1Corresponding author contact: boladele@uj.ac.za Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria 1Babatunde Kasim Oladele, 2Modinat Adetutu Laide-Raji 1Faculty of Education, University of Johannesburg, South Africa 2Institute of Education, University of Ibadan, Nigeria ABSTRACT This study investigated the teachers’ pedagogical skills, students’ readiness, and achievement in data processing in senior secondary schools in the Ibadan metropolis, Oyo State. The correlational design was adopted in this study to establish the relationship among the variables of concern. We used a multi-stage sampling procedure to select samples. Data was gathered using the pedagogical skills rating scale, the student's readiness questionnaire and the data processing achievement test. Data collected from the respondents were analysed using frequency, percentage, graph, Pearson product-moment correlation, and multiple regression analysis. The study revealed the pattern of teachers’ pedagogical skills with regard to communication skills, evaluation skills, adaptability skills, inclusivity skills, and compassion skills, with compassionate skills having the greatest percentage of value. The results further show the composite contributions of teachers’ pedagogical skills and students’ readiness, having a significant contribution to achievement in data processing. Also, there was no significant relative contribution of teacher pedagogical skills, while there was a significant contribution of student readiness to achievement in data processing. It was recommended that the government should not relent in providing appropriate training and seminars to improve teacher pedagogical skills, while students should work hard to attain positive achievement in data processing. Keywords: Achievement in data processing, teachers’ pedagogical skills components, students’ readiness, correlation ISSN 1916-7822. A Journal of Spread Corporation Volume 14 No. 1 2025 Pages 43-61 https://journal.lib.uoguelph.ca/index.php/ajote/index Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 43 INTRODUCTION The rapid progress in computer technology, coupled with its user-friendly nature, has greatly enhanced its attractiveness to a wide range of users. This evolution, paired with the shift of learners to Generation Z in the digital age, necessitates pedagogical adjustments and advancement (Shaari & Kamsin, 2024). Computers have streamlined data processing, making it both accessible and efficient. Consequently, organizations are increasingly reliant on data scientists to meet their unique needs. Data processing serves as a valuable resource for enriching education by providing supplementary materials and resources for classroom instruction. In this data-driven age, educators must adopt creative, innovative, and flexible approaches while being open to adapting teaching strategies to maximize their advantages. Students and teachers are often seen as having more recent experiences of ICT and as being more committed to its use than longer serving teachers (Hammond, Crosson, Fragkouli, Ingram, Johnston‐Wilder, Johnston‐Wilder, Kingston, Pope & Wray, 2009). The commercial world has been completely transformed by computers, and as a result, data processing is clearly in demand. The need for data processing systems (dedicated computer software for processing) has become the priority of most data processing organisations. Considering the importance of data processing enables the students to acquire a specific skill that will enable them to create jobs and generate wealth or face the challenges of the new millennium. Data processing is the method by which unprocessed data is transformed into useful information. There are several difficulties when processing the data. Data Processing integration in school is understood as the usage of technology seamlessly for educational processes like transacting curricular content and students working on technology to do authentic tasks (Kainth & Kaur, 2015). Nowadays, ICT facilities are used to deliver lessons in developed countries, and their use has impacted the teaching-learning process positively. The rise of e-learning resources, educational software, the use of the Internet in education, and the establishment of state databases for student information have led to the creation of extensive repositories of educational data (Romero & Ventura, 2024). The integration of Data Processing (DP) into secondary school education has become increasingly important in preparing students for the digital age. According to a study by Shavinina (2016), students' ability to understand and efficiently use ICT tools was greatly impacted by their past understanding of computer hardware and software. Research Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 44 indicates that students who possess a solid foundation in fundamental computer literacy and digital abilities are more likely to be prepared for data