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Enregistrement W3023977702 · doi:10.21009/jpud.141.04

Recognize Geometry Shapes through Computer Learning in Early Math Skills

2020· article· en· W3023977702 sur OpenAlex

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Notice bibliographique

RevueJPUD - Jurnal Pendidikan Usia Dini · 2020
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueChild Development and Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAnimationLearning cycleImitationComputer scienceMathematics educationGeometryMathematicsArtificial intelligenceComputer graphics (images)Psychology

Résumé

récupéré en direct d'OpenAlex

One form of early mathematical recognition is to introduce the concept of geometric shapes. Geometry is an important scientific discipline for present and future life by developing various ways that fit 21st century skills. This study aims to overcome the problem of early mathematical recognition of early childhood on geometry, especially how to recognize geometric forms based on computer learning. A total of 24 children aged 4-5 years in kindergarten has to carrying out 2 research cycles with a total of 5 meetings. Treatment activities in each learning cycle include mentioning, grouping and imitating geometric shapes. There were only 7 children who were able to recognize the geometric shapes in the pre-research cycle (29.2%). An increase in the number of children who are able to do activities well in each research cycle includes: 1) The activities mentioned in the first cycle and 75% in the second cycle; 2) Classifying activities in the first cycle were 37.5% and 75% in the second cycle; 3) Imitation activities in the first cycle 54.2% and 79.2% in the second cycle. The results of data acquisition show that computer learning application can improve the ability to recognize geometric shapes, this is because computer learning provides software that has activities to recognize geometric shapes with the animation and visuals displayed. Keywords: Early Childhood Computer Learning, Geometry Forms, Early Math Skills Reference Alia, T., & Irwansyah. (2018). Pendampingan Orang Tua pada Anak Usia Dini dalam Penggunaan Teknologi Digital. A Journal of Language, Literature, Culture and Education, 14(1), 65– 78. https://doi.org/10.19166/pji.v14i1.639 Ameliola, S., & Nugraha, H. D. (2013). 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J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., ... Japel, C. (2007). School Readiness and Later Achievement. Developmental Psychology, 43(6), 1428–1446. https://doi.org/10.1037/0012-1649.43.6.1428 Duncan, G. J., & Magnuson, K. (2011). The nature and impact of early achievement skills, attention skills, and behavior problems. Whither Opportunity?: Rising Inequality, Schools, and Children’s Life Chances, (0322356), 47–69. Edwards, S. (2009). Early Childhood Education and Care: a sociocultural Approach. New South Wales: Pademelon Press. Feliyanah, Norman, S., & Yulidesni. (2014). Meningkatkan Kemampuan Matematika dengan Menggunakan Teknik Mengurutkan dan Membandingkan. Universitas Bengkulu. Gardner, H. (2011). Frame of Mind ; The theory of Multiple Intelegences. New York: Basic Book. Gimbert, B., & Cristol, D. (2004). Teaching Curriculum with Technology: Enhancing Children’s Technological Competence During Early Childhood. Early Childhood Education Journal, 31(1). Gulay, H. (2011a). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252. Gulay, H. (2011b). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252–257. Gunawan, I., & Palupi, A. R. (2012). Taksonomi Bloom-Revisi Ranah Kognitif; Kerangka Landasan untuk Pembelajaran, Pengajaran, dan Penilaian. Jurnal Pendidikan Dasar Dan Pembelajaran, 2 No.2, 100–108. Inan, H. Z., & Dogan-Temur, O. (2010). Understanding kindergarten teachers’ perspectives of teaching basic geometric shapes: A phenomenographic research. ZDM - International Journal on Mathematics Education, 42(5), 457–468. https://doi.org/10.1007/s11858-010- 0241-1 Jackman, H. I., Beaver, N. H., & Wyatt, S. S. (2014). Early Childhood Curriculum: A child’s connection to the world. (sixth edit). Canada: Cengage Learning. Kennedy, L. M., Tipps, S., & Johnson, A. (2008). Guiding Children’s Learning of Mathematic (Eleventh E; Belmot, Ed.). CA: Thomson Wadsworth. Mackintosh, B. B., & McCoy, D. C. (2019). Exploring Social Competence as a Mediator of Head Start’s Impact on Children’s Early Math Skills: Evidence from the Head Start Impact Study. Early Education and Development, 30(5), 655–677. https://doi.org/10.1080/10409289.2019.1576156 Martin, M. O., Mullis, I. V. S., Foy, P., & Stanco, G. M. (2011). Results in Science. Mirawati. (2017). Matematika Kreatif; Pembelajaran Matematika bagi Anak Usia Dini Melalui Kegiatan yang Menyenangkan dan Bermakna. Jurnal Anak Usia Dini Dan Pendidikan Anak Usia Dini, 3. Mohammad, M., & Mohammad, H. (2012). Computer integration into the early childhood curriculum. Education, 133(1), 97–116. National Research Council. (2009). Mathematics Learning in Early Chidhood Paths Toward Excellence and Equity (C. T. Cross, T. Woods, & H. Schweingruber, Eds.). Washinton D.C: The National Academies Press. Norton, A., & Nurnberger-Haag, J. (2018). Bridging frameworks for understanding numerical cognition. Journal of Numerical Cognition, 4(1), 1–8. https://doi.org/10.5964/jnc.v4i1.160 Novitasari, D. R. (2010). Pembangunan Media Pembelajaran Bahasa Inggris Untuk Siswa Kelas 1 Pada Sekolah Dasar Negeri 15 Sragen. Sentra Penelitian Engineering Dan Edukas, Volume 2 N. Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2017). Improving Mathematics Teaching in Kindergarten with Realistic Mathematical Education. Early Childhood Education Journal, 45(3), 369–378. https://doi.org/10.1007/s10643-015-0768-4 Papalia, Old, & Feldman. (2009). Human Development (Psikologi Perkembangan (Kesembilan). Jakarta: Kencana. Paquette, K. R., Fello, S. E., & Jalongo, M. R. (2007). The talking drawings strategy: Using primary children’s Illustrations and oral language to improve comprehension of expository text. Early Childhood Education Journal, 35(1), 65–73. https://doi.org/10.1007/s10643- 007-0184-5 Putra, L. D., & Ishartiwi. (2015). Pengembangan Multimedia Pembelajaram Interaktif Mengenal Angka dan Huruf untuk Anak Usia Dini. Jurnal Inovasi Teknologi Pendidikan, 2(2). Rich, B., & Thomas, C. (2009). Geometry: Includes Plane, Analytic, and Transformational Geometries. . (4th Editio). New York: McGraw-Hill. Rochanah, L. (2016). Pemanfaatan Media Berbasis Komputer Untuk Meningkatkan Kemampuan Huruf pada Anak Usia Dini (Urgensi Media Berbasis Komputer pada Peningkatan Kemampuan Mengenal Huruf ). Jurnal Program Studi PGRA, Volume 2 N, 1–8. Runtukahu, T., & Kandou, S. (2014). Pembelajaran matematika dasar bagi anak berkesulitan belajar. Yogyakarta: Ar-ruzz Media. Santrock, J. W. (2016). Children (Thirteenth). New York: McGraw-Hill Education. Sarama, J., & Clements, D. H. (2006). Mathematics, Young Students, and Computers: Software, Teaching Strategies and Professional Development. The Mathematics Educato, 9(2), 112– 134. Schoenfeld, A. H., & Stipek, D. (2011). Math Matters. Barkeley, California.Shilpa, S., & Sunita, M. (2013). A Study About Role of Multimedia i

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,224
Score d'incertitude au seuil0,867

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,302
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle