-situ of students from non-computing disciplines.
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Channing, Jill. "I Will Never Use This: Contextual Teaching and Learning." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/4884.

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Educators can connect life to learning to transform the classroom experience using contextual teaching and learning strategies and assignments such as open educational resources, service learning projects, active learning labs, practical technological applications, and collaborative assignments.
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Moos, Daniel Charles. "Learning with hypermedia examining cognitive, motivational, and contextual factors /." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/6750.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.<br>Thesis research directed by: Human Development. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Johnson, Cynthia L. "A contextual approach to learning collaborative behavior via observation." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4943.

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This dissertation describes a novel technique to creating a simulated team of agents through observation. Simulated human teamwork can be used for a number of purposes, such as expert examples, automated teammates for training purposes and realistic opponents in games and training simulation. Current teamwork simulations require the team member behaviors be programmed into the simulation, often requiring a great deal of time and effort. None are able to observe a team at work and replicate the teamwork behaviors. Machine learning techniques for learning by observation and learning by demonstration have proven successful at observing behavior of humans or other software agents and creating a behavior function for a single agent. The research described here combines current research in teamwork simulations and learning by observation to effectively train a multi-agent system in effective team behavior. The dissertation describes the background and work by others as well as a detailed description of the learning method. A prototype built to evaluate the developed approach as well as the extensive experimentation conducted is also described.<br>ID: 029809360; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 305-314).<br>Ph.D.<br>Doctorate<br>Electrical Engineering and Computer Science<br>Engineering and Computer Science
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Méndez, Daniel. "Learning from Hunger: A Communal Recipe in Contextual Theology." Digital Commons at Loyola Marymount University and Loyola Law School, 2013. https://digitalcommons.lmu.edu/etd/12.

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SIEBRA, Sandra de Albuquerque. "Contextual analysis of users interactions in collaborative learning environments." Universidade Federal de Pernambuco, 2007. https://repositorio.ufpe.br/handle/123456789/2026.

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Made available in DSpace on 2014-06-12T15:53:57Z (GMT). No. of bitstreams: 2 arquivo6411_1.pdf: 5236344 bytes, checksum: eb8f36005a668c44d22d18f4691ce07e (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2007<br>As interações realizadas através de Ambientes de Aprendizagem Colaborativa suportados por Computador (AAC) são um dos aspectos visíveis mais importantes da colaboração. A análise dessas interações pode dar suporte aos processos de reflexão e autoavaliação dos estudantes e às atividades dos professores. Porém, para executar o processo de análise, é importante descobrir e registrar o contexto onde cada interação ocorreu, a fim de entender o verdadeiro significado das interações dos usuários. Entretanto, faltam métodos e ferramentas para a Análise de Interações em AAC que considerem: (1) o contexto onde as interações ocorreram; (2) a diferença de necessidades do ponto de vista do professor e do estudante; e (3) a necessidade de informações históricas contextualizadas, para produzir relatórios mais completos para estudantes e professores. Neste cenário, objetivando prover suporte de boa qualidade para estudantes e professores, essa tese apresenta um Processo para Análise de Interações baseado em Contexto, que estrutura as interações, levando em consideração o contexto onde elas ocorreram. Depois disso, ele armazena as interações em um repositório multidimensional chamado LIM (Memória de Interações de Aprendizagem) e, finalmente, usa consultas analíticas para explorar e analisar as informações armazenadas sob diferentes perspectivas (dimensões), de acordo com as necessidades dos usuários. Essa tese também apresenta um Ambiente Analítico baseado em Contexto chamado SmartChat+: um ambiente para discussões colaborativas de assuntos específicos que segue o Processo baseado em Contexto definido. A experimentação inicial desse ambiente é detalhada e os resultados dos experimentos são discutidos, indicando a viabilidade do processo proposto e seu potencial para apoiar ao aprendizado
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Books on the topic "Contextual learning"

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Lan, Yu-Ju, and Scott Grant, eds. Contextual Language Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3416-1.

