AI Tutor

A number of people have suggested that artificial intelligence (AI) could be very useful as a tutor for students.

There appear to be some clear benefits to having an AI act as a tutor:

• It has the potential to “know” a very broad set of topics and subject matter that could be taught. An AI system could be loaded with millions of documents, textbooks, and other teaching materials covering nearly any academic subject.
• An AI tutor would be infinitely patient. Unlike human tutors who can grow frustrated with students, an AI system would be able to work with students for as long as needed without losing patience.
• AI tutors can adapt to the student’s grade level, vocabulary, and language skills. The system could analyze the student’s knowledge and abilities and adjust its teaching style and complexity of explanations accordingly.

However, there are also some significant limitations and issues with today’s AI capabilities when it comes to tutoring:

• The training may not be sufficient for the material being taught. While AIs can ingest large volumes of content, the training algorithms may not be able to extract the key ideas and concepts required for effective tutoring.
• Current large language models (LLMs) lack an underlying cognitive model to support pedagogical learning. LLMs like GPT-3 don’t have an understanding of how human learning works.
• Performance issues like hallucination can undermine the reliability of an AI tutor. If it generates false information, students could be misled.

However, even with these limitations, today’s AI could still be beneficial as a tutoring aid:

• It could help explain concepts and provide supplemental materials to students.
• It could answer straightforward factual questions.
• It could generate practice test questions and grade responses.

To make AI a more effective tutor in the future will require:

• Providing the AI access to standard textbooks, workbooks, and other teaching materials.
• Developing new techniques to improve training on pedagogical tasks.
• Building cognitive models to support student learning patterns.
• Improving reliability to reduce issues like hallucination.

If these challenges can be met, AI tutoring could become a hugely valuable educational resource. It has the potential to provide high-quality, personalized instruction to every student across a vast range of subjects and needs.

Student learning patterns

Influencing student learning is:

• Prior knowledge - Students come into any learning experience with existing knowledge, misconceptions, skills, and beliefs that impact how they interpret new information. Effective teaching needs to surface and work with this prior knowledge.
• Motivation - Students who are intrinsically motivated to learn a topic are more engaged and persistent. An AI tutor needs to cultivate internal motivation through strategies like relevance to personal interests, autonomy, goal-setting, and choice.
• Cognitive load - Students have a finite working memory capacity. An AI tutor needs to manage cognitive load by breaking content into manageable chunks, removing distractions, and providing worked examples.
• Active learning - Students benefit from actively reconciling new ideas with prior knowledge. An AI tutor can promote active learning by having students explain concepts, answer questions, complete assignments, and get hands-on with materials.
• Metacognition - Successful students reflect on their own thinking and learning processes. An AI tutor can model and encourage metacognitive activities like self-explanation, self-assessment, and strategy adjustment.
• Developmental stages - Younger students think concretely and need manipulatives. Older students can think more abstractly and engage in critical analysis. An AI tutor needs scaffolding strategies tailored to a student’s developmental stage.
• Individual differences - Students have diverse backgrounds, strengths, interests, and needs. AI tutors need to personalize teaching around individual differences in culture, language, ability, learning styles, and more.
• Social interaction - Learning is often enhanced through dialogue and collaboration with others. An AI tutor can facilitate peer interactions and discussions to improve engagement and understanding.