Generative AI Meets Universal Design for Learning

How can educators ensure learning experiences are accessible, inclusive, and engaging for every student? One promising approach is the integration of Generative AI within the Universal Design for Learning (UDL) framework. This article explores how Generative AI tools, such as ChatGPT, Gemini, and Claude, can support educators in creating flexible and inclusive learning environments. UDL guides educators in designing adaptable, student-centered instruction that meets diverse learner needs. By offering multiple ways for learners to engage, represent their understanding, and express their ideas, UDL creates meaningful opportunities for success.

New Possibilities with Generative AI

Generative AI’s ability to produce text, images, and code represents a pivotal shift in education. These tools open new possibilities for personalizing learning, fostering creativity, and improving accessibility for diverse learners (Saborío-Taylor & Rojas-Ramírez, 2024). To maximize its impact, educators should integrate Generative AI with frameworks like UDL to foster inclusive and engaging learning environments.

Generative AI tools can enhance both teaching and learning by managing routine tasks, such as summarizing readings or generating quiz questions, freeing educators to focus on fostering critical thinking and engagement. These tools also support personalized learning by adapting materials for diverse needs. For instance, Gemini can simplify complex text for different reading levels, while Claude can provide structured outlines or comparison tables for students with visual impairments. By offering multimodal content, Generative AI helps create more inclusive learning experiences that align with UDL principles.

What is Universal Design for Learning?

UDL is a framework that supports the creation of flexible learning environments to meet the needs of all learners. It emphasizes engaging, equitable, and accessible learning experiences for all students, regardless of ability. The UDL Guidelines, developed by the Center for Applied Special Technology (CAST), outline a comprehensive approach to UDL implementation. The updated guidelines emphasize equity and inclusion, recognizing that systemic barriers like bias and oppression can impact learning. UDL Guidelines 3.0 highlights the need for learning environments that affirm diverse identities and are free from bias (CAST, 2024).

UDL’s Core Principles

The three core principles of UDL remain central to creating inclusive learning environments:

Multiple Means of Engagement. Motivating and supporting students with diverse interests and learning needs. This includes strategies for recruiting interest (connecting to student passions), sustaining effort through collaboration and feedback, and fostering self-regulation skills like goal setting and reflection.

Multiple Means of Representation. Presenting information in different formats to support diverse sensory needs and learning preferences. This includes using multiple formats (text, audio, video), adjusting the pace of information, highlighting key concepts, and providing glossaries and visual aids.

Multiple Means of Action and Expression. Providing varied ways for students to demonstrate their learning. This includes options for physical interaction (e.g., manipulating objects), tools for expression (e.g., writing, speaking, creating visuals), and support for executive functions, such as planning and organizing learning tasks.

Equity and Inclusion in UDL Guidelines 3.0

The updated UDL principles now emphasize equity and inclusion more explicitly. For example, Multiple Means of Representation now includes authentic representation of diverse identities, challenging biases in content, and valuing diverse ways of knowing and interpreting information. Implementing UDL Guidelines 3.0 allows educators to design more inclusive and effective learning experiences for all students.

How Generative AI Supports UDL Principles

Generative AI platforms like ChatGPT, Gemini, and Claude can play a significant role in supporting the implementation of UDL principles.

Multiple Means of Engagement

Generative AI can enhance learning through interactive and engaging experiences. For example, ChatGPT and Claude can support the creation of games, simulations, and immersive activities that encourage exploration and persistence. AI-powered tools can offer personalized feedback and encouragement, helping students persist in their learning and recognize their progress.

Multiple Means of Representation

Generative AI can create personalized learning materials, such as text=based summaries, guiding questions, and visual comparison tables, to support diverse sensory needs and learning preferences. For example, AI can simplify complex text, generate structured outlines to clarify key points, and provide creative prompts that encourage firsthand exploration and critical thinking.

Multiple Means of Action and Expression

Generative AI can empower students to express their learning creatively. For example, students can compose stories, poems, and essays, experiment with different writing styles, and refine their writing. They can also use AI to create personalized art, music, and multimedia projects, fostering innovative expression. Text-to-speech tools can help students with physical disabilities express ideas verbally and create presentations. Writing assistants can support students with learning disabilities by helping them organize and refine their writing.

