Abstract

21^st century higher training institutions are known to receive the best brains from secondary schools for preparation for the world of work in all areas of specialization.  Secondary school Agriculture prepares learners for further training in higher learning institutions. Despite being a crucial subject, agriculture has been poorly performed in secondary schools an indication that whatever challenges the learners face are likely to influence their training at the university. The aim of this study was to review recent literature on the student and school capacity factors influencing student performance in Agriculture in secondary schools and possible intervention measures for improved performance. First, the reports from Kenya National Examinations Council were reviewed to understand the trend in secondary school Agriculture performance. In the second stage non-systematic review was done to identify studies on secondary school Agriculture performance. In the third stage, a systematic review was carried out to specifically identify empirical articles targeting secondary school Agriculture performance. Only 33 studies addressed secondary school Agriculture. Student factors influencing agriculture performance include attitude, motivation and background while school capacity factors affecting performance are inadequate physical learning resources like the school farm, workshop and library. Integration of ICT was also in the infancy stage with most schools lacking the necessary digital devices and content. The findings inform the universities of the areas where the trainees joining agricultural courses need better capacity building for them to leave as quality graduates.

Keywords

High school Agriculture, University training, Agricultural courses, Capacity building, Students

Introduction

The teaching of Agriculture subject at the secondary school level in Kenya is expected to equip learners with knowledge, competencies and attitudes appropriate for further training and the world of work (Kyule et al., 2018). A competent agricultural workforce is vital given that Agriculture is the bedrock of Kenya’s economy (Ministry of Agriculture, 2019). Despite the role that agriculture plays in realizing the Sustainable Development Goals (SDGs), Vision 2030 and the country’s big four agenda on food security, agriculture subject in secondary schools which is key in preparing the human resource in the sector has been poorly performed. Student performance has been below average in Agriculture in the KCSE and the lowest compared to other technical subjects from 2016 to 2018 (KNEC, 2019).

Table 8.1 shows the dismal performance of the agriculture subject as posted in the last six years.

Source: Kenya National Examinations Council (2019) Vol 2, p83.

The poor performance in Agriculture subject is an indicator of poorly prepared human resources who may not have the necessary knowledge, skills and competencies to tap the potential in the agriculture sector. Besides, the poor performance also lowers the number of students who qualify to pursue further education in agricultural science-related courses. As a result of low performance in Agriculture in the KCSE in the last three years, some of the universities had to close down agriculture-related programmes for lack of students to take up the courses (Daily nation, 8^th May 2019). Many other agriculture-related courses at the University where professionals in the sector would be trained remain on the verge of closing for low student enrollment.

The poor performance presents a grim future in the preparation and training of agricultural scientists consequently impacting agricultural production activities and hence food security (Daily nation, 8^th May 2019). The lack of adequate agricultural scientists is likely to lead to the use of outdated technology and the inability to mitigate overall food insecurity challenges (Ministry of Agriculture, 2019). The poor performance may also be an indicator of the quality of teaching. This study, therefore, seeks to explore a systematic literature review on the student and school factors influencing performance in agriculture, as well as ICT integration in the teaching and learning of Agriculture and possible interventions. The secondary schools prepare the students to be admitted for higher education training. Hence, the inadequacies in training at secondary school affect the quality of students being absorbed in subsequent training levels.

Research Questions

The study was guided by the following research questions:

1. Which student factors influence student performance in secondary school Agriculture?
2. What is the influence of school factors on student performance in secondary school Agriculture?
3. What is the influence of using digital devices in teaching and learning on student performance in secondary school Agriculture?
4. What is the influence of using digital content in teaching and learning on student performance in secondary school Agriculture?
5. What are the gaps in the teaching and learning of Agriculture influencing student performance in secondary school Agriculture?

Training of Agriculture at Secondary School Level

Theoretical Foundation

The system-wide education change and the Social Ecological Model (SEM) theories guided this study. The system-wide educational change theory articulates that change theory can be instrumental in informing education reforms. However, the expected change can only be realized in the hands of people with deep knowledge of the dynamics of how the change factors operate (Naicker & Mestry, 2016). Thus, for better preparation of a competent human resource in agriculture at the secondary school level, learners need experience in building professional knowledge, skills and competencies through the learning of Agriculture. Learners’ exposure to real and concrete learning experiences through digital technology is necessary when providing a permanent learning foundation that prepares the youth for the Fourth industrial revolution phase.