processing (Siu, 2017). The objectives of data processing, as stated by the Nigerian Educational Research and Development Council (2009), are to equip learners with fundamental skills in data management, utilise computers for efficient business transactions, and develop a proficient level of competence in ICT applications that will foster entrepreneurial abilities in students. Data processing is a versatile discipline with wide-ranging applications across several sectors, such as business, education, healthcare, and research. The significance of these disciplines, such as data science, machine learning, artificial intelligence, data quality, and data security, is growing in tandem with their advancements (Omoniyi & Quadri, 2003). However, the inclusion of data processing as a subject of trade is to align with the objectives of the National Empowerment and Economic Development Strategy (NEEDS). These objectives include promoting a change in values, eliminating poverty, creating employment opportunities, generating wealth, and utilising education to empower the population. Therefore, it is crucial to implement teaching methods that encourage active participation and involvement from students to enhance their preparedness and success in the field of data processing. Teachers must be educated with pedagogical expertise, particularly in the use of various types of educational technology (Omar & Mohmad, 2023), as well as become more creative and flexible in providing instruction (Danuri et al., 2021). Extensive research has demonstrated the advantages of data processing in education, which undeniably impacts teaching and learning. Data processing in education significantly enhances teaching and learning outcomes. It enables personalised learning experiences, allowing educators to customise their instructional strategies to meet diverse student needs (Elbouknify etal, 2025; Sajja etal ,2023). Learning analytics play a crucial role in identifying students at risk of academic failure early, thereby improving retention and success rates. Moreover, data processing supports informed decision-making by providing actionable insights based on student performance metrics and behavioural trends. Information and Communication Technology (ICT) tools increase operational efficiency by automating tasks such as student registration and resource allocation (Romero & Ventura, 2024). Multiple challenges hinder the teaching and learning of information and communication technology (ICT), which data processing is one of the components in secondary schools in Nigeria. Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 45 One major hindrance is the insufficient proficiency of ICT teachers to effectively execute the ICT curriculum in secondary schools (Kabiru & Sakiyo, 2013). Access to ICT is a key issue in encouraging teachers to use ICT (Selwood & Pilkington, 2005). Integrating Information and Communication Technology (ICT) into education can greatly enhance teaching and learning. However, challenges like inadequate infrastructure, limited teacher training, and resistance to change hinder effective ICT integration. Research in Sri Lanka indicates that teachers generally possess positive attitudes toward ICT, but poor infrastructure and a lack of professional development opportunities limit its effective implementation (Palagolla & Wickramarachchi, 2019). Also, artificial intelligence through adaptive learning systems and automated grading tools reduces educators' workload and enhances instructional responsiveness. It is satisfying to affirm that the present global trend in education is to investigate the benefits that data processing brings to the teaching and learning process. Teachers can assess students' preparedness through periodic screenings or evaluations and use this data to modify instructional approaches and learning activities. Gandhi (2010) cites Thorndike's law of readiness, which states that learning occurs when there is a state of preparedness for action, achieved through preliminary modification, deposit, or attitude. A study indicated that students with elevated self-efficacy exhibit a strong belief in utilising information and communication technology (ICT) tools and resources to showcase a higher level of preparedness (Law, Pelgrum, & Plomp, 2008). Maswati & Krismiyati (2020) reported that students' readiness to learn is influenced by the learning environment and the teacher's ability to adapt pedagogical strategies to meet students' needs. Studies have shown that students' prior knowledge has a more substantial impact on their final performance than their socio-economic backgrounds. Furthermore, the long-term influence of teachers on students' prior knowledge highlights the importance of effective teaching practices (Polymeropoulou & Lazaridou, 2022) The reform of the senior secondary school curriculum is a significant move towards the goal of building a robust and self-sufficient