By integrating Generative AI within a UDL framework, educators can design more equitable, inclusive, and engaging learning experiences for all students.

Examples of UDL and Generative AI in Action

Now that we explored the alignment between Generative AI and UDL principles, let us look at real-world examples of how these tools can enhance learning in action. Generative AI platforms offer educators flexible ways to engage students, represent content in multiple formats, and support different methods of expression. Below are practical examples demonstrating how these platforms can support each UDL principle in practice (OpenAI, 2024).

Multiple Means of Engagement

Scenario: A sociology professor wants to increase student engagement during a unit on social justice movements.

• Application: The professor uses Claude to create an interactive case study where students explore the impacts of different social policies on various communities. ChatGPT generates role-play prompts where students take on different stakeholder perspectives, such as activists, policymakers, and historians.
• Benefit: By involving students in active, real-world scenarios, the professor taps into student interests and creates opportunities for meaningful exploration and discussion.

Multiple Means of Representation

Scenario: A history professor teaching a course on global revolutions wants to ensure students with different learning preferences can access complex readings.

• Application: The professor uses Gemini to generate concise, accessible summaries of academic journal articles and Claude to produce comparison tables that highlight key differences between historical events. ChatGPT provides guiding questions that prompt students to make connections between the readings and broader themes.
• Benefit: By presenting the same information through summaries, tables, and guiding questions, the professor makes the material more comprehensible for all learners.

Multiple Means of Action and Expression

Scenario: In an English class, students demonstrate their understanding of a novel by creating final projects to reflect their comprehension.

• Application: One student uses ChatGPT to help outline their literary analysis essay, while another uses Claude to draft dialogue for a creative retelling of a scene. A third student uses Gemini to generate questions for a mock interview between themselves and the novel’s protagonist, which they turn into a written Q&A.
• Benefit: These options allow students to choose the format that best aligns with their strengths, fostering autonomy and creativity.

Ethical Considerations in Using Generative AI in Education

It is important to address the ethical challenges associated with using Generative AI in education (Bura & Myakala, 2024).

Data Privacy and Security

Generative AI tools often require collecting and analyzing student data, raising privacy and security concerns. Student data must be collected, stored, and used responsibly, with safeguards to protect privacy.

Bias and Fairness in AI Algorithms

Large datasets train AI algorithms, which may contain biases that the systems can perpetuate or amplify. Ensuring that AI systems in education are fair, unbiased, and non-discriminatory is essential.

The Potential for Misuse of AI Tools by Students

Students may misuse AI tools to plagiarize or generate misleading information. This includes providing clear guidelines for ethical AI use, strategies for detecting AI-generated content, and lessons on the ethical implications of AI.

Lack of Teacher Training and Support

Teachers need the skills to use AI tools effectively, understand their ethical implications, and address integration challenges. Ongoing professional development is essential to help teachers leverage AI to enhance student learning.

Ensuring Equitable Access to AI Technology for All Students

Not all students have equitable access to AI technology and high-speed internet. Addressing the digital divide ensures all students have access to AI technology and support to use it effectively.

Maintaining Human Connection and Authentic Learning Experiences

AI use in education must not detract from human connection and authentic learning experiences. AI can enhance learning but should not replace the human connections between teachers and students.

Conclusion: The Future of UDL and Generative AI

By applying UDL principles and addressing ethical concerns, educators can integrate Generative AI tools like ChatGPT, Gemini, and Claude to create personalized, inclusive, and engaging learning experiences. This requires ongoing research, collaboration across disciplines, and professional development to ensure these technologies enhance, rather than replace, human connection in education.

References:

Bura, C., & Myakala, P.K. (2024). Advancing transformative education: Generative AI as a catalyst for Equity and innovation.