The Social Ecological Model (SEM) in Figure 8.1 was developed by Helitzer et al., 2000 also guides this study. In this model, they opine that individual behaviour is shaped by the social environment which has five levels of influence. The levels are; individual, interpersonal, community, organizational and public policy. The SEM has helped to understand human behaviour and also to propose interventions to support behaviour change.

Figure 8.1. An Illustration of the Social Ecological Model (Helitzer et al., 2000)

According to Max, Sedivy and Garrido, et al (2015), the five levels in SEM relate to individual characteristics which are likely to influence behaviour. These characteristics include knowledge, attitudes, age, gender, economic status, self-efficacy, values and goals, literacy. In this study, the individual level is represented by student factors that influence students’ performance in secondary school Agriculture.

The interpersonal level includes the formal and informal social networks and social support systems that can influence individual behaviour. These include family for students and the community for the teachers. The community represents relationships among organizations, institutions, and informational networks within defined boundaries. The organizational level of influence on human behaviour comprises the social institutions with rules and regulations for operations that affect how well services are provided to individuals or a group. This organizational level represents the school’s capacity for learning and teaching. The public policy level involves the local, national or global laws and policies that may influence someone to behave in a particular manner. As discussed herein, the policy level will be informed by the secondary school agriculture curriculum implemented by the teachers and the agriculture students’ performance in national examinations at the form four level.

Literature Review

Literature was reviewed as per the study research questions in chapter one.

Student Factors Influencing their Performance in Secondary School Agriculture

Student performance in secondary school Agriculture has been on the decline since 2013 posting a mean average score of 41.7% in the last five years (KNEC, 2019). According to existing literature, poor performance in Agriculture subject has been attributed to several student-related factors including attitude, motivation, home background, absenteeism, school fees, peer pressure, parental influence among others (Otekunrin et al., 2019). According to Otekunrin et al., (2019) attitude is considered a major determinant of a person’s intention to perform a particular behaviour. A study done by (Okiror et al., 2017) found that learners had a negative attitude towards Agriculture subject because both students and parents preferred education aimed at white-collar jobs as opposed to blue-collar jobs.  In addition, the home was found to be one of the agents that creates the first impression which lasts throughout a child’s life and is also seen as a place that shapes the child’s attitude and behaviour towards career development (Uche et al., 2018). Besides home background, the method of teaching used by an Agriculture teacher has also been found to influence learner’s achievement (Owoeye, 2017). Generally, young people in South Africa were found to display a poor attitude toward Agriculture (Yusuf, Popoola, Oluwabunmi, Olutegbe, 2019).

According to the study, students’ attitude was degraded due to teachers’ tendency to punish errant behavior by digging in the school farm. A study that was done in Ibadan, Nigeria on students’ attitudes towards practical agriculture among both boys and girls found out that both genders had a positive perception of practical agriculture. However, boys received greater support from parents to pursue agriculture-related professions compared to girls. According to (Kidane & Worth, 2014) positive attitude and determination on the students’ side could lead to success in the agricultural sector. A positive attitude towards Agriculture is one of the attributes that employers would be interested in as they engage their human resources (Yusuf, et.al., 2019). Thus, such attitude needs to be natured among Agriculture learners who form the future workforce from an early life hence interventions on student attitude towards Agriculture subject cannot be ignored.

