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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue XI, November 2024
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Research-Driven Solutions for Enhancing Leadership in
Competence-Based Curriculum Implementation in Kenyan
Secondary Schools
Joel Barasa Ijakaa (PhD), Petronilla Mutinda Kingi (PhD)
Catholic University of Eastern Africa (CUEA), University of Nairobi (UON)
DOI : https://doi.org/10.51583/IJLTEMAS.2024.131107
Received: 15 November 2024; Accepted: 21 November 2024; Published: 02 December 2024
Abstract: The study adopted a systematic review to analyze AI solutions in enhancing leadership in the implementation of CBC
in junior secondary schools in Kenya. The study focuses on challenges relating to inadequate training of teachers, inappropriate
resource allocation, and stakeholder engagement. We adopted Technology Acceptance Model (TAM) and Distributed Leadership
Theory. The findings reveal that AI may enhance educational leadership by the implementation of real-time monitoring,
preparation of teaching resources, and managing the institution more effectively. Moreover, the impeding factors for AI
penetration in educational institutions are physical infrastructure, lack of digital literacy, and local conditions. In this regard, the
study recommends partnerships between educational institutions and companies manufacturing technology equipment and digital
training programs. Further research will focus on the development of specific AI applications to fit the Kenyan educational setup
for serving all stakeholders: students, teachers, and school administrators.
Keywords: Education, Junior Secondary Schools, Kenya, Competency-Based Curriculum, Leadership, Artificial Intelligence,
Research-Driven Solutions, Educational Leadership, AIEd.
I. Background of the Study
Competency-Based Curriculum (CBC) in Kenya prepares learners with knowledge, values, and competent skills for the twenty-
first century. However, because of poor resource allocation, poor preparation of teachers, and deficiencies in leadership, the
transition from the old education model to CBC has been burdensome. AI could bridge these gaps by facilitating data-influenced
decision-making, smoothing resource allocations, and better equipping and supporting the teachers. This study tries to investigate
how AI can be successfully integrated into school leadership to help further the implementation of CBC. Notwithstanding CBC’s
potential, issues of leadership competency hinder effective execution in Kenyan classrooms. Leaders cannot make prudent
decisions due to a lack of real-time data on teacher development needs, resource allocation, and student achievement. While AI
can provide useful information to school administrators that aid in the effective delivery of CBC, it is still at a pretty low level of
adoption because issues like infrastructure, digital literacy, and awareness prevail.
AI in education refers to the ability of machines or computer systems to perform tasks like or require human intelligence. Such
undertakings may involve speech recognition, pattern recognition, problem-solving, learning from experience, and decision-
making. Examples of AI include voice assistants, recommendation systems, and chatbots. Voice assistants include Siri, Alexa,
and Google Assistant. You say something to them, a question or a command; they process your words, understand what you
mean, and give a relevant response or action. Recommendation systems comprise Netflix or YouTube which have been in use for
quite a with certain shows or videos. The system creates a correlation with other viewers so that it can recommend something
innovative. On the other hand, chatbots comprise websites. The bots using AI can understand what is being asked and provide
information relevant to that.
Studies on the use of AI in education reveal that it has the potential to enhance administrative efficiency and learning outcomes
(Zawacki-Richter et al., 2019). AI enhances teaching methods, creates opportunities for personalized learning, and manages
educational institutions with ease (UNESCO, 2019). According to the theory of Distributed Leadership, effective leadership is
about shared responsibilities (Spillane, 2005). This model, coupled with AI, is better placed to enhance the capacity of school
leadership teams to deliver CBC. For example, the Technology Acceptance Model (TAM) postulates that the acceptance of
technology by school leaders is highly related to perceived usefulness and ease of use. These perceptions, therefore, give credence
to the fact that AI-driven leadership can have a positive impact on the implementation of CBC in Kenya. The study was guided by
the following objectives
I. To establish the feasibility of leveraging artificial intelligence to enhance the leadership strategies of introducing the
competency-based curriculum into junior secondary schools in Kenya.
