Relevant bibliographies by topics / Teaching models

Academic literature on the topic 'Teaching models'

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Published: 4 June 2021
Last updated: 29 January 2023

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Journal articles on the topic "Teaching models"

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Kramer, Klaus-Dietrich, Annedore Söchting, and Thomas Stolze. "Fuzzy Control Teaching Models." Issues in Informing Science and Information Technology 13 (2016): 225–33. http://dx.doi.org/10.28945/3490.

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Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool), and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI) applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.
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Nors Nielsen, Søren. "Teaching models in future." Ecological Modelling 220, no. 23 (December 2009): 3475–76. http://dx.doi.org/10.1016/j.ecolmodel.2009.07.019.

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SEO, Min Seok, and Kang Young LEE*. "Teaching Atomic Models: Revisited." New Physics: Sae Mulli 70, no. 2 (February 28, 2020): 168–74. http://dx.doi.org/10.3938/npsm.70.168.

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Chamizo, José Antonio. "Teaching Modern Chemistry through ‘Recurrent Historical Teaching Models’." Science & Education 16, no. 2 (February 2007): 197–216. http://dx.doi.org/10.1007/s11191-005-4784-4.

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Stankovic, Zoran. "Teaching models applying educational software." Godisnjak Pedagoskog fakulteta u Vranju 8, no. 2 (2017): 237–52. http://dx.doi.org/10.5937/gufv1702237s.

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Murray, Michael P. "Teaching About Heterogeneous Response Models." Journal of Economic Education 45, no. 2 (April 3, 2014): 110–20. http://dx.doi.org/10.1080/00220485.2014.889961.

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Gallagher, James J. "Teaching and Learning: New Models." Annual Review of Psychology 45, no. 1 (January 1994): 171–95. http://dx.doi.org/10.1146/annurev.ps.45.020194.001131.

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Chacko, Karen M., Eva Aagard, and David Irby. "Teaching models for outpatient medicine." Clinical Teacher 4, no. 2 (June 2007): 82–86. http://dx.doi.org/10.1111/j.1743-498x.2007.00153.x.

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Schoenfeld, Alan H. "Models of the Teaching Process." Journal of Mathematical Behavior 18, no. 3 (March 1999): 243–61. http://dx.doi.org/10.1016/s0732-3123(99)00031-0.

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Howland, JL. "Simple enzyme models in teaching." Biochemical Education 18, no. 2 (April 1990): 98. http://dx.doi.org/10.1016/0307-4412(90)90187-s.

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Dissertations / Theses on the topic "Teaching models"

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Fleming, Miri. "Teachers' receptivity to teaching models." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185807.

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The focus of this study is teachers' receptivity to new teaching models. Traditionally, research has been conducted to assess teachers' implementation of innovations. The stage prior to learning and implementing the model generally has been generally ignored. In this study, the researcher assumed that the level of teachers' receptivity could influence upon whether and to what extent the new teaching model is implemented. This study was designed to identify personal characteristics and environmental variables that affect the degree of teacher receptivity to a teaching model. Four teacher-participants were selected according to their level of receptivity to one of the models included in the study, Madeline Hunter's Essential Elements of Instruction or Hilda Taba's Teaching Strategies. The data collected through interviews were analyzed in two directions. First, participants' beliefs, experiences, and workplace conditions were identified using qualitative case study methodology. Second, participants' perceptions of the teaching models were analyzed using Rogers' (1962) framework for determining characteristics of an innovation. Several themes related to participants' receptivity to new teaching models, and their beliefs, experiences, and workplace conditions were revealed. These comprise differences in teachers' pedagogical orientations and in their perceptions of teaching models' characteristics, including the way the model was introduced, changes in levels receptivity, teaching models in relation to the student population served, satisfaction with workplace conditions, level of familiarity with the new teaching model, teachers' independence, and behavioral changes required by the teaching model. The study may be of particular interest to staff developers and educators of students teachers because of the importance of considering teachers' individual needs and characteristics when introducing new teaching models.
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Justi, Rosa da Silva. "Models of teaching of chemical kinetics." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388404.