Motivation is one of the factors influencing a learner’s academic performance (Nauzeer & Jaunky, 2019) Motivation is an inspiration that initiates, guides, and maintains goal-oriented behaviors. Nauzeer and Jaunky, (2019) identified five constructs of motivation including intrinsic, extrinsic, motivation, self-efficacy and achievement. Self-determination theory on the other hand considers three categories of human motivation including intrinsic, extrinsic and motivation (Ikeoji & Agwubike, 2007). Intrinsic motivation was identified as a strong type of motivation that can lead to multiple positive outcomes since one does something due to internal satisfaction and fulfilment. Past studies have indicated intrinsic motivation leads learners to strongly engage in learning activities and consequently post better performance. Motivation acts as a prerequisite and an essential element for the engagement of students in learning. A study done by (Ward, 2019) found that there was a lack of motivation and engagement in students in a face-to-face only instructional environment, which led to lower student achievement. The study concluded that students who received blended learning had a more flexible learning environment that reinforces student autonomy. Learner independence was attributed to the connection that exists between blended learning, student motivation and academic achievement. In addition use of e-learning significantly enhances learners’ motivation and subsequently improves their performance in Agriculture  (Penggunaan & Kelas, 2019).

Students’ home background is a major factor influencing learning because different students’ background characteristics exert a strong influence on their academic performance. A study done in Nigeria among secondary school agriculture students indicated that home background had a statistically significant impact difference on the students’ academic performance in agriculture. The study recommended the need for homes to provide the necessary environment for learning that would promote their children’s academic performance in agriculture (Uche et al., 2018). Students’ socioeconomic backgrounds are a significant motivator for a child to succeed in school and take up a science-related career (Max et al., 2015; Ward, 2019). Past studies have also indicated a statistically significant effect of a student’s family background on the academic achievement of such students in agricultural sciences (Abdullahi et al., 2015). Some of the students’ home background variables that positively enhance students’ academic achievement are parents’ visits to schools, provision of pocket money, parents’ education level, parents’ occupation, residential type and family nutritional standard.

Parental influence is one of those factors that influence student performance. Parents or guardians who are interested in Agricultural activities are most likely to influence their children positively in the same professional field (Alexandria, 2018). Kapur, (2018), documented parental associated factors that affect students’ academic achievement in Agriculture. These parental associated factors were categorized into positive and negative factors. The positive factors promoting a student’s performance in Agriculture include a pleasant home environment, encouraging attitude of family members, provision of learning resources, education level of the parents, small family size and provision of the needs and requirements of the children.

In Zambia absenteeism has continued to prove to be problematic in most rural schools (Kabanga & Muauzi, 2020). The study found that absenteeism affects the learning processes leading to poor performance, student indiscipline and insufficient comprehension of Agriculture concepts. Student absenteeism leads to a loss of quality learning leading to unlearned academic skills and objectives, and subsequently a decline in student performance. Additionally, absenteeism may result in unlearned subject material because of fewer hours of instruction, and lead to disruption of class instruction for teachers who have to administer remedial lessons for the absent pupil when he returns to school. According to Kidane & Worth, (2014), absenteeism, which could be encouraged by the lack of class registration, has a significantly negative effect on student achievement in Agricultural sciences. While carrying out a study on absenteeism among university students (Khanal, 2019) notes that absenteeism determines the student’s achievement and their potentiality thus leading to an increased poor academic performance which eventually causes students’ to drop out of their study programmes. A study that was done in India where 75.4% of students were found to be absent from school missing 10% of all school days indicated that student absenteeism impacts on their learning outcomes (Ben et al., 2020). In the long term, absenteeism leads to the student’s financial instability, poor health and unemployment.  Some of the causes for absenteeism identified include student sickness, menstruation and family functions (Ben et al., 2020).

A study done in Enugu state in Nigeria found that parents in the rural areas did not have enough money for their children’s school fees as compared to those in the urban setting (Uche et al., 2018). Thus, absenteeism is common in most day secondary schools in rural locales due to the nature of the student’s background. Absence from school leads to loss of learning time and consequently poor performance in most subjects including agriculture. A similar absenteeism challenge was documented in Zambia by (Kabanga & Muauzi, 2020) in most of the rural schools a case that was attributed to the inability to pay for the necessary school fees. Although tuition was found to have a positive influence on students’ performance in the science subject (Nauzeer & Jaunky, 2019), its affordability is beyond reach for most parents especially those whose students are schooling in rural areas where poverty levels are high. According to (Ministry of Education, 2010) the parents’ inability to raise tuition fees compromised the school’s capacity to provide learning resources which consequently led to poor performance of learners in Agriculture subject.

