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Journal of Applied & Computational Mathematics

ISSN: 2168-9679

Open Access

Volume 12, Issue 1 (2023)

Research Article Pages: 1 - 4

Investigating Similarity Ratios of Student Teachers Unfair Advantage Performance in Mathematics using Kolmogorov-Smirnov Test

Maxwell Seyram Kumah*

DOI: 10.37421/2168-9679.2023.12.510

Student teachers’ increase rate in resit in mathematics courses at college is very worrisome situation that need urgent attention.

Purpose: The study aimed to investigate the similarity ratios that exist between male and female student teacher with casualty and those without casualty in relation to their mathematics performance in college. Two hypotheses were set to test similarity among the variables.

Method: A quantitative research approach with case study research design was employed. Participants (level 300 student teacher who took some mathematics courses) were purposively selected. A sample 999 of them from seven Colleges of Education (CoEs) from Volta and Oti regions were randomly selected.

Results: The results established that there was a significant difference between male and female student teachers, based casualty and non – casualty academic performance. However, it was interesting to note that the difference occurred within the score range of 60 – 69%. For non – casualty distribution group it was found that 0.028 < 0.058 indicating a significant difference between male and female student teachers. Similarly, it was found that 0.028 < 0.038 indicated a significant difference between male and female in the casualty distribution group of student teachers’ academic performance in mathematics at college. In addition, there was an overall academic performance difference between the casualty and non – casualty distribution groups where 0.039 and 0.058 respectively were less than 0.465. This suggest that there is a significant difference between casualty and non – casualty student teachers in their mathematics academic performance.

Mini Review Pages: 1 - 2

Through PBL, Applied mathematics Can Improve Employability Skills

Branko Dragovich*

DOI: 10.37421/2168-9679.2023.12.511

Project-Based Learning (PBL) is a teaching method that involves students in a process of learning through hands-on, real-world experiences. PBL encourages students to engage in self-directed learning, collaborate with others, and apply their knowledge to solve complex problems. Applied mathematics, which is the use of mathematical concepts and methods to solve practical problems in various fields, can be an excellent subject for PBL. Problem-solving: PBL with applied mathematics provides students with the opportunity to solve real-world problems using mathematical concepts and methods. This enhances their problem-solving skills and makes them more attractive to employers. Applied mathematics is the use of mathematical concepts and methods to solve practical problems in various fields, including engineering, physics, computer science, finance, and many others. In today's job market, employers are looking for employees with strong problem-solving skills, creativity, communication skills, and the ability to work in teams. Project-Based Learning (PBL) is a teaching method that involves students in a process of learning through handson, real-world experiences. By engaging in PBL with applied mathematics, students can enhance their employability skills and become more attractive to potential employers.

Google Scholar citation report
Citations: 1282

Journal of Applied & Computational Mathematics received 1282 citations as per Google Scholar report

Journal of Applied & Computational Mathematics peer review process verified at publons

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