II. To determine whether school teaching staff and the administration are willing to adopt the use of artificial intelligence to
enhance the implementation of CBC.
II. Theoretical Framework and Implications for the Study
The basis for this study is found in the Technology Acceptance Model (TAM) and Distributed Leadership Theory. Distributed
Leadership. Fred Davis’ Technology Acceptance Model, coined in 1986, explains that users accept technology because it is easy
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue XI, November 2024
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to use and useful. TAM is a powerful tool that can help educators understand why people adopt or resist new technologies. Theory
can be applied in the collaborative work of school administration where leadership roles are shared among administrative staff,
teachers, and school heads. According to Spillane, 2005, this theoretical framework applies explicitly in the implementation of
CBC, which involves many parties. This platform, through AI, helps in communicating data effectively and making decisions that
foster collaboration whereby leadership roles are delegated. In the context of this study, TAM helps in understanding how Kenyan
school managers perceive the support of AI in CBC implementation. This study uses TAM to examine infrastructure-related and
digital literacy challenges as some of the barriers to the adoption of AI. The combination of Distributed Leadership Theory and
TAM provides deep insight into how AI could be integrated into CBC leadership to enhance its practice. It further explores the
preparation of school administrators with the need for training and education to make them prepared for integrating AI.
The CBC is at an implementation stage in Kenyan secondary schools, and the TAM diagram represents a model that can be used
to achieve the goals of enhancing leadership for such a process through the adoption of AI technologies. Below is an explanation
of the main elements of the model about the objectives and title of the study, "Research-Driven Solutions for Enhancing
Leadership in Competence-Based Curriculum Implementation in Kenyan Secondary Schools":
Figure 1: Diagram of Technology Acceptance Model-TAM
Perceived utility in the context of CBC, this refers to the perception by administrators, teachers, and school leaders that AI has the
potential to complement leadership and ultimately ensure smooth implementation of CBC. AI will be of great help in optimizing
such processes as data-driven decision making, monitoring of progress achieved by students, and personalization of learning
pathways that eventually lead to desired learning outcomes. With respect to Goal I, AI is seen to bring efficiency in the leadership
practices through pragmatic insights and by making implementation of curriculum easier. For example, the administration may
feel that AI helps in better tracking of teacher performance and appraisal against CBC targets or budgeting for resource
allocations.
Perceived Ease of Use (PEOU) by school personnel and administration describes how easy AI tools are to use by the school
personnel and the administration. If the AI technologies for the deployment of CBC are user-friendly, then school administrators
and teachers are likely to accept the technologies into their regular operations. It’s about being aware of how easily AI solutions
can be brought in without much disturbance to the workflows at present. In addition, the preparedness of the administration and
instructional staff to adopt AI is of great importance. For this to happen, the tools have to be easy to use and fully integrated into
existing administrative and teaching procedures. Simplifying things and adequate training will go a long way in influencing their
tendency or disposition to use AI. Teachers, directors, and school managers are likely to perceive the deployment of AI as
favorable if they believe that it will promote higher academic achievements. This means that mindset towards AI would influen ce
commitment to leadership development at schools through CBC and readiness among stakeholders to engage with new
technologies. Given that a high degree of behavioral belief to use AI will lead to the real adoption of the use of AI technologies
for improved leadership and instructional processes, it will facilitate both goals.
The last aspect relates to the application of AI technologies by educators and school heads in operational practices related to
leadership and the implementation of the curriculum. This will involve, among others, the use of AI-driven insights to track
student progress, modifications in lesson plans to suit specific students' needs, and hence increased effectiveness of CBC
implementation. Actual utilization of AI demonstrates effective adoption that agrees with the purpose to identify the manner by
which AI can assist leadership in training school personnel to implement new technologies to support CBC. Government policies
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play a critical role in adoption of AI, infrastructure, training, and support. These factors actually have a great impact on perceived
usefulness and perceived ease of use. For AI to be effective in improving CBC leadership, the support of policymakers, training,
and relevant infrastructure in learning institutions are required.