School Factors influencing Student Performance in Secondary School Agriculture

There is a wide range of school capacity factors that influence the performance of agriculture subjects in secondary schools. Such school capacity factors have been researched in previous studies reviewed. Adequate investment in school educational processes and resources leads to significant increases in student achievement (Owoeye, 2017). The provision of adequate school facilities for learners has been found to promote students’ performance in science subjects (Nauzeer & Jaunky, 2019).  The availability of a farm or field for practical instruction, laboratories, libraries and relevant books on Agriculture subject was found to encourage self-learning and study (Kidane & Worth, 2014). Consequently, these facilities could inspire students to develop ideas and contribute to self-directed learning. According to Umar and Rashid (2019), a well functional workshop that is fully equipped with relevant facilities and equipment is a suitable environment for the acquisition of relevant skills in Agriculture and hence better performance is posted by students. Focusing on gender inclusiveness in the Agricultural high school curriculum in Afghanistan, Salm et al., (2018) noted that the provision of facilities that are gender-sensitive brought a sense of care and belonging promoting student performance in Agriculture in high schools.

School facilities were found to have a 68.9% dominance in influencing students’ performance in Agriculture while the school environment had a 37.1% influence on student performance (Lopes et al., 2019). Besides schools located in poorer communities still do not have the resources to purchase even the most basic digital infrastructure such as computers, printers, software, internet connectivity (Lyons, 2019). Availability of learning resources enhances the effectiveness of schools as such resources bring about good academic performance in the students (Akungu, 2014). According to Okiror et al., (2017), school agriculture was at its best in the 1980s when the government stressed self-reliance as one of the guiding principles in the provision of the country’s education. Thus, school farms were actively utilized, the produce was seen as a source of income and therefore, besides the farm being used as a learning resource, it imparted entrepreneurial skills to the students. This is no longer the case as the focus has shifted to preparing learners to pass examinations and hence most school farms are used for KCSE projects in the fourth year of secondary school (Kyule et al., 2018). Failure to engage learners in practical activities within the school farm has not only influenced their low performance on the subject but has also led to the production of school graduates without agricultural skills for self-reliance after school.

Financial support is also a school factor that influences the teaching and learning and consequently students’ performance in Agriculture. The success of the Agriculture subject as a pillar in the economy of any country is anchored on proper funding for all practical farm-related activities (Konyango et al., 2015). According to Okiror et al., (2017), the Ministry of Education in Uganda did not prioritize the funding of Agriculture subjects. There was no funding for either instructional materials needed or facilities like school farms or gardening tools as did other science subjects such as physics, chemistry, biology and mathematics. Agriculture was also not included among the subjects for ICT training even when social media has many agricultural topics that can be taught to students. In Kenya, the Ministry of Education does not also financially support the learning of Agriculture in school. With free tuition being provided, the allocation of the finances to schools does not factor in a vote head for agriculture resources in schools (Ayako, 2015).  The agriculture students even pay extra fees for the Agriculture KCSE project. The failure to allocate finances to schools indicates the governments’ lack of commitment to supporting the teaching and learning of Agriculture hence poor performance in agriculture subjects because learners miss essential learning resources.

A study was done in Swaziland which reflects the state of ICT infrastructure provision for learning Agriculture in most schools in Kenya today found out that schools were struggling to provide ICT devices like computers, digital cameras, internet access among others to both the students and teachers (Ndwandwe, 2014). Inability to provide such devices coupled with both teacher and learner incapacitation in utilizing them negatively affects the performance of Agriculture subject (Muchiri et al., 2015).

Influence of Using Digital Devices in Teaching and Learning on Student Performance in Secondary School Agriculture

