Movement and Song Idiom Traditional to Enhance Early Mathematical Skills: Gelantram Audio-visual Learning Media

Many studies have shown a link between being competent in early mathematics and achievement in school. Early math skills have the potential to be the best predictors of later performance in reading and mathematics. Movement and songs are activities that children like, making it easier for teachers to apply mathematical concepts through this method. This study aims to develop audio-visual learning media in the form of songs with a mixture of western and traditional musical idioms, accompanied by movements that represent some of the teaching of early mathematics concepts. The stages of developing the ADDIE model are the basis for launching new learning media products related to math and art, and also planting the nation's cultural arts from an early age. These instructional media products were analyzed by experts and tested for their effectiveness through experiments on five children aged 3-4 years. The qualitative data were analyzed using transcripts of field notes and observations and interpreted in a descriptive narrative. The quantitative data were analyzed using gain score statistics. The results showed that there was a significant increase in value for early mathematical understanding of the concepts of geometry, numbers and measurement through this learning medium. The results of the effectiveness test become the final basis of reference for revision and complement the shortcomings of this learning medium. Further research can be carried out to develop other mathematical concepts through motion and song learning media, and to create experiments with a wider sample.  Keywords: Early Mathematical Skills, Movement and Song Idiom Traditional, Audio-visual Learning Media References An, S. A., & Tillman, D. A. (2015). Music activities as a meaningful context for teaching elementary students mathematics: a quasi-experiment time series design with random assigned control group. 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The unexplored potential of virtual reality for cultural learning

[EN] Educational technology tools that improve learning and foster engagement are constantly sought by teachers and researchers. In the domain of Computer-Assisted Language Learning a variety of tools, for instance blogs and podcasts, have been used to promote language and cultural learning (Shih, 2015). More recently, virtual reality has been identified as a technology with great potential for the creation of meaningful and contextualized learning experiences. Despite the  learning affordances of virtual reality, in language education most of the literature has focused on the low-immersive version, whereas research investigating highly immersive virtual environments has only emerged in recent years (e.g., Berti, 2019; Blyth, 2018). In other fields, the use of highly immersive virtual reality has been compared to traditional pedagogical resources and demonstrated that students’ learning improved with the use of virtual environments as compared to two-dimensional video and textbook learning conditions (Allcoat & von Mühlenen, 2018). Considering the potential learning benefits of this technology, this paper argues that longitudinal empirical research in language education is strongly needed to investigate its potential unexplored impact on language and cultural learning.Berti, M. (2021). The unexplored potential of virtual reality for cultural learning. The EuroCALL Review. 29(1):60-67. https://doi.org/10.4995/eurocall.2021.12809OJS6067291Allcoat, D., & von Mühlenen, A. (2018). Learning in virtual reality: Effects on performance, emotion, and engagement. Research in Learning Technology, 26, 1-13. https://doi.org/10.25304/rlt.v26.2140Barab, S. A., Hay, K. E., & Duffy, T. M. (1998). Grounded constructions and how technology can help. TechTrends, 43(2), 15-23. https://doi.org/10.1007/BF02818171Berti, M. (2019). Italian open education: virtual reality immersions for the language classroom. New Case Studies of Openness in and beyond the Language Classroom, Research-publishing. net, 37-47. https://doi.org/10.14705/rpnet.2019.37.965Blyth, C. (2018). Immersive technologies and language learning. Foreign Language Annals, 51(1), 225-232. https://doi.org/10.1111/flan.12327Chen, C. J. (2009). Theoretical bases for using virtual reality in education. Themes in Science and Technology Education, 2(1-2), 71-90.Dawley, L., & Dede, C. (2014). Situated learning in virtual worlds and immersive simulations. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (pp. 723-734). New York: Springer. https://doi.org/10.1007/978-1-4614-3185-5_58Fowler, C. (2015). Virtual reality and learning: Where is the pedagogy? British Journal of Educational Technology, 46(2), 412-422. https://doi.org/10.1111/bjet.12135Freina, L., & Ott, M. (2015). A literature review on immersive virtual reality in education: State of the art and perspectives. eLearning & Software for Education, 1, 133-141.Huang, H. M., Rauch, U., & Liaw, S. S. (2010). Investigating learners' attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171-1182. https://doi.org/10.1016/j.compedu.2010.05.014Jacobson, J. (2017). Authenticity in immersive design. In D., Liu, C., Dede, R., Huang, & J., Richards (Eds.), Virtual, augmented, and mixed realities in education (pp. 35-54). New York: Springer. https://doi.org/10.1007/978-981-10-5490-7_3Lin, T. J., & Lan, Y. J. (2015). Language learning in virtual reality environments: Past, present, and future. Journal of Educational Technology & Society, 18(4), 486-497.Liu, D., Bhagat, K. K., Gao, Y., Chang, T., & Huang, R. (2017). The potentials and trends of virtual reality in education. In D., Liu, C., Dede, R., Huang, & J., Richards (Eds.), Virtual augmented, and mixed realities in education (pp. 105-130). New York: Springer. https://doi.org/10.1007/978-981-10-5490-7_7Lloyd, A., Rogerson, S., & Stead, G. (2017). Imagining the potential for using virtual reality technologies in language learning. In M. Carrier, R. M. Damerow, & K. M. Bailey (Eds.), Digital language learning and teaching: Research, theory, and practice (pp. 222-234). Abingdon: Routledge. https://doi.org/10.4324/9781315523293-19Sadler, R. (2017). Virtual worlds and language education. In S. L. Thorne & S. May (Eds.), Language, education and technology (pp. 375-388). New York: Springer International Publishing. https://doi.org/10.1007/978-3-319-02237-6_29Schott, C., & Marshall, S. (2018). 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Desarrollo de habilidades relacionadas con el uso de los ordenadores como herramienta para resolver problemas en el primer curso de física para ingeniería

[ES] Es usual encontrar tres asignaturas en el primer año de las carreras de ingenierías técnicas, es decir: cálculo, física general y programación. Como la física se encuentra en la base de conocimiento de las ingenierías técnicas, es naturalmente apropiada la introducción del Cálculo y la Programación como valiosas herramientas en el contexto de un problema de Física. Esto se puede lograr trasladando algunas Clases Prácticas de Física (dedicadas a la solución de problemas) hacia el laboratorio de ordenadores y por medio de una reformulación del problema, de modo que sea más adecuado para este tipo de situaciones computacionales. En este entorno, los estudiantes logran reunir, por ejemplo, herramientas de programación y métodos numéricos, junto con las leyes de la Física, con el objetivo de abordar modelos más realistas, diferentes de los que usualmente se tratan comúnmente en el pizarrón. Este tipo de problema computacional de Física incrementa la motivación de los estudiantes de ingeniería por medio de una imbibición en escenarios cuyos modelos son más cercanos a los problemas reales que ellos enfrentarán luego en el desempeño profesional y científico. Este hecho es particularmente relevante para el primer año de las carreras de ingeniería donde el desarrollo de habilidades profesionales es obviado y relegado para años superiores. En el presente trabajo ilustraremos estas ideas a través del conocido problema del "Movimiento del un cuerpo sujeto a la fuerza de arrastre del aire". Las ideas básicas de este trabajo han sido experimentadas en el curso de física de primer año de la carrera de telecomunicaciones y electrónica de la Universidad de Pinar del Río, Cuba en el año 2010.