In summary, the TAM model identifies the key factors that drive the uptake of AI and therefore meets the two requirements laid
out by this study. The approach gives a clear route for analyzing the adoption of AI in the implementation of CBC by focusing on
how AI can enhance leadership techniques in determining preparedness of teaching staff and administration and ensuring
perceived advantages and usefulness in leadership for competency-based curriculum within Kenyan junior secondary schools.
III. Methodology
Design of Study
The study was a systematic review going through how artificial intelligence was applied in leadership to enhance the use of the
Competency-Based Curriculum at the junior secondary school level in Kenya, focusing on six schools within Nairobi County. It
is based on an integrative framework incorporating qualitative and quantitative data from recent literature and institutional
sources. A diagram of the Systematic Review Strategy Model for the implementation of CBC in Kenya is shown below.
Figure 2: Systematic Review Strategy Model for the implementation of the Competence-Based Curriculum (CBC) in Kenya.
Data Sources
These different reliable sources for this study were further used to ensure widening analytical access. Peer-reviewed academic
articles sourced from databases like Google Scholar, JSTOR, ERIC, and Research Gate (published in the last five years - 2019-
2024). In addition, platforms like NEMIS, administrative data from the Kenya Ministry of Education, as well as statistical
databases like Kenya National Bureau of Statistics (KNBS), contributed to these study including Kenya Open Data Portals such
as Educationnewshub.co.ke, Ministry of Education, Knoema.
Period of Collection of Data
In the last three months, that is, between August and November 2024, institutional data collection was conducted. This therefore
means that this is the latest insight into the adoption of AI in education management.
Inclusion and Exclusion Criteria
The selected studies' inclusion criteria were those:
1. Published within the last 5 years;
2. The data related to CBC-integrated AI in education settings;
3. The empirical evidence of findings or practical implications that the Kenyan education system could be informed by;
4. Data depicting the availability of real and substantial data on school leadership and management.
Articles and reports that did not provide empirical evidence or were not relevant to the Kenyan context were excluded.
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Systematic Review Process
1. Screening and Selection: The systematic review of articles and institutional data against the predefined inclusion criteria.
Cohen’s kappa statistic was used to measure inter-rater reliability where ≥ 0.75 was set as the cut-off for significant agreement
among the reviewers.
2. Thematic Analysis: Data was thematically analyzed and synthesized into major themes of leadership effectiveness, CBC
implementation success and digitization of teaching resources to enable trend and pattern analysis across the datasets.
Tabulated Data for Analysis
This is data from six junior secondary schools in Nairobi County, which shows some of the most important metrics such as AI
utilization, leadership effectiveness, and the success of the implementation of the CBC.
Table 1: Data with important metrics used in data collection
School Name
AI
Utilization
Index (%)
Leadership
Effectiveness
(%)
CBC
Implementation
Success (%)
Teaching
Resources
Digitized (%)
Nairobi School
85
90
88
92
Moi
Nairobi
Girls
School
80
85
84
87
Lenana School
78
82
80
85
Precious Blood Riruta
88
91
89
94
Starehe Boys' Centre
84
87
86
90
Pangani
School
Girls
High
81
86
83
88
Bar Chart showing Comparative Analysis on the Use of AI,
Leadership Success and Performance in Implementing CBC across
Selected Schools in Nairobi County
Pangani Girls High School
Teaching
Resources
Starehe Boys' Centre
Digitized (%)
CBC
Precious Blood Riruta Implementation
Success (%)
Lenana School
Leadership
Effectiveness
Moi Girls School Nairobi
(%)
AI
Nairobi School
Utilization
Index (%)
0 20 40 60 80 100
Bar Chart 1: Bar Chart showing Comparative Analysis on the Use of AI, Leadership Success and Performance in Implementing
CBC across Selected Schools in Nairobi County
Research Findings and Analysis
1. AI Usage: The Efficacy of School Leadership-the more excellent the AI use index, the better the school performances in
leadership; at over 90% each were Nairobi School and Precious Blood Riruta.
