The Role of Artificial Intelligence in Enhancing Chemistry Education: A Pathway to Improve Student’s Performance and Academic Achievement in Nsukka Education Zone

The Role of Artificial Intelligence in Enhancing Chemistry Education: A Pathway to Improve Student’s Performance and Academic Achievement in Nsukka Education Zone

Idris Nafisat Oyiza¹, *Okere Ikechukwu Justice², Basil C.E Oguguo³, Dimkpa Chika Hannah⁴, Odo Anthony chikwado⁵, Yohanna Ibrahim⁶, Omatalu Daniel Izuchukwu⁷, Chinweike Jane Ndubumma⁸

^1,2,3,5,6,8Department of Science Education, University of Nigeria Nsukka

⁴Department of Special Needs Education, University of Nigeria Nsukka

⁷Department of Educational Psychology, Federal College of Education, Eha-Amufu

*Corresponding author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.906000384

Received: 29 May 2025; Accepted: 14 June 2025; Published: 18 July 2025

ABSTRACT

This study was carried out to examine the role of artificial intelligence in enhancing student’s performance and academic achievement in chemistry. The study was conducted in Nsukka Education zone.  The study adopted correlation design. Two research questions and two hypotheses were used in the study. The population of the study comprised of 3527 chemistry students from which 305 students were drawn using multistage sampling technique. The instruments; artificial intelligence questionnaire (AIQ), students’ academic pro-forma rating scale (SAPRS) and students’ academic achievement in Chemistry (SAATC) were used in the study. The internal consistency reliability indices of (AIQ) and (SAPRS) were determined to be 0.75 and 0.77 using Cronbach alpha while the internal consistency reliability of (SAATC) was 0.72 using KR-20. Simple linear regression was used to answer the research questions while regression ANOVA was used to test the hypotheses at 0.05 level of significance. The result shows that students’ knowledge of artificial intelligence significantly predict students’ academic performance and achievement in Chemistry. Based on the findings, it was recommended among others that, Chemistry teachers should encourage learners centered method in the process of teaching by so doing students will be exposed to the use of artificial intelligence which will help to improve students’ academic achievement in Chemistry.

Keywords; Artificial Intelligence, Chemistry Education, Students’ Performance and Academic Achievement.

INTRODUCTION

The poor nature of students’ academic achievement in chemistry has drawn researchers and government interest, propelling researchers and government to seek for solutions to the poor academic achievement of students in chemistry. According to Andrew, Steinfelds and Andrew (2023), Chemistry is defined as the scientific study of the composition, behavior and transformations of substances, and the energy changes that accompanies this transformation. Nwafor and Chibueze (2024), defined Chemistry as the branch of science that studies matter, its properties, structure, and how it interacts with other substances. Operationally, chemistry can be defined as the study of chemical processes that occur in living organisms and the environment and the application of chemical principles to understand and solve problems in fields such as medicine, energy and sustainability.

The main objectives and importance of studying Chemistry as a subject in senior secondary school curriculum as articulated by Nigerian Educational Research and Development Council (NERDC, 2013) include; to provide knowledge and understanding of the nature of matter, to develop the skills for scientific inquiry, to promote critical thinking and problem solving, to develop attitudes for scientific endeavors, to prepare students for further studies in chemistry and other related disciplines, to equip students with practical skills for everyday life, to promote technological advancement, to encourage environmental awareness.

In order to achieve these asserted objectives of Chemistry, it is imperative for students to understand Chemistry, as a subject and attain high grade in their internal and external examinations; which could be refers to as academic achievement. Ugwuanyi, Okeke and Ageda (2020) defined academic achievement as how well a student accomplished tasks and studies which were assigned to him or her. Okere, Onoja, Ezeokoye, Ibrahim and Ugwu (2024), noted that academic achievement is the degree at which the goals and objectives of the teachers, students and institution have been attained. Hence, academic achievement is the outcome of education goals and objectives. Academic achievement is the sign indicating if teaching and learning has taken place or not. For learners  to attain a great height in  divergence area of life, be it physical science, natural science, management or occupation, they need a high academic achievement to operate effectively and efficiently (Oparaji & Ugwu, 2019).