The teaching and learning of Agriculture have transformed in an effort to remain relevant in the digital era. Mndzebele, (2018) defines ICT integration as the use of digital devices such as desktop computers, laptops, tablets, software, and the internet for educational purposes. The common digital devices that schools provide for the learning of Agriculture include; computers, printers, digital cameras, internet connectivity and USB flash drives (Lyons, 2019). The use of smart devices in teaching and learning has been found to provide diversity in the pedagogical approaches used by teachers and learning styles among learners (Nath, 2019).  Smart device use also provides a stimulating learning environment. Additionally, a study by Aneke & Udensi (2016) found that the use of smart devices provided learners with many opportunities like having access to many learning resources, participating actively in class and enjoying varied teaching approaches. However, Aneke & Udensi (2016) established that most ICT facilities for use by learners were inadequate, internet connectivity was poor and most learners could not use ICT devices for proper learning. According to Patrick (2019), lack of enough digital devices in schools, technological incapacity and the lack of internet access limited learners’ use of technology in learning hence poor performance. A study done in Adamawa state in Nigeria found that students and academics lacked sufficient Internet access (Joshua & King, 2020). As a result, the study concluded that e-resources did not impact research and teaching of academics neither learning by the learners.

A study done in Kenya on Computer Assisted Teaching found that the use of computers to complement teaching was a motivator to students learning and consequently their performance in Agriculture (Muchiri et al., 2015). Additionally, the use of computers has been shown to produce positive results in teaching difficult topics or where motivation is low in different subjects including Agriculture. Ndwandwe (2014) revealed that schools struggled to provide adequate technology-related equipment such as videos, computers, internet accessibility, audio cassettes, television, digital cameras and USB flash drives.

Influence of Digital Content use in Teaching and Learning on Performance in Secondary School Agriculture

As digital technologies spread rapidly, digital skills and content are required to match education with the world of work (Lyons, 2019). To promote a new way of teaching in the 21^st century, preparation and use of digital content in schools are paramount. There are many benefits of using digital content in the teaching-learning environment including access to a lot of information, easy storage, reduced bulkiness, enhanced sharing capacity among others (Joshua & King, 2020). However, a study done by Garz et.al, (2020) in Spain indicates that teacher training institutions face the challenge of preparing digital competent teachers. Among the digital teaching competence elements that teachers lack include; digital content creation, communication and collaboration through digital tools, digital content security, information and information literacy and problem-solving (Garz et al., 2020). Besides the inability to create digital content for teaching purposes, teachers faced the challenge of access to relevant digital content for classroom teaching (Joshua & King, 2020). The study and learning environments for agricultural science students were found not to be wholly conducive to high achievement because they were often faced with a shortage of teaching infrastructure and support and out-of-class learning materials, access to the internet and laboratories (Kidane & Worth, 2014).  Learners on the other hand were found to lack skills in handling sophisticated digital technology which not only denied them the benefits of using such content but also lead to their poor performance (Sivalogathasan, 2019).

In a study done in Korea by Park et al., (2014) e-learning is worthy even in agricultural education, which stresses hands-on experience and lab activities. The study also indicated that there lacked student-oriented instructional materials in vocational high schools hence the need to develop e-learning content. The use of e-learning significantly improved vocational students learning achievement and motivation as well as their participation in class (Hoerunnisa et al., 2019). The e-learning platform has made room for use of e-maps, e-encyclopedias, e-books, audio and video players for the enhanced conveyance of knowledge and technology in agriculture improving learners’ performance in the subject (Aneke & Udensi, 2016).

Key Gaps Identified and Possible Mitigation Measures

According to Kabanga & Muauzi, (2020); Kidane and Worth, (2014) and Ben et al., (2020) absenteeism is a challenge common among rural day schools that influences a student’s performance in Agriculture subject. Some interventions were recommended by Kabanga & Muauzi, (2020)  in order to curb student absenteeism. These interventions involve the collaboration between the parents, teachers and all stakeholders in education. The school administrators should provide career talk to learners through the invitation of significant people in society to share experiences with learners. The school administration is to also engage in constructive sensitization of parents on the importance of education to curtail student absenteeism. Proper maintenance and instalment of school sanitation facilities be installed to eliminate absenteeism resulting from menstruation. In addition, the provision of e-attendance tracking software aggregates daily attendance data then individual follows up is done on the chronic absentees (Ben et al., 2020).