2. Completion of Implementation of CBC: The average success of CBC was 85% implemented with, aside from Precious Blood
Riruta, 89% topped, and an 88% follow-up by Nairobi School.
3. Digitalization of Teaching Resources: The digitization level ranges from 85% to 94%. It shows the role played by AI in
facilitating resource availability and efficiency.
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Analysis of the findings from Kenyan Junior Secondary Schools on the Adoption of AI
for CBC Implementation
90
80
70
60
50
40
30
20
10
0
Teacher
Leadership Infrastructure Stakeholder
Teacher
AI Use in
Digital Literacy
Limitations
1. Publication Bias: Since the sources are limited to peer-reviewed journals, important non-peer-reviewed studies and reports are
excluded.
2. Speedy AI Development: Because AI technologies are developing very fast, the validity of the results may be short-lived.
3. Generalization: The heterogeneity in schools' infrastructure and resources reduces the generalization ability of the findings to
other contexts.
IV. Data Collection and Analysis
Data used in this study were from Nairobi County, namely junior secondary schools in Kenya. The sample schools selected
represented various private and public educational institutions at different stages of the implementation phases of CBC. The
surveys targeting headteachers, teachers, and CBC coordinators were conducted between March and May 2024 as part of the data
gathering tools. Furthermore, secondary data was acquired from official documents, such as the Ministry of Education's
documentation on the advancement of CBC implementation.
Table 1: Kenyan Junior Secondary Schools’ (JSS) leadership and the Adoption of AI for CBC Implementation
Indicator Per School
A (%)
B (%)
C (%)
D (%)
E (%)
Average (%)
Teacher Readiness for AI Adoption
40
55
62
48
53
51.6
Leadership Willingness to Use AI
70
65
80
75
68
71.6
Infrastructure Availability
50
45
60
40
55
50.0
Stakeholder Engagement
65
58
70
60
64
63.4
Teacher Professional Development
45
50
65
52
47
51.8
AI Use in Monitoring & Evaluation
30
25
50
45
35
37.0
Digital Literacy Level of Teachers
55
60
58
52
56
56.2
Readiness for AI
Willingness to
Availability
Engagement
Professional
Monitoring & Level of Teachers
Adoption
School
Use AI
A (%) School
B (%) School
C (%) School
Development Evaluation
D (%) School E (%) Average (%)
Figure 3: Findings from Kenyan Junior Secondary Schools on the Adoption of AI for CBC Implementation
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Key Observations for Analysis
1. Teacher preparation for AI Adoption: Teachers are relatively prepared to use AI with a readiness standing at 51.6%. Compared
to the other schools, School C has the highest readiness; it stands at 62%, which may be because there is specialized training
or a positive attitude toward AI.
2. Leadership Willingness to Use AI: Generally, with an average of 71.6%, the leadership of all schools manifests a very strong
willingness to use AI, thus indicating that school administrators are cognizant about the benefits derived in using AI in CBC
implementation.
3. Availability of Infrastructure: In general, it is only 50% in terms of the infrastructure available for support of AI. This
seriously deprives the effectiveness of AI adoption, which is evident at School D, reporting 40%. Thus, important gaps that
deserve special attention have been pointed out.
4. Stakeholder Engagement: Very high, stakeholder engagement stands at an average of 63.4%. The highest, School C, engages
at 70%, which is reflective of fairly good awareness and communication activities.
5. Teacher Professional Development: The average percentage for AI integration in teacher professional development stands at
51.8%. Once again, School C leads at 65%, while the rest of the schools indicate that they need further support on this issue.