[EN] Usually one can find three subjects in the first year of the syllabus of any technical engineering career, namely, calculus, general physics and programming. Being physics a matter lying on the grounds of technical engineering it becomes naturally appropriate to introduce the use of calculus and programming as useful tools in the context of a physics problem. This can be accomplished by moving some Practical Classes of Physics (problem solving) into the computer pool and by reformulating the physics problems in order to make them more appropriate for this kind of approach. In this environment, students put together, for instance, programming tools and numerical methods, along with the physical laws in order to address more realistic models, diferent from those which can usually be treated on the blackboard. This kind of computational physics problems increases the motivation of the engineering students by embedding them into sceneries whose models are closer to those real problems they will be facing later in their professional and scientific life. This is particularly relevant for the first year of the engineering careers when the development of this kind of professional skills is usually skipped. In the present work we will illustrate these ideas by means of the known problem of "The motion of a body subject to air drag force". The basic ideas of this work have been experienced in the physics course of first year undergraduate students of telecommunication and electronics engineering of Pinar del Río University, Cuba in 2010.We would like to thank the Department of physics of Pinar del R´ıo University, Cuba for the application of this problem in its teaching process. This work has been partially supported by the Universitat Polit`ecnica de Val`encia under APICID funds and by the Ministerio de Ciencia e Innovación (Spain) under the grant DPI2008- 02953. 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Herramientas digitales para la modelización matemática colaborativa en línea

[EN] To enable collaborative modeling activities online digital tools are essential. In this paper we present a holistic and adaptable concept for the development and implementation of modeling activities – which could especially be fruitful in times of homeschooling and distance learning. The concept is based on two digital tools: Jupyter Notebooks and a communication platform with video conferences.We carried out this concept in the context of two types of modeling activities: guided modeling days, where the students work on previously prepared and didactically developed digital learning material, and modeling weeks, in which the students work on open problems from research and industry very freely. In this paper the usage of Jupyter Notebook in modeling activities is presented and illustrated with the example of the optimization of a solar power plant. On top, we share our experiences in online modeling activities with high-school students in Germany.[ES] Para facilitar las actividades de modelización colaborativa en línea, las herramientas digitales son esenciales. En este trabajo presentamos un concepto holístico y adaptable para el desarrollo y la implementación de actividades de modelización – que podría ser especialmente provechoso en tiempos de educación a distancia. El concepto se basa en dos herramientas digitales: Jupyter Notebooks y una plataforma de comunicación con videoconferencia. Realizamos este concepto en el contexto de dos tipos de actividades de modelización matemática: días de modelización guiada, en los que los alumnos trabajan con material de aprendizaje digital previamente preparado y desarrollado didácticamente, y semanas de modelización, en las que los alumnos trabajan en problemas abiertos de la investigación o de la industria de forma libre. Se presenta el uso de Jupyter Notebook en las actividades de modelización y se ilustra con el ejemplo de la optimización de una planta solar. Además, compartimos nuestras experiencias en actividades de modelización en línea con estudiantes de secundaria en Alemania.Schönbrodt, S.; Wohak, K.; Frank, M. (2022). Digital Tools to Enable Collaborative Mathematical Modeling Online. Modelling in Science Education and Learning. 15(1):151-174. https://doi.org/10.4995/msel.2022.16269OJS151174151Blum, W. (2015). Quality Teaching of Mathematical Modelling: What Do We Know, What Can We Do? In S. J. Cho (Ed.), The Proceedings of the 12th International Congress on Mathematical Education (pp. 73-96). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-12688-3_9Blum, W., & Borromeo Ferri, R. (2009). Mathematical Modelling: Can it Be Taught and Learnt? Journal of Mathematical Modelling and Application, 1 (1), 45-58.Blum, W., Galbraith, P., Henn, H.