“I am a cultural teaching method - I was Successful in the ICT Class in the Global South”

Abstract

The Culturo-Techno-Contextual Approach (CTCA) is a teaching method based on culture, technology, and context to ease difficulties in students’ understanding of concepts. Python Programming as a concept in computer studies is difficult for students to understand at the secondary school level. This study investigates the efficacy of the CTCA in understanding Python Programming in the Nigerian computer science education curriculum. This study adopts a quantitative approach. Analysis of covariance procedure is applied to the data with pretest scores inserted as the Covariate. The results show that the experimental group significantly outperformed the control group. Thus, our findings reveal a statistically significant difference in academic achievement in Python Programming of students taught using CTCA and those taught using the lecture method, regardless of gender. The novelty of this study is hinged on the testing of a cultural teaching method in easing the difficulties relative to the study of Python Programming. This study, therefore, provides empirical evidence for the adoption of the CTCA in computer education.

Keywords:

• Python Programming
• Culturo- Techno-Contextual Approach
• computer science

1. Introduction

Many efforts of curricula design have concentrated on expanding participation in K-12 CS education by introducing innovative approaches, but few have focused on addressing longstanding equity issues through their choices of culturally relevant materials and activities (Kafai et al., 2019). Sociocultural influences, such as family practices and access to quality K-12 education, also contribute to developing a technology identity (Goode, 2010). It follows that culture and society influence educational outcomes, especially in computer science education (Goode, 2010; Kafai et al., 2019).

Using computers effectively has become an essential part of everyone’s education (Goode, 2010). Skills such as bookkeeping, clerical and administrative work, stocktaking and so forth now constitute a set of computerised practices that form the core Information Technology (IT) skills package: spreadsheets, word processors and databases (Reffell & Whitworth, 2012). While Reffell and Whitworth (2012) underscores the importance of computer education and the usage of computers, the successful teaching and learning of computer science that can harness these gains are largely hinged on good teaching methods adopted for teaching the course/programme to enhance student’s understanding. Similarly, Fields et al. (2018) observe that teaching methods are critical in training that enhances the effective use of technology, but not without cultural influences. As a result, researchers have recently recommended the Culturo-Techno-Conceptual Approach (CTCA) propounded by Okebukola (2020) for teaching.

The CTCA is a teaching method based on culture, technology, and the context or the environment in which teaching and learning occur (Okebukola, 2020). It is anchored on Kwame Nkrumah’s ethnophilosophy for culture, Martin Heidegger’s techno-philosophy for technology, and Michael Williams’ contextualism for the contextual element. In support of the CTCA, Awaah (2020a) argues that a new Afrocentric teaching model that emphasises the use of digital technology in methodology and delivery, as well as the relevance of partnerships in meeting the continent’s higher education demands, requires an effective teaching and learning paradigm such as CTCA, especially during the COVID-19 era. Awaah (2020b) refers to the technology component of the CTCA as hinged on the role of technology as a tool that enhances teaching and learning.

This study, therefore, focuses on the perception that Python Programming is difficult to understand (Canning et al., 2018; Hoeg & Bencze, 2017). Various researchers have argued that the difficulties relative to python programming include inadequate teaching methodologies (Mészárosová, 2015). Without testing indigenous teaching methods in breaking difficulties in the study of computer science education, educational managers and teachers in Nigerian senior secondary schools are unable to establish whether the lecture method or the indigenous method holds the key to breaking difficulties in the study of python programming within the Nigerian secondary school system. These compelling deficits in the Python Programming literature necessitate this study to fill the existing gap.

Thus, the study seeks to determine whether (a) CTCA can improve students’ understanding of python programming; and (b) CTCA can improve the difference between male and female students’ understanding of python programming.

In line with the objectives, the researchers formed two hypotheses. (i) there is no statistically significant difference in the achievement in Python Programming of the students taught using CTCA and lecture method (ii) there will be no statistically significant difference between the academic achievement of male and female students taught Python Programming using the CTCA. Both hypotheses were tested at a 0.05 confidence level.

2. Literature review

2.1. Culturo-techno-contextual approach

Okebukola (2020) defines the CTCA as a teaching method based on culture, technology, and the context or the environment in which teaching and learning occur. The CTCA is built on the ethnophilosophy of Kwame Nkrumah for culture, Martin Heidegger’s techno-philosophy for technology, and the contextualism of Michael Williams for the contextual element. These philosophies constitute the pillars of CTCA.

