Effect of Integrating Artificial Intelligence (AI) On the Teaching and Learning of Geometry Within Secondary Schools in Ogun Central Senatorial Districts, Nigeria

Effect of Integrating Artificial Intelligence (AI) On the Teaching and Learning of Geometry Within Secondary Schools in Ogun Central Senatorial Districts, Nigeria

*Akintade. C.A.,  Olaore, F.A

Department of Mathematics, Federal College of Education, Abeokuta, Ogun State, Nigeria.

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000018

Received: 04 August 2025; Accepted: 30 August 2025; Published: 26 September 2025

ABSTRACT

This study investigates the impact of integrating Artificial Intelligence (AI) on teaching and learning of geometry in secondary schools within Ogun Central Senatorial District, Nigeria. The research aims to explore the effectiveness of AI-based instructional materials in enhancing students’ understanding and retention of geometric concepts. In general, the study examines   the impact of AI-based instructional materials on students’ performance in geometry and assess the perceptions of teachers and students towards the integration of AI in geometry education. The research was a pre-test post-test quasi-experimental control group design.  A survey of 300 students (150 males and 150 females) was drawn from four secondary schools within the local Government. Four intact classes were used by the researchers for both experimental and the control groups. The experimental group was taught using Integrated Artificial Intelligent Strategies(IAIS) whereas the control groups was taught conventionally. Data collected was analyzed using descriptive statistics   to answer the research questions raised for the study while the hypotheses were tested using analysis of covariance(ANCOVA). Result of the study revealed that students taught using Integrated Artificial Intelligent Strategies(IAIS) achieved higher mean scores than those students taught using conventional method. The result also revealed non-significant difference in the mean achievement and the mean attitude scores of males and female’s students taught geometry using Integrated Artificial Intelligent Strategies(IAIS). Some recommendations were made among which are that the integration of Artificial Intelligence (AI) in education has the potential to revolutionize the teaching and learning of geometry in secondary schools.

Keywords: Geometry, Integrated Artificial Intelligence Strategies(IAIS), Gender, Attitude.

BACKGROUND OF THE STUDY

Globally, education plays a very important role in all areas of society. Not only is it an investment but a very potent tool that can be used to achieve a more rapid economic, social, political, scientific, technological and cultural development in any nation (Sotayo, Akintade Busari,(2023). Perhaps, this explains why Allison Academy, (2023) described it as the most responsible for the development of civilization as we know it. However, in Nigeria, premium is placed on sciences and science education in Nigerian schools as evident in the government’s policy on education. The policy provides for a 60:40 admission ratio in the tertiary institutions in favor of science education in the government’s policy on education science, technology and mathematics (FRN, 2013). This notwithstanding, the academic performance of students in sciences and mathematics in particular, is at the lowest ebb as reported by Sotayo, Akintade and Busari, (2023). Mathematics educators and researchers have made significant efforts aimed at identifying the major problems associated with the teaching and learning of mathematics. These include students’ study habits (Ayodele and Adebiyi, 2013; Obasoro and Ayodele, 2012); poor intellectual ability, physical limitation, family crisis and inadequate communication (Ige, 2011). Salman, Muhamed, Ogunlade and Ayilara (2012) have identified students’ negative attitude towards mathematics as one of the factors affecting their performance in the subject. Yara (2009) has attributed students’ poor performance in mathematics to the attitudes of teachers towards the subject.  According to Effandi Zakaria and Normah Yusoff. (2009), students’ poor background in mathematics, unqualified teachers in the system, and students’ psychological fear of mathematics are other factors responsible for their poor performance in the subject.

Findings from researchers such as (Sotayo, Akintade Busari, 2023; Ingvarson, Beavis, Bishop, Peck & Elsworth, (2004); Obasoro & Ayodele, (2012), have reported the positive influence of teachers’ content knowledge on students’ success in learning mathematics. This indicates that teachers play a significant role in the life of any student that desires to move from the world of life into the world of symbols and in addition move within the world of symbols itself. Therefore, for any teacher to effectively teach at all levels of education, a deeper and more profound understanding of fundamental skills is required. They should not only have a strong background in mathematics, but also a thorough understanding of pedagogy (Akintade, Ogbonnaya&Mogari, 2013; Effandi Zakaria & Normah Yusoff. 2009).