CAST (2024). Universal Design for Learning Guidelines version 3.0. https://udlguidelines.cast.org

OpenAI. (2024). ChatGPT (December 31 version) [Large language model]. https://chat.openai.com

Saborío-Taylor, S., & Rojas-Ramírez, F. (2024). Universal design for learning and artificial intelligence in the digital era: Fostering inclusion and autonomous learning. International Journal of Professional Development, Learners and Learning, 6(2). https://doi.org/10.30935/ijpdll/14694

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Washington, G. (2024, December 31). Generative AI Meets Universal Design for Learning [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Image by Gerd Altmann from Pixabay

 

Generative AI Meets Pedagogy

Generative Artificial Intelligence (AI) emerged as a powerful tool that can transform teaching and learning. As educators, we are constantly seeking innovative ways to engage our students and enhance their learning experiences. This blog series, Generative AI Meets Pedagogy, aims to explore the intersection of Generative AI and effective teaching strategies, providing practical applications for educators.

Why Focus on Pedagogy?

The key to successful integration lies in aligning Generative AI with sound pedagogical practices. Pedagogy is the art and science of teaching, and it encompasses various approaches that can significantly impact student engagement and success. In this blog series, we will delve into three key pedagogical frameworks.

• Universal Design for Learning (UDL) emphasizes accessibility and inclusivity, ensuring that all students have equal opportunities to learn. UDL principles guide educators in creating flexible, inclusive learning environments that accommodate diverse learners.
• Active learning encourages student engagement and participation in the learning process. It involves activities that require students to think critically, problem-solve, and apply their knowledge.
• Experiential Learning focuses on learning through experience and reflection. It often involves hands-on activities, simulations, real-world scenarios, and immersive learning experiences.

Educators often use these pedagogical frameworks to create effective and engaging learning experiences.

The Role of Generative AI

Generative AI has the potential to enhance these pedagogical approaches in significant ways. Educators can create personalized learning experiences, generate tailored content, facilitate collaboration, and engage students in real-world problem-solving. The integration of Generative AI not only supports diverse learners but also empowers educators to innovate their teaching practices.

Join Us on This Journey

In the upcoming articles, we will explore the intersection of Generative AI and one of the pedagogical frameworks mentioned above. Each article will highlight the potential of Generative AI to enhance teaching and learning experiences and include actionable strategies for educators to implement in their classrooms.

We invite you to follow along as we explore how Generative AI can meet pedagogy in transformative ways. Whether you are a seasoned educator or just starting your teaching journey, this series aims to provide valuable insights that can enhance your practice and enrich your students’ learning experiences.

Until we meet again in December, check out the blog article, Teaching Students Responsible Use of Generative AI. _________________________________________________________________________________________

Scholarly Journal Articles

Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S.K. (2024). Generative AI in
education: Pedagogical, theoretical, and methodological perspectives. International Journal
of Technology in Education (IJTE), 7(3), 373-385. https://doi.org/10.46328/ijte.845

Nikolopoulou, K. (2024). Generative Artificial Intelligence in Higher Education: Exploring Ways of Harnessing Pedagogical Practices with the Assistance of ChatGPT. International Journal of Changes in Education, 1(2), 103–111. https://doi.org/10.47852/bonviewIJCE42022489
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Washington, G. (2024, August 31). Generative AI Meets Pedagogy [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Image generated by Microsoft Designer.

Teaching Students Responsible Use of Generative AI

The educational landscape is constantly evolving, and the emergence of generative artificial intelligence (AI) presents both exciting possibilities and significant challenges.  Large language models (LLMs) such as ChatGPT, Gemini, and Claude 3 can produce human-quality text, code, and even creative content. This can enhance learning experiences by personalizing instruction, fostering creativity, and providing immediate feedback. However, alongside the excitement, addressing the ethical considerations and potential pitfalls of this powerful AI technology is vital.

Simply put, generative AI can be a double-edged sword. While it can be a valuable tool to support learning, it can also lead to plagiarism, the spread of misinformation, and an over-reliance on AI-generated solutions. To ensure generative AI becomes a tool for empowerment rather than a crutch, promoting responsible use and fostering critical thinking skills are fundamental. This article explores strategies for navigating the world of generative AI in the classroom, equipping students to use this technology effectively while developing the critical thinking skills necessary to become informed consumers of information in the digital age.

