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Abstract
The present study investigated the effectiveness of a developed learning package in teaching Geometry 7 specifically in constructions and solving problems involving polygons. Geometry is one of the subjects that many students find to be the most difficult and may be challenging for some children. The major goal of this study is to determine the effect of the developed learning package in teaching Geometry 7 improving the skills of construction and problem solving skills of the students. The learning package sought to provide an engaging learning environment by merging real-world situations and game-based components.
The research design adapted a quasi-experimental design wherein it has a control and an experimental group. Pretest and posttest were conducted in the control and experimental group to compare the performance of students who utilized the learning package with those who did not. With the pretest and posttest scores of the students, it was found that the learning package was not effective in school A but effective in school B. The learning package has had a big impact in rural areas, resulting in the absence of significant differences between rural and urban schools. Furthermore, the study did not produce significant interaction between the locality and the usage of the developed learning package. Thus, the Developed Learning Package improved students’ comprehension and engagement with Geometry.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Sy, J. J. P. P., Ambay, R. J. C., & Mercado, J. C. (2024). Development, Implementation, and Evaluation of Instructional Learning Package in Teaching-Learning Geometry 7. International Journal of Multidisciplinary: Applied Business and Education Research, 5(3), 939-948. https://doi.org/10.11594/ijmaber.05.03.17
References
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Boutte, G. S. (2012). Urban schools. Urban Ed-ucation, 47(2), 515–550. https://doi.org/10.1177/0042085911429583
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Duodu, S., Gyamfi, M. A., Dogli, P. C., & Somea-Addai, E. (2020). Implications of theories for online teaching and learning; an in-tervention to the effects of COVID- 19. . . ResearchGate. https://www.researchgate.net/publication/344575599_Implications_of_theories_for_online_teaching_and_learning_an_intervention_to_the_effects_of_COVID-_19_pandemic_on_Education_in_Ghana
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Fonna, M., & Mursalin, M. (2019). Using of wingeom software in geometry learning to improving the of mathematical repre-sentation ability. Malikussaleh Journal of Mathematics Learning (MJML), 1(2), 40-43. doi:10.29103/mjml.v1i2.1174
Fyfe, E. R., & Brown, S. A. (2020). This is easy, you can do it! Feedback during mathe-matics problem solving is more beneficial when students expect to succeed. Instruc-tional Science. doi:10.1007/s11251-019-09501-5
Gafoor, K. A., & Kurukkan, A. (2015). Why high school students feel mathematics diffi-cult? An exploration of affective beliefs. https://eric.ed.gov/?id=ED560266
Galloway, C. M., & Lasley, T. J. (2010). Effective urban teaching environments for the 21st century. Education and Urban Society, 42(3), 269–282. https://doi.org/10.1177/0013124509357005
Indira, P. (2020). MULTIMEDIA PACKAGE FOR TEACHING COMPUTER SCIENCE AMONG RURAL AND URBAN STUDENTS AT PLUS ONE: VALIDATION AND ITS EFFECIVE-NESS. https://www.semanticscholar.org/paper/MULTIMEDIA-PACKAGE-FOR-TEACHING-COMPUTER-SCIENCE-AT-Indira-Dhanalaksh-mi/81844557bf0f400b7de80926f21ae21ffa6d7840
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Laurens, T., Batlolona, F. A., Batlolona, J. R., & Leasa, M. (2018). How Does Realistic Mathematics Education (RME) Improve Students’ Mathematics Cognitive Achievement?. EURASIA Journal of Math-ematics, Science and Technology Educa-tion, 14(2), 569-578. https://doi.org/10.12973/ejmste/76959
Levy, R. (2018, July 6). 5 tips for improving students’ success in math. Edutopia. https://www.edutopia.org/article/5-tips-improving-students-success-math/
Martin, L., & Towers, J. (2015). Growing math-ematical understanding through collec-tive image making, collective image hav-ing, and collective property noticing. Ed-ucational Studies in Mathematics, 88(1), 3–18. https://doi.org/10.1007/s10649-014-9552-4
McCowan, R. J., & McCowan, S. C. (1999). Item analysis for Criterion-Referenced tests.
Mercado, J. (2020). Development of Laborato-ry Manual in Physics for Engineers. In-ternational Journal of Science and Re-search, 9(10), 200–210.
