AI & Design Insights

GPT-3 and Me: The Implications for Teaching and Learning (Part VI)


AI is rapidly becoming a common feature in school classrooms and workshops worldwide, with many educators and instructors exploring the potential of this technology to improve teaching and learning outcomes.

 

Key features of conversational AI

One of the key features of conversational AI that sets it apart from other technologies is its ability to generate human-like text and perform a wide range of language-related tasks. If you have used tools like ChatGPT or Noodle Factory’s “Walter” platform that leverages the GPT-3 large language model for some services, you have experienced human-like capabilities from a machine learning algorithm. This makes conversational AI particularly useful for generating personalised lesson plans, providing real-time feedback to students, and generating explanations or summaries of complex concepts.

Challenges of using innovative tech in education

Teaching is not just about content; it is about connection. Our first challenge is to connect and communicate with students in innovative ways. As educators, we need to feel comfortable curating our curricula via new tools and platforms to meet our students where they are. We also need to leverage digital capabilities in service of emerging digital pedagogies in ways that foster collaboration and creativity. To paraphrase the way Nerantzi and Beckingham have characterised the ongoing evolution of digital pedagogy, novel approaches are absolutely essential for successful teaching and learning in the digital age.

Chat-based learning

Chat-based learning is traditionally defined as online teaching and learning engagement that takes place through chat or messaging platforms. In chat-based learning, students and instructors have customarily interacted with each other through written messages rather than in person or through video conferencing. Now this communication can be mediated through a conversational AI algorithm. Chat-based learning can be self-paced, with students working through materials at their own speed or structured with set schedules for discussions and assignments. Chat-based learning can be an effective way for students to learn new material and interact with their instructors and peers. It can be particularly useful for those who prefer to learn independently or who are unable to attend in-person classes.

Conversational AI has become the more common and more valuable tool for deploying chat-based learning since it allows for real-time interaction that is mediated by artificial intelligence (i.e. algorithm(s)) and can be personalised to meet the needs of individual students.

Overall, chat-based learning can be a useful complement to other modes of learning, as it offers flexibility, convenience, and the opportunity for collaboration and asynchronous communication:

  • Asynchronous communication: One of the main benefits of chat-based learning is that it allows for asynchronous communication, meaning that students and instructors do not have to be online simultaneously to communicate. This can be particularly useful for students who have busy schedules or are in different time zones.
  • Flexibility: Chat-based learning allows students to access course materials and communicate with their instructors from anywhere with an internet connection, which can be more convenient than attending in-person classes or logging in to a virtual classroom at set times.
  • Collaboration: Chat-based learning platforms often have features that allow students to work together and collaborate on projects, which can be a valuable way to learn and practice skills in a simulated work environment.
  • Supplementation: Chat-based learning can supplement other forms of learning, such as in-person or online classes, by providing an additional avenue for students to ask questions and get instructor feedback.

To allow for greater scalability, conversational AI is artificial intelligence that can carry out a conversation with humans in a way that is similar to that of a teacher or tutor and can be used to power chat-based learning in several ways:

  • As a virtual tutor or teaching assistant: A conversational AI system can answer students' questions and provide real-time feedback on assignments. This can be particularly useful for students who have questions outside regular class hours or need additional support.
  • As a course facilitator: A conversational AI system can be programmed to guide students through a course, presenting materials and assigning tasks as they progress. This can be useful for self-paced learning, as students can work at their own pace and get support from the AI as needed.
  • As a language tutor: A conversational AI system can help students learn a new language by engaging in conversation and providing feedback on pronunciation and grammar.
  • As a personalised learning coach: A conversational AI system can create a personalised learning plan for each student based on their interests and needs. The AI can provide support and encouragement as the student works through their learning plan.

The "Two Sigma Problem"

Benjamin Bloom outlined what he called the “Two Sigma Problem” nearly 40 years ago. In his 1984 article entitled “The Search for Methods of Group Instruction as Effective as One-to-One Tutoring”, Bloom examined methods through which teachers might create conditions under group instruction that yield learning outcomes typically only experienced under ideal one-on-one tutoring conditions. This difference in results in one-to-one tutoring had been observed to be two standard deviations from the mean of group instruction. The problem, at the time, that Bloom was aiming to solve was a practical one: given the relatively high student-to-teacher ratios in even the best-funded institutes, how is it realistic to give every student the type of one-to-one tutoring and ongoing formative assessments that lead to cognitive mastery of a subject and therefore better performance? The answer to this question was that you could not practically solve the Two Sigma Problem.

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Conclusion

This is where CBL environments like Noodle Factory’s “Walter” platform have the potential to impact BOTH teachers and students positively. With AI-powered CBL, teachers now have tools to work towards solving the Two Sigma Problem because they can scale. Thanks to the power of conversational AI, students have the means to engage in effective one-to-one tutoring at any hour, any place, on the device of their choice.

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We hope you enjoyed our series about GPT-3! If you did, make sure to mention us and share the post on Facebook, LinkedIn, and Twitter.

Read all the posts from this series:


We are also excited to announce that we will be adding GPT-3 capabilities to our award-winning AI teaching platform, Walter. Sign up to get a free trial today. 

 

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