Should Students Use AI in Higher Education?

• Artificial Intelligence, Education
• Posted: 10 months ago

With the rise of AI in learning, the question arises: should students be using AI in higher education? This is a hot debate amongst education professionals, and for good reason. The power of AI technology can radically transform the way students learn, but it also comes with its drawbacks. Should we embrace this life-altering tech or exclude it from teaching practices and stay true to more traditional methods? This is a lofty decision which will have far-reaching effects, so it’s important to consider both sides of the argument. In this blog, we’re doing just that.

The Benefits of AI in Higher Education

Let’s start with the good. There are lots of benefits to students using AI in a higher education setting. Some of these advantages include:

1. Personalized Learning Experience:

AI in higher education has introduced a new level of personalization in the learning experience. AI-powered systems can analyze, including their past performance, learning styles, and areas of difficulty. The AI uses this data to create a unique learning path for each student, ensuring that they receive content that aligns with their personal learning needs and preferences. This level of customization is often impossible to achieve in traditional classroom settings where one-size-fits-all teaching methods are common. This customization allows students to learn at their own pace, focusing on areas where they need the most support.

2. Enhanced Learning Efficiency

AI can significantly improve the efficiency of the learning process. Intelligent tutoring systems, powered by AI algorithms, can tailor educational content to match the unique learning pace and style of each individual student. It can assess their strengths and weaknesses, thereby personalizing the learning experience. This real-time indication of progress enables students to have a better grasp on their learning journey, boosting their confidence and motivation levels. Beyond tutoring, AI-powered systems can also automate administrative tasks, like grading. This means educators can dedicate more time to personalized instruction and student engagement.

3. Access to Vast Amounts of Information

AI can provide students with access to a wealth of information. AI-powered search engines and recommendation systems can help students discover relevant resources and expand their knowledge base. This access to diverse information can deepen their understanding of subjects and encourage independent learning. Students are empowered to take control of their educational journey, exploring topics beyond the curriculum and developing a broader knowledge base. This self-directed learning not only nurtures critical thinking skills but also prepares students for a constantly evolving and dynamic knowledge landscape.

4. Personalized Assistance and Support

AI chatbots and virtual assistants can serve as virtual tutors, providing students with instant assistance and support. They use machine learning and natural language processing to understand and respond to student queries. This creates an interactive learning environment that can be tailored to each individual’s needs. AI chatbots can also explain things to students in a simple, understandable way to make complex topics easier to understand. Moreover, these AI tutors can guide students through complex problems step by step. By breaking down difficult concepts into manageable parts, students can better understand and solve problems. This not only enhances their problem-solving skills but also increases their confidence in tackling challenging topics.

The Drawbacks of AI in Higher Education:

While AI brings undeniable advantages to higher education, we must also consider the potential drawbacks and challenges:

1. Lack of Human Interaction

One of the main concerns with using AI in an academic setting is the potential reduction in human interaction. Traditional education has always placed great emphasis on direct, face-to-face interactions between students and educators. This interactive model promotes the development of critical thinking, collaboration, and social skills. There’s also the irreplaceable value of spontaneous classroom discussions and debates that stimulate critical thinking and problem-solving skills. The use of AI in education could also potentially lead to a more isolated learning experience. While some students may thrive in an environment like this, others who need more social interaction could find it challenging. The lack of human connection can make the learning experience less engaging and stimulating for these students.

2. Potential for Bias

AI systems are only as unbiased as the data they are trained on. They learn patterns, make decisions, and carry out operations based on the information provided to them during their training phase. When AI algorithms are trained on biased datasets, they absorb and reflect those biases in their decision-making processes. If the training data contains biases, such as gender or racial biases, the AI algorithms may perpetuate these biases when providing personalized content or feedback.

Moreover, AI systems don’t possess an inherent understanding of societal norms or ethical considerations; they simply learn from the data they are provided. Consequently, if the training data is not representative and diverse, the AI system may lack the necessary context to make fair and unbiased decisions. To mitigate these issues, it is imperative to prioritize diverse and inclusive training datasets. This involves carefully curating data that spans various demographics, ensuring representation across different groups. Ongoing monitoring and evaluation of AI systems in real-world applications are also necessary to identify and address any emerging biases.

3. Ethical Concerns

The use of AI in higher education raises ethical concerns, such as data privacy and security. AI systems collect and analyze large amounts of student data. his includes not only basic personal information but also intricate details such as learning styles, academic performance, and behavioral patterns. The ethical dilemma arises from the necessity to strike a delicate balance between leveraging this data for educational enhancement and safeguarding the privacy rights of the individuals involved.