Although, different methods of teaching have been proposed by different educators and the knowledge of these methods may help in working out a better teaching strategy. However, it is not appropriate for a teacher to commit to one particular method. A teacher should adopt a teaching approach after considering the nature of the children, their attitudes and maturity, and the resources available. According to Agommuoh &Ifeanacho (2013), teaching methods are changing as we renew our focus on students and meaningful learning in a broad set of intellectual domains.

With all the efforts concentrated on how to improve students’ performance in mathematics, there seems to be a dearth of studies on how Artificial Intelligence(AI) can be integrated in the learning of mathematics by students in Nigerian secondary schools. Similarly, the apparent lack of literature on the integration of Artificial Intelligence(AI) for teaching and learning of mathematics in Nigerian secondary schools make a case for this study.

Specifically, the study investigates the effects of integrating Artificial Intelligence(AI) on 2^nd year senior secondary school (equivalent to grade 11) students’ academic achievement and attitude towards the learning of geometry in secondary schools within Ogun Central Senatorial District, Nigeria.

Historical Background of Artificial Intelligence

As reported by Haenlein and Kaplan (2019), the genesis of AI could be traced to the mid-twentieth century and has witnessed substantial improvement and discoveries over the years. In the 1950s and 60s, the early research period of AI field, it was defined by lofty aims, game-changing concepts, and foundational achievements that lay the platform for later progress of AI (Kompa et al., 2022). Research findings (Anyoha, 2017; Newquist, 1994) revealed that the early AI systems had limited capabilities and encountered several problems.  However, they laid the groundwork for the development of more advanced AI techniques in the preceding decades.

Haenlein and Kaplan, (2019) posited that the emphasis on symbolic reasoning, logic, and problem-solving throughout the 1950s and 60s, era prepared AI to evolve into diverse subfields such as machine learning, natural language processing, and expert systems. Reports revealed that John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon laid the groundwork and coined AI as a discipline at this meeting (McCarthy, 1998). These researchers aimed at creating a machine that could solve problems using logical deduction and rule based systems and this strategy emphasized formal languages, algorithms, and mathematical representations. Despite the early enthusiasm in the 50s and 60s, the AI research encountered substantial setbacks in the 1970s and 1980s as there was a dearth of finance and high expectations; therefore, progress was slower than projected. This period, coined the “AI winter” by McCarthy in 1955 (McCarthy et al., 2006), saw reduced interest and slower growth in the discipline. However, in the 2010s, there was a significant synergy between Big Data and Deep Learning, resulting in the availability of vast volumes of data that assisted Deep Learning model training (Shah, 2016). Deep learning, in turn, provided a robust framework for evaluating and extracting insights from Big Data. The convergence of these technologies resulted in substantial advances in AI applications spanning from improved recommendation systems to autonomous vehicles and cutting-edge medical diagnosis. The 2010s was a turning point in AI history, with Big Data and Deep Learning sparking an upsurge in the field (Nguyen, 2023). These technologies provided the groundwork for the AI revolution, which is still shaping our world today, with AI becoming increasingly important. AI has made significant strides and impacts in transforming various aspects of human life, including industries and education. It offers great promise, but it also presents challenges and potential drawbacks.

The place of Artificial Intelligence in Mathematics Education

The Integrating Artificial Intelligence (AI) into mathematics education offers promising advancements and potential pitfalls. Striking a balance between AI-driven developments and preserving core pedagogical principles is critical in the teaching and learning environment. AI has emerged as a transformative force in various fields, including education. In the realm of mathematics education, AI technologies offer a spectrum of potential benefits (including personalize instruction, adaptive assessment, interactive learning environments, and real-time feedback, among others) and challenges (such as lack of creativity and problem-solving skills, inability to explain reasoning, bias in data and algorithms, absence of emotional intelligence and data privacy and security concern etc). This conceptual study used auto ethnography as the methodology and qualitative content approach to analyse data (Opesemowo, & Ndlovu,. 2024). Artificial intelligence (AI) is a multidisciplinary field that focuses on developing intelligent machines that can perform tasks typically performed by humans (Mohamed et al., 2022).