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Graves, Barbara, and Christine Suurtamm. "Disrupting linear models of mathematics teaching|learning." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-79920.

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In this workshop we present an innovative teaching, learning and research setting that engages beginning teachers in mathematical inquiry as they investigate, represent and connect mathematical ideas through mathematical conversation, reasoning and argument. This workshop connects to the themes of teacher preparation and teaching through problem solving. Drawing on new paradigms to think about teaching and learning, we orient our work within complexity theory (Davis & Sumara, 2006; Holland, 1998; Johnson, 2001; Maturana & Varela, 1987; Varela, Thompson & Rosch, 1991) to understand teaching|learning as a complex iterative process through which opportunities for learning arise out of dynamic interactions. Varela, Thompson and Rosch, (1991) use the term co-emergence to understand how the individual and the environment inform each other and are “bound together in reciprocal specification and selection” (p.174). In particular we are interested in the conditions that enable the co-emergence of teaching|learning collectives that support the generation of new mathematical and pedagogical ideas and understandings. The setting is a one-week summer math program designed for prospective elementary teachers to deepen particular mathematical concepts taught in elementary school. The program is facilitated by recently graduated secondary mathematics teachers to provide them an opportunity to experience mathematics teaching|learning through rich problems. The data collected include questionnaires, interviews, and video recordings. Our analyses show that many a-ha moments of mathematical and pedagogical insight are experienced by both groups as they work together throughout the week. In this workshop we will actively engage the audience in an exploration of the mathematics problems that we pose in this unique teaching|learning environment. We will present our data on the participants’ mathematical and pedagogical responses and open a discussion of the implications of our work.
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McBrayer, Mickey Charles. "Calibration of groundwater flow models for modeling and teaching /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Basadien, Soraya. "Teaching logarithmic inequalities using omnigraph." Thesis, University of the Western Cape, 2007. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_5661_1227103274.

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Over the last few years it became clear that the students struggle with the basic concepts of logarithms and inequalities, let alone logarithmic inequalities due to the lack of exposure of these concepts at high school. In order to fully comprehend logarithmic inequalities, a good understanding of the logarithmic graph is important. Thus, the opportunity was seen to change the method of instruction by introducing the graphical method to solve logarithmic inequalities. It was decided to use an mathematical software program, Omnigraph, in this research.

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Kneebone, Roger Lister. "Teaching and learning basic surgical skills using multimedia and models." Thesis, University of Bath, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250935.

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Chittleborough, Gail. "The Role of Teaching Models and Chemical Representations in Developing Students' Mental Models of Chemical Phenomena." Thesis, Curtin University, 2004. http://hdl.handle.net/20.500.11937/763.