society with a thriving and dynamic economy that offers many possibilities for its residents (Osuafor, 2012). Pedagogical competence deals with teaching skills, including teaching techniques, curriculum development and assessment (Irmawati et al., 2017). Pedagogical competency refers to the ability to teach by starting with familiar concepts and progressing to unfamiliar ones; Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 46 beginning with tangible examples and moving towards more abstract ideas; and starting with basic concepts and gradually introducing more advanced ones. Competence is broadly defined as a combination of cognitive, affective, motivational, volitional, and social dispositions that form the basis for performance (Zlatkin-Troitschanskaia et al., 2016). Pedagogical competence significantly influences student achievement, as demonstrated in studies across different subjects and regions (Mohammed, Ado & Ibrahim,2023; Adeyemi, 2020). Padagas (2019) stated that improving teacher education contributes much to the realisation of the goals set for the whole educational system. The relationship between teachers' pedagogical skills and student achievement is evident in various subjects, including data processing, where effective teaching methods can lead to improved student outcomes (Mercado, 2022). Hathaway and Fletcher (2018) highlighted the importance of preparing teachers with the awareness to appropriately discern differences among learners to negotiate the pedagogical challenges related to the impact of learner diversity. In the context of teaching techniques, they utilise various strategies such as independent learning, differentiated learning, and interactive or collaborative learning. Self- regulated learning has a positive effect on academic outcomes (Dignath and Büttner, 2018). Also, teachers' pedagogical communication skills, such as building rapport and varying teaching methods, are important for creating a supportive learning environment (Akinbode, Aderanti & Ayodele, 2023). Effective teaching requires a combination of skills, including set induction, closure, use of examples, and questioning, which are essential for engaging students and facilitating understanding (Umoh, 2024). The instructional strategies and pedagogical approaches used by educators have a considerable impact on students' preparedness and success in data processing. In research done in Malaysia, the results revealed that implementing student-centred and inquiry- based learning methodologies enhanced students' ICT skills (Hakim & Ting, 2017). Law, Pelgrum, and Plomp (2008) wrote a book at the University of Hong Kong that revealed that project-based learning and group projects, when utilising information and communication technology (ICT), enhance student engagement, foster critical thinking, and facilitate problem-solving. Internationally, educational systems are embracing innovative technology to integrate data processing into the instructional and learning process to equip students with the requisite information and abilities in their respective fields. The teaching profession is transitioning from a Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 47 focus on teachers to a focus on students in the design of learning environments. Student readiness, in a broad sense, refers to a learner's capacity to acquire knowledge and make behavioural changes that result in effective and successful outcomes. A well-prepared student for a course will not only have the essential information and skills required to confidently grasp the topic being taught but also demonstrate open-mindedness and a strong desire to learn. Santrock (2012) stated that students who show a great level of readiness and excel academically are less likely to feel frustrated in the classroom because they can complete their tasks efficiently, have positive self-perceptions, and show a strong enthusiasm for learning compared to students who struggle with learning. Pedagogical skills encompass a teacher's ability to effectively deliver content, engage students, and adapt teaching methods to suit diverse learning needs. These skills are crucial in fostering an environment conducive to learning, which in turn affects students' readiness and achievement. This research highlights the importance of these skills in various educational contexts, emphasising their role in enhancing student performance. This study, therefore, investigated teachers’ pedagogical skills, students’ readiness and achievements in data processing in senior secondary school to ascertain the status of both teachers and students concerning the variables of concern. The following research questions were asked, and answers were provided. 1. What is the pattern of teacher pedagogical skills in senior secondary schools in Ibadan Metropolis, Nigeria? 2. What are the composite contributions of teachers’ pedagogical skills and students’ readiness to achievement in data processing in senior secondary schools in Ibadan Metropolis, Nigeria? 