Generative AI in Higher Education: Personalized Learning for All

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An artist’s illustration of artificial intelligence (AI). This image represents the concept of Artificial General Intelligence (AGI) and the potential of generative AI. It was created by D...
Credit: pexels.com, An artist’s illustration of artificial intelligence (AI). This image represents the concept of Artificial General Intelligence (AGI) and the potential of generative AI. It was created by D...

Generative AI in higher education has the potential to revolutionize the way we learn. By leveraging AI's ability to generate personalized content, students can receive tailored learning experiences that cater to their unique needs and abilities.

According to research, students who receive personalized learning experiences show significant improvements in academic performance and engagement. This is because generative AI can adapt to individual learning styles, pace, and interests.

One key benefit of generative AI in higher education is that it can help bridge the gap between students from diverse backgrounds. By providing accessible and inclusive learning materials, AI can help level the playing field and ensure that all students have an equal opportunity to succeed.

Generative AI in Higher Education

Generative AI in higher education is a rapidly evolving field that's generating significant concerns about academic integrity, ethics, access, and bias.

Generative AI technologies are opening up a world of possibilities, but it's essential to consider their impact on your classroom.

Credit: youtube.com, Gen AI in Higher Ed: Present and Future

To get started, reflect on your feelings about generative AI - are you concerned, excited, or a little of both? What additional information do you need to make informed decisions about incorporating it into your courses?

Try out generative AI platforms like ChatGPT, Gemini, or DALL-E 2 to experiment with their capabilities. Ask the tool to complete an assignment you'd give your students, and see how it responds.

There are four general steps to consider when evaluating generative AI in higher education:

  • Reflect on your feelings and concerns
  • Try out generative AI platforms
  • Predict and inquire about student use and potential issues
  • Learn more and set parameters for student use

By following these steps, you can make informed decisions about incorporating generative AI into your courses, and even use it to assist your teaching.

Impact on Higher Education

Generative AI in higher education is a rapidly evolving field with both exciting possibilities and significant concerns. Generative AI can open up a world of possibilities, but it also raises concerns about academic integrity, ethics, access, and bias.

Nobody knows the true impact that generative AI will have on higher education, but it's clear that institutions need to take a proactive approach to addressing these concerns. EDUCAUSE recommends that institutions develop generative AI policies that address issues of ethics, equity, and accuracy.

Credit: youtube.com, ChatGPT and generative AI in higher education

Some institutions are already taking steps to incorporate generative AI into their courses. For example, the University of California, Los Angeles suggests asking students to use generative AI tools and then fact-check the responses to ensure accuracy. This approach can help students develop critical thinking skills and learn to evaluate information from multiple sources.

Generative AI can also enhance students' learning experiences by providing a range of perspectives and viewpoints. Students can use generative AI tools to research practical methodologies, explore instructional texts in multiple formats, and engage in written conversations in their target language.

Here are some ways that generative AI can support students' learning across a range of subjects:

  • Generating alternative explanations and examples to support students' understanding of a topic
  • Providing opportunities for students to explore instructional texts in multiple formats
  • Supporting students in understanding instructional texts, including how-to guides
  • Helping students describe existing code or identify computer code errors

Three Areas of Focus

Governance is a crucial aspect of generative AI policies, as they can sometimes produce biased outputs that don't account for social and cultural differences in the user population.

Generative AI policies should address issues of ethics, equity, and accuracy, as these are key concerns in higher education. Clemson University warns against allowing people to enter private data into public generative AI models, which can use data from chats to train the models and potentially violate federal and state privacy and data protection laws.

Credit: youtube.com, Higher Education Focus in 2023 - Digital Strategy, Interoperability and Lifelong Learning

To promote pedagogy, colleges and universities should encourage professors to establish clear and specific generative AI guidance for their courses, outlining what is allowed and forbidden in the course syllabus.

The University of California, Los Angeles suggests asking students to use ChatGPT and fact-check the response provided by finding primary and secondary sources to back up the information.

Universities may also need to consider the operational aspects of generative AI, including designing and maintaining AI infrastructures that require technical training and support.

EDUCAUSE recommends developing AI policy development activities at four levels: individual, department or unit, institution, and multi-institution.

Here are the four levels of AI policy development activities recommended by EDUCAUSE:

  1. Individual: Engage students and faculty to find out how they use generative AI and how they feel about ethics and the impact on learning.
  2. Department or unit: Assess the role of generative AI in academic programs and find common ground between departments.
  3. Institution: Establish an AI governing body for oversight and guidelines that foster equity and accuracy.
  4. Multi-institution: Consult with other universities and private sector organizations to find out how they are handling generative AI challenges.

How Will Impact Higher Ed?

Generative AI is opening up a world of possibilities in higher education, but it's also generating significant concerns about academic integrity, ethics, access, and bias. The true impact of generative AI on higher education is still unknown, but it's rapidly evolving in complexity and type of use.

Curious to learn more? Check out: Generative Artificial Intelligence in Education

Credit: youtube.com, AI’s Role in Higher Ed | Jennifer Pintar | TEDxYoungstown

To incorporate generative AI into your courses, start by reflecting on how you feel about it. Are you concerned, excited, or a little of both? What additional information do you need to make informed decisions about its use in your teaching?

Experiment with generative AI platforms relevant to your discipline, like ChatGPT, Gemini, or DALL-E 2. Ask the tool to complete an assignment you'd give your students, and see the results. Can you identify possible areas of concern for academic integrity, or opportunities for student learning?

Generative AI can be used to support students' learning across various subjects, developing outputs that range from text-based to non-text-based problems. It can also be used to help students understand instructional texts by offering opportunities to explore them in multiple formats.

