The Impact of Demographics on AI Usage in Education: Insights from Recent Research
In recent years, artificial intelligence (AI) has rapidly grown in various sectors, including education. Understanding how different demographic factors influence the adoption of AI among teachers is crucial for developing strategies to maximise its benefits. Georgia Green, CAVA’s Communication and Events officer, recently focused on this very topic, examining how age, gender, teaching experience, and academic stream impact teachers' use of AI in the classroom. The findings provide valuable insights that can help educational institutions tailor their approaches to integrate AI more effectively.
This research was undertaken as part of Georgia’s dissertation for her Masters in Psychology. She produced a survey to gain information about educator’s demographics and how it correlated to their use of AI. She shared it with various schools and colleges around the country, as well as sharing on social media. Overall, data was collected from 98 participants from a range of ages, gender and academic stream.
One of the most striking findings was the disparity between teachers identifying as male and female in using AI. The data revealed that men are significantly more likely to incorporate AI tools into their teaching practices than women. This gender gap suggests a potential area for intervention, perhaps through targeted training and support programs aimed at encouraging female teachers to engage with AI technology.
Age emerged as a critical factor in AI adoption, with younger teachers being more inclined to use AI than their older counterparts. The analysis indicated that age 34 appears to be a pivotal point, after which AI usage begins to drop. This lines up with the digital native generation, aligning with the broader pattern of technology adoption, where younger individuals are often more tech-savvy and quicker to embrace new technologies.
Experience in teaching also plays a significant role in the use of AI, with less experienced teachers more likely to utilise these tools. However, it's important to note that age and experience are closely correlated. This near-perfect correlation makes it challenging to determine if the willingness to use AI is driven more by age or by teaching experience. Nonetheless, the data clearly shows that those newer to the profession are more open to integrating AI into their classrooms.
Interestingly, the academic stream did not show a clear impact on AI usage. However, there were patterns indicating that teachers instructing older students were more likely to use AI, with primary school teachers significantly less engaged with AI tools than their colleagues teaching FE or HE. This could be due to the perceived appropriateness or utility of AI in different educational contexts, where AI tools might be seen as more beneficial or easier to implement in FE and HE compared to primary education.
These findings can support CAVA and our members, by highlighting the importance of understanding and assisting staff who are not currently utilising AI. Many educators are unaware of the available AI tools or what they can do. Last year we released a blog post highlighting 5 useful AI tools for educators. These tools are still some of our favourite ones, and a useful starting point for anyone exploring AI.
Support moving forward may require practical demonstrations and time to experiment with these technologies. The research emphasises that colleges should focus their efforts on supporting their older and female staff members. By providing targeted training, showcasing AI applications, and allocating time for exploration and experimentation, institutions can foster a more inclusive and effective adoption of AI across all teaching demographics.
Insights from Georgia Green.
Research approach
This research was undertaken as part of Georgia’s dissertation for her Masters in Psychology. She produced a survey to gain information about educator’s demographics and how it correlated to their use of AI. She shared it with various schools and colleges around the country, as well as sharing on social media. Overall, data was collected from 98 participants from a range of ages, gender and academic stream.
Key Findings
Gender Differences in AI Adoption
One of the most striking findings was the disparity between teachers identifying as male and female in using AI. The data revealed that men are significantly more likely to incorporate AI tools into their teaching practices than women. This gender gap suggests a potential area for intervention, perhaps through targeted training and support programs aimed at encouraging female teachers to engage with AI technology.
Age as a Determinant Factor
Age emerged as a critical factor in AI adoption, with younger teachers being more inclined to use AI than their older counterparts. The analysis indicated that age 34 appears to be a pivotal point, after which AI usage begins to drop. This lines up with the digital native generation, aligning with the broader pattern of technology adoption, where younger individuals are often more tech-savvy and quicker to embrace new technologies.
Experience Level and AI Usage
Experience in teaching also plays a significant role in the use of AI, with less experienced teachers more likely to utilise these tools. However, it's important to note that age and experience are closely correlated. This near-perfect correlation makes it challenging to determine if the willingness to use AI is driven more by age or by teaching experience. Nonetheless, the data clearly shows that those newer to the profession are more open to integrating AI into their classrooms.
Academic Stream and Student Age Group
Interestingly, the academic stream did not show a clear impact on AI usage. However, there were patterns indicating that teachers instructing older students were more likely to use AI, with primary school teachers significantly less engaged with AI tools than their colleagues teaching FE or HE. This could be due to the perceived appropriateness or utility of AI in different educational contexts, where AI tools might be seen as more beneficial or easier to implement in FE and HE compared to primary education.
Implementations for CAVA
These findings can support CAVA and our members, by highlighting the importance of understanding and assisting staff who are not currently utilising AI. Many educators are unaware of the available AI tools or what they can do. Last year we released a blog post highlighting 5 useful AI tools for educators. These tools are still some of our favourite ones, and a useful starting point for anyone exploring AI.
Support moving forward may require practical demonstrations and time to experiment with these technologies. The research emphasises that colleges should focus their efforts on supporting their older and female staff members. By providing targeted training, showcasing AI applications, and allocating time for exploration and experimentation, institutions can foster a more inclusive and effective adoption of AI across all teaching demographics.
Insights from Georgia Green.
