| dc.description.abstract | Mathematics as a backbone of Science, Technology, Engineering, and Mathematics
(STEM) develop students' abilities to innovate, make well-informed choices, and solve problems
which lead to personal achievements, societal advancement, and economic growth. However, poor
academic performance in Mathematics starting from the announced KJSEA 2025 has emerged as
a major issue in the country. The current study focused on examining the influence of cognitive
load on learner academic performance in Mathematics among grade nine students in public junior
secondary schools in Kajiado-west Sub- County, Kajiado County, Kenya. The study was guided
by cognitive load theory and scaffolding theory. The study used convergent parallel mixed
research design. The study targeted 1830 Grade Nine students and 74 Mathematics subject teachers
from 35 public junior secondary schools in the Kajiado-West sub-county, Kajiado county, Kenya.
Yamane's (1967) formula was used to determine students’ sample size while proportionate
stratified random sampling formula to determine school sample size per category. Both stratified
and simple random sampling were used to sample the participants. The study used questionnaires
and interview to collect data. Construct validity was supported by content validity through
Exploratory Factor Analysis (EFA) and University supervisors assessed the study instruments to
establish face validity. Cronbach alpha coefficient was used to assess the instruments' internal
consistency. Descriptive statistics which include means, standard deviations, and frequency
distributions were used to summarize data while Pearson Coefficient correlation and multiple
linear regression analysis used for inferential statistics. The research findings established a
significant positive relationship between cognitive load dimensions and academic performance in
Mathematics. Intrinsic cognitive load (r = .805, p < .001), extraneous cognitive load (r = .724, p <
.001), and germane cognitive load (r = .813, p < .001) significantly influenced academic
performance. The regression analysis demonstrated that cognitive load accounted for 68.1% of
performance variations (R2 = .681) with germane cognitive load showing the highest prediction
power (β = .397), followed by intrinsic cognitive load (β=.270), and finally extraneous cognitive
load (β =.173). The study results demonstrate that students will achieve better results when they
manage to direct their mental resources in an efficient manner during their learning process.
Students who actively participated in concept understanding and integration activities showed the
highest improvement in their performance levels. The research shows that learning task complexity
impacts results but inefficient teaching methods produce minimal effects through unneeded mental
effort. Teachers need to develop their lesson plans properly because students will succeed better
when they learn in meaningful ways which teachers create for them. The study recommends that
education policies that will help improve Mathematics performance in junior secondary schools in
Kajiado-West sub-county besides improving country wide performance. Similarly, Mathematics
teachers should apply student-focused methods which break down difficult topics while they
connect fresh information to existing knowledge and maintain student involvement. The study
further recommends that school administrators create ongoing teacher training programs on
cognitive load management and effective Mathematics teaching methods. The schools need to
establish proper educational material supply and create learning spaces which support student
success. | en_US |