It involves studying, designing, and developing Algorithms and systems that can make decisions based on what they perceive and experience in their environment. Machine learning, natural language processing, computer vision, robotics, expert systems, and other subfields are all part of AI ( Opesemowo, & Ndlovu, 2024). These subfields use various approaches and strategies to allow machines to emulate or simulate human cognitive processes. An AI seeks to create intelligent systems that can perform tasks autonomously and adapt to various environments (Ayanwale et al., 2024; Opesemowo & Adekomaya, 2024). Understanding natural language, detecting, and interpreting visual and auditory information, making predictions, solving problems, and even displaying creativity and social intelligence are all examples of abilities.

Opesemowo and Adekomaya, (2024) stressed that AI can potentially enhance mathematics learning experiences in several ways such as Personalized Instruction, Interactive Learning Environments, Grading Automation, Real-Time Feedback, Reinforcement Learning for Math Tutoring, Augmented Reality Applications, Data Analytics for Teachers Teacher Professional Development Online Math Competitions. These tools promote active participation, problem-solving, and critical thinking skills, making mathematics more accessible and exciting for students (Mohamed et al., 2022).

AI algorithms can analyze student data and provide personalized instruction based on individual needs, learning styles, and performance in mathematics. This tailored approach according to the researchers, allows students to progress at their own pace, fill knowledge gaps, and receive targeted support, resulting in improved learning outcomes.  The researcher emphasised that AI-powered assessment tools can offer adaptive testing, dynamically adjusting the difficulty of questions based on students’ responses. According to Kumar, 2022), AI can generate personalized mathematics questions and examinations for each student based on their knowledge level and progress. These tests adjust the difficulty of questions in real time, ensuring that students are suitably pushed and tested, resulting in more accurate assessments of their mathematical abilities. AI technologies like virtual simulations and gamification create engaging learning environments.

Several researchers such as (Ayanwale et al., 2024; Opesemowo & Adekomaya, 2024; Owan et al., 2023), opined that AI can automate the grading of mathematics assignments and assessments, saving teachers time and allowing them to focus on other areas of teaching practices.  The researchers posit that Grading automation in mathematics education is a ground-breaking AI program that automates the evaluation and feedback process for assignments and assessments.

Ayanwale et al., (2024); Opesemowo & Adekomaya, (2024) stressed that AI-based math applications (such as Photomath, Soratic, Mahtway, Maple Calculator, and Microsoft Math Solver) can provide immediate feedback on students’ math problem solutions. The applications assist students in identifying and correcting errors, so reinforcing learning and developing problem-solving skills. Another good feature of AI is Teacher Professional Development.  The application can help mathematics teachers with individualized professional development. AI systems can offer customized training modules, workshops, and resources to improve teachers’ instructional skills and pedagogical approaches by analysing their performance and areas for growth.  Furthermore, the reinforcement learning algorithms powered by AI can continuously optimize tutoring tactics for math instruction. AI algorithms adjust and refine their instructional approaches based on the effectiveness of previous exchanges when students interact with the tutoring system.

The online mathematics competition is another feature of AI that provide participants with adaptable and demanding problem sets. These tournaments establish a competitive yet enjoyable environment, motivating children to thrive in mathematics and demonstrate problem-solving abilities. The ChartGPT (Chart Generative Pre trained Transformer) is a sophisticated chatbot that responds to questions using AI and natural language processing. It also responds to requests to generate text or graphics by training models on data from the internet, books, papers, and other sources (OpenAI, 2022). ChatGPT is a text-based AI platform powered by AI that uses machine learning to automate repetitive operations and boost client engagement. It employs natural language processing algorithms to comprehend human-like text and generate accurate responses to basic inquiries. ChatGPT provides a wide range of benefits (such as timesaving, content creation quality, human-like rejoinders with follow-up questions, virtual assistance, learning exploration, search engine optimization, and generate mathematics assessment questions, etc.) by integrating machine learning technology, which can significantly boost users’ satisfaction.