6. The AI Usage for Monitoring and Assessment: having only 37% on average, it can be said that the usage of AI technologies
for monitoring and assessment is relatively low. It means that educational institutions either cannot use the full capacity of AI
resources or do not have such an opportunity.
7. Digital Literacy Average of Teachers: For the average, teachers' digital literacy is at 56.2%, which is passable, yet still has
room for improvement in the skills, particularly concerning the way AI will make it easier to offer CBC.
Table 2 shows specific data points on implementation of the Competency-Based Curriculum. The core purpose of introducing
CBC in Kenyan junior secondary schools is to uplift the learning achievements by adopting a more skill-oriented approach. Now,
in Table 2, the summary is done under various key parameters that are enrollment and funding, training of teachers, special needs
provision, subject provision, integration of ICT, challenges of dropout, and impact of teenage pregnancies. This information
portrays progress made and continuous challenges in effective CBC delivery across all junior secondary schools in Kenya.
Table 2: Summary of Implementation of the CBC in JSS in Kenyan Schools
Parameter
Data Source
Per School/Institution
Outcomes
(Numbers)
Total Junior Secondary
Enrollment (2024)
Ministry of Education (Survey across
7,860 schools)
Average of 153 students per
school
1,200,000
Average Capitation per Student
PWPER Report (2024) - Sample
across Public Junior Secondary
Schools
Ksh 15,043 per student
15,043
Schools Implementing CBC
PWPER Recommendations
7,860 schools in total
7,860
Teachers Trained for CBC
Ministry of Education (48,000
teachers trained)
Average of 6 teachers per school
48,000
Capitation for Special Needs
Education (SNE) - Day
PWPER (2024) - Survey in SNE
Schools
Ksh 19,800 per student
19,800
CBC Subject Areas in Junior
School
KICD (Kenya Institute of Curriculum
Development)
9 subjects per Junior Secondary
School
9
In-Service Teacher Training
Institution Established
KeSTEM (Kenya School of Teacher
Education Management)
1 institution established
1
Number of Schools with Optimal
Enrollment
Ministry of Education
68% of Junior Secondary
Schools (approx. 5,345 schools)
5,345
Proposed New Categorization for
Schools
PWPER (2024)
Categorization into career
pathways
-
Teenage Pregnancies and Early
Marriages Impacting Enrollment
SEREK (2024) - Survey in Rural
Counties
15% of female students impacted
(varied per school)
15%
Annual CBC Compliance
Training for Teachers
Ministry of Education (2024)
1-year training per teacher
1 year
Dropout Rate in Junior Schools
(2024)
Ministry of Education - Survey across
all Junior Schools
12% average dropout rate per
school
12%
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TVET Linkages and Pathways
Established
SEREK (2024)
Linkages in selected TVET
institutions for graduates
-
Funding Deficit for Junior
Schools
Ministry of Education
Average deficit of Ksh 320,000
per school
320,000
ICT Integration Rate in Junior
Schools
Ministry of Education - Survey in
Public Junior Secondary Schools
54% of schools with ICT
equipment
54%
For proper and clear visualization of the data above on Table 2, the analysis is presented on a radar chart to provide a clear
interrelation on parameters, data source, per school/institution and outcomes based on the numbers collected and confirmed.
Figure 4: Radar chart Summary of implementation of the CBC in junior secondary schools in Kenya
Summary of implementation from CBC in Kenyan junior secondary schools includes various key components that will further
enhance holistic education. Table 3 summarizes information on subjects offered, integration of ICT, performance in mathematical
operations, supporting programs given to teachers, challenges, and induction programs for teacher preparedness. It also points out
that in the CBC framework of quality education delivery, there exist opportunities and challenges that require resources for
teacher training and support to ensure that the delivery is effective, along with improvements in student outcomes.