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Imel, Susan. Contextual learning in adult education. Columbus, OH: ERIC Clearinghouse on Adult, Career, and Vocational Education, Center on Education and Training for Employment, College of Education, the Ohio State University, 2000.

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Therese, Divita, Kohanek Jean, and Educational Resources Information Center (U.S.), eds. Contextual learning [and] vocational assessment. [Washington, DC: National Transition Alliance for Youth with Disabilities, Academy for Educational Development], 1997.

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J, Sternberg Robert, and Spear-Swerling Louise, eds. Perspectives on learning disabilities: Biological, cognitive, contextual. Boulder, Colo: Westview Press, 1999.

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Stairs, Andrea J. Research on urban teacher learning: Examining contextual factors over time. Charlotte, N.C: IAP-Information Age Pub., Inc., 2010.

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J, Stairs Andrea, and Donnell Kelly A, eds. Research on urban teaching learning examining contextual factors over time. Published by Charlotte, N.C: IAP-Information Age Pub., Inc., 2010.

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Barrett, Everard. Mathematics power learning for children-Book 3: Activating the contextual learner. 5th ed. N. Baldwin, NY: Professor B Enterprises, Inc., 1993.

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David, Watkins, and Biggs John B, eds. The Chinese learner: Cultural, psychological, and contextual influences. Hong Kong: CERC, 1996.

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Parnell, Dale. Contextual Learning Institute and Consortium (CLIC) for selected urban high schools: Final project report. [Corvallis, Or.]: Oregon State University School of Education, 1997.

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ERIC Clearinghouse on Adult, Career, and Vocational Education., ed. Contextual teaching and learning: Preparing teachers to enhance student success in and beyond school. Columbus, Ohio: ERIC Clearinghouse on Adult, Career, and Vocational Education, Center on Education and Training for Employment, College of Education, 1998.

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Book chapters on the topic "Contextual learning"

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Kutz, Matthew. "Leveraging Learning." In Contextual Intelligence, 79–92. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_7.

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Reddy, P. Janardhana Kumar, and K. Revathy. "Contextual Learning." In Digital Skill Development for Industry 4.0, 83–104. Boca Raton: Auerbach Publications, 2024. http://dx.doi.org/10.1201/9781003504894-8.

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Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Contextual Advertising." In Encyclopedia of Machine Learning, 226. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_170.

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Jiang, Yuhong, and Marvin M. Chun. "Contextual cueing." In Attention and Implicit Learning, 277–96. Amsterdam: John Benjamins Publishing Company, 2003. http://dx.doi.org/10.1075/aicr.48.15jia.

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Jiang, Yuhong V., and Caitlin A. Sisk. "Contextual Cueing." In Spatial Learning and Attention Guidance, 59–72. New York, NY: Springer US, 2019. http://dx.doi.org/10.1007/7657_2019_19.

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Knox, Alan B. "Recognizing Contextual Influences." In Improving Professional Learning, 93–102. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003445265-17.

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Stefaniak, Jill E. "Contextual Analysis." In Needs Assessment for Learning and Performance, 57–72. New York, NY : Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9780429287510-5.

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Guerra, Aida, and Jette E. Holgaard. "Contextual Learning for Sustainability." In Encyclopedia of Sustainability in Higher Education, 298–308. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11352-0_340.

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Guerra, Aida, and Jette E. Holgaard. "Contextual Learning for Sustainability." In Encyclopedia of Sustainability in Higher Education, 1–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-63951-2_340-1.

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Wloka, Bartholomäus, and Werner Winiwarter. "COLLEAP – COntextual Language LEArning Pipeline." In Advances in Web-Based Learning – ICWL 2013, 330–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41175-5_34.