Ensuring data privacy in AI applications involves establishing robust security measures to protect against unauthorized access, breaches, and potential misuse of sensitive information. Institutions need to implement encryption techniques, secure storage protocols, and access controls to safeguard the vast repositories of student data. Regular audits and assessments of these security measures are essential to identify and address vulnerabilities promptly. Safeguarding student data and ensuring its responsible use is paramount to protect student privacy and prevent misuse.

4. Dependency on Technology

Integrating AI in higher education may inadvertently create a dependency on technology. As AI becomes more prevalent in classrooms, there is a risk that students may rely excessively on AI systems to provide quick answers and solutions. This reliance could potentially stifle their natural ability to think critically, solve problems independently, and develop essential analytical skills. When students depend heavily on AI for information and problem-solving, there is a risk of diminishing their motivation to engage in deep and meaningful learning experiences.

The convenience of AI-generated answers may lead to a surface-level understanding of topics rather than fostering a deeper comprehension and mastery of the subject matter. This shallow engagement may hinder the development of critical thinking skills, creativity, and the ability to approach challenges with a nuanced perspective. To mitigate these potential negative consequences, it is essential to strike a delicate balance in integrating AI into the educational environment. Educators play a pivotal role in guiding students to use AI as a supplementary resource while encouraging them to actively participate in the learning process.

Ivy Tech’s AI-Infused Intervention:

Ivy Tech Community College Ivy Tech Community College revolutionized its approach to student success by using artificial intelligence (AI). The Chief Technology Officer, Lige Hensley, and the team faced the challenge of managing a huge database with 26 terabytes of student data. Despite this, they embarked on a mission to leverage this vast information reservoir for proactive intervention. Shifting to Google Cloud allowed Ivy Tech to scale operations and handle a staggering 12 million data points. Doing this paved the way for the development of a sophisticated machine-learning algorithm designed to predict student engagement and course outcomes with 80% accuracy using anonymized metadata.

During a pilot test in the fall of 2016, Project Student Success identified 16,000 students statistically at risk for failing by the second week of the semester. Ivy Tech implemented personalized interventions that addressed various non-academic obstacles, and 3,000 students improved their grades to a C or better. The AI also helped with non-academic issues like power outages and missing materials. Since then, Project Student Success has positively affected 34,712 students, changing how the college supports them.

Julian: Walden University’s Innovative AI-Driven Learning Platform

Walden University, a pioneer in online and distance learning, has harnessed the power of Google Cloud technology to launch Julian. Julian is a groundbreaking dynamic interactive tutor for teaching and learning. By using Google Cloud Student Success Services, Walden developed a scalable online tutor equipped with Google’s advanced AI and ML capabilities. Julian caters to Walden’s diverse student base of working professionals, offering personalized, on-demand learning experiences 24/7.

Built on Google’s Bidirectional Encoder Representations from Transformers (BERT), Julian incorporates a pretrained natural language processing model. This allowed it to engage in dynamic, unscripted interactions with users. The AI-based tutor introduces innovative features such as Choose the Fact, Knowledge Notes, Paraphrase, and Ask Question, revolutionizing the learning experience. The pilot phase in early childhood education and sociology got positive feedback from 60+ students. Faculty appreciated the automation of practice work, which afforded them more time for teaching.

Julian is different from traditional support systems in that it empowers students not only by reinforcing concepts and identifying learning gaps but also by offering a unique set of activities during each interaction. This dynamic learning approach is further complemented by Julian’s feature to generate comprehensive notes, serving as valuable references throughout the academic program.

Striking the Balance When Using AI in Higher Education

The debate surrounding the use of AI in higher education is complex and multifaceted. While AI offers significant benefits, such as personalized learning experiences and enhanced efficiency, it also poses challenges, including the potential reduction of human interaction and ethical concerns.

To harness the full potential of AI in higher education, it is crucial to strike a balance between leveraging AI as a tool for personalized learning and maintaining the essential aspects of human interaction and critical thinking. Educators and institutions must carefully consider the ethical implications, mitigate biases, and ensure student privacy and security.

AI has the power to transform higher education by empowering students with personalized support and efficient learning experiences. However, it should be implemented thoughtfully, keeping in mind the importance of human connections and fostering students’ independent thinking skills. By embracing AI as a complementary tool, higher education can embrace the opportunities it offers while maintaining the essence of a holistic and engaging learning environment.