Authors :
Samuel Okechukwu Nnaji; Christabel Linda Uchenwa; Favour Ahonwo Ifeanyichukwu
Volume/Issue :
Volume 11 - 2026, Issue 6 - June
Google Scholar :
https://tinyurl.com/3s3p8z5e
Scribd :
https://tinyurl.com/3a7zab8f
DOI :
https://doi.org/10.38124/ijisrt/26jun2050
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The reliability of the instrument were determined using Cronbach's Alpha reliability
coefficient. A reliability coefficient of 0.98 and 0.97 for cluster 1 and 2 respectively and 0.98 for overall, the result were
considered acceptable for the study. The data collected were 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 revealed a very weak relationship for educational level (year of study)
with students performance in computer programming, whereas weak correlation for marital status demonstrated a
comparatively. It was therefore, recommended among others that structured programming support programs should be
established by federal universities, especially for first- and second-year students who frequently struggle to adjust to
programming principles. As students advance through various academic levels, tutorials, mentoring programs, coding
clinics, and peer-assisted learning activities should be arranged on a regular basis to boost their proficiency and selfassurance and lecturers of computer programming should create instructional strategies that take into account the diverse
practical and cognitive requirements of students at different academic levels. While lower-level students should receive
basic help to enable steady skill growth and increased academic achievement, advanced students should be introduced to
more challenging programming tasks.
Keywords :
Educational Level, Marital Status, Demographic Correlates, Students Performance, Computer Programming, Federal Universities.
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The reliability of the instrument were determined using Cronbach's Alpha reliability
coefficient. A reliability coefficient of 0.98 and 0.97 for cluster 1 and 2 respectively and 0.98 for overall, the result were
considered acceptable for the study. The data collected were 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 revealed a very weak relationship for educational level (year of study)
with students performance in computer programming, whereas weak correlation for marital status demonstrated a
comparatively. It was therefore, recommended among others that structured programming support programs should be
established by federal universities, especially for first- and second-year students who frequently struggle to adjust to
programming principles. As students advance through various academic levels, tutorials, mentoring programs, coding
clinics, and peer-assisted learning activities should be arranged on a regular basis to boost their proficiency and selfassurance and lecturers of computer programming should create instructional strategies that take into account the diverse
practical and cognitive requirements of students at different academic levels. While lower-level students should receive
basic help to enable steady skill growth and increased academic achievement, advanced students should be introduced to
more challenging programming tasks.
Keywords :
Educational Level, Marital Status, Demographic Correlates, Students Performance, Computer Programming, Federal Universities.