Ethno-philosophy is rooted in the idea of the uniqueness and specific culture of the African people as pioneered by Kwame Nkrumah, who opined that African culture is unique from European ways of life but in no sense inferior to it (Hountondji, 1996). The techno-philosophy philosophy is deeply rooted in the “Heideggerian” definition of technology as “a technique of disclosing the universe, a revelation in which people seize authority over reality” (Okebukola, 2020, p. 92). Contextualism claims that our acts, utterances, expressions, and learning can only be understood in the context in which they occur (Okebukola, 2020). Thus, the elements of the CTCA (culture, technology and context) respectively reflect the concepts of ethnophilosophy, techno-philosophy and contextualism. Okebukola (2020) concludes that when using CTCA to teach pupils, the material should be relevant to their immediate environment to absorb the explanation quickly.

The CTCA has witnessed some studies to test its efficacy in many subject areas. For instance, Awaah (2021) tested the potency of the CTCA in enhancing performance in difficult concepts in the Ghanaian undergraduate public administration curriculum and found that the CTCA is a better teaching method than the lecture method in studying politics and bureaucracy in the Ghanaian undergraduate public administration curriculum (Awaah, 2021).

Adeola (2020) also explored the efficacy of the CTCA in improving the achievement of secondary school students in Adaptation. He used CTCA for the experimental group and the lecture method for the control group. The sample was of mixed ability and mixed-sex groups. The ANCOVA result of the researcher [F (1, 46) = 21.844; p = .000] shows that there is a statistically significant difference in the achievement of CTCA and control groups in Adaptation. Therefore, the null hypothesis of the study that there will be no statistical difference between CTCA and the control group was rejected.

Further, Adam (2019) reports that the CTCA enhances achievement, as the experimental group students outperformed their control group mates on the achievement measure. However, Egerue (2019) cautions that students should not permit cultural and religious views to obstruct scientific explanations of fundamental concepts.

2.2. Difficulties in learning programming

Different studies have catalogued challenges relative to the study of computer science and Python Programming in particular. For instance, Mészárosová (2015) posits that the problem with the Python Programming language is mainly the lack of methodologies and textbooks for secondary schools in the Slovak language. Mészárosová’s (2015) observation is not too different from the African case. Python Programming is taught in English in African schools, and the teaching methodologies are usually not Afrocentric. This poses challenges to students’ understanding of the concept. To overcome the language challenge identified by Mészárosová (2015) in the Slovak environment, there is a need to test the CTCA as a teaching tool and methodology in an African setting to establish whether it will enhance students’ understanding of Python Programming.

Hosseini et al. (2020) also argue that, although examples have been consistently proven to be valuable for students’ learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage students. This makes the study of computer science and Python Programming especially challenging for students to comprehend. The CTCA proposes that teachers should teach using culturally relevant examples relative to the student’s environment for students to understand scientific concepts. In recognition of this proposal, the CTCA is being tested in this study to unveil its efficacy or otherwise in enhancing students’ understanding of Python Programming.

Kpaji and Ibrahim (2015) accentuate that many untrained teachers teach science in abstraction, making science lectures uninteresting and increasing students’ difficulties learning scientific concepts, abilities, and principles. This barrier will be overcome when Python Programming teachers use a cultural approach to teaching concepts. This seems to find a solution in the contextual component of the CTCA, which proposes that teachers should teach science, bearing in mind the context (environment) within which the concepts are taught by drawing from indigenous examples relative to those environs.

Last but not least, Okebukola et al. (2016) also submit that pre-service and in-service science teacher preparation should focus more on providing teachers with some CTCA experience in searching for culturally and contextually relevant science education methods. Okebukola et al. (2016) believe that learning python programming in the computer science curriculum may be much easier when students’ cultural backgrounds are factored in the teaching process.