3. What are the relative contributions of teachers’ pedagogical skills and students’ readiness to achievement in data processing in senior secondary schools in Ibadan Metropolis, Nigeria? METHODOLOGY The study adopted a correlational design to ascertain the relationship that exists among the variables of the study. The variables of the study include the independent variables which are teacher pedagogical skills and student readiness, and the dependent variable, which is achievement in data processing without any manipulation. The population of the study comprised students in all the senior secondary school students who offered data processing in the Ibadan Metropolis of Oyo State. A multistage sampling procedure was used to select samples for the study. In Ibadan, there are two educational zones, which are Ibadan Metropolis and Ibadan Less City. A purposive Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 48 sampling technique was used to select Ibadan Metropolis because of the availability of ICT facilities in the school located in the zone. A simple random sampling technique was used to select two Local Government Areas (LGAs) from the five LGAs in the zone. The two Local Government Areas selected are Ibadan Southwest and Southeast. Also, a simple random sampling technique was used to sample five schools each from the two selected LGAs, totalling 10 schools, and a simple random sampling technique was used to select 40 students each from the ten schools. The envisaged sample size was 400, but 387 students finally participated in the study. The following three instruments were used to collect data: the Teacher Pedagogical Skills Rating Scale (TPRS), the Student Readiness Questionnaire (SRQ) and the Data Processing Achievement Test (DPAT). Some constructs captured by the TPRS instruments include teachers’ communication skill, evaluation skill, adaptability skill, inclusive skill and compassion skill. The SRQ instrument captured statements such as “I make myself prepared for the data processing subject”, “I actively participate in the discussion and/or clarifying things I did not know”, “I always keen for data processing class”, and Data processing is my best subject The data processing achievement test was used to assess the students’ ability in data processing. Items for the data processing achievement test were adopted from the standardised 2021 test items of the West Africa Examinations Council (WAEC). The Teacher Pedagogical Rating Scale (TPRS) and Student Readiness Questionnaire (SRQ) instrument’s reliability coefficients were established using the Cronbach Alpha method, while the Data Processing Achievement Test (DPAT) reliability coefficient was established using the Kuder Richardson reliability method 20 for revalidation of the test item. The reliability estimates from the collected data for the instruments are as follows: Teacher Pedagogical Rating Scale (r = 0.90), Student Readiness Questionnaire (r = 0.87), and Data Processing Achievement Test (r = 0.72), respectively. Also, informed consent was sought from all the respondents and the school authorities. ethical approval was obtained from the school authorities and students who participated in the study before conducting the study to ensure the protection of participants' rights and confidentiality. Data collected were analysed using frequency, percentages, Pearson product movement correlation and multiple regression at ∞ = 0.05 level of significance. Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 49 RESULTS AND FINDINGS Table 4.1: Socio-Demographic Distribution of Students Variable Frequency Percent Gender Male 154 41 Female 230 59 Total 387 100 Age 14-16 337 87 17-19 48 12 20 and above 2 6 Total 387 100 Table 4.1 revealed that 41% of the students are male and 59% are female. This indicated that there are more female students than male students in the school sampled. For the age distribution of the respondents, 87% are between 14 and 16 years old, while 12% are between 17 and 17 years old, and 6% are between 20 and above. This indicates that most of the students are between the ages of 14 and 16, which is the stipulated age for this level of education. The analysis of the sociodemographic data suggests that there is a greater representation of female students in the sampled population because 41% of the students are male and 59% of the students are female. Given that prior research frequently emphasizes gender-based disparities in academic performance, study habits, and learning readiness, this gender distribution may have an impact on findings about readiness and achievement. Most respondents are in the typical age range for secondary education, with 87% of students being between the ages of 14 and 16. This implies that the results will primarily represent the preparedness and performance of pupils in this age range. The