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Chemical representations play a vital part in the teaching and learning of chemistry. The aim of this research was to investigate students’ understanding of chemical representations and to ascertain the influence of chemical representations on students’ developing mental models of chemical phenomena. Three primary threads flowing through the thesis are models, representations and learning. Each thread was found to play a vital part in students’ learning of chemical content, in their learning of the scientific process and in their learning about the process of learning itself. This research with students from Year 8 to first year university level comprised four studies that provide comparisons between ages, abilities, learning settings and teaching and learning approaches. Students’ modelling ability was observed to develop and improve through instruction and practice and usually coincided with an improvement in their understanding of chemical concepts. While students were observed to actively use models to make predictions and test ideas, some were not aware of the predictive nature of models when asked about it. From the research, five characteristics of scientific models have been identified: scientific models as multiple representations, scientific models as exact replicas, scientific models as explanatory tools, how scientific models are used, and the dynamic nature of scientific models. A theoretical framework relating the four types of models - teaching, scientific, mental and expressed - and a typology of models that highlights the significant attributes of models, support the research results. The data showed that students’ ability to describe the role of the scientific model in the process of science improved with their increasing age and maturity.The relationship between the three levels of chemical representation of matter - the macroscopic level, the sub-microscopic level and the symbolic level - revealed some complexities concerning the representational and theoretical qualities and the reality of each level. The research data showed that generally most students had a good understanding of the macroscopic and symbolic levels of chemical representation of matter. However, students’ understanding of the sub-microscopic level varied, with some students being able to spontaneously envisage the sub- microscopic view while for others their understanding of the sub-microscopic level of chemical representation was lacking. To make sense of the sub-microscopic level, students’ appreciation of the accuracy and detail of any scientific model, or representation upon which their mental model is built, depended on them being able to distinguish reality from representation, distinguish reality from theory, know what a representation is, understand the role of a representation in the process of science, and understand the role of a theory in the process of science. In considering learning, the importance of an individual’s modelling ability was examined alongside the role of chemical representations and models in providing clear and concise explanations. Examining the links forged between the three levels of chemical representation of matter provided an insight into how students were learning and understanding chemical concepts. Throughout this research, aspects of students’ metacognition and intention were identified as being closely related to their development of mental models.The research identified numerous factors that influenced learning, including internal factors such as students’ prior chemical and mathematical knowledge, their modelling ability and use of chemical representations, motivation, metacognitive ability and time management as well as external factors such as organisation, assessment, teaching resources, getting feedback and good explanations. The choice of learning strategies by students and instructors appeared to be influenced by those factors that influenced learning. Feedback to students, in the form of discussion with classmates, online quizzes and help from instructors on their understanding was observed to be significant in promoting the learning process. Many first year university non-major chemistry students had difficulties understanding chemical concepts due to a limited background knowledge in chemistry and mathematics. Accordingly, greater emphasis at the macroscopic level of representation of matter with contextual references is recommended. The research results confirmed the theoretical construct for learning chemistry - the rising iceberg - that suggests all chemistry teaching begins at the macroscopic level, with the sub-microscopic and symbolic levels being introduced as needed. More of the iceberg becomes visible as the students’ mental model and depth of understanding increases. In a variety of situations, the changing status of a concept was observed as students’ understanding in terms of the intelligibility, plausibility and fruitfulness of a concept developed.The research data supported four aspects of learning - epistemological, ontological, social affective and metacognitive - as being significant in the students’ learning and the development of their mental models. Many university students, who are mature and are experienced learners, exhibited strong rnetacognitive awareness and an intentional approach to learning. It is proposed that the intentional and metacognitive learning approaches and strategies could be used to encourage students to be more responsible for their own learning.
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Chittleborough, Gail Diane. "The Role of Teaching Models and Chemical Representations in Developing Students' Mental Models of Chemical Phenomena." Curtin University of Technology, Science and Mathematics Education Centre, 2004. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=15381.