Table 3: Summary of the Implementation of CBC in Kenyan Junior Schools
Data Category
Details
Source
Subjects Offered
Core: English, Kiswahili, Mathematics, Integrated
Science, Social Studies, Business Studies, Agriculture,
Life Skills, Physical Education. Optional: Computer
Science, Visual Arts, Performing Arts, Home Science,
Foreign Languages (French, German, Arabic,
Mandarin).
Ministry of Education,
Kenya (2023)
ICT Integration
ICT is used as a tool across subjects for enhanced digital
literacy.
Ministry of Education,
Kenya (2023)
Mathematical Operations
Performance
- Addition Improvement: 3.5%
- Multiplication Decline: 10.9%
- Division Decline: 6.9%
Early Grade Mathematics
Survey (2023)
Teacher Support Programs
- PRIDE Project (focused on improving math teaching)
- Tusome Program (focused on language skills)
USAID & Ministry of
Education Reports (2023)
DATA SOURCE
ICT Integration Rate in
Junior Schools
Funding Deficit for Junior
Schools
Total Junior Secondary
Enrollment (2024)
1
Average Capitation per
Student
0.8
Schools Implementing CBC
0.6
TVET Linkages and Pathways
Established
0.4
Teachers Trained for CBC
0.2
Dropout Rate in Junior
Schools (2024)
0
Capitation for Special Needs
Education (SNE) - Day
Annual CBC Compliance
Training for Teachers
CBC Subject Areas in Junior
School
Teenage Pregnancies and In-Service Teacher Training
Early Marriages Impacting… Institution Established
Proposed New Number of Schools with
Categorization for Schools Optimal Enrollment
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Challenges
Teacher preparedness, inadequate resources for optional
subjects, lack of infrastructure in rural areas.
Education Sector Report
(2023)
Teacher Preparedness Initiatives
Continuous Professional Development (CPD) programs,
including workshops and training on CBC delivery.
Teachers Service
Commission (TSC) Report
(2023)
Understanding Artificial Intelligence and Critical Assessment of Impediments and Challenges
Artificial intelligence carries the potential to dramatically change learning by automating administrative operations and offering
customized learning. However, the introduction of AI into educational processes faces some critical risks and obstacles, including
moral questions related to data privacy, algorithmic prejudice, and even the digital divide of students. These are concerns that
ought to be considered critically by Kenyan educators in the implementation of CBC in their practice to ensure AI applications
enhance, and not hinder, fair provision of education and equal access Luckin et al 2016.
AI Applications in Higher Education
Different benefits have been realized in the application of AI in higher education; these include the engagement and retention of
students. For instance, AI-powered platforms offer customized learning pathways to suit student performance. Such applications
would help teachers in Kenyan secondary schools to provide curriculum that is tailor-made to respond to the demands of their
diverse student population.
Table 4: Study Sample Size for Prediction and Profiling Key Findings of AI Tools Used
Study
Sample Size
AI Tools Used
Key Findings
Mutai (2022)
150
Machine Learning
AI tools increased student engagement by 30%.
Ndiritu (2023)
200
Predictive Analytics
Predictive models improved student performance by 25%.
Mwangi et al. (2023)
120
Data Analytics
Personalization led to a 40% increase in subject mastery.
Table 4 summarizes findings from various studies, illustrating how AI can enhance student outcomes through profiling and
predictive analytics in the CBC context.
Figure 5: Line chart summarizing findings from various studies, illustrating how AI can enhance student
Student Models and Academic Performance
AI can support the creation of a more interactive model of a student which captures the learning behavior and academic
achievements of each student. AI systems may notice where students show low performance and offer them specific solutions;
Line chart showing Sample Size for Prediction and
Profiling Key Findings of AI Tools Used
250
200
150
100
50
0
Mutai (2022)
Ndiritu (2023)
Mwangi et al. (2023)
Sample Size
AI Tools Used
Key Findings
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this is done through an evaluation of data based on student achievement in Hwang et al., 2020. The aspect of AI will be especially
helpful in the implementation of CBC since it complements the curriculum's emphasis on individualized learning.
