How Is AI in Higher Education Enhancing Learning Efficacy In 2024? | Magic EdTech (2024)

Does your university have a Chief AI Officer? Well, it may seem unlikely but the Western University in Ontario, Canada, has become the premier institution to establish such a position. The University’s Chief AI Officer oversees over 30 pilot AI projects. One of these projects involves collaborating with humanities faculty to create new courses.

“AI is like a research team who have read a million books and many journal papers,” said Michael Levitt, a Nobel Prize winner in Chemistry, as quoted in Inside Higher Ed. AI in higher education research supported large language models (LLMs) assisting in creating drafts, establishing lengthy summaries, and finding research gaps to cover unexplored areas.

AI in higher education is multifaceted. Examples of AI in higher education encompass personalized learning and institutional administration. AI-based tools, software, and plugins are revolutionizing the traditional learning landscape. One of the areas where AI holds significant promise is in addressing the learning-efficacy challenges faced in online learning programs.

How can AI be used to improve learning efficacy in online programs?

Enhance engagement and interaction

One of the primary challenges in online learning is maintaining engagement and interaction among learners. Unlike traditional classrooms where students can engage in immediate discussions and receive real-time feedback, online programs often limit the level of interactivity. AI-powered chatbots and virtual assistants can provide personalized support to students and facilitate interactive discussions. For example, a study from the University of Melbourne revealed how generative AI is increasingly being used as a learning partner by university students. Students share that while AI helps them get a broad overview of a topic, they prefer to keep assignments completely self-directed.

Additionally, by plugging in virtual reality and augmented reality, universities can foster active engagement. For instance, Arizona State University is using the realm of virtual reality to educate business students in supply chain management. By entering virtual coffee shops students are addressing operational and staffing requirements and measuring their impact on revenue thus learning from their mistakes in real time.

Increased accessibility

The lack of engagement in online learning programs is also attributed to difficulty in content accessibility. Making the content accessible to English language learners and students with disabilities is significant to bridging the digital divide. AI-driven voice-activated tools, real-time transcription and captioning services, and screen readers are helping address the need for equitable and accessible learning.

Improved assessment and learning

Online learning program assessments like multiple-choice questions and quizzes may fail to capture the student’s cognitive skills. Poor assessments can lead to inaccurate feedback and reduced scope of improvement. AI’s autonomous machine learning ability is helping educators address this gap and provide timely interventions. Ivy Tech’s machine learning algorithm to detect at-risk students before examinations helped the university in delivering early interventions for better outcomes. By shifting the focus of data analysis from reaction to prediction, the university was able to predict course outcomes in the second week of the semester with 80% accuracy.

Collaborative learning

Two heads are better than one. This potency of shared intellect is introduced to us through the traditional learning system. However, technology issues, lack of physical presence, and unequal participation pose challenges to collaborative learning in online learning platforms. Artificial intelligence is radically changing this for improved learning outcomes. AI-based adaptive group formations that divide students into well-balanced groups and intelligent moderation programs that monitor multiple discussions together are facilitating fruitful collaborations.

The use of AI in higher education has entered into a new era of innovation, promising to revolutionize higher education learning. As universities grapple with the challenges of ensuring learning efficacy in online programs, AI solutions offer potential avenues for improvement. However, alongside the promise of AI-driven advancements, university leaders have certain apprehensions about its implementation.

The Challenging Impact Of AI in Higher Education

Plagiarism and academic integrity

The widespread adoption of AI is increasing speculations about plagiarism. University leaders are looking for ways to enforce academic integrity among students. However, the inherent problem of plagiarism is – how it is viewed. The University of South Carolina addresses these concerns via two modules: academic resources and honor codes. Similarly, Stevenson University in Maryland mandates all new students to take an online academic integrity tutorial. By establishing codes of conduct, leaders can create a good understanding of academic integrity among students.

Algorithmic bias

Algorithmic bias in higher education is showing up in multiple ways. From racism in admissions to poor assessments based on past performances and data groups, the algorithm is creating structural bias. Researchers at MIT have come up with a fair machine learning model that enables fair outputs even if it is trained on unfair data. Further, they are interested in defining proper metrics for auditing fairness.

Data privacy and safety

Students care about data privacy and this concern is increasing. University leaders are equally cognizant of protecting student data from veritable exposures. By establishing regulatory guidance through privacy programs universities can address the issue. This includes determining how data is collected, managed, processed, and stored.

By understanding and mitigating these apprehensions, universities can unlock the full potential of AI in higher education to enhance learning outcomes while preserving the human-centered nature of education. Through the integration of AI, universities can prepare learners for careers in technology and lead the way in transforming higher education for the opportunities of tomorrow.