Mishra, P., Pandey, C. K., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statisti-cal data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.aca_157_18
Morales, M. P. E. (2012). Development and Validation of a Concept Test in Introduc-tory Physics for Biology Students. https://www.semanticscholar.org/paper/Development-and-Validation-of-aConcept-Test-in-for-Mo-rales/01b0b681e209a7ccd34012fd9e2c693c5c540f80
Nasseri, Y. S. A., Renganathan, L., Nasseri, F. A., & Balushi, A. a. A. (2014). Impact of Stu-dents-Teacher Relationship on Student’s Learning: A Review of literature. Interna-tional Journal of Nursing Education, 6(1), 167. https://doi.org/10.5958/j.0974-9357.6.1.034
Ras, E. (2008). Improving application and un-derstanding of experience packages through learning spaces. https://doi.org/10.1145/1414004.1414058
Sawangsri, B. (2016). Learning Package by Means of the Inductive Teaching with Group Process. Universal Journal of Edu-cational Research, 4(8), 1924–1929. https://doi.org/10.13189/ujer.2016.040824
Sellström, E., & Bremberg, S. (2006). Is there a “school effect” on pupil outcomes? A re-view of multilevel studies. Journal of Epi-demiology and Community Health, 60, 149 - 155. https://doi.org/10.1136/jech.2005.036707.
Serin, H. (2018). Perspectives on the Teaching of Geometry: Teaching and learning Methods. Journal of Education and Train-ing, 5(1), 1. https://doi.org/10.5296/jet.v5i1.12115
Suantoa, E., Zakaria, E., & Maat, S. M. (2019). The development of the KARA module based on experiential learning approach-es in the threedimensional geometry blocks topic for lower secondary school students. International Journal of Innova-tion, Creativity and Change, 7(11), 26-46.
Supple, A. J., & Small, S. (2006). The influence of parental support, knowledge, and au-thoritative parenting on Hmong and Eu-ropean American adolescent develop-ment. Journal of Family Issues, 27(9), 1214–1232. https://doi.org/10.1177/0192513x06289063
Surya, E., & Putri, F. A. (2017). Improving Mathematical Problem-Solving Ability and SelfConfidence of High School Stu-dents through Contextual Learning Mod-el. Journal on Mathematics Education, 8(1), 85-94. http://dx.doi.org/10.22342/jme.8.1.3324.85-94
Tabot, B. A. & Mottanya, C. D. (2012). Effect of contextual characteristics of teaching practice schools on student teachers’ per-formance in Kenya. https://www.semanticscholar.org/paper/Effect-of-contextual-characteristics-of-teaching-on-Tabot-Mottan-ya/0006a84a875986d43ab9cbdaaacafd19fab7b212
Tongco, J., Silvederio, W. C., Salanawon, P. J., & Mercado, J. (2021). Development of Vir-tual Laboratory Simulation: e-SCILAB on Waves for Grade 7 Science. International Journal of Multidisciplinary: Applied Busi-ness and Education Research, 2(11), 1283-1297. https://doi.org/10.11594/10.11594/ijmaber.02.11.20
Verschaffel, L. & De Corte, E., (2015). Students' non-realistic mathematical modeling as a drawback of teachers' beliefs about and approaches to word problem solving. In B. Pepin & B. Roesken-Winter (Eds.), From beliefs to dynamic affect systems in mathematics education: Exploring a mo-saic of relationships and interactions (pp. 137–156). Springer International Publish-ing/Springer Nature. https://doi.org/10.1007/978-3-319-06808-4_7
Willson, V. L., & Putnam, R. R. (1982). A meta-analysis of pretest sensitization effects in experimental design. American Educa-tional Research Journal, 19(2), 249–258. https://doi.org/10.3102/00028312019002249
Zhao, C., & Kuh, G. (2004). Adding Value: Learning Communities and Student En-gagement. Research in Higher Education, 45, 115-138. https://doi.org/10.1023/B:RIHE.0000015692.88534.DE
Alegre, C.C. (2012) Computer Aided Instruc-tional tool in Linear Equation in two vari-ables. (Unpublished dissertation, Notre Dame of Marbel University Research and Publication Center
Alokan, F. B. (2013, September 3). Rural and Urban Differential in Student’s Academic Performance among Secondary School Students In Ondo State, Nigeria. https://www.richtmann.org/journal/index.php/jesr/article/view/559
Asare, N. A., & Siaw, A. (2015). Rural–Urban disparity in students’ academic perfor-mance in visual arts education. SAGE Open. https://doi.org/10.1177/2158244015612523
Bajaj, S. (2013). Study of learning environment of urban and rural government middle schools: An overview of Jammu district. https://www.semanticscholar.org/paper/Study-of-learning-environment-of-urban-and-rural-An-Ba-jaj/4e858d65f75d32048c0d3701ecf79213e57b1dez
Baker, D. P. (2009). The Educational Trans-formation of Work: Towards a New Syn-thesis. Journal of Education and Work, 22, 163-191. http://dx.doi.org/10.1080/13639080902957822
Boutte, G. S. (2012). Urban schools. Urban Ed-ucation, 47(2), 515–550. https://doi.org/10.1177/0042085911429583
Carini, R., Kuh, G., & Klein, S. (2006). Student Engagement and Student Learning: Test-ing the Linkages*. Research in Higher Ed-ucation, 47, 1-32. https://doi.org/10.1007/S11162-005-8150-9.