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Chemical representations play a vital part in the teaching and learning of chemistry. The aim of this research was to investigate students’ understanding of chemical representations and to ascertain the influence of chemical representations on students’ developing mental models of chemical phenomena. Three primary threads flowing through the thesis are models, representations and learning. Each thread was found to play a vital part in students’ learning of chemical content, in their learning of the scientific process and in their learning about the process of learning itself. This research with students from Year 8 to first year university level comprised four studies that provide comparisons between ages, abilities, learning settings and teaching and learning approaches. Students’ modelling ability was observed to develop and improve through instruction and practice and usually coincided with an improvement in their understanding of chemical concepts. While students were observed to actively use models to make predictions and test ideas, some were not aware of the predictive nature of models when asked about it. From the research, five characteristics of scientific models have been identified: scientific models as multiple representations, scientific models as exact replicas, scientific models as explanatory tools, how scientific models are used, and the dynamic nature of scientific models. A theoretical framework relating the four types of models - teaching, scientific, mental and expressed - and a typology of models that highlights the significant attributes of models, support the research results. The data showed that students’ ability to describe the role of the scientific model in the process of science improved with their increasing age and maturity.
The relationship between the three levels of chemical representation of matter - the macroscopic level, the sub-microscopic level and the symbolic level - revealed some complexities concerning the representational and theoretical qualities and the reality of each level. The research data showed that generally most students had a good understanding of the macroscopic and symbolic levels of chemical representation of matter. However, students’ understanding of the sub-microscopic level varied, with some students being able to spontaneously envisage the sub- microscopic view while for others their understanding of the sub-microscopic level of chemical representation was lacking. To make sense of the sub-microscopic level, students’ appreciation of the accuracy and detail of any scientific model, or representation upon which their mental model is built, depended on them being able to distinguish reality from representation, distinguish reality from theory, know what a representation is, understand the role of a representation in the process of science, and understand the role of a theory in the process of science. In considering learning, the importance of an individual’s modelling ability was examined alongside the role of chemical representations and models in providing clear and concise explanations. Examining the links forged between the three levels of chemical representation of matter provided an insight into how students were learning and understanding chemical concepts. Throughout this research, aspects of students’ metacognition and intention were identified as being closely related to their development of mental models.
The research identified numerous factors that influenced learning, including internal factors such as students’ prior chemical and mathematical knowledge, their modelling ability and use of chemical representations, motivation, metacognitive ability and time management as well as external factors such as organisation, assessment, teaching resources, getting feedback and good explanations. The choice of learning strategies by students and instructors appeared to be influenced by those factors that influenced learning. Feedback to students, in the form of discussion with classmates, online quizzes and help from instructors on their understanding was observed to be significant in promoting the learning process. Many first year university non-major chemistry students had difficulties understanding chemical concepts due to a limited background knowledge in chemistry and mathematics. Accordingly, greater emphasis at the macroscopic level of representation of matter with contextual references is recommended. The research results confirmed the theoretical construct for learning chemistry - the rising iceberg - that suggests all chemistry teaching begins at the macroscopic level, with the sub-microscopic and symbolic levels being introduced as needed. More of the iceberg becomes visible as the students’ mental model and depth of understanding increases. In a variety of situations, the changing status of a concept was observed as students’ understanding in terms of the intelligibility, plausibility and fruitfulness of a concept developed.
The research data supported four aspects of learning - epistemological, ontological, social affective and metacognitive - as being significant in the students’ learning and the development of their mental models. Many university students, who are mature and are experienced learners, exhibited strong rnetacognitive awareness and an intentional approach to learning. It is proposed that the intentional and metacognitive learning approaches and strategies could be used to encourage students to be more responsible for their own learning.
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Page-Shipp, R., and Niekerk C. Van. "Mental models in the learning and teaching of music theory concepts." Journal for New Generation Sciences, Vol 11, Issue 2: Central University of Technology, Free State, Bloemfontein, 2013. http://hdl.handle.net/11462/637.

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A retired physicist attempting to master elements of music theory in a short time found the Mental Model of the keyboard layout invaluable in overcoming some of the related learning challenges and this has been followed up in collaboration with a professor of Music Education. Possible cognitive mechanisms for his response are discussed and it is concluded that his engrained learning habits, which emphasise models as found in physics, are potentially of wider applicability. A survey of the use of Mental Models among competent young musicians indicated that although various models are widely used, this is largely subconscious. The practical question of whether exposure of students to the keyboard would assist them in mastering music theory remains unresolved.
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Martin, Jeffrey Harold. "Evaluating models for Bible teaching at a residential summer camp an expository model, a reenactment model, and an experiential model /." Online full text .pdf document, available to Fuller patrons only, 2003. http://www.tren.com.

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Books on the topic "Teaching models"

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Joyce, Bruce R. Models of teaching. 6th ed. Boston: Allyn and Bacon, 2000.

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Joyce, Bruce. Models of teaching. 4th ed. Boston: Allyn and Bacon, 1992.

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Marsha, Weil, and Showers Beverly, eds. Models of teaching. 4th ed. Boston: Allyn and Bacon, 1992.

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Marsha, Weil, ed. Models of teaching. 5th ed. Boston: Allyn and Bacon, 1996.