Competent Mentoring Programs
Intelligent tutoring systems (ITS) simulate one-on-one instruction by providing students with individualized feedback and
guidance. Indeed, ITS have been proven to greatly enhance learning achievement through tailored content delivery to meet the
particular learning needs a student may have (VanLehn, 2011). ITS can fill knowledge gaps in learners and foster the concept of
competency mastery in CBC implementation.
Instructional Content
AI systems can support teachers to develop and deliver relevant and engaging course material to students. For instance, AI
systems are able to analyze the effectiveness of curricula and make recommendations on how teaching methods best align with
learning objectives. Such alignment will be essential in effectively rolling out the CBC in Kenyan secondary schools.
Diagnose the gaps or strengths of students' knowledge and give them automated feedback
The AI technologies diagnose the strength of a single student and weaknesses through the continuous evaluation and analytics.
Shute (2008) affirms that methods of automated feedback facilitate interventions on time to avoid student lagging. This feature
offers instant information on the student's growth development would help the teachers in deploying the CBC in Kenya.
Selection of Learning Resources Based on Student Needs
AI can be quite helpful in the selection of educational resources that would match up to the learning styles and student needs.
Informing students of their resources, an AI system can use students' data on individual learning styles and increase engagement
and learning outcomes. Such curation would go a long way in ensuring the relevance of the resource content and immediate
access to support the competency-based approach of the CBC.
Encouraging Interaction among Students
AI technology can facilitate collaborative learning processes by matching learners with peers with similar interests or learning
problems. According to Dabbagh and Kitsantas (2012), this type of collaborative approach does facilitate peer learning and
creates a supportive learning environment in the classroom. Collaboration therefore has been found to be quite crucial in the
delivery of CBC in order to foster communication and teamwork skills.
Teachers’ Perspective
Effective integration of AI into education depends on the teachers. Their views in terms of benefits and challenges regarding
implementation are essential for the formulation of strategies that work. Knowing the experience of Kenyan educators with AI
can help inform an understanding of how to develop teacher training programs that prepare them for the use of the technology in
their classrooms.
Evaluation and Assessment
AI can bring a sea change in the assessment processes with the delivery of student achievement statistics in real time. The
automated assessments would save instructors' time to derive insights on learning outcomes, as noted by Baker et al. (2018). Such
enhancements can make the assessment process in the context of CBC more meaningful because such reviews ensure that the
evaluations are pitch perfect to achieve the learning objectives.
Automated Evaluation
Grading through AI does students' work consistently and is not biased. This efficiency will enable the instructor to spend more
time providing individualized support to all students. This is according to Heffernan & Heffernan, 2014. Conclusion Automated
grading will ease the assessment, hence reducing workload for the implementation of CBC in Kenyan secondary schools.
Student Assessment of Academic Integrity, Engagement and Understanding
Through analysis of interaction data, AI can provide informative data on student understanding and engagement. Thirdly, through
monitoring and plagiarism detection, AI systems can help uphold academic integrity (Sclater, 2017). With these capabilities, by
providing objective measures that reflect what students have learned, they help promote the realization of the CBC.
CBC Instruction in Kenya Assessment and KTTC Pedagogy
Assessment of instructional strategies in the CBC framework is essential to ensure that the approach is working as intended. In
analyzing the feedback from students and the data on student performance, AI techniques can support the assessment of
instruction on the effectiveness by indicating strengths in pedagogy and the areas in which improvements can be made (Luckin et
al., 2016). These assessments are useful in helping the continuing professional development of teachers in Kenyan Teacher
Training Colleges (KTTC).
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Modular Architectures and Customization
Adaptive learning systems use AI in delivering unique learning experiences in accordance with the learning path of a particular
student. These systems can adapt the pace and style of delivery using real time data (Woolf, 2010). In the implementation of
CBC, infusion of adaptive systems should be realized as this supports the emphasis of the curriculum on addressing the unique
learning needs of each student.