Chang, M., & Li, Y. (2015). Smart learning envi-ronments. In Lecture notes in educational technology. Springer Nature. https://doi.org/10.1007/978-3-662-44447-4
Duodu, S., Gyamfi, M. A., Dogli, P. C., & Somea-Addai, E. (2020). Implications of theories for online teaching and learning; an in-tervention to the effects of COVID- 19. . . ResearchGate. https://www.researchgate.net/publication/344575599_Implications_of_theories_for_online_teaching_and_learning_an_intervention_to_the_effects_of_COVID-_19_pandemic_on_Education_in_Ghana
Eash, T. (2017). The Importance of Variety in Mathematics Instruction. Study.com. Re-trieved October 28, 2022, from https://study.com/academy/lesson/theimportance-of-variety-in-mathematics-instruction.html
Fleming, G. (2019, August 7). Why math is dif-ficult - math and brain types. ThoughtCo. Retrieved October 28, 2022, from https://www.thoughtco.com/why-math-seems-moredifficult-for-some-students1857216
Fonna, M., & Mursalin, M. (2019). Using of wingeom software in geometry learning to improving the of mathematical repre-sentation ability. Malikussaleh Journal of Mathematics Learning (MJML), 1(2), 40-43. doi:10.29103/mjml.v1i2.1174
Fyfe, E. R., & Brown, S. A. (2020). This is easy, you can do it! Feedback during mathe-matics problem solving is more beneficial when students expect to succeed. Instruc-tional Science. doi:10.1007/s11251-019-09501-5
Gafoor, K. A., & Kurukkan, A. (2015). Why high school students feel mathematics diffi-cult? An exploration of affective beliefs. https://eric.ed.gov/?id=ED560266
Galloway, C. M., & Lasley, T. J. (2010). Effective urban teaching environments for the 21st century. Education and Urban Society, 42(3), 269–282. https://doi.org/10.1177/0013124509357005
Indira, P. (2020). MULTIMEDIA PACKAGE FOR TEACHING COMPUTER SCIENCE AMONG RURAL AND URBAN STUDENTS AT PLUS ONE: VALIDATION AND ITS EFFECIVE-NESS. https://www.semanticscholar.org/paper/MULTIMEDIA-PACKAGE-FOR-TEACHING-COMPUTER-SCIENCE-AT-Indira-Dhanalaksh-mi/81844557bf0f400b7de80926f21ae21ffa6d7840
Langoban, M. (2020). What Makes Mathemat-ics Difficult as a Subject for most Students in Higher Education? ResearchGate. https://www.researchgate.net/publication/342888714_What_Makes_Mathematics_Difficult_as_a_Subject_for_most_Students_in_Higher_Education
Laurens, T., Batlolona, F. A., Batlolona, J. R., & Leasa, M. (2018). How Does Realistic Mathematics Education (RME) Improve Students’ Mathematics Cognitive Achievement?. EURASIA Journal of Math-ematics, Science and Technology Educa-tion, 14(2), 569-578. https://doi.org/10.12973/ejmste/76959
Levy, R. (2018, July 6). 5 tips for improving students’ success in math. Edutopia. https://www.edutopia.org/article/5-tips-improving-students-success-math/
Martin, L., & Towers, J. (2015). Growing math-ematical understanding through collec-tive image making, collective image hav-ing, and collective property noticing. Ed-ucational Studies in Mathematics, 88(1), 3–18. https://doi.org/10.1007/s10649-014-9552-4
McCowan, R. J., & McCowan, S. C. (1999). Item analysis for Criterion-Referenced tests.