small proportion of older pupils (6% over the age of 20 and 12% between the ages of 17 and 18) may be a sign of delayed academic progress or other factors affecting school attendance, which could influence their readiness and Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 50 achievement differently from younger peers. The results of the statistical analysis conducted in this study and answers to the research questions raised are presented as follows: Research Question #1: What is the pattern of teacher pedagogical skills in senior secondary schools in the Ibadan metropolis? The result of the analysis of the pattern of the teacher's pedagogical skills is presented in Table 4.2. Table 4.2: Analysis of Students' Responses on the Pattern of Teachers' Pedagogical Skills S/N Statement Excellent Good Moderate Poor A Communication N % N % N % N % 1. Convey ideas and information orally 210 54.3 134 34.6 30 7.8 13 3.4 2. Teaching resources are well- organised 214 55.3 117 30.2 42 10.9 14 3.6 3. Check students' work at regular intervals 226 58.4 119 30.7 29 7.5 13 3.4 4. Ability to speak professionally and articulately 184 47.5 148 38.2 35 9.0 20 5.2 5. Ability to be an empathetic listener 177 45.7 145 37.5 41 10.6 24 6.2 6. Ability to provide accurate and comprehensive explanations and answers 213 55.0 123 31.8 27 7.0 24 6.2 B Evaluation 7. Identify what and how the student is thinking and learning 152 39.3 139 35.9 77 19.9 18 4.7 8. Identify the student's level of knowledge, skills and understanding 174 45.0 156 40.3 39 10.1 18 4.7 9 Identify strengths and weaknesses in students’ work 196 50.6 112 28.9 57 14.7 22 5.7 10. The materials provided were helpful 179 150 38.8 34 8.8 24 6.2 11. The information was clear and understandable 202 52.2 127 32.8 26 6.7 32 8.3 Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 51 C Adaptability 12. Making use of well-designed (existing) resources 152 39.3 145 37.5 61 15.8 29 7.5 13. Building in additional practice 162 41.9 139 39.5 58 15.0 28 7.2 14 Reframing questions to provide greater scaffolding 173 44.7 145 37.5 44 11.4 25 6.5 15 Plan to connect new content with students' existing knowledge 188 48.6 131 33.9 37 9.6 31 8.0 16. See opportunity where others see failure 163 42.1 121 31.3 72 18.6 31 8.0 17. Quickly and easily adjust their teaching methods to meet the needs of students 199 54.4 119 30.7 40 10.3 29 7.5 18. Able to motivate others despite setbacks 192 49.6 124 32.0 40 10.3 31 8.0 D Inclusivity 19 Create a safe learning environment 229 59.2 121 31.3 22 5.7 15 3.9 20 Diversify learning materials 152 39.3 153 39.5 62 16.0 20 5.2 21. Taking students’ needs into account 157 40.6 131 33.9 54 14.0 45 11.6 22. Develop a rapport with each other 149 38.5 153 39.5 55 14.2 30 7.8 23 Offer an open and welcoming environment 176 45.5 128 33.1 56 14.5 27 7.0 25 Actively work to combat biases 160 41.3 143 37.0 59 15.2 25 6.5 E Compassion 26 Greet students by name 196 50.6 121 31.3 41 10.6 29 7.5 27 Ask about students' work 161 41.6 133 34.4 52 13.4 41 10.6 28 Create a safe and supportive environment 196 50.6 128 33.1 38 9.8 25 6.5 29 Say encouraging words 188 48.6 108 27.9 48 124 43 11.1 30 Show care about what is happening in students’ lives in and out of the classroom 195 50.4 110 28.4 50 12.9 32 8.3 31 Forgiveness for mistakes 151 39.0 136 35.1 57 14.7 43 11.1 32 Awareness of students’ feelings 137 35.4 149 38.5 62 16.0 39 10.1 Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 52 33 Respectful behaviour toward the teachers, peers, and the classroom 192 49.6 121 31.3 50 12.9 24 6.2 Table 4.2 shows that students generally support teachers' ability to convey ideas and information orally, with 54.3% of them expressing positive opinions. Teachers receive praise for their ability to organize teaching resources, regularly check student work, speak professionally, listen emphatically, provide accurate explanations, identify students' thinking and learning levels, incorporate additional practice, reframe questions, plan new content, recognize opportunities where others perceive failure, and adapt teaching methods to meet students' needs. Students also appreciate teachers' ability to create a safe learning environment, with 31.3% rating them as good, 5.7% as moderate, and 3.9% as poor. They also appreciate teachers' ability to diversify learning materials, take students' needs into account, develop rapport with each other, and offer an open and welcoming environment. Teachers also focus on boosting and maintaining student motivation, actively working to combat biases, greeting students by name, asking about students' interests, creating a safe and supportive environment, saying encouraging words, showing care about students' lives in and out of the classroom, forgiveness for mistakes, awareness of students' feelings, and respecting their behaviour towards teachers, peers, and the classroom. In terms of teaching resources, 55.3% of students rated