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11_04_2019 EDUCON Award: "Promoting computational thinking skills in Primary School students to improve learning of geometry", UAM

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Authors: Leovy Echeverría, Ruth Cobos, Mario Morales, Fernando Moreno y Víctor Negrete (Universidad Autónoma de Madrid, Spain)

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11_04_2019 EDUCON Award: "Promoting computational thinking skills in Primary School students to improve learning of geometry", UAM

  1. 1. Promoting Computational Thinking skills in primary school students to improve learning of geometry Ruth Cobos Computer Science and Engineering Department Universidad Autónoma de Madrid Madrid, Spain ruth.cobos@uam.es Victor Negrete Facultad de Ingeniería Informática Universidad Pontificia Bolivariana Montería, Colombia victor.negreteb@upb.edu.co Leovy Echeverría Facultad de Ingeniería Informática Universidad Pontificia Bolivariana Montería, Colombia leovy.echeverria@upb.edu.co Mario Morales Departamento de Matemáticas y Estadística Universidad de Córdoba Montería, Colombia mamorales@correo.unicordoba.edu.co Fernando Moreno Facultad de Ingeniería Informática Universidad Pontificia Bolivariana Montería, Colombia fernando.morenoo@upb.edu.co
  2. 2. AGENDA I. INTRODUCTION  What’s Computational Thinking?  This paper’s scope II. STATE OF THE ART  Concepts related to Computational Thinking  Computational Thinking initiatives III. APPROACH  General Description  The Environment IV. EXPERIMENTATION  An exploratory data analysis  Case study  Results and discussions V. CONCLUSIONS AND FUTURE WORK
  3. 3. I. INTRODUCTION What’s Computational Thinking? Learning strategy based on the use of Computer Science concepts to solve a problem in any domain. Kindergarten Primary school Secondary school Higher education CT
  4. 4. I. INTRODUCTION This paper’s scope Learning of geometry for both primary and secondary school students cognitive aspects of visualization Integrating technological aspects into the teaching of geometry to promote computational thinking (CT) Implementation of CT initiatives to improve STEM (Science, Technology, Engineering, and Mathematics) Education
  5. 5. II. STATE OF THE ART Concepts related to CT Structure models  Michaelson  Barr & Stephenson  Weintrop K-12 curriculum standard CT Language (CTL) Data Algorithm design Automation Problem solving
  6. 6. II. STATE OF THE ART CT Initiatives STEM skills development Infuse any subject Visual Tangible Gamified Automation Design Communication FRAMEWORK …
  7. 7. III. APPROACH General Description  Face-to-face activities + geometry learning activities supported by Moodle-G  Two CT skills based on Mathematics and Science taxonomy (4 categories and 22 CT skills):  To analyse and to visualize data  Practice exercises about geometric solids
  8. 8. III. APPROACH The environment: Moodle-G
  9. 9. IV. EXPERIMENTATION Students’ opinion on the potential use of the proposed toolLearning tools known and used by the students 5 schools 185 primary students of them  Age: 9-10 years old AS CL C FJC PS TOTAL WEB and others 20 22 20 13 27 102 57 52 55 36 75 55 % NONE 2 13 7 16 4 42 5 30 19 44 11 22 % An exploratory data analysis
  10. 10. IV. EXPERIMENTATION Case study Comfacor school 32 students from fourth grade Topic: construction of geometric solids.  Prisms  Pyramids  Round bodies Two types of exercises:  Watching and selecting  Elaboration and analyzing of geometric solids Exercise CT Skill involved Finalized taxonomy practice Select a prism Selection and watching Visualization Analysis Draw a pyramid Data generation Analysis Exercises conducted
