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Like many others, having observed ChartGPT burst onto the scene in the last few months, the disruption it has caused to education – both in terms of pupil and teacher use, it now seems that every other day there is news of a new AI platform being released.

In terms of the public arena, OpenAI launched ChatGPT in November 2022, and since then Google has launched Bard; Microsoft is integrating OpenAI to Bing (and firing a lot of their staff); Twitter has begun plans to use AI to detect & highlight any manipulation of public opinion, presumably from those pesky Russians & Chinese influencers who have been wreaking havoc on everything from Brexit to the rise in cost of Freddos (please re-read that sentence with your tongue in your cheek – that’s where mine is currently). An interesting entrance to the AI arena came from Alibaba. If you’ve never heard of them, go spend some time on their site-they are the wholesale trade entry point for the world. Want to sell anything from drones to dinnerware? Alibaba is the answer! (That sales patter was just me, I’m not receiving any commision from Alibaba to talk them up.)

As far as education goes, there are issues that we need to resolve in the classroom to adapt to the existence of AI. The ability of AI to evade plagiarism tools is an issue for many teachers and lecturers who set assignments. For students, the lure of a higher grade might be too tempting to resist. This story, published recently on the BBC (9th April 2023), shows how one student at Cardiff University revealed that he recently submitted two assignments. With one he used ChatGPT and got a first. In the second assignment, which he submitted without using the AI software, he got a a low 2:1. Interestingly in this story, the student stated that he didn’t copy everything word for word, but used it as a prompt – with questions to frame and plan his work. To me, this would reduce calls of cheating to being similar to using a tutor – albeit a digital one. Also interestingly, a FoI request to Cardiff University showed in the January 2023 assessment period there were 14,443 recorded visits to CHatGPT on the university Wi-Fi network, with 0 (zero!) logged visits in the month previous. Clearly the ‘problem’ if it is one (which I don’t have the evidence to say either way) is at a large scale in the HE sector, where the stakes of achieving a good degree classification, in order to secure career employment are high.

So the existence of ChatGPT is an issue – but it does have benefits.

While I can’t really offer any solution to the issues faced by HE, I want to focus on what it can do for us in the classroom. As a teacher, I do use ChatGPT. I have found it useful to create essay questions for exam classes. With past paper exams, there are only so many questions I can use to prepare my students for their exam, so having new questions generated in a particular style is going to be very helpful for them to prepare for a wide range of questions, and useful for me as it gives me a wider pool of questions to use.

Strategy 1: AI-created examples

AI creating examples

Teachers can leverage AI-created examples in their teaching in a variety of ways, depending on the subject, school year, and specific learning objectives. Here are some potential approaches:

  1. Supplementing lesson materials: AI-generated examples can be used to enhance existing lesson materials. For example, in a maths class, teachers can use generated maths problems as additional practice exercises or homework assignments. These examples can provide students with diverse and varied practice opportunities that are automatically generated by the AI, saving teachers time and effort in creating a large number of practice problems.
  2. Customising instruction: AI can analyse data on students’ learning styles, strengths, and weaknesses, and generate personalised examples tailored to individual students’ needs. This can enable teachers to provide differentiated instruction, addressing the unique learning needs of each student. For example, an AI-powered language learning tool can generate sentences or phrases with varying levels of difficulty based on a student’s language proficiency level.
  3. Encouraging critical thinking: generated examples can serve as prompts for students to engage in critical thinking and problem-solving skills. Teachers can use AI-generated scenarios or simulations that present real-world challenges, allowing students to analyse and evaluate the situation, apply their knowledge, and generate solutions. This can foster creativity, innovation, and analytical skills among students.
  4. Enhancing feedback and assessment: AI can automatically assess student work and provide instant feedback. Teachers can use generated feedback to complement their own feedback, providing students with more comprehensive and timely insights into their performance. For example, an AI-powered writing tool can analyse students’ writing samples and provide feedback on grammar, style, and content, helping students improve their writing skills.
  5. Sparking curiosity and engagement: generated examples can be used to capture students’ attention and stimulate their curiosity. For instance, virtual reality simulations or AI-generated visualisations can make abstract concepts more concrete and accessible to students, enhancing their engagement and understanding of the subject matter.
  6. Teaching ethics and responsible AI use: As AI becomes increasingly prevalent in various domains, teachers can use AI-generated examples to teach students about ethical considerations and responsible use of AI. Discussing topics such as bias in AI, the limitations and risks of AI, as well as the ethical implications of generated content can help students develop critical thinking skills and digital citizenship.

It’s important for teachers to use generated examples judiciously, ensuring that they align with curriculum goals, are appropriate for students’ developmental levels, and are used in conjunction with human instruction and guidance. Teachers should also be aware of issues such as data privacy, bias, and responsible AI use when incorporating generated examples into their teaching practices.