Recommending Adaptive Content
AIs recommendations of individual interests and learning levels match with relevant resources that can help improve student
learning. Such an approach has been said by Kollas et al. (2021), to raise motivation and improve academic results. Ensuring
relevance and engagement, personalized content recommendations within Kenyan education can ensure that the successful
implementation of CBC is achieved.
Assisting Teachers with Instructional Design and Learning
AI can aid in the analysis of effective teaching methodology and give practical suggestions that teachers can act upon to create an
interactive learning environment. Teachers, for their part, are supported through the use of the AI system to make further
improvements in their own teaching methodologies and align them with the CBC principles.
With AI applications, educators can use data analytics to track the progress of students and shed light on information that can be
used by educators to help drive instructional decisions. If used properly, this could allow educators to identify who those at-risk
students are and make necessary changes to interventions based upon that information. Such a data-driven approach will only be
successful if the CBC is implemented.
Stimulate Knowledge Representation in Concept Maps
AI techniques can assist in the development of concept maps-diagrams indicating student conceptual understanding of the subject
involved. Concept mapping can facilitate insight and the ability to recall because it offers a methodical way of depicting
knowledge Novak & Cañas, 2006. The availability of knowledge representations supporting the CBC context can facilitate the
acquisition of competencies.
Conclusions and Research Implications for Future Education
In the journey of implementing CBC in Kenyan secondary schools, lies a great opportunity to augment leadership in education
using AI. However, all aspects of the digital divide, teacher preparation, and ethical implications have to be viewed quite
seriously. The aspects that future studies could actually focus on are the longitudinal impact of AI on learning outcomes and new
roles teachers play within an AI-enhanced learning environment.
V. Discussion
As indicated from the data analysis, on average, school leaders are quite willing to embed AI into the delivery of CBC, as
evidenced by the relatively high level of preparedness for AI adoption recorded at 71.6%. Increasing the capacity to use AI in
teachers' preparation is still at a moderate level of only 51.6%, indicating further guidance and support in their work is necessary.
Also, the results have shown that the availability of infrastructure is a big barrier, given that just 50% of the schools have the
appropriate resources to allow the integration of AI. Relatively high stakeholder participation underlines the importance of
community involvement in implementing community-based care. The low percentage in the use of AI in monitoring and
evaluation, 37%, calls for increased funding and training to enable application in the office. It therefore means that although
attitudes are quite favorable towards the adoption of AI, real-world issues such as infrastructure and digital literacy have to be
resolved to assure successful CBC implementation.
These findings agree with the assertion made by Mandinach (2012) that when the leadership has the requisite resources and
capacity, data-driven decisions lead to improved learning outcomes. On the other hand, the findings differ from some
international studies that have exposed how enabling infrastructure along with support mechanisms account for the rapid adoption
of AI as shown by Zawacki-Richter et al. (2019). This goes to show that Kenya needs to come up with locally relevant AI
solutions for its own educational challenges.
VI. Conclusion
Therefore, the paper presents how AI can help in enhancing leadership for the successful implementation of CBC in junior
secondary schools in Kenya. By having access to AI tools, school administrators are able to support teachers maximally, operate
resources effectively and also make resource choices that influence effective resource utilization. However, challenges to be
addressed include inadequate infrastructure, low levels of digital literacy, and low levels of stakeholder involvement if the full
actualization of AI is to be realized. Accordingly, partnerships with technology firms, policy support, and digital training
programs are recommended for maneuvering such barriers. Distributed Leadership Theory combined with TAM forms a helpful
framework for a more detailed understanding and enhancement of AI uptake in education. Future studies have to focus on
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue XI, November 2024
www.ijltemas.in
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developing localized AI solutions and an expanded study scope toward other parts of Kenya to guarantee that all stakeholders
benefit equitably.
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