Here are some practical strategies you can implement to guide your students toward responsible AI use:

Transparency and Open Discussion:

• Start with the Basics: Begin by introducing students to the concept of generative AI, its capabilities, and limitations. Discuss how these models work and the types of content they can generate.
• Open Dialogue: Facilitate discussions about the ethical implications of AI-generated content. Explore issues like plagiarism, bias, and the spread of misinformation.
• Expectations and Guidelines: Clearly outline your expectations regarding generative AI use in your classroom. Specify when and how AI tools can be used for assignments and projects.

Fostering Critical Thinking and Evaluation:

• Fact-Checking and Verification: Incorporate activities that require students to evaluate the accuracy and credibility of AI-generated content. Teach them to use reliable sources to fact-check information and identify potential biases.
• Source Attribution and Citation: Emphasize the importance of citing sources, even when using AI-generated content as a starting point. Discuss plagiarism policies and responsible use of intellectual property.
• Critical Analysis Skills: Develop activities that encourage students to analyze AI-generated content for accuracy, logic, and coherence.

Leveraging AI for Enhanced Learning:

• Brainstorming and Idea Generation: Encourage students to use generative AI tools for brainstorming new ideas, generating creative prompts, or outlining arguments for essays.
• Personalized Learning: Explore AI-powered platforms that offer individualized learning paths based on student strengths and weaknesses.
• Feedback and Revision: Utilize generative AI tools that provide automated feedback on grammar, style, and clarity. This can be a valuable aid in the revision process, but should not replace human evaluation.

Developing Skills Beyond AI:

• Prioritize Critical Thinking: While generative AI can be a powerful tool, emphasize the importance of independent thinking, research skills, and problem-solving abilities.
• Communication and Collaboration: Focus on developing strong communication and collaboration skills that machines cannot replicate.
• Human Creativity: Encourage students to explore creative endeavors that leverage their imagination and go beyond what AI can currently generate.

By implementing these strategies, you can foster a culture of responsible generative AI use in your classroom. Students will develop critical thinking skills, become informed consumers of information, and learn to leverage AI as a powerful tool for enhancing learning, not replacing it. Remember, generative AI is still under development, and ongoing discussions about its implications are crucial. Embrace this new technology as an opportunity to equip students with the skills they need to thrive in an AI-powered future.

Resources:

Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4475995

Walczak, K., & Cellary, W. (2023). Challenges for higher education in the era of widespread access to generative AI. Economics and Business Review, 9(2). https://doi.org/10.18559/ebr.2023.2.743

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Washington, G. (2024, April 30). Teaching Students Responsible Use of Generative AI [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Image Generated with AI

Navigating the Generative AI Landscape

The emergence of generative artificial intelligence (AI) presents exciting possibilities for teaching and learning. These large language models generate text, translate languages, write different kinds of creative content, and even answer users' questions. But with several options, deciding which generative AI to explore is daunting. In this article, we briefly explore ChatGPT, Bard, and Claude to help you navigate the generative AI landscape.

ChatGPT (Open AI) excels at generating creative text formats, like poems, code, scripts, musical pieces, and even emails. As a creative text generator, its strength lies in its conversational fluency, engaging users in open-ended dialogues, and producing creative text formats. Its ability to adapt to different writing styles and tones makes ChatGPT a valuable tool for brainstorming ideas, exploring different perspectives, and practicing writing skills. However, ChatGPT's focus on creativity can sometimes come at the expense of factual accuracy. Its outputs may lack citations or references, and its understanding of complex topics is sometimes limited. However, concerns regarding potential bias and misinformation in ChatGPT necessitate careful monitoring and face-checking of its responses (Sætra, 2023).

On the other hand, Bard (Google AI) prioritizes factual accuracy and information retrieval. Bard leverages Google’s vast knowledge base to provide informative and comprehensive answers. Bard is great at summarizing articles and papers or generating reports. It provides citations and references to support its claims, making it reliable for research and academic writing. However, Bard's focus on factual accuracy sometimes makes its responses seem less creative or engaging than ChatGPT. Bard’s ability to generate creative text formats is still under development (Tan, Chen, & Chua, 2023).