Strategy 2: AI-created explanations

AI chat GPT

AI-created explanations can be a valuable tool for teachers to enhance their teaching in several ways:

  1. Simplifying complex concepts: AI-generated explanations can simplify complex concepts by breaking them down into understandable language. For example, in a science class, an AI-generated explanation can clarify intricate scientific concepts or processes, making them more accessible to students who may struggle with the material.
  2. Providing multiple perspectives: AI can generate explanations from different perspectives or angles, providing a more comprehensive understanding of a topic. Teachers can use these diverse explanations to help students develop a broader and more nuanced understanding of complex topics that may have multiple interpretations or viewpoints.
  3. Supporting flipped classrooms: In a flipped classroom model where students learn independently outside of class and come to class for discussion and application, AI-generated explanations can provide self-paced learning opportunities. Students can access AI-generated explanations online, review them at their own pace, and come to class prepared for more in-depth discussions and activities.
  4. Personalising instruction: AI can analyse individual student’s strengths and weaknesses and generate explanations tailored to their learning needs. This can help teachers provide personalised instruction and support to students who may require additional explanations or different approaches to learning.
  5. Enhancing multimedia learning: AI-generated explanations can be combined with other multimedia resources such as videos, diagrams, and interactive simulations to create a rich and immersive learning experience. Teachers can use these multimedia resources, including AI-generated explanations, to create a multi-modal learning environment that caters to different learning styles and preferences.
  6. Promoting self-directed learning: AI-generated explanations can empower students to take ownership of their learning by allowing them to explore topics independently and at their own pace. Students can use AI-generated explanations to deepen their understanding, ask questions, and seek clarifications, fostering a sense of self-directed learning and curiosity.
  7. Teaching critical thinking skills: Teachers can use AI-generated explanations as prompts for critical thinking and analysis. They can encourage students to evaluate the quality and reliability of AI-generated explanations, assess potential biases or limitations, and compare them with other sources of information. This can help students develop critical thinking skills and become discerning consumers of AI-generated content.

It’s important for teachers to use AI-generated explanations as a supplement to their own expertise and judgment, and not as a replacement for human instruction. Teachers should also ensure that AI-generated explanations are accurate, reliable, and age-appropriate, and align with curriculum goals and learning objectives. Teachers should actively engage with the AI-generated explanations, provide context, and facilitate discussions to help students develop a deep and meaningful understanding of the content.

Strategy 3: Using AI to develop low-stakes tests

AI and testing

Teachers can leverage AI to develop low-stakes tests, which are informal assessments that do not carry significant consequences for students, but are valuable for gauging student learning and providing feedback. Here are some ways teachers can use AI in the development of low-stakes tests:

  1. Automated item generation: AI can automatically generate test items, such as multiple-choice questions, true/false statements, or fill-in-the-blank exercises. Teachers can use AI-powered tools to generate a large number of test items quickly and easily, saving time and effort in creating tests from scratch.
  2. Adaptive testing: AI can analyse data on students’ performance and generate adaptive tests that adjust the difficulty level of the questions based on students’ responses. This can help tailor the test to each student’s ability level, providing a more personalised assessment experience. For example, if a student answers a question correctly, the AI can generate a more challenging question, while if a student answers incorrectly, the AI can generate a less difficult question to help assess their knowledge level accurately.
  3. Automatic scoring: AI can automatically score low-stakes tests, providing instant feedback to students and saving teachers time in grading. AI-powered scoring tools can evaluate students’ responses to various types of questions, such as multiple-choice or short-answer questions, and provide immediate feedback on their performance.
  4. Item analysis: AI can analyse data on test items, such as difficulty level, discrimination index, and item-response patterns, to help teachers identify the quality and effectiveness of the test items. Teachers can use this information to refine their test items and improve the validity and reliability of their assessments.
  5. Content customisation: AI can customise test content based on various factors, such as the curriculum, learning objectives, and student preferences. Teachers can use AI-powered tools to create tests that align with specific learning goals, reflect the content covered in their lessons, and match the students’ learning pace or interests.
  6. Question variety: AI can generate a diverse range of test questions, including different formats, levels of difficulty, and cognitive levels. This can help teachers create tests that assess various aspects of student learning, such as factual knowledge, critical thinking skills, and problem-solving abilities.
  7. Test security: AI can help detect potential cheating or plagiarism in low-stakes tests. AI-powered tools can analyse patterns of similarity in students’ responses, compare them with a large database of known sources, and flag potential instances of plagiarism or cheating.

It’s important for teachers to use AI-generated tests thoughtfully and in conjunction with their professional judgment. Teachers should ensure that the test items are aligned with the curriculum, learning objectives, and the abilities of their students. Additionally, teachers should also consider issues related to data privacy, fairness, and ethical use of AI in assessment practices. It’s crucial to balance the benefits of using AI in test development with the need to maintain a fair, reliable, and valid assessment process for students.