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Conference papers on the topic "Contextual learning"

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Gulhane, Anushka Milind, Dipti Patil, and Vinita Chimalgi. "Contextual Object Detection Using Deep Learning." In 2025 1st International Conference on AIML-Applications for Engineering & Technology (ICAET), 1–6. IEEE, 2025. https://doi.org/10.1109/icaet63349.2025.10932235.

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Jain, Shrey, Zoë Hitzig, and Pamela Mishkin. "Position: Contextual Confidence and Generative AI." In 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 281–301. IEEE, 2025. https://doi.org/10.1109/satml64287.2025.00022.

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Sung, Changki, Wanhee Kim, Jungho An, Wooju Lee, Hyungtae Lim, and Hyun Myung. "Contextrast: Contextual Contrastive Learning for Semantic Segmentation." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3732–42. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.00358.

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Zhang, Fan, Siyang Gao, and Jie Song. "Offline Contextual Learning with Correlated Bayesian Beliefs." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), 2496–500. IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711762.

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Liu, Ying, Zeyu Yu, Zhongxiang Deng, Shuang Liu, Zhong Zhang, and Chaojun Shi. "Learning Contextual Information for Ground-Based Cloud Detection." In 2024 4th International Conference on Computer Science and Blockchain (CCSB), 334–37. IEEE, 2024. http://dx.doi.org/10.1109/ccsb63463.2024.10735654.

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Ibarra-Fiallo, Julio, and Juan A. Lara. "Contextual Deep Learning Approaches for Time Series Reconstruction." In 2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/coins61597.2024.10622120.

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Langford, John. "Contextual reinforcement learning." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8257902.

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Shukla, Jainendra, Puneet Gupta, Aniket Bera, Arka Sarkar, Prakhar Goel, Shubhangi Butta, Anup Kumar Gupta, et al. "Contextual Emotion Learning Challenge." In 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021). IEEE, 2021. http://dx.doi.org/10.1109/fg52635.2021.9667034.

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Miaschi, Alessio, and Felice Dell’Orletta. "Contextual and Non-Contextual Word Embeddings: an in-depth Linguistic Investigation." In Proceedings of the 5th Workshop on Representation Learning for NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.repl4nlp-1.15.

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Agrawal, Rahul, Saurabh Kumar, Shubham Kumar, Nitesh Goyal, and Shashank Sinha. "WASABI Contextual BOT." In 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA). IEEE, 2022. http://dx.doi.org/10.1109/icccmla56841.2022.9989007.

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Reports on the topic "Contextual learning"

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St John, Mark F., and James L. McClelland. Learning and Applying Contextual Constraints in Sentence Comprehension. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada218908.

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Fu, Yun. Modeling Spatiotemporal Contextual Dynamics with Sparse-Coded Transfer Learning. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada587078.

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Wei, Xin, Amanda Wortman, Cristina Heffernan, Li Cheng, Neil Heffernan, April Murphy, Cristina Zepeda, Ben Motz, Harmony Jankowski, and Jeremy Roschelle. Language and Mathematics Learning: A Comparative Study of Digital Learning Platforms. SEERNet, Digital Promise, March 2024. http://dx.doi.org/10.51388/20.500.12265/206.

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This paper presents a conceptual exploration of how Digital Learning Platforms (DLPs) can be utilized to investigate the impact of language clarity, precision, engagement, and contextual relevance on mathematics learning from word problems. Focusing on three distinct DLPs—ASSISTments/E-TRIALS, MATHia/UpGrade, and Canvas/Terracotta—we propose hypothetical studies aimed at uncovering how nuanced language modifications can enhance mathematical understanding and engagement. While these studies are illustrative in nature, they provide a blueprint for researchers interested in leveraging DLPs for empirical investigation so that future investigators gain a better understanding of the emerging infrastructure for research in DLPs and the opportunities provided by them. In highlighting three distinct implementations of the same core research question, we reveal both commonalities as well as differences in how different educational technologies might build evidence, offering a unique opportunity to advance the field of math education and other education research fields.
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Gosh, Anushka. Building self-efficacy and literacy through edutainment: experimental evidence from Kenya. Busara, July 2024. http://dx.doi.org/10.62372/aory8993.