-W., & Niss, M. (2007). Modelling and Applications in Mathematics Education. New York: Springer. https://doi.org/10.1007/978-0-387-29822-1Blum, W., & Lei, D. (2007). How do students and teachers deal with modelling problems? In C. Haines, P. Galbraith, W. Blum, & S. Khan (Eds.), Mathematical Modelling (ICTMA 12): Education, Engineering and Economics (pp. 222-231). Chichester: Horwood Publishing. https://doi.org/10.1533/9780857099419.5.221Borromeo Ferri, R. (2006, 04). Theoretical and empirical differentiations of phases in the modeling process. ZDM, 38(2), 86-95. doi: 10.1007/BF02655883 https://doi.org/10.1007/BF02655883Bruffee, K. (1995). Sharing Our Toys: Cooperative Learning versus Collaborative Learning. Change, 27 (1), 12-18. https://doi.org/10.1080/00091383.1995.9937722Computer-Based Maths. (n.d.). The Computational Thinking Process Poster. www.computationalthinking.org/helix. (accessed: 2021-01-23)Frank, M., Richter, P., Roeckerath, C., & Schönbrodt, S. (2018). Wie funktioniert eigentlich GPS? - Ein Computergestützter Modellierungsworkshop [How does GPS actually work? - A Computer-Supported Modeling Workshop]. In Greefrath, G. and Siller, S. (Ed.), Digitale Werkzeuge, Simulationen und mathematisches Modellieren [Digital tools, simulations and mathematical modeling] (pp. 137-163). Wiesbaden: Springer-Verlag. https://doi.org/10.1007/978-3-658-21940-6_7Frey, K. (2012). Die Projektmethode: Der Weg zum bildenden Tun [The project method: the path to educational action] (12th ed.; U. Schäfer, Ed.). Weinheim: Beltz.Gerhard, M., Hattebuhr, M., Schönbrodt, S., & Wohak, K. (2021). Aufbau und Einsatzmöglichkeiten des Lehr- und Lernmaterials [Structure and possible applications of the teaching and learning material]. In M. Frank & C. Roeckerath (Eds.), Neue Materialien für einen realitätsbezogenen Mathematikunterricht 9 [New materials for reality-based mathematics teaching 9]. Springer Spektrum.Greefrath, G., & Siller, H.-S. (2018). Digitale Werkzeuge, Simulationen und mathematisches Modellieren [Digital tools, simulations and mathematical modeling]. In Greefrath, G. and Siller, S. (Ed.), Digitale Werkzeuge, Simulationen und mathematisches Modellieren [Digital tools, simulations and mathematical modeling] (pp. 3-22). Wiesbaden: Springer-Verlag. https://doi.org/10.1007/978-3-658-21940-6_1Golub, J. (1988). Focus on Collaborative Learning. Urbana, Illinois: National Council of Teachers of English.Johnson, D., & Johnson, R. (1989). Cooperation and Competition: Theory and Research. Interaction Book Company.Johnson, D., & Johnson, R. (2014). Using technology to revolutionize cooperative learning: An opinion. Frontiers in Psychology, 5 , 1-3. https://doi.org/10.3389/fpsyg.2014.01156Panitz, T. (1999a). Collaborative versus cooperative learning: A comparison of the two concepts which will help us understand the underlying nature of interactive learning. ERIC Document Reproduction Service No. ED448443.Panitz, T. (1999b). The Motivational Benefits of Cooperative Learning. New directions for teaching and learning, 78. https://doi.org/10.1002/tl.7806Roberts, T. (2004). Preface. In T. Robert (Ed.), Online Collaborative Learning. Hershey, London: Information Science Publishing.Nason R. and Woodruff E. (2004). Online Collaborative Learning in Mathematics: Some Necessary Innovations. Online Collaborative Learning. Robert T.S (Ed.) pp 103-131 Information Science Publishing, Hershey (London) https://doi.org/10.4018/978-1-59140-174-2.ch005Siller, H.-S., & Greefrath, G. (2010). Mathematical Modelling in Class regarding to Technology. In Proceedings of the 6th CERME conference (pp. 2136-2145). (CERME-Proceedings)Greefrath G.and Siller H-St (2018). Digitale Werkzeuge, Simulationen und mathematisches Modellieren (Digital tools, simulations and mathematical modeling). Digitale Werkzeuge, Simulationen und mathematisches Modellieren (Digital tools, simulations and mathematical modeling). Greefrath G. and Siller S. (Eds.) pp. 3-22. Springer-Verlag (Wiesbaden) https://doi.org/10.1007/978-3-658-21940-6_1Hänze, M., Schmidt-Weigand, F., & Staudel, L. (2010). Gestufte Lernhilfen [Staggered learning aids]. In S. Boller & R. Lau (Eds.), Innere Differenzierung in der Sekundarstufe II. Ein Praxishandbuch für Lehrer/innen [Inner differentiation in