Students and Teacher’s Perspectives on learning experiences with AI: Findings from a case study on the implementation of AI in an International (IB) School
The rapid pace of technological development is driven by the quest to develop new ways of learning and augment the classroom environment by incorporating new technologies and methods. Artificial Intelligence (AI) in Education has emerged as one of the most important topics concerning learning in educational contexts recently. AI has made great strides in developing different applications to support teaching and learning.
The presentation addresses the outcomes of a case study on the implementation of AI in an international school in the UK. This research aimed to explore the potential role and impact of AI on teaching and learning at the secondary level. The study collected perspectives of students and the mathematics teacher on the implementation of AI, using an online survey which was followed by individual online interviews. The participants in this study were 6 high school students aged 14-16 years and one mathematics teacher. The data were collected using three variables:-Learning Environment, Curriculum & Pedagogy, Assessment & Feedback.
The presentation highlights findings offering insights into key issues, including a distinct benefit in teaching and learning.
The analysis summary of student's perspectives
1. Learning Experience
The students reported AI application offered access to a conducive and high-quality digital learning environment with a wide range of learning resources and well-designed learning tasks. It helped to understand the subject-specific strengths and weaknesses through a diagnostic assessment at the start which created an individual learning path for the participating students. This enabled students to practice a range of topics at their own pace based on their individual abilities and to access learning tasks based on individual skills. The students shared this aided in understanding the subject-specific content and complex concepts with confidence which subsequently resulted in active student engagement in the learning process.
The students reported the feedback process was prompt and indicated what was right or wrong which facilitated continuous reflection and engagement in self-assessment, a process that allowed students to monitor their learning. The student responses reflected diversity of views regarding integrating real-life situations and setting personal learning goals.
2. Cognitive and Affective Experience
The AI Application aimed at metacognition intervention by providing an open student model that allowed students to make flexible choices about the topics and difficulty level to work on, which scaffolded the self-regulatory process, encouraged informed choice, self-management and reflection through regular progress reports. The process of consistent, supportive interventions helped students develop self-monitoring and self-evaluation skills, which in turn fostered self-confidence and a sense of ownership over their learning, aligning with principles of self-management and self-regulated learning.
Some of the factors that contributed to the success in addressing student cognition include personalisation of the difficulty of selected mathematics problems; provision of scaffolding; solved animated examples and video tutorials; additional practice tasks for improving the foundational subject skills and revision support in the absence of the teacher.
The analysis summary of Teacher’s Perspectives
The mathematics teacher shared the AI application was beneficial in accessing prior knowledge through a process of diagnostic assessments, identifying strengths, weaknesses, gaps in knowledge of individual students and to structure appropriate scaffolding by creating an individual learning path. This helped the teacher in differentiating learning without physically creating additional tasks/worksheets and activities for different students. The teacher reported quality of content and practice questions supported classroom learning. The practice tasks became progressively harder which catered to the individual ability of the students and consequently motivated them to work on challenging areas in mathematics.
The AI application offered an effective overview of student learning with clear indicators of time spent on the activities and thus supported the teacher in monitoring learning. The prompt progress reports led to early interventions and personalised the learning process.
Limitations
One of the technical limitations of this specific AI application was the feedback process. Though it offered prompt feedback it did not indicate the computational errors in the process. Interestingly, the teacher found the feedback process particularly helpful as the AI application got locked after a few wrong attempts which prompted teacher’s mediation, this created a necessary opportunity for human intervention which was valuable for student support and stresses on the ongoing importance of human input in the learning process.
Conclusion
The presentation offered insights on early outcomes from a case study that recognise the potential of AI in teaching and learning, including its current limitations in an international school context. The outcomes of this research will benefit different constituencies such as school leaders, teachers, curriculum developers and policy makers. Since AI is a burgeoning area of research, its application carries the potential to benefit teaching and learning in educational settings however, it needs careful consideration and nuanced discussions regarding its implications on different subjects, age groups and learning environments. Additionally, it requires regular trials to evaluate the assistance and limitations of human-machine interactions in different learning environments.
View the full presentation here:
Farooqi, N. (2025, September 29). Students and Teacher's Perspectives on learning experiences with AI: Findings from a case study on the implementation of AI in an International (IB) School. AIEOU Inaugural Conference, University of Oxford. Zenodo. https://doi.org/10.5281/zenodo.17225320
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