2.3. Theoretical antecedence of the CTCA

The claims of the CTCA are not isolated in theories on teaching and learning. Several theorists (Ausubel, 1960; Piaget, 1976; Vygotsky, 1997) have made similar claims that have been proven efficient in education studies. The propositions of these theorists underpinned the CTCA. Illustratively, Piaget (1976) propounded cognitive constructivism theory. This theory deals with the nature of knowledge itself and how humans gradually come to acquire, construct and use it. In his view, cognitive development is a pragmatic reorganisation of mental processes resulting from biological maturation and environmental experience (Piaget, 1976). This assertion which influences learning, relates to the contextualism of the CTCA. Contextualism suggests that when pupils learn within their environs, they are likely to better understand concepts than learning relative to a foreign environment (Okebukola, 2020).

Vygotsky (1997) also propounded the cultural-historical theory, which observed the Marxist notion of tool invention’s impact on human mental life and the anthropological perspective of culture’s function in human evolution via dialectical synthesis. He aimed to classify cultural signals and symbols as psychological tools, which he characterised as cognitive growth instruments (Gredler, 2014). The aim of the person in society is to adapt one’s culture’s symbol systems to create similar kinds of thinking (ontogeny). This orientation by Vygotsky, as reflected in Gredler (2014), finds linkage in the cultural component of the CTCA as espoused by Okebukola (2020). This implies that signs and symbols such as human speech, written language, and algebraic and mathematical symbols used in computer science education have culturally served as transmitters of both meaning and social cohesion in human lives.

Vygotsky (1997) highlighted a second critical role: helping people in mastering complicated cognitive skills that are not completely formed until puberty (Gredler, 2014). According to Gredler (2014), these skills are voluntary (self-regulated) attention, categorical perception, conceptual reasoning, and logical memory, which Vygotsky refers to as complex or higher cognitive processes. This component of Vygotsky’s theory relates to the first leg of Okebukolas’ CTCA, where cultural knowledge is expected to be harnessed from the elderly, self, relatives, friends and the immediate environment. The conceptual reasoning aspect of Vygotsky also finds congruence with the contextual component of CTCA.

The final theory underpinning the CTCA is Ausubel’s (1960) theory of advance organisers. Ausubel (1960) promotes advanced organisers to connect new learning material with existing notions. Advanced organisers are brief introductions to a topic that provides the structure for the student to link the new material provided with his prior knowledge. This is related to the teaching process of CTCA, where students are expected to gain prior knowledge of the topic to be taught through friends, relatives, parents, internet sources and the environment.

These theories and the philosophies reviewed earlier have informed the conceptual framework of the CTCA (Figure 1).

Figure 1. The CTCA Framework

3. Methodology

3.1. Research design

The study adopts a quantitative approach. The quantitative approach allowed the researchers to carry out a quasi-experimental study. This approach also helps to discover the link between the variables and produce statistical findings to aid generalisations (Creswell, 2014; Tetteh et al., 2022).

The researchers used a pretest and posttest design with a quasi-experimental-control group. Before the treatment, both groups were given a pretest to evaluate the students’ baseline abilities. The Culturo-Techno-Contextual Approach was used to teach Python Programming to the experimental group. The control group received identical information via lecture. After the treatment, both groups were given a posttest (see Figure 2)

Figure 2. Representations of methods of experimental and control groups

A quasi-experimental approach was used because the researcher could not assign individuals to groups at random. In a quasi-experiment, people are divided into groups based on non-random factors rather than random assignment. Existing schools and classes were used in our study, with no changes to the number of students in the classrooms. This necessitated the use of a quasi-experimental design. As the name implies, “quasi-experiments” aim to approximate “experimental methods” in situations where “full experimental control” is not possible, such as when researchers are attempting to identify the consequences of social change in naturalistic settings (Awaah et al., 2021; Yi & Chan, 2013).

3.2. Population and sampling

The study population consists of senior secondary (SS) students in the Lagos State of Nigeria. The target population comprises private secondary schools in Lagos State with two private schools grouped into A and B. This was based on two considerations. Private schools in Lagos state in Nigeria have more well-equipped computer laboratories than public schools. Most students in private secondary schools in Lagos state are exposed to cellphones and the internet, which was needed for the CTCA process.

The participants include forty-one (41) students in the SS2 class of school A (experimental group) and fifty-three (53) students in the SS2 class of school B. Thus, the total number of participants for this study is ninety-four (94).