Strategy 4: Assessing what students know, and what they are confused by


Teachers can leverage AI to assess what students know and what they are confused by in a variety of ways:

  1. Natural Language Processing (NLP): AI-powered NLP algorithms can analyse students’ responses to open-ended questions or written assignments to identify their understanding of the subject matter. NLP can help teachers automatically evaluate the content, coherence, and quality of students’ responses, providing insights into their knowledge level and areas of confusion.
  2. Sentiment Analysis: AI can analyze students’ written or verbal responses to assess their emotional state or sentiment towards a particular topic. For example, sentiment analysis can help identify if students express confusion, frustration, or confidence in their responses, providing valuable cues to teachers about their understanding of the material.
  3. Adaptive Assessments: AI can generate adaptive assessments that adjust the difficulty level of questions based on students’ responses. By analysing students’ answers, AI can infer their level of knowledge and pinpoint areas of confusion. The adaptive assessments can then provide targeted feedback or additional questions to help students address their knowledge gaps.
  4. Learning Analytics: AI-powered learning analytics tools can track students’ interactions with digital learning resources, such as online lectures, videos, or simulations. These tools can analyse the data on students’ engagement, progress, and performance, and provide insights to teachers about their strengths, weaknesses, and areas of confusion.
  5. Automated Formative Assessment: AI can automate the process of formative assessment, which involves ongoing, low-stakes assessments to provide feedback and monitor student progress. AI-powered tools can generate quizzes, polls, or other interactive assessments to quickly assess students’ understanding of the material and identify areas of confusion in real-time.
  6. Data Visualisation: AI can analyse and visualise data on students’ performance, engagement, and progress in visually appealing and easy-to-understand formats. Teachers can use AI-generated data visualisations to quickly identify patterns, trends, or areas of confusion among their students, and tailor their instruction accordingly.
  7. Chatbots or Virtual Assistants: AI-powered chatbots or virtual assistants can engage in conversations with students and provide personalized support. Students can ask questions, seek clarification, or express confusion to the chatbot or virtual assistant, which can then provide immediate responses or refer students to relevant resources or activities.

It’s important for teachers to use AI-generated assessments or analytics as part of a comprehensive assessment strategy that includes other forms of assessment, such as teacher-led assessments, peer assessments, or self-assessments. Teachers should interpret the results of AI-generated assessments in conjunction with their professional judgment and consider the limitations and potential biases of AI algorithms. Additionally, teachers should ensure that student data privacy and security are maintained in compliance with relevant laws and regulations.

Strategy 5: Distributed practice with AI


Distributed practice, also known as spaced practice, is a learning technique that involves spacing out learning sessions over time to enhance long-term retention and understanding of information. AI can be used to facilitate distributed practice in various ways:

  1. Personalised Learning Paths: AI-powered adaptive learning platforms can create personalised learning paths for individual students based on their performance, strengths, and weaknesses. These platforms can use algorithms to determine the optimal timing and sequencing of learning activities for each student, ensuring that students revisit and review previously learned concepts at appropriate intervals for effective distributed practice.
  2. Intelligent Tutoring Systems: AI-powered intelligent tutoring systems can provide personalised feedback and guidance to students during their learning sessions. These systems can adapt to individual students’ needs, pace, and performance, and provide targeted practice activities or review sessions to reinforce previously learned material, promoting distributed practice.
  3. Spaced Repetition Algorithms: AI-powered spaced repetition algorithms can optimise the timing and frequency of reviewing material to enhance long-term retention. These algorithms can determine the optimal time intervals for students to review previously learned information, and generate reminders or prompts for students to revisit the material for distributed practice.
  4. Gamification and Adaptive Quizzing: AI-powered gamified learning platforms or adaptive quizzing tools can provide students with opportunities for distributed practice in a fun and engaging way. These tools can generate quizzes, games, or interactive activities that adapt to students’ performance and provide immediate feedback, allowing students to review and reinforce their learning in a distributed manner.
  5. Learning Analytics: AI-powered learning analytics tools can track students’ learning activities and performance over time, providing insights to teachers about the effectiveness of distributed practice. Teachers can use these insights to monitor students’ engagement, progress, and retention of previously learned material, and provide targeted feedback or additional practice opportunities as needed.
  6. Content Recommendation Systems: AI-powered content recommendation systems can suggest relevant learning resources or activities for students to revisit and review in a distributed manner. These systems can analyse students’ learning history, performance, and preferences to recommend appropriate content for review, helping students reinforce their learning through distributed practice.