The place of Geometry in mathematics

Geometry is an aspect of mathematics that deals with the study of different shapes. These shapes may be plane or solid. A plane shape is a geometrical form such that the straight line that joins any two points on it wholly lies on the surface (Akintade, Ogunrinade & Awe (2024).  A solid shape, on the other hand, is bound by surfaces that may not wholly be represented on a plane surface. Plane shapes are shapes with only two dimensions (length and breadth), e.g., quadrilateral (square, rectangle, kite, rhombus, parallelogram, and trapezium), which are all four-sided figures. Also included are triangles of different types and circles in which area and perimeter are calculated. Solid shapes are three-dimensional figures (length, breath, and height), e.g., cubes, cylinders, spheres, cones, pyramids, etc. Total surface area and volume are normally found here. At the primary and Junior secondary school level, basic geometrical concepts were introduced informally and expands on them for a deeper knowledge of their properties. Constructions of solid shapes from nets; copying of figures (angles and triangles) using protractor and ruler only; an in-depth study of triangles (classification by angles and by sides); and symmetrical plane figures are concepts directly concerned with geometry content. Other curricular contents have application and computational values, e.g., areas, perimeters, and volumes of geometrical shapes (plane or solid), calculation of missing angles, circular faces, sectors, segments, etc.

Report findings over the years indicate that topics such as construction, geometrical proofs, locus, geometry that prepare students for all engineering courses in tertiary institutions are difficult for many candidates in Nigerian secondary schools.  According to the researchers, students equipped with mathematical knowledge and skills would be active players in technology and vocational areas that are crucial to the economic development and transformation of any country.  Akintade, Ogbonnaya &Mogari, (2013) have reported that some Nigerian mathematics teachers lacked a pedagogical approach to teaching some topics such as geometry to their students. This research study, therefore, has sought to examine whether the integration of artificial intelligence(AI) on senior secondary school mathematics students’ learning of solid Geometry in Ogun State Senetorial Districts Nigeria, has any effect on their academic achievement and attitude in mathematics.

Gender and Students’ Academic Performance in mathematics

Examining the relationships between gender and academic performance in mathematics becomes primarily necessary in view of the observed wide gap in the mean academic performance in respect of gender as noted in studies such as Nwona and Akogun, (2015) in his study on science, technology and mathematics.  Machin and Mcnally, (2006) in their study on gender and students’ achievement in English schools noted that the gap appears more controversial for students taking national examinations at the end of their compulsory secondary education.

Theoretical framework for the study

The study adopts Social constructivism theoretical framework. Social constructivism developed by Vygotsky (1978), emphasizes how meanings and understandings grow out of social encounters. This learning theory claims that knowledge is constructed based on personal experience and hypotheses of the environment and that learners continuously test these hypotheses through social negotiations.

Significance of the Study

The researchers aimed at examining the effect of integrating Artificial Intelligence(AI) on Senior Secondary School mathematics students’ learning of solid Geometry in Ogun state Senetorial Districts, Nigeria. It is a fact that students equipped with mathematical knowledge and skills will be active players in technology and vocational areas that are the bases for the economic development and transformation of the country. Therefore, this study will be   significant as it has an input to improve Nigeria’s education policy specifically applicable to the methodology of mathematics teaching and learning. The   study will contribute to the existing stock of knowledge and widens the literature in this area of education.

Objectives of the study

The purpose of this study was to   examine whether the integration of artificial intelligence(AI) on senior secondary school students has any effect on their learning of Geometry in the mathematics classroom in Ogun State Senetorial Districts Nigeria.

The main objective of the study will be to determine and document the effect of integrating   Artificial Intelligence(AI) on senior secondary school students on their learning of Solid Geometry in the mathematics classrooms.

1. investigate the effect of AI integration on students’ performance in geometry at the senior Secondary school level;
2. investigate the effect of AI integration on students’ attitude towards the learning of Geometry at the senior Secondary school level;
3. investigate the effect of AI integration and gender on students’ performance towards the learning of Geometry at the senior Secondary school level;

Research Questions

The following research questions were raised to guide this study:

1. What are the mean achievement scores of students taught using Integrated Artificial Intelligent Strategies(IAIS) on students’ performance in Geometry at the senior Secondary school level.
2. 2. What are the mean achievement scores of male and female students taught using AI integration package on students’ learning of Geometry at the senior Secondary school level.
3. How does students’ attitude affect their learning of Geometry at the Senior Secondary school level using Integrated Artificial Intelligent Strategies(IAIS)?

Research hypotheses

The following hypotheses were formulated and tested at 0.05 level of significance.

1. There is no significant difference in the mean achievement scores of students taught Geometry using Integrated Artificial Intelligent Strategies(IAIS)?
2. There is no significant difference in the mean achievement scores of male and female students taught Geometry using level using Integrated Artificial Intelligent Strategies(IAIS)
3. There is no significant difference in students’ attitude in their learning of Geometry using level using Integrated Artificial Intelligent Strategies(IAIS)?