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Although access to primary education has increased in recent decades, the "learning crisis" continues to prevail. This was exacerbated by the COVID-19 pandemic, widening the learning gap for communities on the margin. In this context, educational Technology (EdTech) could play an important role in bridging the educational gap. Edtech has the power to reach communities through simple, low-cost solutions, and could make learning relevant and fun. With Ubongo, we explored the possibility of combining evidence and good old story telling that is rooted in African experiences to bring quality learnings to children's homes. We unpack the findings from a randomized controlled trial in Kenya that explores how contextual storytelling and effective demonstration of learning strategies could potentially build confident and curious readers.
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Khrykov, Yevhen M., Alla A. Kharkivska, and Halyna F. Ponomarova. Modeling the training system of masters of public service using Web 2.0. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3862.

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The article concerns grounding the technology of training masters of public service with the use of Web 2.0. This technology is based on the concept of sign-contextual learning, the positions of the laboratory-brigade method, the concept of Web 2.0, case technology, project method, problem learning. The main features of this technology are changes in the correlation between theoretical and practical training, in-class and individual studying; changing teachers’ functions; extensive use of information technology capabilities in learning.
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Thomson, Sue, Nicole Wernert, Sarah Buckley, Sima Rodrigues, Elizabeth O’Grady, and Marina Schmid. TIMSS 2019 Australia. Volume II: School and classroom contexts for learning. Australian Council for Educational Research, April 2021. http://dx.doi.org/10.37517/978-1-74286-615-4.

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This is the second of two reports that look at the results of TIMSS 2019 and Australia’s performance. Volume I focuses specifically on the achievement results, detailing Australia’s results within the international context, and presents results for the Australian jurisdictions, and for the different demographic groups within Australia, including male and female students. This report, Volume II, presents the results from the contextual questionnaires, and examines the contexts in which learning and achievement occur, including home, school, and classroom contexts, as well as student attitudes. Each chapter focuses on different indicators that cover the school community, the school learning environment, mathematics and science teacher characteristics, mathematics and science classroom learning environments, and students’ attitudes and beliefs. Together, the different indicators of student and school life illustrate some of the many key aspects that make up the school experience.
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Desk, Front. Social Return on Investment Analysis of Support from the Commonwealth of Learning for the Open and Innovative Schooling Model. Commonwealth of Learning (COL), October 2021. http://dx.doi.org/10.56059/11599/3934.

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As the Commonwealth of Learning (COL) was in the last year of its 2015–2021 strategic plan, COL sought to evaluate the impact of its interventions in open and innovative schooling (OIS) in the period 2018–2021 through an external review. An online quantitative study was carried out in Belize, Malawi, Mozambique, Trinidad and Tobago, and Zambia, followed by a contextual cost–benefit analysis, and a social return on investment (SROI) analysis. Overall, COL’s contribution to the OIS programme in terms of Phase 1 and Phase 2 activities is perceived to have significantly contributed to the success noted so far in the five countries under study. The SROI ratios for all countries were positive, indicating that the social returns on this intervention are desirable, justifying a case for continued support of such OIS initiatives.
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Wernert, Nicole, Sima Rodrigues, Marina Schmid, and Catherine Underwood. TIMSS 2023 Australia. Volume II: Student and school characteristics. Australian Council for Educational Research, June 2025. https://doi.org/10.37517/978-1-74286-756-4.