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Marsha, Weil, ed. Models of teaching. 3rd ed. Englewood Cliffs, N.J: Prentice-Hall, 1986.

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Marsha, Weil, and Calhoun Emily, eds. Models of teaching. 7th ed. Boston: Allyn and Bacon, 2004.

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Joyce, Bruce. Models of teaching. 3rd ed. London: Prentice Hall, 1986.

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Gilbert, Stephen W. Models-based science teaching. Arlington, Va: NSTA Press, 2011.

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Emily, Calhoun, and Hopkins David 1949-, eds. Models of learning: Tools for teaching. 2nd ed. Buckingham [England]: Open University, 2002.

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Emily, Calhoun, and Hopkins David 1949-, eds. Models of learning: Tools for teaching. Buckingham [England]: Open University Press, 1997.

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Book chapters on the topic "Teaching models"

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Zaidi, Shabih, and Mona Nasir. "Different Teaching Models." In Teaching and Learning Methods in Medicine, 267–309. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06850-3_8.

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Belikuşaklı-Çardak, Çiğdem S. "Models of Teaching." In Instructional Process and Concepts in Theory and Practice, 5–56. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2519-8_1.

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Halder, Santoshi, and Sanju Saha. "Models of Teaching." In The Routledge Handbook of Education Technology, 142–51. London: Routledge India, 2023. http://dx.doi.org/10.4324/9781003293545-12.

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Engels, Gregor, Jan Hendrik Hausmann, Marc Lohmann, and Stefan Sauer. "Teaching UML Is Teaching Software Engineering Is Teaching Abstraction." In Satellite Events at the MoDELS 2005 Conference, 306–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11663430_32.

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Justi, Rosária S. "Teaching with Historical Models." In Developing Models in Science Education, 209–26. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0876-1_11.

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Bishop, Peter C., and Andy Hines. "Models of Change." In Teaching about the Future, 19–62. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9781137020703_2.

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Bezivin, Jean, Robert France, Martin Gogolla, Oystein Haugen, Gabriele Taentzer, and Daniel Varro. "Teaching Modeling: Why, When, What?" In Models in Software Engineering, 55–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12261-3_6.

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Rogoff, Barbara, Eugene Matusov, and Cynthia White. "Models of Teaching and Learning." In The Handbook of Education and Human Development, 373–98. Oxford, UK: Blackwell Publishing Ltd, 2018. http://dx.doi.org/10.1111/b.9780631211860.1998.00019.x.

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Gilbert, John K., and Rosária Justi. "Models of Modelling." In Modelling-based Teaching in Science Education, 17–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29039-3_2.

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Lamie, Judith M. "Models of Change." In Evaluating Change in English Language Teaching, 60–81. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230598638_4.

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Conference papers on the topic "Teaching models"

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Stevens, Perdita. "Teaching and learning about abstraction." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3270112.3270138.

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Fuksa, Mario, and Steffen Becker. "Mini Programming Worlds: Teaching MDSD via the Hamster Simulator." In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2021. http://dx.doi.org/10.1109/models-c53483.2021.00113.

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Jouault, Frederic, Valentin Sebille, Valentin Besnard, Theo Le Calvar, Ciprian Teodorov, Matthias Brun, and Jerome Delatour. "AnimUML as a UML Modeling and Verification Teaching Tool." In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2021. http://dx.doi.org/10.1109/models-c53483.2021.00094.

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Gogolla, Martin, and Bran Selic. "On teaching descriptive and prescriptive modeling." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3418744.

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Kramer, Klaus-Dietrich, Annedore Söchting, and Thomas Stolze. "Fuzzy Control Teaching Models." In InSITE 2016: Informing Science + IT Education Conferences: Lithuania. Informing Science Institute, 2016. http://dx.doi.org/10.28945/3422.

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Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool), and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI) applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.
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Saini, Rijul, Gunter Mussbacher, Jin L. C. Guo, and Joerg Kienzle. "Teaching Modelling Literacy: An Artificial Intelligence Approach." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00108.

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Santiyadnya, Nyoman, I. N. Sukajaya, Gusti Ketut Arya Sunu, and I. Made Candiasa. "Working while Teaching: Balinese Culture-based Teaching Models." In Proceedings of the 1st International Conference on Innovation in Education (ICoIE 2018). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/icoie-18.2019.79.

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Zam, Michel. "Teaching modeling to anyone the aristotelian way." In MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550356.3556504.

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Butting, Arvid, Sinem Konar, Bernhard Rumpe, and Andreas Wortmann. "Teaching model-based systems engineering for industry 4.0." In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3270112.3270122.

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Hussain, Tauqeer. "Teaching Entity-Relationship Models Effectively." In 2016 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2016. http://dx.doi.org/10.1109/csci.2016.0058.

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Reports on the topic "Teaching models"

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Lyubenova, Velislav, Maya Ignatova, and Georgi Kostov. Interactive Teaching System for Structural and Parametric Identification of Bioprocess Models. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, June 2018. http://dx.doi.org/10.7546/crabs.2018.06.13.

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Yechkalo, Yuliia, Viktoriia Tkachuk, Tetiana Hruntova, Dmytro Brovko, and Vitaliy Tron. Augmented Reality in Training Engineering Students: Teaching Techniques. [б. в.], June 2019. http://dx.doi.org/10.31812/123456789/3176.

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The research aim. The research is intended to theoretically substantiate, develop and test methods of applying augmented reality to training future engineers. The research tasks include adaptation of augmented reality tools to apply them to laboratory classes while training future engineers; visualization of theoretical models of physical phenomena and processes using augmented reality tools; theoretical substantiation and development of methods of applying augmented reality to training future engineers. The research object is training future engineers at engineering universities. The research subject is methods of applying augmented reality to training future engineers. The research results are the following. There are analyzed national and foreign researches into issues of applying augmented reality to training future engineers at engineering universities. The augmented reality tools (HP Reveal) is adapted to be used in laboratory classes in physics while training future engineers. There are created augmented reality objects in the form of educational videos in which the structure of laboratory machines and procedures of working with them are explained. Methods of applying augmented reality to training future engineers at engineering universities are developed.
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Barkatov, Igor V., Volodymyr S. Farafonov, Valeriy O. Tiurin, Serhiy S. Honcharuk, Vitaliy I. Barkatov, and Hennadiy M. Kravtsov. New effective aid for teaching technology subjects: 3D spherical panoramas joined with virtual reality. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4407.

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Rapid development of modern technology and its increasing complexity make high demands to the quality of training of its users. Among others, an important class is vehicles, both civil and military. In the teaching of associated subjects, the accepted hierarchy of teaching aids includes common visual aids (posters, videos, scale models etc.) on the first stage, followed by simulators ranging in complexity, and finished at real vehicles. It allows achieving some balance between cost and efficiency by partial replacement of more expensive and elaborated aids with the less expensive ones. However, the analysis of teaching experience in the Military Institute of Armored Forces of National Technical University “Kharkiv Polytechnic Institute” (Institute) reveals that the balance is still suboptimal, and the present teaching aids are still not enough to allow efficient teaching. This fact raises the problem of extending the range of available teaching aids for vehicle-related subjects, which is the aim of the work. Benefiting from the modern information and visualization technologies, we present a new teaching aid that constitutes a spherical (360° or 3D) photographic panorama and a Virtual Reality (VR) device. The nature of the aid, its potential applications, limitations and benefits in comparison to the common aids are discussed. The proposed aid is shown to be cost-effective and is proved to increase efficiency of training, according to the results of a teaching experiment that was carried out in the Institute. For the implementation, a tight collaboration between the Institute and an IT company “Innovative Distance Learning Systems Limited” was established. A series of panoramas, which are already available, and its planned expansions are presented. The authors conclude that the proposed aid may significantly improve the cost-efficiency balance of teaching a range of technology subjects.
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Kiv, Arnold E., Vladyslav V. Bilous, Dmytro M. Bodnenko, Dmytro V. Horbatovskyi, Oksana S. Lytvyn, and Volodymyr V. Proshkin. The development and use of mobile app AR Physics in physics teaching at the university. [б. в.], July 2021. http://dx.doi.org/10.31812/123456789/4629.

