Volume 15 Issue 05, May 2025
Impact factor: 2019: 4.679 2020: 5.015 2021: 5.436, 2022: 5.242, 2023:
6.995, 2024 7.75
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259
ENHANCING MATHEMATICAL OPERATIONS PROFICIENCY IN SECONDARY
STUDENTS USING MICROSOFT ACCESS: AN EXPERIMENTAL STUDY.
Bahronov Otabek Najmiddinovich
Polytechnical school No. 1 of Gijduvan district, Bukhara, Uzbekistan
Abstract :
This study examines the impact of Microsoft Access as a tool for improving
secondary students’ proficiency in mathematical operations, focusing on algebraic expressions
and basic statistical computations. A randomized controlled trial involved 80 students (aged 15–
17) split into an experimental group (n=40) using Microsoft Access queries and a control group
(n=40) employing traditional methods. The intervention included tasks such as solving linear
equations and calculating statistical measures (mean, variance) within Access databases. Pre- and
post-intervention assessments showed the experimental group improved significantly (p < 0.001),
with a mean post-test score of 88.6 (SD = 6.9) compared to 74.3 (SD = 7.8) for the control group.
Student surveys indicated higher motivation and perceived relevance in the experimental group.
These findings suggest that Microsoft Access can enhance mathematical skills by integrating
computational practice with data management, offering a novel approach to mathematics
education.
Keywords:
Microsoft Access, mathematical operations, algebraic expressions, statistical
computations, educational technology, student engagement
Mastery of mathematical operations, including algebra and statistics, is critical for academic and
professional success (Smith, 2020). However, students often struggle to connect theoretical
concepts to practical applications, leading to reduced motivation (Jones & Lee, 2019). Microsoft
Access, a relational database management system, provides an interactive platform for
performing mathematical operations on real-world datasets. This study investigates whether
Access can improve students’ proficiency in algebraic and statistical operations, hypothesizing
that its query-based environment enhances both accuracy and engagement.
A randomized controlled trial was conducted with 80 secondary students (aged 15–17) from a
suburban high school. Participants were randomly assigned to an experimental group (n=40),
using Microsoft Access, or a control group (n=40), using traditional methods (e.g., calculators,
paper-based exercises). The intervention lasted 10 weeks, with weekly two-hour sessions.
The experimental group was trained to use Microsoft Access for:
- Designing tables to store numerical data (e.g., inventory records, survey responses).
- Writing queries to solve linear equations (e.g., calculating profit: Revenue - Cost).
- Computing statistical measures (e.g., mean, variance) using built-in functions.
The control group solved equivalent problems using manual calculations and graphing
calculators. Both groups followed the same curriculum standards for algebra and introductory
statistics.
Pre- and post-tests evaluated proficiency in solving algebraic expressions (10 items) and
statistical calculations (10 items). Each test was scored out of 100. A motivation survey (Likert
scale, 1–5) assessed engagement and perceived relevance. Classroom observations provided
qualitative insights into student behavior.
Volume 15 Issue 05, May 2025
Impact factor: 2019: 4.679 2020: 5.015 2021: 5.436, 2022: 5.242, 2023:
6.995, 2024 7.75
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Quantitative data were analyzed using R (v4.4.2). Paired t-tests compared pre- and post-test
scores within groups, and an independent t-test compared post-test scores between groups.
Survey responses were analyzed for mean scores and thematic trends. Qualitative observations
were coded for engagement patterns.
The experimental group’s mean pre-test score was 62.4 (SD = 9.2), increasing to 88.6 (SD = 6.9)
post-intervention. The control group’s mean pre-test score was 61.9 (SD = 8.8), rising to 74.3
(SD = 7.8). Paired t-tests showed significant improvement in both groups (experimental: t(39) =
12.67, p < 0.001; control: t(39) = 5.89, p < 0.001). An independent t-test confirmed the
experimental group’s superior post-test performance (t(78) = 4.52, p < 0.001). Effect size
(Cohen’s d = 0.92) indicated strong practical significance.
Survey results showed the experimental group rated motivation higher (M = 4.3, SD = 0.6) than
the control group (M = 3.2, SD = 0.8). Students valued “practical application” (e.g., analyzing
survey data) and “error reduction” through query automation. Observations noted increased
collaboration in the experimental group, though some students required additional support to
master Access’s interface.
The results support the hypothesis that Microsoft Access enhances proficiency in mathematical
operations, aligning with studies on technology-driven learning (Jones & Lee, 2019; Brown,
2021). The query-based approach allowed students to visualize algebraic and statistical
operations within datasets, fostering deeper understanding (Smith, 2020). Higher motivation
scores suggest that contextualized learning increases engagement, corroborating Davis (2022).
Challenges, such as navigating Access’s interface, highlight the need for structured onboarding.
Microsoft Access proves to be a powerful tool for teaching mathematical operations, blending
computational practice with real-world data manipulation. Educators should integrate such tools
into curricula, ensuring sufficient training to mitigate learning curves. Future studies could
explore cross-disciplinary applications (e.g., combining Access with science education) and
longitudinal effects on student outcomes.
This article evaluates Microsoft Access as a tool for enhancing secondary students’ proficiency
in algebraic and statistical operations through a randomized controlled trial. The experimental
group, using Access queries, outperformed the control group (p < 0.001), with notable gains in
accuracy and motivation. Statistical analyses (t-tests, Cohen’s d) and survey data highlight the
tool’s efficacy and engagement benefits. The study underscores the potential of database
software in mathematics education, recommending its adoption with proper instructional support.
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Impact factor: 2019: 4.679 2020: 5.015 2021: 5.436, 2022: 5.242, 2023:
6.995, 2024 7.75
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