Abstract
This chapter examines AI's role in Caribbean high school and college assessments, analyzing teacher and student perspectives. A quantitative study surveyed 160 students and 102 teachers via Google Forms in September 2023, investigating AI tool usage, its effects on grading and feedback, fairness, and ethical concerns. Key findings include students' prevalent use of Grammarly and ChatGPT and plagiarism software by teachers, with significant AI encounters at the high school level. Positive correlations emerged between teachers' views on AI's grading efficiency, optimism for its future, and students' appreciation for AI's timely feedback. Concerns about AI-induced discrimination showed no significant differences across countries or educational levels, highlighting ethics and transparency as crucial. The need for targeted AI integration training is emphasized, suggesting future research should address AI biases and explore new tools for enhancing Caribbean educational outcomes.
TopIntroduction
Education in the Caribbean has undergone significant evolution shaped by a complex interplay of cultural, socioeconomic, and political factors across its diverse islands (Brissett, 2018). Historically, education in the Caribbean was driven by colonial interests, with European powers primarily establishing educational systems to serve their needs rather than the local populations (Campbell, 2003; Sherlock, 1950). Fast forward to the post-colonial era, many Caribbean countries sought to decolonize their education systems by incorporating local languages, history, and cultural traditions into the curriculum, but it has been a challenging transition (Brissett, 2021; Jules, 2008). Despite the challenges of the decolonization of educational systems, such as limited resources, inadequate infrastructure, and socioeconomic factors, the Caribbean has made significant academic strides in recent decades. Many countries have implemented initiatives to improve literacy rates, expand secondary and tertiary education access, and enhance vocational training opportunities (Ahmad, 2020; Brissett, 2021; Louisy, 2004).
Additionally, regional organizations such as the Caribbean Community (CARICOM) have promoted cooperation and collaboration in education, facilitating the exchange of ideas, resources, and best practices among member states. Furthermore, alignment with UNESCO's EFA goals has continued to move Caribbean education systems forward in a way that embraces 21st-century teaching and learning. Continued investment in education and a commitment to addressing systemic issues are essential for the region's future development and prosperity (UNESCO, 2023).
Caribbean nations have demonstrated notable progress in incorporating Information and Communication Technology (ICT) within educational frameworks in the past decade, enriching 21st-century learning methodologies (Mayne, 2014). This advancement aligns with the objectives of UNESCO's Education for All (EFA) initiative. Commenced in 2000, the EFA goals seek to guarantee inclusive and fair access to quality education for all, emphasizing the core tenets of accessibility, equity, and educational quality (Bowe, 2015).
However, Caribbean countries face challenges in ICT in education due to many socioeconomic and political factors. These challenges hinder the effective adoption of digital technologies in education. Additionally, the rapid emergence of Artificial Intelligence (AI) in education adds complexity to this issue, requiring careful policy consideration and strategic planning. This chapter examines AI's role in Caribbean high school and college assessments from the perspectives of teachers and students.
Education policymakers within the Caribbean stress the significance of tackling education-related challenges by implementing initiatives advocated by the Caribbean Community (CARICOM). CARICOM has sanctioned the use of UNESCO's guidance documents for the modernization and alignment of 21st-century skills, which includes guiding documents such as the ICT Competency Framework for Teachers, AI, and Education: A Guidance for Policymakers and the latest Guidance for Generative AI in Education and Research. These frameworks provide helpful direction for policymakers and educators to effectively integrate AI and digital technologies in education worldwide, accommodating the Caribbean's socioeconomic and political issues. Specifically, AI's increasing role in education for societal transformation is now an integral part of global discussions (Holmes & Miao, 2023; Mayne, 2014; Miao et al., 2021). Notably, AI is gaining traction in the Caribbean in education due to the sharp growth of ICTs in education and assessment practices.
Key Terms in this Chapter
Adaptive Learning: A method of education that uses AI algorithms to adapt learning content and activities to the individual learner's abilities and preferences.
Chatbots: AI-powered conversational agents that can interact with students in natural language, providing assistance, answering questions, and facilitating learning.
AI-Assisted Education: Artificial intelligence-assisted education involves using artificial intelligence technologies to enhance teaching and learning processes. It includes personalized learning, intelligent tutoring systems, automated grading, and data-driven insights to improve student outcomes. AI helps tailor educational experiences to individual needs, making learning more efficient, engaging, and accessible.
Educational Data Mining (EDM): The process of analyzing educational data to improve learning outcomes. EDM can use AI techniques to identify patterns and provide insights into student learning behaviors.
Formative Assessment Tools: Digital tools and platforms that support ongoing assessment and feedback during the learning process, helping students monitor their progress and identify areas for improvement.
Educational Digital Transformation: The integration of digital technology into all aspects of the school system, fundamentally changing its operations and value delivery from top down to bottom up. It involves rethinking operational models, teaching and learning models, embracing new approaches, and increasing agility to respond to educational changes. Specifically, from a school operational level, it includes adopting digital tools, using data analytics, and personalizing learning experiences.
AI-Efficacy: This refers to the effectiveness of AI technologies when used within educational settings. It involves using AI tools or applications to increase efficiency, improve teacher productivity, and enhance educational performance.
Digital Technologies: The use of hardware, software, and online tools that create personalized learning experiences, enrich educational practices, and transform the traditional learning environment.
21st-Century Learning: This is a concept of learning that emphasizes critical thinking, creativity, collaboration, communication, and technology integration to prepare students for a rapidly changing global landscape.
Educational Predictive Analytics: This form of educational analysis uses a combination of student data, statistical algorithms, and machine learning techniques to identify various teaching and learning issues, such as identifying students needing additional learning support in literacy and numeracy.
Performance-Based Assessment: An individualized learning approach that focuses on the development of critical thinking and problem-solving skills through real-world projects rather than relying on traditional measures of testing such as written examinations. Performance-based assessments help students gain practical experience and develop meaningful strategies that prepare them for challenges beyond the classroom.
Learning Analytics: The measurement, collection, analysis, and reporting of data about learners and their contexts. AI can enhance learning analytics to provide real-time feedback and personalized learning paths.
AI-Driven: The use of artificial intelligence technologies to support, enhance, and optimize existing processes within educational institutions.