The quasi-experimental-control group study methodology entails selecting groups on whom the variable is tested without any random pre-selection process. The sample was made up of people of mixed ages, abilities, and genders (Awaah, 2021).

3.3. Research instruments

A Python Programming achievement test was used to collect this study’s data. The researchers designed the instrument, which consisted of forty (40) multiple-choice items. The questions were developed from the lesson notes prepared by the researchers for teaching the students using the CTCA. In contrast, some questions were extracted from past Senior Secondary Certificate Examination (SSCE), and some questions were retrieved online by searching for multiple-choice questions on Python Programming.

It was subjected to test-retest reliability testing to ensure that the Python Programming achievement test was consistent and accurate. In doing this, the instrument was first administered to 50 students from school B. Two weeks later, the instrument was re-administered to the same students. To avoid a mismatch in the first and second administration, the questionnaire was numbered against each participant’s identity. The first and second responses were then collated and subjected to stability testing, and the reliability coefficient of r = .71 was derived. This value above the acceptable level of r ≥ 0.7 indicates the instrument is reliable and will, under similar conditions, continue to measure what it is designed to. The reliability was tested using a Split Half reliability check.

The Python Programming achievement test was validated by a team of 9 experts in computer science education to ensure that the instrument measures what it intends to measure. On the advice of the experts, the exercise required that some initial questions be removed based on content validity.

3.4. CTCA and Python Programming perspectives

Python Programming is a topic that has been perceived to be difficult in secondary schools. The under-listed headings were treated in the lesson.

• Definition of Python Programming.

• Python Basic Syntax

• Practical examples of Python Programming

• Use of Python Programming as a mathematical tool

3.5. Procedure for data collection

After seeking permission from school authorities to conduct the survey (principal and vice principal), the researchers ensured a friendly atmosphere wherein the respondents felt relaxed and ready to participate (this was achieved with the help of the subject teachers).

The Python Programming Achievement Test was administered to both classes (experimental and control) classes to help set a baseline before the experiment was conducted. Afterwards, the various teaching methods associated with each class were used to teach the topic “Python Programming”.

At the experiment phase in school A, the following procedure was adopted for the treatment following the CTCA for SS 2 students.

Step 1: The teacher gives a pre-lesson assignment to the students to seek information from their family and friends on indigenous knowledge and cultural practices on Python Programming and use their mobile phones or internet-enabled devices to search the web for resources and watch YouTube videos on the topic “Python Programming”.

Step 2: The teacher welcomes the students to the class and divides the students into a group of 10 males and females with mixed academic intelligence.

Step 3: The teacher tells each group to select a leader to give a detailed summary of their discussion on the topic.

Step 4: Each group is given 8 minutes to discuss and share their various opinions and provide insights on the allotted topic.

Step 5: The teacher proceeds with the topic “Python Programming” by relating the topic to serve cultural attributes (Cultural Approach), pointing out several examples and instances Python Programming can be related to incantations used by herbalists to consult the oracle.

Step 6: The teacher advances the instructional process by applying a contextual approach while teaching the topic to the students to help them familiarise Python Programming with everyday life.

Step 7: After the class, the teacher sent what was learned (content) to the students through WhatsApp or SMS.

The following procedure was adopted to use the lecture method for SS2 students of the Control group.

Step 1: The teacher introduced Python Programming and its various definitions to the students.

Step 2: The teacher defined Python programming to students.

Step 3: The teacher guides the students in understanding Python Programming syntax and its use.

Step 4: The teacher gives practical examples of Python Programming code.

Step 5: The teacher guides do independent Python Programming exercises.

Step 6: The teacher summarised the lesson by going over the salient points.

The teacher then administered the Python Programming Achievement Test after the lessons. This data (posttest) and the pretest data were used in the ANCOVA analysis.

3.6. Practicum of the CTCA in teaching Python Programming in school A

After establishing all the protocols with the school, the teacher was scheduled for two lessons in a week on the timetable. The first meeting with the students was on Tuesday 11^th of May 2021. The teacher introduced himself and asked the students to do the same. The teacher went on to teach the topic of Python Programming and informed students to (a) read about it whiles at home, (b) find out from their friends, parents and their immediate surroundings about indigenous knowledge systems relative to Python Programming, (c) use intent sources to find out indigenous knowledge systems related to Python Programming. The students had the task of doing all of these and reporting the knowledge found in the next lesson.