Mercado, J. (2020). Development of Laborato-ry Manual in Physics for Engineers. In-ternational Journal of Science and Re-search, 9(10), 200–210.
Mishra, P., Pandey, C. K., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statisti-cal data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.aca_157_18
Morales, M. P. E. (2012). Development and Validation of a Concept Test in Introduc-tory Physics for Biology Students. https://www.semanticscholar.org/paper/Development-and-Validation-of-aConcept-Test-in-for-Mo-rales/01b0b681e209a7ccd34012fd9e2c693c5c540f80
Nasseri, Y. S. A., Renganathan, L., Nasseri, F. A., & Balushi, A. a. A. (2014). Impact of Stu-dents-Teacher Relationship on Student’s Learning: A Review of literature. Interna-tional Journal of Nursing Education, 6(1), 167. https://doi.org/10.5958/j.0974-9357.6.1.034
Ras, E. (2008). Improving application and un-derstanding of experience packages through learning spaces. https://doi.org/10.1145/1414004.1414058
Sawangsri, B. (2016). Learning Package by Means of the Inductive Teaching with Group Process. Universal Journal of Edu-cational Research, 4(8), 1924–1929. https://doi.org/10.13189/ujer.2016.040824
Sellström, E., & Bremberg, S. (2006). Is there a “school effect” on pupil outcomes? A re-view of multilevel studies. Journal of Epi-demiology and Community Health, 60, 149 - 155. https://doi.org/10.1136/jech.2005.036707.
Serin, H. (2018). Perspectives on the Teaching of Geometry: Teaching and learning Methods. Journal of Education and Train-ing, 5(1), 1. https://doi.org/10.5296/jet.v5i1.12115
Suantoa, E., Zakaria, E., & Maat, S. M. (2019). The development of the KARA module based on experiential learning approach-es in the threedimensional geometry blocks topic for lower secondary school students. International Journal of Innova-tion, Creativity and Change, 7(11), 26-46.
Supple, A. J., & Small, S. (2006). The influence of parental support, knowledge, and au-thoritative parenting on Hmong and Eu-ropean American adolescent develop-ment. Journal of Family Issues, 27(9), 1214–1232. https://doi.org/10.1177/0192513x06289063
Surya, E., & Putri, F. A. (2017). Improving Mathematical Problem-Solving Ability and SelfConfidence of High School Stu-dents through Contextual Learning Mod-el. Journal on Mathematics Education, 8(1), 85-94. http://dx.doi.org/10.22342/jme.8.1.3324.85-94
Tabot, B. A. & Mottanya, C. D. (2012). Effect of contextual characteristics of teaching practice schools on student teachers’ per-formance in Kenya. https://www.semanticscholar.org/paper/Effect-of-contextual-characteristics-of-teaching-on-Tabot-Mottan-ya/0006a84a875986d43ab9cbdaaacafd19fab7b212
Tongco, J., Silvederio, W. C., Salanawon, P. J., & Mercado, J. (2021). Development of Vir-tual Laboratory Simulation: e-SCILAB on Waves for Grade 7 Science. International Journal of Multidisciplinary: Applied Busi-ness and Education Research, 2(11), 1283-1297. https://doi.org/10.11594/10.11594/ijmaber.02.11.20
Verschaffel, L. & De Corte, E., (2015). Students' non-realistic mathematical modeling as a drawback of teachers' beliefs about and approaches to word problem solving. In B. Pepin & B. Roesken-Winter (Eds.), From beliefs to dynamic affect systems in mathematics education: Exploring a mo-saic of relationships and interactions (pp. 137–156). Springer International Publish-ing/Springer Nature. https://doi.org/10.1007/978-3-319-06808-4_7
Willson, V. L., & Putnam, R. R. (1982). A meta-analysis of pretest sensitization effects in experimental design. American Educa-tional Research Journal, 19(2), 249–258. https://doi.org/10.3102/00028312019002249
Zhao, C., & Kuh, G. (2004). Adding Value: Learning Communities and Student En-gagement. Research in Higher Education, 45, 115-138. https://doi.org/10.1023/B:RIHE.0000015692.88534.DE