upper secondary education. A practical handbook for teachers] (pp. 63-73). Weinheim: Beltz.Kaiser, G., & Schwarz, B. (2010). Authentic Modelling Problems in Mathematics Education - Examples and Experiences. Journal fur Mathematik-Didaktik, 31 , 51-76. https://doi.org/10.1007/s13138-010-0001-3Krajcik J.S. and Blumenfeld Ph.C. (2005). Project-Based Learning. The Cambridge Handbook of the Learning Sciences. Sawyer, R. Keith (Ed.) pp 317-334. Cambridge Handbooks in Psychology. Cambridge University Press (Cambridge) doi:10.1017/CBO9780511816833.020 https://doi.org/10.1017/CBO9780511816833.020Ludwig, M. (1997). Projekte im Mathematikunterricht des Gymnasiums [Projects in mathematics lessons of the high school] (phdthesis). Julius-Maximilians-Universitöt Würzburg. https://doi.org/10.1007/BF03338857Maaß, K. (2010). Classifiation Scheme for Modelling Tasks. Journal fur Mathematik-Didaktik, 31 (2), 285-311. doi: 10.1007/s13138-010-0010-2 https://doi.org/10.1007/s13138-010-0010-2Bock, W., & Bracke, M. (2015). Applied School Mathematics - Made in Kaiserslautern. In H. Neuntzer & D. Prätzel-Wolters (Eds.), Currents in industrial mathematics: From concepts to research to education (pp. 403-437). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-48258-2Kronberg, R., York-Barr, J., Arnold, K., Gombos, S., Truex, S., Vallejo, B., & Stevenson, J. (1997). Differentiated Teaching & Learning in Heterogeneous Classrooms: Strategies for Meeting the Needs of All Students. Washington D.C.: ERIC Clearinghouse. Retrieved from https://eric.ed.gov/?id=ED418538Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409-426). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511816833.025Niss, M. (1992). Applications and modelling in school mathematics - directions for future development. Roskilde: IMFUFA Roskilde Universitetscenter.Schmidt, L. (2019). Machine Learning: automatische Bilderkennung mit Mathematik?! - Ein Lehr-Lern- Modul im Rahmen eines mathematischen Modellierungstages für Schülerinnen und Schüler der Sekundarstufe II [Machine Learning: automatic image recognition with mathematics?! - A teaching-learning module in the context of a mathematical modeling day for high school students]. www.cammp.online Masterthesis4druck.pdf. (Master's thesis, RWTH Aachen, accessed: 2021-02-23)Schönbrodt, S., & Frank, M. (2020). Schüler/innen forschen zu erneuerbaren Energien - Optimierung eines Solarkraftwerks [Students research on renewable energies - Optimization of a solar power plant]. In H.-S. Siller, W. Weigel, & J. F. Worler (Eds.), Beiträge zum Mathematikunterricht [Contributions to mathematics education] (pp. 1534-1534). Münster: WTM-Verlag.Schönbrodt, S. (2019). Maschinelle Lernmethoden für Klassifizierungsprobleme - Perspektiven für die mathematische Modellierung mit Schülerinnen und Schülern [Machine learning methods for classification problems - perspectives for mathematical modeling with students]. Wiesbaden: Springer Spektrum. https://doi.org/10.1007/978-3-658-25137-6Vos, P. (2011). What is 'authentic' in the teaching and learning of mathematical modelling? In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman (Eds.), Trends in Teaching and Learning of Mathematical Modelling, ICTMA 14 (pp. 713-722). Dordrecht: Springer. https://doi.org/10.1007/978-94-007-0910-2_68Winter, H. (1995). Mathematikunterricht und Allgemeinbildung [Mathematics education and general education]. Mitteilungen der Gesellschaft für Didaktik der Mathematik, 61 , 37-46. Retrieved 23 January, 2021, from https://ojs.didaktik-der-mathematik.de/index.php/mgdm/article/view/69/80Wohak, K., & Frank, M. (2019). Complex Modeling: Insights into our body through computer tomography - perspectives of a project day on inverse problems. In U. T. Jankvist, M. van den Heuvel-Panhuizen, & M. Veldhuis (Eds.), Eleventh Congress of the European Society for Research in Mathematics Education (pp. 4815-4822). Utrecht: Freudenthal Group.Wohak, K., Sube, M., Schönbrodt, S., Frank, M., & Roeckerath, C. (2021). Authentische und relevante Modellierung mit Schülerinnen und Schülern an nur einem Tag?! [Authentic and relevant modeling with students in just one day?!]. In M. Bracke, M. Ludwig, & K. Vorhölter (Eds.), Modellierungsprojekte mit Schülerinnen und Schülern. 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Learning to communicate computationally with Flip: a bi-modal programming language for game creation