The teacher grouped the student into ten individuals with mixed abilities and sexes in the next lesson. Each group had the responsibility of choosing a leader who would present the outcomes of their discussion to the entire class. The students discussed the findings of their indigenous knowledge relative to Python Programming about their parents, relatives, environment, and internet sources. After 8 minutes, the teacher instructed all the leaders of the various groups to report their findings from their group’s perspective. Summarised accounts of the groups’ presentations are in the ensuing;

Oladejo (pseudo name) reported that python programming languages are like gods used in Igbo land, popularly known as amadioha. The gods listen to people’s requests and only respond to them, just like python programming, which only solves the problem it is designed to solve.

Gbeleyi (pseudo name) Also reported that python programming could be related to a baby’s language as babies cannot speak but communicate to their parents through cries and laughter.

Agbanimu (pseudo name) further reported that python programming could be related to the language used by masquerades to communicate with each other, which normal humans can hardly interpret. Python programming transmits to the computer to perform specific tasks only the two devices understand.

Tokunbo (pseudo name) Reported that Python Programming works like signs used to communicate to the deaf, the only language they can understand, just like the computer understands python programming.

After these narrations by the group leaders, the teacher continued to teach Python Programming drawing from his indigenous examples.

• Python Programming can be described as the language understood by a popular god in the Yoruba land called “IFA”. The herbalists (native doctors) use incantations (special language) to communicate on people’s behalf to the gods.

• Python Programming can be related to the language magicians use to enchant, trick, and perform illusions that seem impossible or supernatural to the being in Yoruba and Igbo cultures.

The teacher corrected some misconceptions relative to some examples of group leaders in their presentations. For instance, he fixed Oladejo (pseudo name), who explained that Python Programming could be related to the languages used to communicate to gods, not the gods themselves.

The teacher introduced humour by telling the ensuing story to keep students calm and focused.

A man is seated in darkness and said he had lost the phone and went ahead to use his phone’s light to look for his phone. He got a phone call and responded, “I can’t find my phone,” and subsequently called the police with the same phone to inform them that his phone was lost. The whole class burst into laughter, after which the lesson continued with the teacher further drawing examples from the schools’ environment to enhance understanding of python programming. The lesson ended with the teacher sending the ensuing summary to all students via WhatsApp.

A computer language, also known as a programming language, is a special language understood by a computer. It consists of various commands given to the computer to carry out tasks. The computer may find it difficult to understand native languages like Igbo, Yoruba, and Hausa because they are quite foreign and strange, so it uses its language for communication. A computer language is a set of words, symbols, and codes used to write a computer program. Programming languages can be seen as incantations used by the herbalists in the various tribe to consult the gods (oracle) to solve a particular problem. Python was invented by Guido van Rossum in 1991 at CWI in Netherland. The idea of Python programming language was taken from the ABC programming language. The print () function displays the given object to the standard output device (screen) or the text stream file. Unlike the other programming languages, the Python print () function is the most unique and versatile function

3.7. Data analysis technique

The experimental phase entailed data (Quantitative) generated from the Python programming achievement test, which was analysed using IBM—SPSS 20, and Analysis of Covariance (ANCOVA) was used to test for statistical difference between the CTCA and lecture method in learning Python programing at alpha level p < 0.05. Qualitative data from students were gathered to establish why teaching Python programing with CTCA makes the student understand Python programming better.

Analysis of covariance drags everyone back onto the baseline irrespective of the initial entry-level of the groups being used for the study. Some assumptions were met, such as the normality of the population, homogeneity of variance, random assignment, and homoscedasticity of data (Korede, 2020). The initial differences of the learners were taken into consideration which led to giving out a pretest to both experimental and control groups before the treatment, and the achievement pretest is known as Covariate (Olelewe & Agomuo, 2016)

4. Results

Table 1 shows the populations of students and thier genders in both the CTCA and Lecture method classrooms. Several basic assumptions such as population normality, random assignment, and variance homogeneity were met before the analysis of covariance was done. From Table 2, the significance value of Levene’s test of equality of error variances is 0.353, which signifies that it is not significant (it is not homogeneous) since the value is greater than 0.05, which means that variance does not differ significantly from each other.