METHODOLOGY

The study adopted a pre-test, post-test quasi-experimental design method to investigate the effect of integrating Artificial Intelligence(AI) on Senior Secondary School mathematics students’ learning of   Geometry in Ogun central Senetorial Districts in Nigeria (Creswell, 2013; Cohen Manion, & Morrison, 2007).

This is symbolically represented below.

O₁        X₁     O₂    Experimental Group (Integrated Artificial Intelligent Strategies(IAIS)

O₁          O₂    Control Group (Conventional Integrated Artificial Intelligent Strategies (CIAIS)

O₁ – represents pre-test measure, O₂ – represent post-test measure, X₁ – (Integrated Artificial Intelligent Strategies.

The effectiveness of the Integrated Artificial Intelligent Strategies(IAIS)package was   determined using a quasi-experimental procedure (pre-test, post-test, non-randomized, experimental and control groups) used at two levels of independent primary variable. The independent variables were the Integrated Artificial Intelligent Strategies(IAIS) and the Conventional Integrated Artificial Intelligent Strategies(CIAIS) while the dependent variable was the post-test performance of the students. Achievement Test in Geometry (ATG) was administered on both the Control and Experimental groups as pre-test and post-test. The Experimental Group was subjected to a treatment using (IAIS) while the Control Group was taught using Conventional Teaching method.

Population, Sample and Sampling Technique

Population for the study comprised of all 2^nd year   Secondary School mathematics students’ in Ogun state senatorial districts, Nigeria. The selection of the 300 participants for the study was through simple random sample. The researchers randomly assigned two schools as experimental schools and were taught using the Integrated Artificial Intelligent Strategies(IAIS) adopted by the researchers, while the other two schools categorized as control schools were taught using (chalk& talk) conventional Teaching method. Both purposive and random sampling techniques were adopted in the selection of three hundred (300) students from the three senatorial Districts in Ogun state, namely: Ogun Central; Ogun West and Ogun East.

Instrumentation

Instrument for data collection was Achievement Test in geometry (ATPG) and was used as Pre and Post-test for the study. Experts in mathematics validated the instrument in terms of (i) language clarity to the targeted audience (ii) relevance to the aims of the study, and (iii) coverage of the topics in the study. The reliability of test items was determined through the application of the spearman Brown formula with the sample of 150 participants.  However, the Cronbach Alpha computed to determine the internal consistency and reliability of the test was r =0.84.  It can be concluded, therefore, that the five test items are reliable and moderate difficulty level (Hill& Lewicki, 2007). The research instruments were validated by mathematics lecturers for face and content validity. The research questions were answered using descriptive statistics while the hypotheses were analyzed using Analysis of Covariance (ANCOVA) and the significance of the statistical analyses was ascertained at 0.05 alpha levels.

RESULT AND DISCUSSION

Table 1.  Post t-test gender results

From the table, the probability of error is greater than 0.05 (P= 4.77>0.05) for the males, and (P = 4.65>0.05) for the females. The results reveal that both males and their females’ counterparts in the two groups were not significantly different, an indication that the treatment was statistically not significant on either males or their females’ counterparts. Hence,   the  null hypothesis is  not rejected but accepted.

Hypothesis One

Null hypothesis (H₀):  There is no significant difference in the mean achievement scores of students taught   Geometry using AI integration package and those taught using conventional method.    

Alternative Hypothesis (H1_): There is statistically significant difference in the mean achievement scores of students taught   Geometry using AI integration package and those taught using conventional method.   

 conventional method.   

Table 2: The test of Between –Subject Effects

From Table 2, the result confirms the classification of pre-test scores as a covariate, and therefore, the use of ANCOVA analysis is established. In addition, the main effect AI integration package is observed after controlling for the pre-test scores. Thus, after the removal of the effect of pre-test, the AI integration package becomes obvious and significant as confirmed by F (1,311) =539.596, p<0.05. The significant result at level P< 0.05 indicates a less than 5% chance that the result is due to randomness. The flip side of this result indicates a 95% chance that the difference in the post-test achievement scores between the two groups is real difference and not simply due to chance. Hence, the null hypothesis ((H₀) is therefore rejected, an indication that the use  AI integration package  to teach  geometry  in the  classroom  accelerates students’ learning of    of the topic than the conventional teaching approach often employed by their teachers to teach the topic. Thus, Artificial Intelligent integration package   H_1: µ>µ Conventional method

Hypothesis Two

Null hypothesis (H₀₂): There is no significant difference in the mean achievement scores of male and female students taught Geometry using AI integration package and those taught using conventional method.   