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This paper outlines the importance of using Augmented Reality (AR) in physics education at the university as a valuable tool for visualization and increasing the attention and motivation of students to study, solving educational problems related to future professional activities, improving the interaction of teachers and students. Provided an analysis of the types of AR technology and software for developing AR apps. The sequences of actions for developing the mobile application AR Physics in the study of topics: “Direct electronic current”, “Fundamentals of the theory of electronic circuits”. The software tools for mobile application development (Android Studio, SDK, NDK, Google Sceneform, 3Ds MAX, Core Animation, Asset Media Recorder, Ashampoo Music Studio, Google Translate Plugin) are described. The bank of 3D models of elements of electrical circuits (sources of current, consumers, measuring devices, conductors) is created. Because of the students’ and teachers’ surveys, the advantages and disadvantages of using AR in the teaching process are discussed. Mann-Whitney U-test proved the effectiveness of the use of AR for laboratory works in physics by students majoring in “Mathematics”, “Computer Science”, and “Cybersecurity”.
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Panchenko, Liubov, and Andrii Khomiak. Education Statistics: Looking for Case-Study for Modeling. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4461.

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The article deals with the problem of using modeling in social statistics courses. It allows the student-researcher to build one-dimensional and multidimensional models of the phenomena and processes that are being studied. Social Statistics course programs from foreign universities (University of Arkansas; Athabasca University; HSE University, Russia; McMaster University, Canada) are analyzed. The article provides an example using the education data set – Guardian UK universities ranking in Social Statistics course. Examples of research questions are given, data analysis for these questions is performed (correlation, hypothesis testing, discriminant analysis). During the research the discriminant model with group variable – modified Guardian score – and 9 predictors: course satisfaction, teaching quality, feedback, staff-student ratio, money spent on each student and other) was built. Lower student’s satisfaction with feedback was found to be significantly different from the satisfaction with teaching. The article notes the modeling and statistical analysis should be accompanied by a meaningful interpretation of the results. In this example, we discussed the essence of university ratings, the purpose of Guardian rating, the operationalization and measurement of such concepts as satisfaction with teaching, feedback; ways to use statistics in education, data sources etc. with students. Ways of using this education data in group and individual work of students are suggested.
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Dabrowski, Anna, Yung Nietschke, Pauline Taylor-Guy, and Anne-Marie Chase. Mitigating the impacts of COVID-19: Lessons from Australia in remote education. Australian Council for Educational Research, December 2020. http://dx.doi.org/10.37517/978-1-74286-618-5.

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This literature review provides an overview of past and present responses to remote schooling in Australia, drawing on international research. The paper begins by discussing historical responses to emergency and extended schooling, including during the COVID-19 crisis. The discussion then focuses on effective teaching and learning practices and different learning design models. The review considers the available evidence on technology-based interventions and their use during remote schooling periods. Although this research is emergent, it offers insights into the availability and suitability of different mechanisms that can be used in remote learning contexts. Noting that the local empirical research base is limited, the discussion focuses on the ways in which Australia has drawn upon international best practices in remote schooling in order to enhance teaching and learning experiences. The paper concludes by discussing the conditions that can support effective remote schooling in different contexts, and the considerations that must be made around schooling during and post pandemic.
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McElhaney, Kevin, Anthony Baker, Carly Chillmon, Zareen Kasad, Babe Liberman, and Jeremy Roschelle. An Initial Logic Model to Guide OpenSciEd Research: Updated Version. Digital Promise, March 2022. http://dx.doi.org/10.51388/20.500.12265/152.

