Age and Gender as a Demographic Factors that Correlates Students’ Performance in Computer Programming in Colleges of Education in Enugu State, Nigeria

Samuel Okechukwu Nnaji, Prof. Nnenna. E. Ibezim, Nneamaka Felicia Anyalebechi, Maduabuchi Bartholomew Ikezue

Age, Gender, Demographic, Correlates, Students, Performance, Computer, Programming, Colleges, Education.

The aim of this study was to investigate age and gender as a demographic factors that correlates students’ performance in computer programming in Colleges of Education. The study was carried out in Colleges of Education. Two objectives, two research questions and two hypotheses were formulated to guide the study. The study adopted correlational survey research design. The study was carried out using government owned Colleges of Education. The population for the study was forty nine (49) computer education students (final year) from the two (2) government owned Colleges of Education in Enugu State, Nigeria. The entire population was studied due to the fact that it is manageable. Hence, total population sampling technique was adopted. The instrument that was used for the study was student’s result scores and a structured questionnaire titled “Age and Gender as a Demographic Factors that Correlates of Student’s Performance in Computer Programming (AGDFCSPCP) questionnaire”. The research instrument was subjected to face validation by three experts, two experts in the Department of Computer & Robotics Education and one from Measurement and Evaluation unit, all from University of Nigeria, Nsukka. The internal consistency of the questionnaire was determined using Cronbach’s Alpha reliability test which yielded co-efficient of 0.98 and 0.97 for clusters 1 and 2 respectively and 0.98 for the entire instrument. The instrument for data collection were administered by the researcher and two research assistants. The data collected was analyzed using Pearson Product Moment Correlation Coefficient to answer the research questions. The null hypotheses were tested using One Way Analysis of Variance (ANOVA) at .05 level of significance. The findings from the study revealed a very weak relationship among age, gender, and performance of computer education students’ in computer programming. In addition, the findings on hypothesis tested revealed that there was no statistically significant relationship among computer education students’ age, gender and their performances in computer programming course. It was therefore, recommended among others that since demographic factors don't differentiate performance, the effectiveness of teaching methods and curriculum content becomes paramount. The researcher suggested that the study should be replicated in other states of our country to investigate demographic factors as correlate students’ performance in computer programming in Colleges of Education. It is recommend that, invest in training for computer programming instructors on effective pedagogical approaches, such as problem-based learning, project-based learning, collaborative coding, and active learning strategies. Regularly review and update the computer programming curriculum to ensure it is relevant, engaging, and aligned with industry needs.

Received: 07 Nov 2025, Received in revised form: 05 Dec 2025, Accepted: 10 Dec 2025, Available online: 15 Dec 2025

10.22161/ijaers.1212.3