Teaching basic computational concepts and skills to school children is currently a curricular focus in many countries. Running parallel to this trend are advances in programming environments and teaching methods which aim to make computer science more accessible, and more motivating. In this paper, we describe the design and evaluation of Flip, a programming language that aims to help 11–15 year olds develop computational skills through creating their own 3D role-playing games. Flip has two main components: 1) a visual language (based on an interlocking blocks design common to many current visual languages), and 2) a dynamically updating natural language version of the script under creation. This programming-language/natural-language pairing is a unique feature of Flip, designed to allow learners to draw upon their familiarity with natural language to “decode the code”. Flip aims to support young people in developing an understanding of computational concepts as well as the skills to use and communicate these concepts effectively. This paper investigates the extent to which Flip can be used by young people to create working scripts, and examines improvements in their expression of computational rules and concepts after using the tool. We provide an overview of the design and implementation of Flip before describing an evaluation study carried out with 12–13 year olds in a naturalistic setting. Over the course of 8 weeks, the majority of students were able to use Flip to write small programs to bring about interactive behaviours in the games they created. Furthermore, there was a significant improvement in their computational communication after using Flip (as measured by a pre/post-test). An additional finding was that girls wrote more, and more complex, scripts than did boys, and there was a trend for girls to show greater learning gains relative to the boys

Hiding in Plain Sight: Identifying Computational Thinking in the Ontario Elementary School Curriculum

Given a growing digital economy with complex problems, demands are being made for education to address computational thinking (CT) – an approach to problem solving that draws on the tenets of computer science. We conducted a comprehensive content analysis of the Ontario elementary school curriculum documents for 44 CT-related terms to examine the extent to which CT may already be considered within the curriculum. The quantitative analysis strategy provided frequencies of terms, and a qualitative analysis provided information about how and where terms were being used. As predicted, results showed that while CT terms appeared mostly in Mathematics, and concepts and perspectives were more frequently cited than practices, related terms appeared across almost all disciplines and grades. Findings suggest that CT is already a relevant consideration for educators in terms of concepts and perspectives; however, CT practices should be more widely incorporated to promote 21st century skills across disciplines. Future research would benefit from continued examination of the implementation and assessment of CT and its related concepts, practices, and perspectives

Computer Programming Effects in Elementary: Perceptions and Career Aspirations in STEM

The development of elementary-aged students’ STEM and computer science (CS) literacy is critical in this evolving technological landscape, thus, promoting success for college, career, and STEM/CS professional paths. Research has suggested that elementary- aged students need developmentally appropriate STEM integrated opportunities in the classroom; however, little is known about the potential impact of CS programming and how these opportunities engender positive perceptions, foster confidence, and promote perseverance to nurture students’ early career aspirations related to STEM/CS. The main purpose of this mixed-method study was to examine elementary-aged students’ (N = 132) perceptions of STEM, career choices, and effects from pre- to post-test intervention of CS lessons (N = 183) over a three-month period. Findings included positive and significant changes from students’ pre- to post-tests as well as augmented themes from 52 student interviews to represent increased enjoyment of CS lessons, early exposure, and its benefits for learning to future careers