Claude strikes a balance between ChatGPT’s creativity and Bard’s factual accuracy but prioritizes ethical interactions and responsible AI development (Anthropic, 2023). Claude excels at identifying and mitigating potential biases in its responses, making it suitable for tasks requiring sensitive information or ethical considerations and promoting inclusive learning environments. However, Claude is still under development and may not be as refined as ChatGPT or Bard in some areas. (Gabriel, 2020).

In summary, ChatGPT, Bard, and Claude are key players in the generative AI landscape. They possess unique features and potential applications. For generating writing prompts, creating outlines, crafting distinct character voices, or assisting with brainstorming ideas, ChatGPT acts as a writing partner. Bard and Claude are options for fostering historical understanding and encouraging critical thinking. Bard’s online access facilitates accurate information on historical events and figures. Claude, with its emphasis on safety and minimizing bias, provides fair and objective debate opportunities. Bard and ChatGPT hold potential as personalized learning assistants with Bard's responses being more factual while ChatGPT's engaging conversational style makes learning more interactive. For assisting with coding practice, both Bard and Claude demonstrate promise. Bard’s access to technical information is invaluable in explaining complex concepts or identifying errors in student code. Claude’s commitment to safety fosters a secure learning environment. As these models continue to learn and improve their potential to assist users will continue to grow.

References

Gabriel, I. (2020). Artificial intelligence, values, and alignment. Minds & Machines 30(3), 411–437. https://doi.org/10.1007/s11023-020-09539-2

Sætra, H. S. (2023). Generative AI: Here to stay, but for good? Technology in Society, 75, 102372. https://doi.org/10.1016/j.techsoc.2023.102372

Tan, S. C., Chen, W., & Chua, B. L. (2023). Leveraging generative artificial intelligence based on large language models for collaborative learning. Learning: Research & Practice, 9(2), 125–134. https://doi.org/10.1080/23735082.2023.2258895

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Washington, G. (2024, January 31). Navigating the Generative AI Landscape [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Photo by Mohamed Nohassi on Unsplash

Claude 2: An Alternative to ChatGPT

 

We have witnessed an explosion in the development of large language models (LLMs). These AI-powered systems, trained on massive datasets of text and code, can now generate human-quality text, translate languages, write various kinds of content, and even answer your questions in an informative way. OpenAI's ChatGPT opened doors in conversational artificial intelligence (AI), but Anthropic's Claude 2 steps onto the stage with a transformative vision. Claude 2 offers distinct features and capabilities that make it a compelling alternative, particularly for educational settings.

What is Claude 2?

Claude 2 is an updated version of Claude, an AI assistant created by startup Anthropic, an AI safety and research company. It employs natural language processing to answer questions, have discussions, and generally assist users through written conversations (Anthropic, 2023). Relative to the original Claude model, Claude 2 demonstrates enhanced conversational abilities, more comprehensive knowledge of a diversity of topics, and improved common sense comprehension for contextual responses.

A distinctive feature of the Claude 2 model involves its adherence to Constitutional AI principles, meaning its design intentionally constrains certain possibilities in favor of increased safety (Gabriel, 2020). Claude 2 is trained to be helpful, harmless, and honest while focusing on avoiding toxic, biased, or misleading responses. Its training incorporates reinforcement learning from human feedback. Claude 2 prioritizes truthfulness, cites its knowledge sources, and acknowledges the boundaries of its understanding. It is designed to be safer than competing models, such as ChatGPT and Bard (Anthropic, 2023).

In addition, Claude 2 has an expansive 100,000-token context window which allows it to analyze prompts deeply and respond with precise, well-referenced answers. Claude 2 thrives in extended dialogues and complex tasks with consistently relevant and informed responses (Anthropic, 2023). Its unique features unlock opportunities for personalized learning and inquiry-based exploration within educational settings.

Benefits of Claude 2 for Education

Claude 2 can adapt explanations and examples to individual learning styles making it a powerful tool for personalized, engaging, and empowering learning experiences. Its adaptive nature allows it to adjust explanations and examples, therefore, fostering personalized learning experiences. It can generate learning materials, help find relevant sources, and even identify factual inconsistencies, turning students into active participants in their learning journey.

