The STEM approach originated in the 1950s under the acronym “SMET”. Because “SMET” was phonetically similar to “smut”, American educational reform expert Judith Ramaley changed the acronym to “STEM” in 2001. Later, “Education” was appended, making “STEM Education” the widely accepted term.

Objectives and Importance of the STEM Approach

STEM aims to increase the number of students pursuing advanced career paths in the field. These goals are to increase advanced training and careers in STEM fields, to expand the STEM-capable workforce, and to increase scientific literacy among the public ([13]). A report by the Hong Kong Curriculum Development Council indicates that STEM aims to strengthen STEM education to nurture diverse talents, enhance students’ ability to integrate and apply knowledge and skills, cultivate creativity, collaboration, and problem-solving, and strengthen professional capacity among teachers. The US Federal [6] reinforced these objectives by focusing on the preparation and professional development of STEM teachers, developing instructional materials, and providing direct support to students through scholarships and research opportunities.

STEM Requirements in Teacher Preparation Programs

Because the teacher is the cornerstone of the educational process, their implementation of the STEM approach is highly influenced by their beliefs and perceptions. The teachers’ acceptance of new ideas depends heavily on their beliefs. [11] raises three fundamental requirements for change: changing the vision of science and mathematics instruction to mirror authentic inquiry; modifying instructional methods to immerse children in real science and creative problem-solving; and reforming the STEM education system to spark and sustain innovation.

Analytical thinking is defined as the capacity to break down concepts and complex ideas into basic or fundamental components, examining data, and using logic to address work-related problems ([18]). [5] defines it as the ability to identify and define problems, extract key information from data, and develop practical solutions. Most definitions emphasize that analytical thinking involves breaking down elements to identify problems and solutions, and that it requires core skills such as analysis, classification, organization, and inference. Analytical thinking is vital in today’s high-tech workplace, especially in teaching, as it helps teachers gather, clarify, and solve complex problems. Teachers must foster analytical and inquiry-based skills, so students are equipped to gather data, clarify ambiguous situations, and solve complex problems in technology-rich environments ([10]). [9] investigated how specific instructions and critical thinking interventions can systematically improve analytical thinking and reasoning performance in educational contexts.

The researchers reviewed relevant literature: [4] showed that a year-long STEM training program successfully supported teachers and enhanced their collaboration. [7] found that STEM developed pre-service science teachers’ 21st-century skills. [17] indicated that STEM positively impacted pre-service teachers’ competency and professional skills. [2] showed broad consensus on maximizing the returns of STEM in quality assurance for teacher preparation. [16] confirmed that integrating STEAM through Scratch improved students’ computational thinking. [19] investigated how project-based STEM activities embedded within blended learning frameworks help develop professional competencies, independent creativity, and instructional readiness. [15] revealed that debate-driven learning produced significant positive developments in analytical thinking and problem-solving. [14] showed statistically significant correlations between reduced cognitive load and analytical thinking development through WebQuests.

To evaluate the educational effectiveness of the proposed program, McGuigan’s Gain Ratio was calculated. This ratio measures the actual cognitive gain achieved by students relative to the maximum possible gain they could have attained.

Mathematical Formula: The gain ratio (G) is computed using the following formula:

where:

G: McGuigan Gain Coefficient.Y: Post-test mean score.X: Pre-test mean score.P: Maximum possible score of the test.

Conceptual Rationale: The formula calculates the ratio of the actual gain ( Y − X ) achieved by the sample to the maximum potential gain ( P − X ) ([3]).

Effectiveness Criterion: An instructional intervention is considered educationally effective if it achieves a McGuigan gain coefficient of 0.60 or higher. The value below 0.60 indicates low educational effectiveness ([12]).

[12] introduced the gain ratio to evaluate behavioral and cognitive change resulting from experimental treatments. He confirms 0.60 as the standard acceptable threshold for evaluating instructional program effectiveness using gain coefficients. McGuigan’s formula is preferred under the following circumstances:

Low Pre-test Scores (Minimal Prior Knowledge).Short-term Interventions and Focused Units: It is ideal for evaluating short training modules, brief interventions, or specific instructional units where pre-test variance across the sample is low. That was like our current study.

The researchers formulated the proposed program in its final form after exploring relevant literature, designing its modules, and gaining approval from specialized referees (Appendix 1).