Sadly, Senior Secondary School students’ academic achievement in Chemistry, has not been encouraging. Particularly in recent years, the academic performance of secondary school students in West African Certificate Examinations Council (WAEC) in Chemistry has not been encouraging.  This is shown in WAEC Chief Examiner’s Reports of 2020, 2021, 2022, 2023 and 2024. The students’ academic achievement in Chemistry in Nigeria has been tremendously poor (Vazsonyi, Javakhishvili & Blatny, 2022). Specifically, the observed poor academic achievement of students in Chemistry in Nsukka Education Zone Enugu State is shown in students’ WASSCE results of 2020, 2021, 2022 and 2023 with percentage failure rates of 54%, 72.1%, 70.4% and 62.2% respectively. This implies that the proportion of Chemistry students who attain a pass mark has never been up to 45% in each of these years. This situation is common in most L.G.A including Nsukka Education Zone, Enugu State. Therefore, the government employed teachers to redefined academic achievement of students for a better result, yet poor academic achievement in Chemistry still persist (Idika, Onuoha, Nji & Eze, 2018). However, Okoro, Nwagbo, Ugwuanyi and Ugwu (2022) as well as Okere, Onoja, Njoku, Oguebie, Ugwu and Ugwuanyi (2024) suggested factors that could influence students’ academic achievement which includes; motivation, self-control, students’ engagement, location, self-regulationtask persistence and introduction of artificial intelligence tools.

Artificial intelligence is very important in improving students’ academic performance as well as achievement because it promotes students’ academic engagement. According to Okere, Onoja, Njoku, Oguebie, Ugwu and Ugwuanyi (2024), Artificial Intelligence can be defined as the improvement of computer systems which is capable of performing tasks that truly require human intelligence to carry out. Yaping, Junjie and Nor (2022) addressed that artificial intelligent can be seen as the ability of computers to understand, create human language and interpret. Artificial intelligence regenerates tasks like machine translation, sentiment analysis and speech recognition. However, Wardat, Tashtoush, AlAli, and Saleh, (2023) conducted a study on Artificial Intelligence in Education: Mathematics Teachers’ Perspectives, Practices and Challenges. The authors stipulated that artificial intelligence influences students academic performance as well as students academic achievement. Again, Okere, Onoja, Njoku, Oguebie, Ugwu and Ugwuanyi (2024) who worked on assessment of the level of Economics teachers awareness and the applications of artificial intelligence in teaching and learning Economics found that artificial intelligence knowledge improvers  students’ academic achievement Uygun, Aktaş, Duygulu and Köseer (2024) also addressed that teachers’ knowledge of artificial intelligence enhances students’ academic achievement.  More also, Cardoso (2022) pointed out that teachers knowledge of artificial intelligence promotes students’ performance and achievement. Considering the importance of the applications of artificial intelligence in teaching and learning which could in turn improve students’ achievement and performance, teachers’ skills and the poor performance of chemistry students, the researchers deemed it necessary to investigate more on the role of artificial intelligence in enhancing chemistry education: a pathway to improve student’s performance and academic achievement in Nsukka Education Zone, Engu State.

The purpose of this study is to investigate secondary school students’ knowledge of artificial intelligence in enhancing student’s performance and academic achievement in Chemistry. Particularly, the study sought to determine the amount of;

1. Variation in secondary school students’ performance in Chemistry that is attributed to students’ knowledge of artificial intelligence.
2. Variation in secondary school students’ achievement in Chemistry that is attributed to students’ knowledge of artificial intelligence.

In line with the purpose of the study two research questions were posed;

1. What is the amount of variation in secondary school students’ academic performance in Chemistry that is attributed to students’ knowledge of artificial intelligence?
2. What is the amount of variation in secondary school students’ academic achievement in Chemistry that is attributed to students’ knowledge of artificial intelligence?

In line with the purpose and research question of the study two null hypotheses were formulated and were tested at 0.05 level of significant.

Ho₁: students’ knowledge of artificial intelligence is not a significant predictor of students’ academic performance in Chemistry.

Ho₂: students’ knowledge of artificial intelligence is not a significant predictor of students’ academic achievement in Chemistry.