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This is the second of 2 reports that look at the results of TIMSS 2023 and Australia’s performance. This report, Volume II, presents the results from the contextual questionnaires, and examines the home, school, and classroom contexts in which learning and achievement occur, as well as student attitudes. Each chapter focuses on different indicators concerning the school community; the school learning environment; mathematics and science teacher characteristics; mathematics and science classroom learning environments; and, students’ attitudes and beliefs and use of technology. Together, the different indicators of student and school life illustrate some of the many key aspects that make up the school experience. The Trends in International Mathematics and Science Study (TIMSS) is an international comparative study of student achievement directed by the International Association for the Evaluation of Educational Achievement (IEA). TIMSS was first conducted in 1995 and the 2023 assessment formed the eighth cycle, providing 28 years of trends in mathematics and science achievement at Year 4 and Year 8.
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Goh, Jonathan, and Hairon Salleh. An investigation of the impact of leadership practices on student learning and development outcomes in Singapore schools. National Institute of Education, Nanyang Technological University, Singapore, 2020. https://doi.org/10.32658/10497/22713.

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Policymakers and the public in many developed countries have demanded for greater public school accountability in the hope of improving academic and non-academic school outcomes, as well as decreasing the achievement gaps among subpopulations of students (Heck &amp; Moriyama, 2010). In response, there has been a growing conversation amongst educational practitioners and researchers on how educational leadership might be linked to effective teaching, and student learning and ‘achievement’ outcomes. Educational-effectiveness researchers have attempted to link (directly and/or indirect) existing research with theory about educational processes to identify contextual, school factors (including leadership), and classroom factors (including teacher effectiveness) to student learning and ‘achievement’ outcomes (Creemers, 1994; Creemers &amp; Kyriakides, 2008; Heck &amp; Moriyama, 2010; Leithwood &amp; Mascall, 2008; Scheerens, 1990, 1992; Stringfield &amp; Slavin, 1992; Teddlie &amp; Reynolds, 2000). It is clear that the ‘Principal as the sole decision maker’ conception of leadership and bureaucratic organizational structures are no longer consistent with the new school leadership climate (Pearce &amp; Conger, 2003). Proponents of this view have argued that a dispersed form of leadership is thought to enhance opportunities for the organization to benefit from the capacities of more of its members rather than a single leader (Leithwood &amp; Mascall, 2008).
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Abich, Yohannes, and Getachew Azeze Eriku. Challenges and Opportunities for the Adoption of e-Learning at the University of Gondar: A Qualitative Study. Mary Lou Fulton Teachers College, December 2023. http://dx.doi.org/10.14507/mcf-eli.i6.

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E-Learning has grown significantly across the globe since the start of the COVID-19 pandemic. However, the usage of e-Learning in higher education is still in its infancy and under-utilized in the Ethiopian context. Contextual understanding of the main challenges and enabling factors are essential for the effective implementation of an e-Learning system. Therefore, the aim of the study was to explore the challenges and to identify the enabling factors for the adoption of e-Learning at the University of Gondar. This study aimed to explore the main challenges and to identify the enabling factors for the adoption of e-Learning at the University of Gondar, Ethiopia. Methodologically, the study used thematic analysis to identify, analyze, and report findings. A total of 31 participants with a wide range of characteristics were purposely sampled and interviewed. Seven themes emerged during the analysis. Major challenges, such as infrastructure, poor knowledge, awareness and attitude towards information technology or e-Learning, new culture and resistance to accept the teaching system, lack of expertise on e-Learning, negatively affected the implementation of e-Learning. Other emerging themes included the pathways to overcome the challenges, opportunities in the University of Gondar’s context, and advantages and disadvantages of e-Learning from the participants’ perspective. The findings of this study revealed that there is willingness to implement e-Learning systems in developing countries like Ethiopia. The study identified the major challenges that significantly affect the adoption of an e-Learning system in Ethiopia. The study confirmed that establishing e-Learning infrastructures, increasing commitment and offering in-depth training are key elements for the successful implementation of e-Learning in higher education. This study also provided important recommendations and can serve as a baseline for policy-makers, designers, and researchers that help them to bettr understand the essential components of the e-Learning system.
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