Literature has also indicated that students’ motivation for Agriculture subject is low (Nauzeer & Jaunky, 2019; Ward, 2019). Student motivation toward Agriculture subject can be improved through positive reinforcement from teachers, parents and peers (Kapur, 2018). Student background, parental influence and lack of school fees are also factors influencing student performance in Agriculture (Abdullahi et al., 2015; Alexandria, 2018; Kapur, 2018; Uche et al., 2018). The absence or inadequate school learning resources and facilities are other gaps identified through the literature review. Such resources and facilities include laboratories, agriculture workshops, digital libraries, funding, ICT resources, the school farm among others (Nauzeer & Jaunky, 2019; Umar and Rashid, 2019;  Lopes et al., 2019). The provision of adequate learning resources and the use of interactive teaching approaches have also been found to motivate Agriculture students to perform better (Muchiri et al., 2015). The Ministry of Education and the School administration sensitize parents on the need for more parental engagement which positively influences student performance (Mogadime et al., 2015). The Ministry of Education to prioritises funding provision for the different resources needed in the teaching and learning of Agriculture. The Ministry of Education should finance and support ICT integration in the teaching of Agriculture in secondary schools (Okiror et al., 2017). Integration of ICT by agricultural science teachers during teaching will help to produce youths who are informed with global knowledge in Agriculture as well as the youth of high intelligence (Aneke & Udensi, 2016).

Methods

Search Terms

Eleven search terms were formulated as per the key phrases in the research questions (see Appendix A). The Boolean phrase used across all search phrases was AND.  Asterisks were also used with some search words as presented in Appendix A.

Databases Searched

This literature review was limited to Google scholar as it was the only accessible database with articles relevant to the subject of interest.  However, the use of Google scholar posed a limitation to the study as it is extremely difficult to have control over the searches even when using the advanced search. It was a challenge to restrict the searches phrases to the article titles or abstracts. However, Mendeley referencing software was used to select only those items that had the intended phrases within the title and abstract.

Inclusion Criteria

The study search and screen process was used to search for literature to be adopted. Peer-reviewed articles, PhD dissertations and Master’s Theses of interest were reviewed. The articles downloaded must also have been in PDF format. This focused on all the articles published in Google scholar Database with the key phrases formulated. The key phrases must have appeared in the article’s title. The search was limited to articles published in the period between 2014 and 2020 to obtain the current literature as possible. The subject area was limited to education only. Relevance of the article content was also key in the inclusion criteria.

Exclusion Criteria

Any article published before 2014 was excluded. All articles outside the education subject were also excluded from the study. Articles that were not in PDF format and inaccessible we also excluded. Asterisks on some of the key phrases were used as exclusion criteria.  Four steps of identification, screening, eligibility and inclusion were followed as proposed by Petticrew et al., (2015). Figure 8.2, presents the path followed in the exclusion criteria.

Figure 8.2. A flow path of the inclusion-exclusion criterianclusion of articles in each of the analysis tables

The articles were then further filtered per the findings of the keywords for each objective. The sample size, research design, major findings, the journal where the article was published, the authors and the year of publication were reviewed and presented. The research design and sample size were crucial aspects to analyse in the review because they indicate the quality of research and generalizability of study findings. The journal where an article is published was necessary to ensure that only peer-reviewed articles were selected for this study. The year of publication was critical since the more current the data the more the accuracy with which it addresses a given challenge as it exists. Therefore, the researchers’ comments on the importance of each of the article’s findings and how they inform the study were also presented in the analysis tables thereafter.

Analysis, Results and Findings

Table 8.2. Analysis and Results of Student Factors Influencing Performance in Secondary School Agriculture

Table 8.3. Analysis and Results of the Influence of School Capacity Factors on Student Performance in Secondary School Agriculture

Table 8.4. Analysis & Results of the Influence of Using Digital Devices in Teaching and Learning on Student Performance in Secondary School Agriculture

Table 8.5. Analysis and Results of Influence of Using Digital Content in Teaching and Learning on Performance in Secondary School Agriculture

Discussion

This section deals with the research results as presented in four sections. The first part dealt with the student factors influencing student performance in Agriculture subject in a secondary school based on the studies in Table 8.2. From the literature from the four articles reviewed, it is eminent that a student’s home background and parental influence are the pillars of a student’s performance in school. The students’ home background dictates the parents’ ability to pay for school fees as well as their influence on the student’s academic life as supported by three of the four articles. The financial and social support from parents and the home background determine their ability to pay school fees and hence students’ presence or absence from school. The home background and parental support also influence students’ attitude and motivation towards the agriculture subject and consequently their performance. The interrelationships between the student factors and performance in Agriculture subject in secondary schools is articulated in the model therein.