Here are some potential ways to use generative AI in your teaching:

  • Ask students to engage in written conversations with generative AI in their target language, allowing them to practice real-time interactions.
  • Consider asking students to create multiple versions of example texts in many languages and ask students to translate them and compare translations or their own writing.
  • Ask students to use generative AI to help them describe existing code or identify computer code errors.

To use generative AI effectively, consider setting clear parameters and expectations with your students. Decide whether and when you want them to use the technology in your courses, and communicate your expectations clearly.

Academic Integrity and Tools

Credit: youtube.com, Academic Integrity and Assessment in a Generative AI World | ASU+GSV Summit 2024

Detecting AI-generated text is notoriously unreliable, as a report from the University of Kansas Center for Teaching Excellence points out.

Tools for detecting AI-generated text are not foolproof, and this can make it difficult for professors to catch students who are cheating.

Generative AI makes it easy for students to create text that seems like a human wrote it, which can be a problem for academic integrity.

Students can be tempted to cut corners and use generative AI when under pressure to finish assignments.

One solution is to change the design and structure of assignments, which can substantially reduce students' likelihood of cheating and enhance their learning, according to Yale University.

Princeton University suggests facilitating a discussion between students and their drafts, including one generated by ChatGPT, to help them analyze the differences and become better digital citizens.

Enhancing Student Learning

Generative AI can be a game-changer in higher education, and one of the most exciting ways it can enhance student learning is by providing instant access to vast amounts of information quickly.

Credit: youtube.com, Generative AI + Education: Will Generative AI Transform Learning and Education

Students can use generative AI to explore different perspectives on a topic, generating alternative explanations and examples that can enrich their understanding. This can be especially useful in classes where students are encouraged to think critically and develop their own opinions.

By using generative AI to research practical methodologies, students can gain a deeper understanding of why certain techniques are used and how they relate to formal laboratory teaching protocols. This can help build their confidence in undertaking experiments and learning about different approaches to experimental design.

Here are some ways generative AI can support student learning across different subjects:

  • Text-based problems: generative AI can support students learning languages, generating example texts and translations, and helping them practice real-time interactions.
  • Non-text-based problems: generative AI can support students learning computer programming, analyzing code, and identifying errors.

By incorporating generative AI into their learning, students can develop a more nuanced understanding of complex topics and improve their critical thinking and problem-solving skills.

Personalized Enrollment Assistant

A personalized enrollment assistant can be a game-changer for students navigating the application process.

The biggest drop-offs in the full-funnel data occur at mid-funnel, where partners lose most of their applicants.

Credit: youtube.com, The Student Learning Plan: Personalized Education Program

With a Gen AI Conversational Assistant, students can get personalized assistance throughout the enrollment process, answering questions 24/7 and providing guidance on application requirements.

These assistants can also guide students through financial aid options, provide comparative analysis on competitor universities, and send personalized reminders about important deadlines.

During peak times, these assistants can handle a high volume of inquiries simultaneously, providing consistent responses and reducing the workload on admissions teams.

By using these assistants, universities can enhance the efficiency and effectiveness of the entire enrollment process, provide a more streamlined and personalized experience for applicants, and significantly increase their Lead-to-Enroll ratio while also reducing Cost-Per-Enrollment.

Enhancing Student Learning in Class

Generative AI can be a valuable tool to enrich and support students in developing their contextual understanding of a topic. By asking students to seek outputs from generative AI based on a range of discussion topics, you can facilitate discussions between students and encourage them to question one another on their respective outputs.

Credit: youtube.com, Enhancing Student Learning - Effective Educational Strategies (5 Minutes)

This can help students understand the range of perspectives that can be generated through different AI prompts and/or tools. For example, you can ask students to explore different generative AI tools and prompts to see how they generate alternative explanations and examples.

Students can also use generative AI to research practical methodologies before a laboratory class, which can help them understand the underlying experimental rationale and build their confidence in undertaking experiments.

Here are some ways you can incorporate generative AI into your class:

  • Ask students to engage in written conversations with generative AI in their target language to practice real-time interactions.
  • Have students create multiple versions of example texts in many languages and ask them to translate and compare translations or their own writing.
  • Use generative AI to help students describe existing code or identify computer code errors, promoting a clearer understanding and iterative development.

By incorporating generative AI into your class, you can provide students with a range of perspectives, support their language development, and promote critical thinking and problem-solving skills.

Policy and Guidelines

Developing a policy for generative AI in higher education can feel overwhelming, but it's essential to start small and build from there. Begin with clear guidance on acceptable AI use, like Stanford University's policy, which prohibits using generative AI tools to substantially complete an assignment or exam.

Credit: youtube.com, Shaping the Future: Policy Considerations for AI in Higher Education Institutions

Start by establishing a flexible foundation that acknowledges the rapidly evolving nature of AI technologies. Standardized policies are not sustainable in the long term, as Duke University experts caution.

To create an effective policy, set aside time to understand the issues at stake for faculty, students, staff, and administrators. This includes considering the potential risks of cheating, fairness, and data security.

Consider starting with a simple rule of thumb: requiring students to acknowledge the use of generative AI and default to disclosing such assistance when in doubt. This approach can help you build a solid foundation for more complex policies down the line.

Frequently Asked Questions

What are the risks of generative AI in higher education?

Generative AI in higher education poses risks such as security issues, high implementation costs, and overreliance on AI models hindering their development. These challenges can lead to decreased student motivation and a lack of focus on essential soft skills

Jay Matsuda

Lead Writer

Jay Matsuda is an accomplished writer and blogger who has been sharing his insights and experiences with readers for over a decade. He has a talent for crafting engaging content that resonates with audiences, whether he's writing about travel, food, or personal growth. With a deep passion for exploring new places and meeting new people, Jay brings a unique perspective to everything he writes.

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