By leveraging AI in these ways, teachers can effectively implement distributed practice in their teaching, promoting long-term retention and understanding of information among their students. It’s important for teachers to carefully select and use AI-powered tools that align with their instructional goals, and to monitor students’ progress and engagement to ensure the effectiveness of distributed practice.

Teaching with AI help

teaching with AI help

Teachers can incorporate AI into their teaching in several ways to enhance their instructional practices and support student learning:

  1. Personalised Learning: AI-powered adaptive learning platforms can create personalised learning paths for individual students, tailoring instruction to their unique needs, pace, and preferences. These platforms can use AI algorithms to analyse students’ performance data, provide targeted feedback, and recommend appropriate learning resources or activities, allowing teachers to provide individualised instruction to each student.
  2. Content Creation: Artificial Intelligence can help teachers create instructional materials, such as lesson plans, assessments, and learning resources. AI-powered tools can generate content based on curriculum standards, learning objectives, and student characteristics, saving teachers time and effort in creating high-quality instructional materials.
  3. Data Analytics: AI-powered learning analytics tools can analyse students’ learning data, such as performance, engagement, and progress, to provide insights to teachers about student strengths, weaknesses, and areas of improvement. Teachers can use these insights to inform their instructional decisions, tailor their teaching to individual student needs, and provide timely interventions.
  4. Feedback and Assessment: Artificial Intelligence can provide automated feedback on students’ assignments, quizzes, and assessments. AI-powered tools can analyse students’ responses and provide immediate feedback on correctness, coherence, and quality, allowing teachers to provide timely feedback and address misconceptions more efficiently.
  5. Virtual Mentoring: AI-powered virtual mentors or tutoring systems can provide additional support to students outside of the classroom. These systems can engage in interactive conversations with students, answer questions, and provide explanations or clarifications, extending the availability of instructional support beyond regular class time.
  6. Language Learning: AI-powered language learning applications can assist teachers in teaching foreign languages. These applications can provide language exercises, pronunciation practice, and real-time feedback on speaking and writing skills, helping students improve their language proficiency.
  7. Classroom Management: Artificial Intelligence can help teachers manage classroom logistics, such as attendance, scheduling, and grading. AI-powered tools can automate routine administrative tasks, freeing up teachers’ time to focus on instructional activities and student interactions.
  8. Accessibility Support: AI-powered accessibility tools, such as text-to-speech or speech-to-text, can support students with special needs, including those with visual or hearing impairments. These tools can help teachers create inclusive learning environments and provide equitable access to educational materials.

It’s important for teachers to thoughtfully integrate AI into their instructional practices, keeping in mind the unique needs and characteristics of their students, and balancing AI-powered tools with traditional teaching methods. Teachers should also consider the ethical implications of using Artificial Intelligence in education, including data privacy, bias, and fairness, and ensure that student well-being and educational outcomes are prioritised.

Final Thoughts

In conclusion, Artificial Intelligence has the potential to significantly enhance teaching practices, making them easier and more impactful. By leveraging AI-powered tools and technologies, teachers can personalise learning, create content, analyse data, provide feedback, offer virtual mentoring, facilitate language learning, manage classrooms, and support accessibility, among other benefits. It can save teachers time and effort, provide valuable insights, and enhance instructional delivery, ultimately leading to improved student outcomes.

Teachers can use it to create personalised learning experiences that cater to individual students’ needs, pace, and preferences. AI-powered tools can generate content based on curriculum standards, provide timely feedback on student performance, and offer virtual mentoring or tutoring support. Teachers can also analyse data to gain insights into student strengths and weaknesses, informing their instructional decisions and interventions. It can assist in managing classroom logistics, such as attendance and scheduling, freeing up teachers’ time to focus on instructional activities and student interactions.

Furthermore, Artificial Inteligence can support accessibility, making education more inclusive for students with special needs. AI-powered tools, such as text-to-speech or speech-to-text, can provide equitable access to educational materials for students with visual or hearing impairments, promoting inclusivity in the classroom.

It’s important to note that while it has the potential to revolutionise education, it should be used thoughtfully and ethically, keeping student well-being and educational outcomes at the forefront. Teachers should consider the limitations and ethical implications of using AI in education, including data privacy, bias, and fairness, and use AI as a complement to traditional teaching methods, rather than a replacement.

In summary, Artificial Intelligence has the potential to make teaching easier and more impactful by offering personalised learning, content creation, data analytics, feedback and assessment, virtual mentoring, classroom management, accessibility support, and other benefits. By leveraging AI in a thoughtful and responsible manner, teachers can enhance their instructional practices and create engaging and effective learning experiences for their students.

The one thing AI cannot do, is teach like a human, interact with the nuance of a human, or cre like a human. These core aspects of how we relate to one is a major part of teaching and learning. That is something that can’t be artificially replicated.

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