Enhancing Adolescent Analytical Skills through Mathematics and Mathematics Teaching Methods at the Secondary Level

Marzina Akter Reba; Rojina Akter

doi:10.18034/ajase.v12i1.13

Authors

Marzina Akter Reba Lecturer (Mathematics), School of Business, Asian University of Bangladesh, Dhaka, Bangladesh
Rojina Akter Lecturer (Accounting), School of Business, Asian University of Bangladesh, Dhaka, Bangladesh

Keywords:

Adolescent

Mathematics Skill

Secondary Teachers

Teaching Strategies

Mathematical Tasks

Abstract

This article is a conceptual paper that describes different approaches for teaching mathematics to secondary school students that blend learning with the intrinsic motivation that comes from their reactive intelligence. Students ultimately study mathematics after "learning math." The level of the children's mathematical knowledge is revealed by their ability to read a text and recognize symbols, including numbers, and visuals like diagrams and graphs. Adolescents use their diverse skill sets to master mathematics in these different contexts at the secondary level. Here it is found that the students often use the knowledge from their daily lived experiences (from direct and indirect engagements) to assist them with the mathematics in the textbook and used conceptual understanding rather than formal procedures in response to the mathematics textbook. Stimulating questions, analyzing problems, successful responses, and solving techniques are significant motivating tools in mathematics, which is especially beneficial in the framework of Mathematics learning. These tools and techniques are often used at the secondary to teach mathematics.

References

Ayres, P., Dinham, S., & Sawyer, W. (2004). Effective teaching in the context of grade 12 high-stakes external examination in New South Wales, Australia. British Educational Research Journal, 30, 141-165.

Ballou, D., Sanders, W., & Wright, P. (2004). Controlling for Student Background in Value-Added Assessment of Teachers. Journal of Educational and Behavioral Statistics, 29(1), 37–65. https://doi.org/10.3102/10769986029001037

Bass, H. (1997). Mathematicians as educators. Notices of the American Mathematical Society, 44(1), 18–21.

Baumert, J., Kunter, M., Blum, W. et al. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.

Bodepudi, A., Reddy, M., Gutlapalli, S. S., & Mandapuram, M. (2019). Voice Recognition Systems in the Cloud Networks: Has It Reached Its Full Potential?. Asian Journal of Applied Science and Engineering, 8(1), 51–60. https://doi.org/10.18034/ajase.v8i1.12

Bodrova, E., Leong, D.J. (2018). Tools of the Mind: A Vygotskian Early Childhood Curriculum. In: Fleer, M., van Oers, B. (eds) International Handbook of Early Childhood Education. Springer International Handbooks of Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-0927-7_56

Dunphy, E., Dooley, T., Shiel, G., Butler, D., Corcoran, D., Ryan, M., Travers, J., & Perry, B. (2014). Mathematics in early childhood and primary education (3 - 8 years): Definitions, theories, development and progression. National Council for Curriculum and Assessment.

Guin, D. and Trouche, L. (1999). The complex process of converting tools into mathematical instruments: the case of calculators. International Journal of Computers for Mathematical Learning, 3(3), 195–227.

Gutlapalli, S. S. (2017a). Analysis of Multimodal Data Using Deep Learning and Machine Learning. Asian Journal of Humanity, Art and Literature, 4(2), 171–176. https://doi.org/10.18034/ajhal.v4i2.658

Gutlapalli, S. S. (2017b). The Role of Deep Learning in the Fourth Industrial Revolution: A Digital Transformation Approach. Asian Accounting and Auditing Advancement, 8(1), 52–56. Retrieved from https://4ajournal.com/article/view/77

Gutlapalli, S. S., Mandapuram, M., Reddy, M., & Bodepudi, A. (2019). Evaluation of Hospital Information Systems (HIS) in terms of their Suitability for Tasks. Malaysian Journal of Medical and Biological Research, 6(2), 143–150. https://doi.org/10.18034/mjmbr.v6i2.661

Mandapuram, M. (2016). Applications of Blockchain and Distributed Ledger Technology (DLT) in Commercial Settings. Asian Accounting and Auditing Advancement, 7(1), 50–57. Retrieved from https://4ajournal.com/article/view/76

Mandapuram, M., & Hosen, M. F. (2018). The Object-Oriented Database Management System versus the Relational Database Management System: A Comparison. Global Disclosure of Economics and Business, 7(2), 89–96. https://doi.org/10.18034/gdeb.v7i2.657

Mandapuram, M., Gutlapalli, S. S., Bodepudi, A., & Reddy, M. (2018). Investigating the Prospects of Generative Artificial Intelligence. Asian Journal of Humanity, Art and Literature, 5(2), 167–174. https://doi.org/10.18034/ajhal.v5i2.659

Reddy, M., Bodepudi, A., Mandapuram, M., & Gutlapalli, S. S. (2020). Face Detection and Recognition Techniques through the Cloud Network: An Exploratory Study. ABC Journal of Advanced Research, 9(2), 103–114. https://doi.org/10.18034/abcjar.v9i2.660