METHODS

The study adopted correlation research design. Correlation research design is a design that allows a researcher to establish relationships that exist between two or more variables (Nworgu, 2015). This design is considered appropriate for the study because the study seeks to ascertain the relationship that exists between students’ performance, achievement in Chemistry and students’ knowledge of artificial intelligence. The population comprised of 3063 (Igbo-etiti; 634, Nsukka; 2105 and Uzouwani; 324 total of 3063) senior secondary school II (SSS2) Chemistry students in the 60 public secondary schools found in Nsukka Educational zone of Enugu State. (Source: Post Primary Schools Education Management Board Enugu, 2023- 2024).  The sample size of 305 was used in the study.

Three instruments; Students knowledge of artificial intelligence Questionnaire (SKAIQ), students’ academic pro-former rating scale (SAPRS) and Chemistry achievement Test (CAT) were used in the study. Students’ knowledge of artificial intelligence Questionnaire (SKAIQ), was developed by the researchers. The instrument contain, 20 items related on a four-point scale. 4-Strongly Agree, 3 -Agree, 2 -Disagree and 1 – Strongly Disagree. SKAIQ was used to measure students’ knowledge of artificial intelligence. Students’ academic Pro-former rating scale (SAPRS) was adopted by the researchers. The instrument contains 20 items designed on a four-point scale; 4-Excellent, 3 -Good, 2 –Poor and 1–Very Poor. SAPRS was used to measure students’ performance. Chemistry Achievement Test (CAT) contains 30 items and was constructed by the researchers with the use of test blueprint. CAT contains instruction and options letter A-D with one as the right option. Each correct item in CAT was scored 1 mark. The instrument was used to measure students’ achievement in Chemistry. The instrument was trial tested by administering the instruments on 20 SS2 Chemistry students in Obollo-Afor L.G.A. Enugu State which was not part of the schools and L.G.A sampled. The school was used because it is close to the sampled schools and may have same characteristics with the selected schools. Hence, internal consistency reliability of the instrument (SKAIQ) and (SAPRS) was established using Cronbach-alpha method because the instruments were polytomousely scored; instruments with no right or wrong answer. The reliability co-efficient of 0.75 and 0.77 was obtained for SKAIQ and SAPRC respectively.

Again, the internal consistency reliability of CAT was established using Kudder-Richardson 20 (KR-20). This method was used in that it is better for estimating internal consistency of instruments that are dichotomously scored; Meaning instruments with right/wrong responses. Hence, reliability co-efficient of 0.72 was obtained. The researchers presented a letter to school principals in order to permit them carry out a research using SSS2 Chemistry students. They also requested that Chemistry teachers in each of the schools sampled should assist them in carrying out the research, which was granted. The research assistants were informed on the system of administration as well as collection of the instruments. The researchers and the research assistant; Chemistry teachers in each of the sampled schools made use of face-to-face method to administer and collect the instruments from the respondents. This method was to ensure sufficient return of the instrument as well as to enable researchers attend to respondents’ questions, while responding to the items of the instruments. The research assistants also helped the researchers in scoring the instruments immediately the respondents finished responding to the items of the instrument. From the data collected, Simple linear regression was used to answer all research questions while regression ANOVA was used to test the null hypotheses at 0.05 alpha level. A correlation co-efficient of 0.00 to 0.20 was seen as very low, 0.20 to 0.40 was considered low, 0.4 to 0.60 moderate or medium, 0.60 to 0.80 was seen as high while 0.80 and above was considered very high (Nworgu, 2015).

RESULTS

The results of the data analyzed in this study are presented in tables according to the research questions and hypotheses stated.

Research question one; What is the amount of variation in secondary school students’ academic performance in Chemistry that is attributed to students’ knowledge of artificial intelligence?

Table 1: Linear regression analysis of the amount of variation in secondary school students’ academic performance in Chemistry that is attributed to students’ knowledge of artificial intelligence

Table 1 above shows the regression analysis of the amount of relationship between secondary school students’ academic performance in Chemistry and students’ knowledge of artificial intelligence. The result shows a correlation coefficient (r) of 0.24. This implies that there is a low relationship between students’ academic performance in Chemistry and students’ knowledge of artificial intelligence. Furthermore, the coefficient of determination (R²) associated with the correlation coefficient of it is 0.05. This means that 5% of variation in students’ performance is attributed to students’ knowledge of artificial intelligence. The result indicates that, 95% of variation in students’ performance is attributed to other factors order than students’ knowledge of artificial intelligence.