Table 1. Breakdown of class, gender and teaching approaches for multiple-choice items for control and experimental groups

Gender	CTCA		Lecture		Full Sample
	n	%	n	%	n	%
Male	23	56.10	34	64.15	57	60.64
Female	18	43.90	19	35.85	37	39.36
Total	41	100	53	100	94	100

Table 2. Levene’s test of equality of error variances

F	df1	df2	Significant value
1.100	3	90	0.353

From Table 3, the total mean of the CTCA method is 23.09 with a standard deviation of 3.89, and the lecture method has a mean of 20.25 with a standard deviation of 4.69.

Table 3. Means of CTCA and lecture method for both genders

Gender	CTCA		Lecture		Full Sample
	M	SD	M	SD	M	SD
Male	22.3478	3.43258	20.6471	5.53163	21.3333	4.83415
Female	24.0556	4.33145	19.5263	2.56836	21.7297	4.17432
Total	23.0976	3.89747	20.2453	4.69003	21.4894	4.56670

From Table 4, the achievement pretest p-value is 0.000, which shows that students from the two groups (CTCA and Lecture method) have different initial entry levels, and that is what the Pretest is set to achieve. Still, the analysis of covariance drags everyone to the baseline base.

Table 4. Summary table of ANCOVA dependent variable: achievement post-test

Source	Type III sum of squares	Df	Mean square	F	Sig.	Partial Eta Squared
Corrected model	829.63^a	4	207.41	16.63	0.00	0.43
Intercept	548.15	1	548.15	43.96	0.00	0.33
Achievement Pretest	596.80	1	596.80	47.86	0.00	0.35
Method	210.74	1	210.74	16.89	0.00	0.16
Gender	19.32	1	19.32	1.55	0.22	0.02
Method*Gender	9.93	1	0.82	1.15	0.29	0.02
Error	1109.86	89	12.47
Total	45,348.00	94
Corrected Total	1939.49	93

Note: A RSquared = 0.428 (Adjusted RSquared = 0.402)

Research hypothesis one: there is no statistically significant difference in the achievement in Python Programming of the students taught using CTCA and lecture method

The ANCOVA result shows a statistically significant difference in python programming achievement of students taught using the CTCA and the lecture method [F (1.89) = 16.89; p < 0.05]. Thus the null hypothesis is rejected.

Research hypothesis two: there will be no statistically significant difference between the academic achievement of male and female students taught Python Programming using the CTCA

The ANCOVA result showed no statistically significant difference between the academic achievement of male and female students taught Python programming using the CTCA. [F (1.89) = 1.55; p > 0.05]. Thus the null hypothesis is accepted.

5. Discussions

5.1. Research hypothesis one

The first research hypothesis sought to test whether “there is no statistically significant difference in the achievement in Python Programming of the students taught using CTCA and lecture method”. The result indicated a statistically significant difference in the achievement in the Python Programming of the students taught using CTCA and lecture method, thereby rejecting the null hypothesis. This proves that the CTCA is a better method of teaching Python Programming than the lecture method.

This finding agrees with the study of Awaah (2021), which experimented with the potency of the CTCA in enhancing performance in difficult concepts in the Ghanaian undergraduate public administration curriculum. Their study found that the CTCA is a better teaching method than the lecture method in studying politics and bureaucracy in the Ghanaian university public administration curriculum (Awaah et al., 2021).

Our result is also consistent with Adeola’s (2020) finding on the efficacy of the CTCA in improving the achievement of secondary school students in Adaptation, where the researcher used CTCA for the experimental group and the traditional method to teaching the control group and obtained statistical difference between CTCA and the control group.

Furthermore, the result of this study supports the finding of Adam (2019) that the CTCA has a significant impact on achievement, as the experimental group students outperformed their control group mates on the achievement measure. Our qualitative result further confirms Adam’s (2019) finding as it highlighted clearly that the adoption of the CTCA in the teaching of Python Programming had improved the understanding and performance of the students in the achievement test.

Many untrained teachers teach science in abstraction, making science lectures uninteresting and increasing students’ difficulties in learning scientific concepts and principles (Kpaji & Ibrahim, 2015). Overcoming this barrier, this study provides empirical evidence to adopt the CTCA in the teaching of the Python Programming, a deduction that is consistent with Okebukola et al. (2016) work, which suggests that pre-service and in-service science teacher preparation should begin to focus more on providing teachers with some CTCA experience in the search for culturally and contextually relevant methods of education.