Also, Claude 2 excels in open-ended dialogue and inquiry-based learning. Its conversational ability promotes active participation, critical thinking, and deep understanding of complex topics. It assists in content creation, research, and problem-solving, equipping students with the tools to become independent learners and explore their interests.

How to try Claude 2

You can access Claude 2 through a new public-facing website, Claude.ai, which is currently in open beta. From there, you talk to Claude by starting a conversation or using one of Claude's default prompts. Anthropic recently introduced Claude Pro, a paid plan for their Claude.ai. You can also access Claude through Quora's Poe, which allows you to interact directly with the Claude 2 100K model (among other AI models).

Conclusion

Claude 2's advanced capabilities present a promising alternative to ChatGPT. As a safety-focused conversational language model, Claude 2’s use in educational settings provides a valuable tool for fostering deeper learning, critical thinking, and personalized learning experiences. Its potential for transforming educational practices should be further explored and evaluated through rigorous research.

References

Anthropic. (2023). Claude 2: AI assistant focused on safety. https://www.anthropic.com

Gabriel, I. (2020). Artificial intelligence, values, and alignment. Minds & Machines 30(3), 411–437. https://doi.org/10.1007/s11023-020-09539-2

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Washington, G. (2023, December 31). Claude 2: An Alternative to ChatGPT [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Bard – Google’s Conversational AI

The release of ChatGPT free version GPT 3.5 by OpenAI sparked the appearance of other generative large language models (LLMs), such as Google Bard. LLMs are a type of artificial intelligence (AI) trained on a massive dataset of text and code. They learn the statistical relationship between words and phrases to generate responses that are like human-written text. Like ChatGPT, Bard responds to prompts or questions. Bard generates text, translates languages, writes different kinds of creative content, and answers questions in an informative way. As an AI chatbot, Bard is meant to be a rival to the popular ChatGPT. This article introduces Bard, discusses how it can be used in education, and compares it to ChatGPT.

What is Bard?

In February 2023, Google revealed its conversational AI called Bard in response to ChatGPT. Bard was based on Google's Language Model for Dialogue Applications (LaMDA). It uses machine learning and natural processing techniques to generate human-like text responses to various prompts. Bard draws on information from the web to provide direct responses to prompts and questions (Pichai, 2023). When you ask Bard a question or give it a prompt, the model uses its knowledge of the world to generate an answer. The model also uses its knowledge of language to make sure that the answer is grammatically correct and easy to understand. It represents a significant advancement in AI technology creating entirely new ways to engage with information.

How to Use Bard?

Bard was originally available to a limited number of users. It is still labeled as an “experiment,” but it is now available to everyone. To access Bard, go to bard.google.com in a browser and sign in with a Google account. Enter a prompt or question, either by typing or selecting the microphone and talking. Press enter or return and wait for Bard’s response. Once Bard responds with an answer, you receive a set of optional actions: View other drafts to access drafts of the same answer, Regenerate drafts to have Bard attempt another answer, Edit the prompt by clicking the pencil icon, Google It to switch to a standard keyword search query derived from your prompt, Share & Export the response, Copy the content to paste into another application, Report a legal issue to signal a significant content concern, provide feedback with a thumbs up (Good Response) or down (Bad Response) or enter another prompt to continue the chat.

Here are some ways to use Bard (Bard, 2023).

• Answer questions: Bard can be used to answer questions about any topic. It can provide summaries of factual topics or create stories.
• Generate text: Bard can be used to generate text, such as poems, code, scripts, musical pieces, emails, letters, etc.
• Translate languages: Bard can be used to translate languages.
• Write different kinds of creative content: Bard can be used to write different kinds of creative content, such as poems, stories, or scripts.
• Collaborate with others: Bard can be used to collaborate with others on projects.
• Access and process information from the real world: Bard can access and process information from the real world through Google Search and keep its response consistent with search results.

In education, AI can deepen our understanding of information and turn it into useful knowledge.