Hypothesis One; Students’ knowledge of artificial intelligence is not a significant predictor of students’ academic performance in Chemistry.

Table 2: Regression ANOVA result of the relationship between students’ knowledge of artificial intelligence and academic performance.

Result in table 2 shows (F (1,304) = 17.776 p = 0.000) the relationship between knowledge of artificial intelligence and academic performance. Since the p-value of 0.000 is less than alpha level of 0.05, the null hypothesis is rejected. Therefore, the researchers conclude that there is a significant relationship between knowledge of artificial intelligence and academic performance of the students.

Research Question 2; What is the amount of variation in secondary school students’ academic achievement in Chemistry that is attributed to students’ knowledge of artificial intelligence?

Table 3: Regression analysis of the relationship between students’ knowledge of artificial intelligence and academic achievement of the students

Table 3 above shows the regression analysis of the relationship between knowledge of artificial intelligence and academic achievement in chemistry. The result indicates that a correlation coefficient (r) of 0.33. This implies a positive low relationship between knowledge of artificial intelligence and academic achievement in chemistry. The coefficient of determination (R²) associated with the correlation coefficient of it is 0.11. This means that 11% variation in students’ academic achievement is attributed to students’ knowledge of artificial intelligence. The result also indicates that, 89% variation on students’ academic achievement is attributed to other factors order than students’ knowledge of artificial intelligence.

Hypothesis Two; students’ knowledge of artificial intelligence is not a significant predictor of students’ academic achievement in Chemistry.

Table 4: Regression ANOVA results of students’ knowledge and its relationship with students academic achievement.

Result in table 4 indicate (F (1,303) = 36.028p = 0.000) the relationship between knowledge of artificial intelligence and academic achievement. Considering the fact that the p-value of 0.000 is less than alpha level of 0.05, the null hypothesis is rejected. Hence, the researchers conclude that there is a significant relationship artificial intelligence and academic achievement

DISCUSSION OF THE FINDINGS

The findings of this study show that the knowledge of artificial intelligence significantly influences students’ academic achievement and performance. The findings agree with the findings of Wardat, Tashtoush, AlAli, and Saleh, (2023) that artificial intelligence influence students’ academic performance and students academic achievement. The findings is also in consonant with the findings of Okere, Onoja, Njoku, Oguebie, Ugwu and Ugwuanyi (2024) who pointed out that artificial intelligence knowledge improvers  students’ academic achievement. The findings is also in line with Uygun, Aktaş, Duygulu and Köseer, (2024) that teachers’ knowledge of artificial intelligence enhances students’ academic achievement. Finally. the finding is in agreement with the findings of Zatt, Rocha,  Anjos,  Caldas, Cardoso and Rabelo (2022) that teachers knowledge of artificial intelligence promotes students’ performance and achievement.

CONCLUSIONS OF THE STUDY

The findings of this study show that students’ knowledge of artificial intelligence significantly predicts students’ academic performance. Also, students’ knowledge of artificial intelligence significantly predicts students’ academic achievement. Therefore, the following conclusions were made thus; since students’ knowledge of artificial intelligence significantly predict students’ academic performance as well as students’ academic achievement and students’ knowledge of artificial intelligence has a positive relationship with students’ academic performance and academic achievement. One can conclude that if students can embrace artificial intelligence which enables them to be actively engaged in teaching and learning, students’ academic achievement will improve adequately thereby reducing students’ poor academic achievement.

RECOMMENDATIONS

 The following recommendations were made base on the findings of this study,

1. Parents should provide internet facilities for their children at home. So that they can always interact with artificial intelligence tools at home as these will enable the student to have a better understanding of AI which will help to improve academic achievement of students.
2. Teachers should always encourage students to be actively engaged while teaching and learning is going on particularly with respect to artificial intelligence.
3. Chemistry teachers should encourage learners centered method in the process of teaching so that students will be exposed to the use of artificial intelligence as this will help to improve students’ academic performance and achievement in Chemistry.
4. The staff and management of schools should ensure they create an enabling environment for teachers so that they can engage in all forms of in-service training geared toward improving their artificial intelligence skills.
5. Federal government, state ministry and education stakeholders should ensure that free workshops and conferences are organized for teachers as well as students on the applications of artificial intelligence, this will help to improve students’ academic achievement in chemistry.

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