  11. 11. IV. EXPERIMENTATION  Results and discussions Students’ motivation “The results obtained with the t-test corroborated that the students in the experimental group obtained better performance (Mean=3.9) than the students from control group (Mean=3.5).” Group G N Mean Min Max Control F 17.0 3.5 2.0 4.0 M 17.0 3.4 2.0 4.0 Experimental F 17.0 3.8 3.0 5.0 M 15.0 3.9 2.0 5.0 USAGE LEARNING SOCIAL TOTAL MOTIVATION - 0 0 0 0 0 0 0 0 5 1 2 8 16 3 6 8 % + 13 11 5 29 40 34 16 31 % 14 20 25 59 44 63 78 61 % Students’ scores G: gender N: sample size
  12. 12. V. CONCLUSIONS AND FUTURE WORK STEM Education initiative Two specific CT skills: the visualization and the analysis of geometric solids Moodle-G platform Positive results in the students’ motivation were found. Specifically, the most of the students felt very motivated with the social interaction supported by the Moodle-G platform The assertive results derived from the case study corroborate that the implementation of the proposed approach enhances the students’ performance We propose to enhance both the approach and the environment
  13. 13. REFERENCES  M. Dogan and R. Icel, “The Role of Dynamic Geometry Software in the Process of Learning: GeoGebra Example about Triangles,” Int. J. Hum. Sci., vol. 8, no. 1, pp. 1441–1458, 2011.  K. K. Bhagat and C. Y. Chang, “Incorporating GeoGebra into geometry learning-A lesson from India,” Eurasia J. Math. Sci. Technol. Educ., vol. 11, no. 1, pp. 77–86, 2015.  R. A. Saha, A. F. M. Ayub, and R. A. Tarmizi, “The effects of GeoGebra on mathematics achievement: Enlightening Coordinate Geometry learning,” in Procedia - Social and Behavioral Sciences, 2010, vol. 8, pp. 686–693.  N. Sinclair and C. D. Bruce, “New opportunities in geometry education at the primary school,” ZDM, vol. 47, no. 3, pp. 319– 329, 2015.  R. Marrades and Á. Gutiérrez, “Proofs produced by secondary school students learning geometry in a dynamic computer environment,” Educ. Stud. Math., vol. 44, no. 1–3, pp. 87–125, 2000.  M. T. Battista, “Spatial visualization and gender differences in high school geometry,” J. Res. Math. Educ., vol. 21, no. 1, pp. 47–60, 1990.  Á. Gutiérrez, “Visualization in 3-Dimensional Geometry: In Search of a Framework,” Proc. 20th PME Conf., vol. 1, pp. 3–19, 1996.  H. Kaufmann, D. Schmalstieg, and M. Wagner, “Construct3D: A Virtual Reality Application for Mathematics and Geometry Education,” Educ. Inf. Technol., vol. 5, no. 4, pp. 263–276, 2000.  J. A. Qualls and L. B. Sherrell, “Why Computational Thinking Should Be Integrated Into the Curriculum,” J. Comput. Sci. Coll., vol. 25, no. 5, pp. 66–71, 2010.  L. Wolf, A. Yadav, J. Good, M. Margaritis, and M. Berges, “Computer Science (CS) and Computational Thinking (CT) International Perspectives on Developing Student and Teacher Competencies,” in SITE–Society for Information Technology and Teacher Education, 2015, pp. 7633–7636.  V. Barr and C. Stephenson, “Bringing Computational Thinking to K-12: What is Involved and What is the Role of the Computer Science Education Community ?,” ACM Inroads, vol. 2, no. 1, pp. 48–54, 2011.  G. Keren and M. Fridin, “Kindergarten Social Assistive Robot (KindSAR) for children’s geometric thinking and metacognitive development in preschool education: A pilot study,” Comput. Human Behav., vol. 35, pp. 400–412, 2014.
  14. 14. ACKNOWLEDGMENT This research was partly funded by UPB Montería project number 018-03/16-SI007 and e-Madrid project, number P2018/TCS-4307. Besides, the participation of the Comfacor School in the city of Montería is acknowledged and appreciated
  15. 15. THANKS FOR YOUR ATTENTION

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