Bard in Education

Bard has the potential to have a significant impact on education. It could be used to personalize learning, promote active learning, facilitate collaborative learning, and provide access to information. Personalized learning involves identifying the student's strengths and weaknesses, and then creating a plan that focuses on the areas where the student needs the most help. Active learning in the classroom promotes engagement by posing questions to students, encouraging them to think critically and creatively, and helping them to learn by doing. Collaborative learning helps students to work together on projects, share ideas, and learn from each other. Bard provides students with access to a vast amount of information. This could help them to find information on any topic and to learn about different perspectives. Bard has the potential to motivate students to learn.

Bard vs ChatGPT

Both Bard and ChatGPT are large language models trained on massive datasets of text and code. They are both capable of generating human-quality text, translating languages, writing different kinds of creative content, and answering questions in an informative way. Both are still under development, which means they are constantly being improved and are likely to become even more powerful and versatile in the future. Both have the potential to be used on a wide range of tasks. However, there are some differences between the chatbots.

One of the biggest differences between Bard and ChatGPT is the data they are trained on. Bard is trained on a massive dataset of text and code, including scientific papers, mathematical expressions, and source code. This gives Bard a strong foundation in technical topics and allows it to generate more accurate and informative responses. ChatGPT, on the other hand, is trained on a dataset of text from the internet. This gives ChatGPT a wider range of knowledge, but it also means that it is more likely to generate inaccurate or misleading information (Bard, 2023).

Another difference between Bard and ChatGPT is their access to information. Bard has access to the internet, which means that it can always get the latest information. ChatGPT, on the other hand, is limited to the information that was included in its training dataset. This difference in access to information can be seen in the way that Bard and ChatGPT answer questions. When asked a question, Bard will often go out and research the answer on the internet. ChatGPT, on the other hand, will typically rely on the information that it was trained on (Bard, 2023).

Bal Ram and Pratima Verma (2023) found that ChatGPT was better at generating creative text formats, such as poems, code, scripts, musical pieces, emails, and letters. Google AI Bard was better at answering questions in a comprehensive and informative way, even if the questions were open-ended, challenging, or strange.

Summary

Like ChatGPT, Bard is a conversational AI chatbot that can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Give Bard a prompt or ask it a question and the chatbot can answer it in a surprisingly natural and conversational language. Bard can access the internet to leverage Google search for its responses while ChatGPT can only provide historical content gathered through 2021. It is important to note that Google Bard does not use ChatGPT. Bard uses its own proprietary AI technology.

References

Bal Ram, & Pratima Verma. (2023). Artificial Intelligence AI-based chatbot study of CHATGPT, Google AI Bard, and Baidu AI. World Journal of Advanced Engineering Technology and Sciences, 8(1), 258–261. https://doi.org/10.30574/wjaets.2023.8.1.0045

Bard. (2023, August 15). Differences between Bard and ChatGPT. Retrieved from https://bard.google/

Bard. (2023, August 15). How to use Google Bard. Retrieved from https://bard.google/

Pichai, S. (2023, February 6). An important next step on our AI journey. Google. https://blog.google/intl/en-africa/products/explore-get-answers/an-important-next-step-on-our-ai-journey/

Related Scholarly Articles:

Laato, S., Morschheuser, B., Hamari, J., & Björne, J. (2023). AI-assisted learning with ChatGPT and large language models: Implications for higher education. ResearchGate<. https://www.researchgate.net/publication/370535123_AI-assisted_Learning_with_ChatGPT_and_Large_Language_Models_Implications_for_Higher_Education

Meyer, J. G., Urbanowicz, R. J., Martin, P. C., O’Connor, K., Li, R., Peng, P.-C., Bright, T. J., Tatonetti, N., Won, K. J., Gonzalez-Hernandez, G., & Moore, J. H. (2023). ChatGPT and large language models in academia: Opportunities and challenges. BioData Mining, 16(1). https://doi.org/10.1186/s13040-023-00339-9

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Washington, G. (2023, August 31). Bard – Google’s Conversational AI [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