Figure 8.3. The interrelationships model between the student factors and performance in Agriculture subject in secondary schools

Source: Conceptualized by the author

The second section dealt with the school capacity factors and student performance in secondary school Agriculture. The school capacity factors identified in the literature reviewed can be summarized into three categories which are physical and long-term facilities and resources, consumable resources and digital infrastructure. The physical and long-term facilities and resources include the school farm, agriculture workshop, classrooms, library and laboratory.  The consumable resources include funding, farm inputs, books among others. The digital infrastructure includes a digital library and a digital laboratory. From the reviewed literature most schools have not met the threshold in terms of availing of these resources for learning purposes. Although the school farm is available in most schools, it has not been utilized maximally for teaching-learning purposes hence the poor performance in Agriculture. The schools were found to be struggling to catch up with digital advancements in teaching and learning Agriculture. Most schools lack the digital infrastructure that they would use to integrate ICT into their curriculum implementation. These findings agree with those of (Ngeze, 2017) where most schools did not have  ICT infrastructure in place. Where computers were available in schools, then the student computer ratio was very high an indication of the need to equip schools with appropriate and adequate digital devices for better ICT integration.

The third part dealt with the influence of using digital devices in teaching and learning on student performance in secondary school Agriculture. The common digital devices that schools provide for learning Agriculture include; computers, laptops, printers, internet access, smartphones, memory sticks/USB flash drives and cameras (Lyons, 2019). Although the use of digital devices stimulates learning and hence better performance in Agriculture subject, most schools lack adequate ICT facilities, experience poor internet connectivity and most learners cannot utilize ICT devices for proper learning (Aneke & Udensi, 2016). These findings agree with those of (Mwanda et al., 2017) that most schools had few computers which was an impediment to ICT integration in teaching. Additionally, Akala (2021) observed that teachers lacked adequate training on the use of computer technology in teaching besides the absence of a policy framework to guide proper computer integration into the instructional process.

Section four dealt with the influence of the use of digital content in teaching and learning on student performance in secondary school Agriculture as reviewed in the literature. The digital content for use includes videos, audio, e-books, simulations, animations and games. Although the use of digital content has been found to have many benefits, most teachers face the challenge of accessing relevant digital content for classroom teaching. Teachers were also found to lack the competencies related to digital content creation, digital content security, use of communication and collaboration tools and problem-solving (Garz et.al, 2020). A study by Parsons et al., (2020) indicates that students involved in digital-based instruction were found to score higher than their counterparts who had no access to digital instruction. Thus, digital content for use during instruction cannot be overemphasized.

Conclusions

For universities to seal the gaps as a result of secondary school training they need to be aware of student and institutional factors that are likely to perpetuate poor performance among agriculture trainees. Hence the study concludes that:

1. The student factors influencing student performance in the Agriculture subject are the students’ home background, parental influence, absenteeism, school fees, attitude and motivation.
2. Secondary schools have inadequate physical and long-term facilities, consumable resources and digital infrastructure that influence students’ performance in Agriculture subject.
3. Most secondary schools lack digital devices for teaching and learning Agriculture. The students and teachers have little technical know-how in the utilization of digital devices in the teaching-learning process making ICT integration a challenge, hence leading to poor performance in Agriculture subject.
4. Digital content for teaching and learning Agriculture in secondary schools was not readily accessible to teachers and learners, therefore, influencing the students’ performance. Teachers were also found to be lacking essential competencies in digital content use hence hindering their ability to integrate technology in their teaching.

Acknowledgement

The author appreciates Diversity Education Institute (DEI) for its support in putting up literature reviewed work. I am grateful to the institute for thrusting me to study the status of teaching agriculture at secondary school to mirror the training gaps awaiting the university level using an approach that was new to me. Despite the challenges of accessing databases through my institution at the time, DEI’s guidance through the writing process is highly appreciated.