Theoretically, our finding supports the theories that underpin the CTCA: cognitive constructivism theory (Piaget, 1976), cultural-historical theory (Vygotsky, 1997), and theory of advance organisers (Ausubel, 1960). For instance, the cognitive constructivism theory in education recognises students’ understanding and knowledge based on their experiences before entering school. This is reflective in the performance of the CTCA group on the lecture method since the CTCA group had prior knowledge as a prerequisite for its study. This further shows the efficiency of using CTCA in education when adopted in various disciplines and contexts.

5.2. Research hypothesis two

The second hypothesis set out to test whether “there will be no statistically significant difference between the academic achievement of male and female students taught Python Programming using the CTCA”. The result showed no statistically significant difference between the academic achievements of males and females; thus, the null hypothesis was supported.

Our finding is consistent with the work of Piraksa et al. (2014), who implemented the LCTSR to assess students’ scientific reasoning abilities in six constructs: I Conservation of Mass and Volume (CMV), (ii) Proportional Thinking (PPT), (iii) Control of Variables (CV), (iv) Probabilistic Thinking (PBT), (v) Correlational Thinking (CT), and (vi) Hypothetical-deductive Thinking (HT) (HDR). Their findings reveal that gender had no bearing on students’ scientific reasoning abilities for any construct. Furthermore, the lowest mean score for the students’ scientific reasoning abilities was HDR, CV, and PPT for both genders. Our findings and supporting literature justify the usefulness of the CTCA to encourage students to complete pre-assignments about cultural practices related to the topic of study, which has an across-the-board impact on students, regardless of gender, because of their experiences are made according to their environment or context.

6. Conclusions

This quasi-experimental study set out to test two hypotheses (i) there is no statistically significant difference in the achievement in Python Programming of the students taught using CTCA and lecture method (ii) there will be no statistically significant difference between the academic achievement of male and female students taught Python Programming using the CTCA.

A comparison between the lecture method and the CTCA using ANCOVA showed significant results [F (1.89) = 16.89; p < 0.05]. This indicates a statistically significant difference in the achievement of the experimental and control groups. The significance favours the experimental group, implying the CTCA is a better model than the lecture method in enhancing students’ understanding of python programming in the study of computer science education.

The study further found that there is no statistically significant difference between the academic achievements of male and female students taught Python programming using the CTCA ([F (1.89) = 1.55; p > 0.05]).

These findings demonstrate the efficacy of the CTCA in teaching python programming and in improving the difference between male and female students’ in their understanding of python programming.

7. Practical implications

The findings of the study suggest the following practical implications. First, as an emerging cultural oriented teaching method, the CTCA has proven effective in teaching python programming. With already known deficits in laboratories, equipment and other relevant tools for the learning of computer science, the implication of this study is tied to African schools, moving from the lecture method to one that guarantees the success of learning based on the cultural values of the students, the teachers, and the teaching environment. Again, the findings of this study are pointers to the ministry of education to formalise the teaching and learning of computer science education in line with the traditions and culture of the people of Nigeria.

Further, CTCA should be adopted in Nigerian schools to teach python programming. Again, lecturers must encourage students to use mobile phones to their learning advantage. Additionally, the Ministry of Education and professional organisations should organise workshops, seminars, and conferences for python programming lecturers to use the CTC Approach. Finally, the computer science curriculum should take a much more explicit account of the cultural context of the society which provides its setting and whose needs it exists to serve.

8. Limitation of the study

Despite the significant contribution of this study to the extant literature, the relatively small sample size (i.e., the use of two schools) limits the generalisation of the findings. Again, the study was conducted in Nigeria; hence countries with different cultural backgrounds may have to apply our findings with caution. Therefore, future studies should investigate the phenomenon by increasing the sample size and perhaps in other jurisdictions to see if the same or similar findings will be made.

Acknowledgements

We acknowledge the contributions of Mr Solomon Yeboah, Ms Dorcas Adomaa Addo, and Ms Emmanuella Sefiamor Heloo to this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors have no funding to report