Alternative Hypothesis 🙁 H₂₎    There is significant difference in the mean achievement scores of male and female students taught Geometry using AI integration package and those taught using conventional method.   Hypothesis two (H₀₂₎  was tested to further establish the claims   that there is no significant difference in students’ post-test achievement mean scores for males and females in the experimental group.

Table 3 ANCOVA Summary of ANCOVA on  Students’ achievement

a.R Squared =.648 (Adjusted R Squared =.285) **Denotes not significant at 0.05 alpha level.

As observed from the table (F (_{1, 310)} = 0.008, p=0.987, n²p=0.001) the effect of gender is not significant. The result indicates no significant difference in  the  male students’ performance  from that of their female counterparts when they are taught Geometry using Artificial Inteligence integration package    and the covariate (pre-test) is statistically controlled. The result reveals that the significance of F = 0.987 is greater than 0.05 alpha levels. The   use of  Artificial Inteligence integration package  to teach both male and female student does not produce any significant difference in their post-test performances.  Hence, the  null hypothesis was upheld  that there is no significant difference between students’ achievement in   Geometry  for the two groups based on gender when exposed to the Artificial Inteligence integration  method of instruction.

Hypothesis Three

Null hypothesis (H₀₃):  There is no significant difference in students’ learning attitude in   Geometry using AI integration Package for the control and the experimental groups.

Alternative Hypothesis: (H₀₃):    There is significant difference in students’ learning attitude in    Geometry using AI integration Package for the control and the experimental groups.

To further substantiate the claims that a significant difference exists in students’ post-treatment attitude mean scores in the experimental group, hypothesis three was tested.   The students’ post-intervention attitudes score in the experimental and control groups using ANCOVA indicate that the difference in means between the two groups is statistically significant: F _(1.299) = 23.405, p =.000*, n²_p = .073). As observed in the table, the two-tailed p-value was 0.000, meaning that random sampling from identical populations would lead to a difference smaller than was observed in 100% of experiments and larger than was observed in 0% of experiments. Thus, the null hypothesis four is rejected and we uphold that there is a significant main effect from intervention on students’ attitudes towards geometry.

 Table 4. Summary of    Students’ post-attitude treatment

1. R Squared = .653 (Adjusted R Squared = .639) * Sign ** Not Sign

DISCUSSION OF FINDINGS

Results of this study showed a significant difference between the post-test achievement means scores of the experimental and control the group. Therefore, using Integrated Artificial Intelligent Strategies (IAIS) to teach Geometry at the senior Secondary school level is effective.  Finding of this study supports earlier findings Ayanwale et al., (2024); Opesemowo & Adekomaya, (2024) who stressed that AI-based math applications (such as Photomath, Soratic, Mahtway, Maple Calculator, and Microsoft Math Solver) can provide immediate feedback on students’ math problem solutions. The findings also supported those researchers such as (Ayanwale et al., 2024; Opesemowo & Adekomaya, 2024), who opined that AI can automate the grading of mathematics assignments and assessments, saving teachers time and allowing them to focus on other areas of teaching practices.   The finding is consistent with the assertion of Nwona and Akogun, (2015) in their study on science, technology and mathematics that the relationships between gender and academic performance in mathematics becomes primarily necessary in view of the observed wide gap in the mean academic performance in respect of gender. Aloso consistent with Machin and Mcnally, (2006) findings in their study on gender and students’ achievement in English schools who noted that the gap appears more controversial for students taking national examinations at the end of their compulsory secondary education.  Akintade, Ogbonnaya, &Mogari, (2013); Agommuoh, &Ifeanacho, (2013); Akintade, Ogunrinade &Akintade, (2019) reported that strategy such as the intergration of Artificial intelligence can promote students’ achievements significantly in subject content. The non-significant main effect of gender on students’ achievement in plane geometry is in line with previous studies (Akintade 2017, Akintade, Ogunrinade and Campbell 2018, Fatade, 2012) who reported a non-significant main effect of gender on students’ performance in science and plane geometry. Findings of the   present study revealed a significant difference between students’ leaning attitude and their academic achievement in geometry as supported (Agommuoh, and Ifeanacho,2013) when they were exposed to the use of Integrated Artificial Intelligent Strategies (IAIS) to learn Geometry at the senior Secondary school level. Onyebuchi & Nwachukwu, (2021) reported that this level of technological advancement will benefit the most Nigerian secondary schools that have an unrelenting problem regarding; huge student enrollment ratio, scanty teaching aids, and students’ heterogeneous learning difficulties.   With all the beneficial effect of the integrations of Artificial intelligence strategy as discussed in the study, it is reasonable to conclude that the approach has positively enhanced the development of students’ achievement and attitude towards the learning of Geometry.

