Impact of Animated Computer-Assisted Instruction on Biology Achievement in Niger State: Post-COVID-19 Teaching Solution

This research explored the impact of computer-assisted instruction (CAI) with animation on the academic performance of biology students in Niger State, designed as a post-COVID-19 strategy to enhance teaching and learning. The study utilized an experimental design, focusing on Senior Secondary II (SSII) students. Participants were selected using a simple random sampling method, which included schools, class groups, and students, resulting in two equivalent groups of 30 students each (15 males and 15 females). The instrument's reliability was verified using the PPMC formula, producing a coefficient value of 0.75. Data analysis was conducted using Analysis of Variance (ANOVA) to test the hypotheses. The results revealed that the first null hypothesis was rejected, while the second was accepted. The study highlighted that incorporating CAI with animation as a teaching aid significantly improved students' academic achievements in biology. This enhancement was attributed to the integration of traditional teaching approaches with effective instructional materials, which created a more engaging and interactive learning environment. The findings recommend implementing CAI with animation software across all senior secondary schools to boost students’ understanding and performance in biology and other science subjects. Such an approach addresses educational challenges exacerbated by the pandemic while fostering dynamic and effective learning experiences.

Authors

Institutions

Publication Details

Journal
Ceddi Journal of Education
Published
2024-12-12
DOI
https://doi.org/10.56134/cje.v3i2.67
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Animated Computer-Assisted Instruction on Biology Achievement in Niger State: Post-COVID-19 Teaching Solution

C. S. Tukura, Y Mendoza Montero Fátima, Faisal R. Ali, Ibrahim Ismaila Kuta et al.
Ceddi Journal of Education
Technology-Enhanced Education Studies
article

Impact of Animated Computer-Assisted Instruction on Biology Achievement in Niger State: Post-COVID-19 Teaching Solution

C. S. Tukura, Y Mendoza Montero Fátima, Faisal R. Ali, Ibrahim Ismaila Kuta, Abdulkadir Ndatsu
article en

Abstract

This research explored the impact of computer-assisted instruction (CAI) with animation on the academic performance of biology students in Niger State, designed as a post-COVID-19 strategy to enhance teaching and learning. The study utilized an experimental design, focusing on Senior Secondary II (SSII) students. Participants were selected using a simple random sampling method, which included schools, class groups, and students, resulting in two equivalent groups of 30 students each (15 males and 15 females). The instrument's reliability was verified using the PPMC formula, producing a coefficient value of 0.75. Data analysis was conducted using Analysis of Variance (ANOVA) to test the hypotheses. The results revealed that the first null hypothesis was rejected, while the second was accepted. The study highlighted that incorporating CAI with animation as a teaching aid significantly improved students' academic achievements in biology. This enhancement was attributed to the integration of traditional teaching approaches with effective instructional materials, which created a more engaging and interactive learning environment. The findings recommend implementing CAI with animation software across all senior secondary schools to boost students’ understanding and performance in biology and other science subjects. Such an approach addresses educational challenges exacerbated by the pandemic while fostering dynamic and effective learning experiences.

Ceddi Journal of EducationVol. 3(2)
Federal University of Technology (NG)
Good health and well-being
Openalex Percentile: Top 67%
Technology-Enhanced Education Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.