them as excellent, with 30.2% rating them as good, 10.9% as moderate, and 3.6% as poor. Students praise teachers for their professional speaking, empathic listening, accurate explanations and answers, ability to identify students' strengths and weaknesses, provision of helpful materials, and use of well-designed resources. Furthermore, students appreciate teachers' ability to quickly and easily adjust their teaching methods to meet their needs, with 49.6% stating they can motivate others despite setbacks. Overall, students generally support teachers' ability to create a supportive and engaging learning environment, fostering a positive learning environment for all students. For a better picture of the pattern of the teacher's pedagogical skills, a graphical presentation is provided in Figure 1. Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 53 Figure 1: Pattern of the teacher's pedagogical skills It could be concluded from Figure 1 that the data processing teachers in the school sampled are compassionate and motivational to the students with regards to 23.80% and 21.06% responses received from the students concerning their teacher pedagogical skills. Research Question #2: What is the composite contribution of a teacher’s pedagogical skills and a student’s readiness to achievement in data processing? Table 4.5: Summary of Regression Analysis of Composite Contribution of Teacher Pedagogical Skills and Student’s Readiness on Achievement in Data Processing Model Summary R = 0.14 R Square = 0.19 Adjusted R Square = 0.01 Std Error of the Estimate = 18.91 ANOVA Sum of Squares Df Mean Square F P-Value 2658.18 2 1329.09 3.72 0 .03* 18.96 15.21 20.97 21.06 23.80 0.00 5.00 10.00 15.00 20.00 25.00 Communication Evaluation Adaptability Inclusivity Compasson Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 54 Regression Residual 137291.33 384 357.53 Total 130049.51 386 *Significant at p< 0.05, NS= Not Significant, p > 0.05 Table 4.5 shows that the co-efficient of regression R= .14 which is the combined relationship and adjusted R2 = 0.19 indicating a positive contribution of 1.9% on the variance to contributing to achievement in the data processing. In addition, the results show the contributions of teachers’ pedagogical skills and students' readiness having significant contributions (F (2,386) = 3.72, p= 0.03) to achievement in data processing. This implies that both the teacher’s pedagogical skills and the student’s readiness contribute to the student’s achievement in data processing when combined. Research Question #3: What is the relative contribution of teachers’ pedagogical skills and student readiness to achievement in data processing? Table 4.6 Relative Contribution of Teachers’ Pedagogical Skills and Student Readiness to Achievement in Data Processing *Significant at p< 0.05, NS= Not Significant, p > 0.05 Unstd Model Coefficients Std Coefficients Std Error Beta t P- value Tolerance VIF B (Constant) 71.84 8.50 8.44 0.00 Pedagogical Skills 0.13 0.10 -.07 -1.26 0.21 0.96 1.04 Students Readiness 0.14 0.07 -.11 -2.14 0.03* 0.95 1.04 Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 55 Table 4.5 shows that there is no significant relative contribution of teacher pedagogical skills (β = -.07; p= 0.21) while there is a significant contribution of student readiness (β= -.11; p= 0.03) to achievement in the data processing. This implies that only student readiness has a relative contribution to achievement in data processing. In addition, the independent variables do not have any multicollinearity as the tolerance valves are not less than 0.1 and the variance inflation factor valves are not greater than 10. This indicates that teacher pedagogical skills and student readiness are not correlated but only make a significant relative contribution to data processing. Discussion The findings from the data analysis showed that the five components of the teacher's pedagogical skills investigated in the study contributed considerably to the students' achievement in data processing. Poonsook (2013) stated that student prosperity relies on the measure of discovering what happens in the classrooms. From the graphical representation of the pattern of the teacher's pedagogical skills, it was observed that compassion-based skills made the highest contribution to the students’ achievement in data processing. This is in line with what Chuleepon (2011) disclosed that for students to perform well in any examination, one of the requirements is that their educators must know them and have significant information about their physical, scholarly and mental preparation. Based on the result, it implies that the compassion-based teacher pedagogical skill observed in this study shows a great extent of positive impact on students’ data processing achievement. This also supports the findings of Omoniyi and Quadri (2003) that most secondary school teachers lack the necessary ICT proficiency. The findings