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This white paper supports an ongoing effort to define a research agenda and catalyze a research community around the OpenSciEd curriculum materials. Rigorous research on these materials is needed in order to answer questions about the equitable design of instructional materials, impacts on student learning, effective and equitable classroom teaching practices, teacher professional development approaches, and models for school adoption that address the diverse needs of historically marginalized students in STEM. Research findings have the potential to advance the knowledge, skills, and practices that will promote key student, teacher, and system outcomes. The research agenda stands to accelerate the research timeline and stimulate a broad range of research projects addressing these critical needs. To support the collaborative development and activation of the research agenda, we outline an initial logic model for OpenSciEd. The logic model can shape research efforts by clarifying intended relationships among (1) the principles, commitments, and key affordances of OpenSciEd; (2) the components of OpenSciEd and how they are implemented and supported in classrooms, schools, districts, and states; and (3) the desired outcomes of OpenSciEd.
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NELYUBINA, E. G., and L. V. PANFILOVA. METHODOLOGICAL ASPECTS OF IMPLEMENTATION OF TECHNOLOGY “INVERTED LEARNING” IN CHEMISTRY LESSONS. Science and Innovation Center Publishing House, April 2022. http://dx.doi.org/10.12731/2658-4034-2022-13-1-2-45-62.

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At the present time - the time of information technology and the rapid development of science and technology - a person has to constantly learn and retrain. The changes that have taken place in the education system in recent years have led to a rethinking of teaching methods and technologies. The technology of blended learning, one of the models of which is “inverted learning”, allows to succinctly include information and communication technologies in the educational process, while increasing the quality of education, creating a new level of personal responsibility for the student and by creating conditions for the development of metasubject competencies. Purpose - to develop methodological techniques for the implementation of the “flipped learning” technology in the framework of teaching chemistry in basic school, aimed at the formation of subject universal educational activities in chemistry. Method or methodology of the work: the main research methods were analysis, pedagogical experiment and interpretation of the results of the experiment. Results: solved at the theoretical and methodological level the problem of selection of methodological techniques aimed at the implementation of the technology “inverted learning” in the basic school.
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McGarrigle, M. Embedding Building Information Modelling into Construction Technology and Documentation Courses. Unitec ePress, November 2014. http://dx.doi.org/10.34074/rsrp.005.

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The aim of this research is to generate a resource to assist construction lecturers in identifying opportunities where Building Information Modelling [BIM] could be employed to augment the delivery of subject content within individual courses on construction technology programmes. The methodology involved a detailed analysis of the learning objectives and underpinning knowledge of the course content by topic area, within the residential Construction Systems 1 course presently delivered at Unitec on the National Diplomas in Architectural Technology[NDAT], Construction Management [NDCM] and Quantity Surveying [NDQS]. The objective is to aid students’ understanding of specific aspects such as planning controls or sub-floor framing by using BIM models, and investigate how these could enhance delivery modes using image,animation and interactive student activity. A framework maps the BIM teaching opportunities against each topic area highlighting where these could be embedded into construction course delivery. This template also records software options and could be used in similar analyses of other courses within similar programmes to assist with embedding BIM in subject delivery.
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McGarrigle, M. Embedding Building Information Modelling into Construction Technology and Documentation Courses. Unitec ePress, November 2014. http://dx.doi.org/10.34074/rsrp.005.

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The aim of this research is to generate a resource to assist construction lecturers in identifying opportunities where Building Information Modelling [BIM] could be employed to augment the delivery of subject content within individual courses on construction technology programmes. The methodology involved a detailed analysis of the learning objectives and underpinning knowledge of the course content by topic area, within the residential Construction Systems 1 course presently delivered at Unitec on the National Diplomas in Architectural Technology[NDAT], Construction Management [NDCM] and Quantity Surveying [NDQS]. The objective is to aid students’ understanding of specific aspects such as planning controls or sub-floor framing by using BIM models, and investigate how these could enhance delivery modes using image,animation and interactive student activity. A framework maps the BIM teaching opportunities against each topic area highlighting where these could be embedded into construction course delivery. This template also records software options and could be used in similar analyses of other courses within similar programmes to assist with embedding BIM in subject delivery.
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