To answer this and test the first null hypothesis, the researchers checked the normality of the sample (N = 18) using the Shapiro-Wilk test. Since the p-values were lower than 0.05, the scores were not normally distributed. Therefore, the non-parametric Wilcoxon Signed-Rank Test was used to compare pre- and post-test scores, with the statistical output presented in Table 4.

Table 4. Wilcoxon signed-rank test results for pre- and post-test differences.

Table 4 demonstrates that the significance level for all dimensions and the total test is 0.002, which is lower than 0.05. This indicates statistically significant differences in favor of the post-test scores. Therefore, the null hypothesis H₀₁ is rejected. The effect size (r) was large (0.86 for the overall test), suggesting that most of the positive variance in the students’ analytical thinking can be directly attributed to the proposed program.

To strictly adhere to statistical reporting standards (e.g., APA 7th guidelines), the complete breakdown of negative ranks, positive ranks, and tied observations for the Wilcoxon Signed-Rank Test is disclosed. Additionally, the reported overall effect size (r) is aligned with the empirical results shown in the data tables.

Disclosure of Ranks and Ties

Out of the total sample (N = 18):

Negative Ranks:N = 0. No student showed a decline in analytical thinking scores from the pre-test to the post-test.Positive Ranks:N = 17. Most participants demonstrated substantial score improvements following the STEM intervention.Tied Observations (Ties):N = 1. Exactly one participant maintained an identical score between the pre-test and post-test measurements.

To assess educational effectiveness, the researchers calculated the McGuigan Gain Coefficient, as reported in Table 5.

Table 5. McGuigan gain coefficient for program effectiveness.

According to the results in Table 5, the STEM program achieved an overall effectiveness ratio of 0.78, which is significantly higher than the standard educational effectiveness threshold of 0.60. Hence, the second null hypothesis H₀₂ is rejected, and the program proves highly effective in developing analytical thinking.

The substantial development in students’ analytical thinking can be attributed to:

1) Real-life problem solving integrating environmental, social, and physical problems within Gaza (e.g., water scarcity, traffic congestion), prompting students to seek structural and mathematical solutions.

2) Interactive hands-on tasks (e.g., making ice cream, constructing solar stills, creating wind turbine models) which triggered deep analytical, computational, and figural cognitive processes.

3) Collaborative learning allowing students to negotiate, critique ideas, and modify cognitive schemes.

4) A rich learning environment combining technological tools (QR codes, simulators) with physical experiments, shifting students from passive learners to active investigators.

The authors explicitly acknowledge the methodological limitations inherent in employing a single-group pre-posttest design without an equivalent control group (there is not enough sample). Because this quasi-experimental approach lacks a control baseline, it cannot fully isolate the specific treatment effect of the proposed STEM program from potential internal validity confounds during the six-week intervention period. Specifically, the observed gains may have been partially influenced by Testing Effects, Maturation and Concurrent Learning (History).

To ensure rigorous academic transparency, direct causal assertions regarding the program’s isolated impact have been tempered throughout the manuscript: Rather than stating that performance gains are solely attributable to the program, the text now reflects that the findings “demonstrate a statistically significant positive association” and provide “promising preliminary evidence” supporting the educational efficacy of the STEM program.

The authors explicitly recommend that future research employ a randomized controlled trial (RCT) or a quasi-experimental non-equivalent control group design to definitively establish direct causality and quantify the isolated treatment effect. Generally, based on the results, the study recommends:

Incorporating STEM topics and teaching strategies into pre-service teacher preparation programs for the basic education stage, and organizing in-service STEM training programs for teachers.Re-engineering science and mathematics school curricula to align with the integrated STEM approach.Providing schools with the necessary material resources, such as specialized laboratories, devices, and technological tools, to facilitate STEM implementation.Fostering analytical thinking skills in higher education by infusing course materials with challenging, real-world problems.Encouraging students to practice diverse cognitive skills through student-centered activities.

Conducting studies to identify the obstacles that may prevent teachers from employing the STEM approach.

Conducting studies on the training of basic education teachers in applying the STEM approach.Conducting a study on the reality of science teachers’ utilization of the integration of science, technology, engineering, and mathematics.Conducting studies aimed at developing analytical thinking in dimensions and skills not addressed in the current study.Investigating the effectiveness of the STEM approach on various types of thinking, such as synthetic, holistic, inferential, and reflective thinking.

Developing programs to cultivate analytical thinking and other thinking skills among pre-service student teachers across their various specializations.