of research question #2 showed that the independent variables in the study contributed 1.9% to the variance of contributing to the achievement of students in data processing. That implies that a combination of teachers’ pedagogical skills and students’ readiness are predictors of students’ achievement in data processing. Research question #3 revealed that both teachers’ pedagogical skills and students’ readiness impact student achievement in data processing. The results showed that student readiness contributed significantly, but the second predictor-teacher pedagogical skill, did not contribute significantly to the model. Therefore, student readiness is a more potent predictor of a student’s achievement in data processing than a teacher’s pedagogical skill. This finding opposes prior research suggesting that teachers' pedagogical abilities largely influence students' performance in Babatunde Kasim Oladele, Modinat Adetutu Laide-Raji AJOTE Vol.14 No.1 (2025),43-61 56 data processing. These findings emphasised the importance of students’ readiness to achieve in data processing. The study of König and Kramer (2016) found that classroom management expertise can be empirically separated from general pedagogical knowledge, although the two constructs are positively intercorrelated. Research consistently highlights the significant impact of teachers' pedagogical skills on student achievement. The Technological Pedagogical Content Knowledge (TPACK) framework, developed by Mishra and Koehler (2006), emphasizes the importance of integrating technology, pedagogy, and content knowledge for effective teaching. Doukakis et al. (2021) in their study assessing in-service computer science teachers revealed that, while content and technological knowledge were rated highly, there was less confidence in pedagogical content knowledge. This indicates a need for balanced development across all TPACK domains. Roddun (2010) and Naugue (2011) have found evidence suggesting that the level of competence in the professional development of ICT teachers is insufficient. This calls for urgent attention to the pedagogical skills of teachers who teach data processing. Conclusion and Recommendations From the findings of the study, it was observed that there are positive relationships among teachers’ pedagogical skills, student readiness, and achievement in data processing. Therefore, when teachers gear up efforts in using appropriate pedagogical skills and students see themselves as available to learn, or when students are ready to learn, it will improve students' achievement as additional knowledge will be acquired in the process. Moreover, since the finding of the study reveals that there was a significant relationship between pedagogical skills and student achievement, the government should employ more teachers who have the required skills to teach data processing as one of the entrepreneurship subjects, students should develop positive attitude and readiness towards learning and teachers should collaborate with their colleagues who have better skills in the subject areas to discharge duties correctly and appropriately. Limitations and Suggestions for Further Studies The study has limitations, including gender imbalance, age distribution bias, and sample size. The higher proportion of female respondents (59% compared to 41%), which may limit the generalizability of the results to mixed-gender populations, may not fully capture older students' perspectives, readiness, and achievements. The results may not reflect broader trends in other Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria AJOTE Vol.14 No.1 (2025), 43-61 57 schools or regions if conducted within a single school or limited geographical area. Other factors, such as socioeconomic background, learning environment, parental support, or prior academic performance, could significantly influence readiness and achievement. Self-reported data may also be a risk of response bias. Suggestions for future studies include expanding the sample size, achieving a more balanced gender representation, broadening the age range, incorporating additional variables, conducting longitudinal studies, using objective measures, exploring gender differences, and analyzing intervention effectiveness. These measures will help to ensure that the findings are equally applicable to both male and female students and provide insights into how these factors evolve as students’ progress through their education. References Adeyemi, B. A. (2020). Teachers’ Effectiveness and Students’ Academic Achievement in Senior Secondary School Civic, Osun State, Nigeria. 7(2), 99–103. https://doi.org/10.20448/JOURNAL.500.2020.72.99.103 Akinbode O. E., Aderanti R. & Ayodele, K. O. (2023). Principals’ administrative skills and teachers’ productivity in public senior secondary schools, Alimosho Local Government, Lagos State, Nigeria. 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