CONCLUSION

In conclusion, this   approach has positively enhanced the development of students’ achievement and attitude towards learning of Geometry at the senior Secondary school level. Also, the impact of integrating Artificial Intelligence (AI) on the teaching and learning of geometry in secondary schools within Ogun Central Senatorial District, Nigeria has enhanced students’ understanding and retention of geometric concepts. Furthermore, the use of Integrated Artificial Intelligent Strategies (IAIS) to learn Geometry in secondary schools within Ogun Central Senatorial District, has created opportunities for students to investigate, discover, examine, apply, prove and communicate both plane and solid geometry.  It is therefore necessary for teachers of mathematics to review their approaches and methods of teaching geometry in the school in light of the present findings.  

RECOMMENDATION

Findings from the study have indicated that using Integrated Artificial Intelligent Strategies (IAIS) to teach Geometry at the senior Secondary school level is effective. The researchers, therefore, recommend the following proposals.

• That the use of Integrated Artificial Intelligent Strategies (IAIS) to teach Geometry at the senior Secondary school level   should be implemented in Nigerian secondary schools in order to enhance students’ performance on the topic.
• That the adoption of Integrated Artificial Intelligent Strategies (IAIS) to teach Geometry at the senior Secondary school level in Nigerian secondary schools would motivate students to learn, stimulate their interest and ultimately, improve their performances in mathematics.
• That the Federal Government should re- emphasize that teachers are to be more computer literate since the lack of it will decelerate the implementation of Integrated Artificial Intelligent Strategies (IAIS) to teach Geometry at the senior Secondary school level
• Children are to be motivated by their parents with various and relevant computer gadgets such as Integrated Artificial Intelligent Strategies to enhance their performance in geometry.
• Computer laboratory that is fully equipped with computer system, and good conducive environment for learning should be mandatory in schools. However, both the Government and school authority should support them financially.

While the potential for AI to revolutionize education is recognized, successful implementation requires substantial government investment in infrastructure, policy development for ethical use, data protection and comprehensive professional training for educators.

Ethical Consideration

Ethical protocols were strictly followed throughout the study since it deals with human subjects.  Informed consent was obtained from the local education authorities, school principals to use their schools and their students. They were all briefed on the study’s objectives and their rights.  None of the participants used for the study were forced to participate, and the identity of every participant was kept under strict confidentiality. The researchers were honest in their dealings with all participants and were mindful of their personal cost such as an affront to dignity; embarrassment, loss of trust, and lowered self-esteem.  In addition, measures were implemented to minimize participant distress, with support available as necessary, and cultural sensitivity was maintained in all interactions. Transparency was ensured in reporting findings, and any potential conflicts of interest were disclosed to maintain objectivity and credibility.

Disclaimer (Artificial Intelligence Use)

To keep up with the developing technologies and applying them in the secondary schools in Nigerria  for the learners’ benefit, the authors  employed both ChatGPT and Copilot, to assist in refining the manuscript. Moreover, the reseachers employed AI-powered platforms for paraphrasing content, checking grammar, improving readability, and enhancing coherence while preserving the intended meaning of the original text. Similarly, the  free versions of ChatGPT and Copilot were  used to streamline writing processes and ensure clarity in communication. However, the integration of these AI tools aimed to support academic writing while maintaining research integrity and authorial intent.

ACKNOWLEDGEMENT

The authors wish to thank the Sponsor, Tertiary Education Trust Fund, Abuja, Nigeria. The grant number is TETF/DR&D/CE/COE/OSIELE/IBR/2021/VOL 1I.

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