Implementing ChatGPT in Online Teaching and Learning

Ready or not, here comes ChatGPT! ChatGPT (Chat Generative Pre-Trained Transformer) is a generative artificial intelligence (AI) chatbot that uses machine learning models to produce human-like text. It can complete sentences, answer questions, generate text, and even hold a conversation with a human user. ChatGPT was trained on a massive amount of text data from the internet and other sources, allowing it to understand and generate responses to a wide variety of topics. As an instructor, you may be curious about how ChatGPT can be utilized in online courses to enhance teaching and learning. Here are some practical tips for implementing ChatGPT:

Virtual Class Discussions: Use ChatGPT as a discussion partner in virtual classes. Students can interact with ChatGPT and engage in meaningful conversations on different topics related to the curriculum. ChatGPT can generate responses, ask questions, and provide additional information to stimulate discussions and encourage critical thinking.

Virtual Office Hours: Use ChatGPT as a virtual assistant during office hours. Students can ask questions, seek clarification, or request assistance from ChatGPT, just like they would with an instructor. ChatGPT can provide quick responses and support students in real time, facilitating a personalized learning experience.

Automated Feedback: Use ChatGPT to provide automated feedback on student assignments or assessments. ChatGPT can generate feedback on written assignments, provide explanations for incorrect answers, and offer suggestions for improvement. This can save time for the instructor while providing timely feedback to students.

Virtual Tutoring: Use ChatGPT as a virtual tutor to provide additional support to students who need extra help. ChatGPT can provide explanations, examples, and practice exercises on specific topics or concepts, catering to the individual needs of students and supplementing the instruction provided by the instructor.

Resource Generator: Use ChatGPT to generate learning resources such as study guides, summaries, or quiz questions. ChatGPT can quickly generate content based on the curriculum or specific learning outcomes, providing students with additional study materials and practice opportunities.

Practice: Use ChatGPT for language practice in online language courses. Students can engage in conversational exchanges with ChatGPT to practice their speaking and writing skills in a supportive and interactive environment. ChatGPT can provide feedback and corrections to help students improve their language proficiency.

Digital Research Assistant: Use ChatGPT as a digital research assistant to help students find relevant information for their projects or assignments. ChatGPT can generate responses to questions, provide summaries of articles or papers, and offer suggestions for credible sources, helping students conduct efficient and effective research.

It is important to provide clear instructions and guidelines to students on how to effectively use ChatGPT as a learning tool, emphasizing responsible and ethical use. Regular monitoring and review of ChatGPT-generated content should be conducted to ensure accuracy and appropriateness. Additionally, instructors should be open to feedback from students and continuously evaluate the effectiveness of ChatGPT in enhancing the online teaching and learning experience.

In conclusion, ChatGPT can be a valuable tool in online teaching and learning, providing opportunities for interactive discussions, personalized feedback, virtual tutoring, resource generation, language practice, and research assistance. By incorporating ChatGPT thoughtfully into online educational settings, instructors can create engaging and innovative learning experiences that enhance student learning outcomes.

Please share your plans, ideas, questions, or concerns about using ChatGPT or other AI in your teaching.

References:

OpenAI. (2022, September 2). About OpenAI. OpenAI. Retrieved January 24, 2023, from https://openai.com/about/.

OpenAI. (2023, April 19). ChatGPT [Computer software]. Retrieved from https://www.openai.com/chatgpt/.

Cooper, G. (2023). Examining science education in CHATGPT: An exploratory study of Generative Artificial Intelligence. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-023-10039-y

Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1–12. https://doi.org/10.1080/14703297.2023.2190148

Mollick, E. R., & Mollick, L. (2022). New modes of learning enabled by AI Chatbots: Three methods and assignments. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4300783

O’Connor, S., & ChatGPT. (2023). Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice, 66, N.PAG. https://doi.org/10.1016/j.nepr.2022.103537

Pavlik, J. V. (2023). Collaborating with ChatGPT: Considering the implications of Generative Artificial Intelligence for Journalism and Media Education. Journalism &amp; Mass Communication Educator, 78(1), 84–93. https://doi.org/10.1177/10776958221149577

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Washington, G. (2023, April 20). Implementing ChatGPT in Online Teaching and Learning [Blog post]. Retrieved from https://pedagogybeforetechnology.blogspot.com/

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