Technological innovations have expanded the parameters of what we thought artificial intelligence (AI) could do. And with all the recent talk surrounding ChatGPT, many experts believe AI will disrupt higher education and raise questions about what is ethical within the academic sphere.
We remain at the frontier at which what we formerly considered a thought experiment is becoming tangible and part of our daily reality. AI creates an immersive and virtual learning experience for students and teachers by filling learning gaps and creating a more personalized plan for each student.
AI Boosts the College Admissions Process
The college admissions process is stressful for high school students. But AI can make valuable predictions and suggestions through virtual platforms and mobile applications.
For instance, a personalized guidance counselor may interest high school students who need readily available access to college advisors. College advisors are crucial to college admissions, providing students with the necessary insight and information to make critical decisions.
Students can ask questions like, “How do I choose a college?” “What are my chances of getting into my dream school?” “What can I do to increase my chances of getting into college?” and “Once I get in, how will I be able to afford college tuition?”
Additionally, AI-based chatbots use prior knowledge and institutional documentation to provide accurate information. They provide automated responses to prospective student queries and help them complete basic tasks on the college website.
Chatbots help students find answers to questions through natural conversations. College chatbots are great for providing certain information, including the dates of application deadlines, links to register for an open house, where to submit a FAFSA, or even how to apply for housing on campus.
Chatbots can also check in with students about their mental health. A JMIR study found that groups of students using a clinically proven, AI-powered mental health chatbot called Tess reported significantly reduced anxiety symptoms.
Researchers also noted a statistically notable difference in the symptoms of depression reported by the intervention group compared with the control group.
On the other hand, university admissions leaders are finding ways to leverage AI within academia. Mainly, this technology helps institutions increase early acceptance rates while cutting back on expensive and time-consuming calls to staff.
Personality research helps admissions officers understand how students will perform in the classroom. And extracting and analyzing this information can help uncover red flags or potential successes early in the application process.
But an admissions system still needs to assess personality and psychological characteristics. So personality variables related to student outcomes may be missed.
AI can help smooth the admissions process and synthesize large amounts of information through a well-trained algorithm. This technology can extract data from thousands of student materials and train a model to make admission-related predictions or recommendations.
“Fairness and consistency are core tenets of the college admissions process. The introduction of AI in college admissions used correctly, is an opportunity to improve upon those aims,” William Rose, CTO of Student Select, wrote in a recent interview.
“For example, reviewing admission essays is a mostly subjective practice. On the other hand, AI-produced insights can paint a more objective – and predictive- picture of the applicant and their potential as a successful student. This can then equip admissions deciders with more quality data to ultimately inform their selection decisions,” Rose continued.
AI Changes the Way Students Learn
Fast learners must stay engaged, while slow learners can’t be left behind. Through personalized programs, AI allows learning to be tailored and adapted to every student’s needs, goals, and abilities. AI can help set the ideal pace for every student.
Two types of assessment include rules-based and machine learning-based AI. The former uses decision-making rules to produce a recommendation or a solution. One example of this system is an intelligent tutoring system (ITS), which can provide granular and specific feedback to students.
The ‘intelligence’ of ITS comes from AI techniques which are used in four interacting components: The knowledge base contains the domain knowledge, the student model represents the student's current knowledge state, the pedagogical module has suitable instructional measures which are contingent on the content of the student model, and the user interface enables an effective dialog between ITS and student.
The software collects information on a student's performance and other cognitive and noncognitive variables, adjusts feedback, and provides hints. Additionally, the software can make inferences about strengths and weaknesses and suggest additional work.
Students can also use AI software to grade their own work. The ability to estimate the quality of their work before submission could encourage further academic engagement and mitigate the element of surprise that often discourages students who are disappointed in their grades.
Therefore, researchers have worked on automated essay grading and short answer scoring for decades.
Automated essay scoring (AES) is a computer-based assessment system that automatically scores or grades student responses by considering appropriate features. The AES research started in 1966 with the Project Essay Grader (PEG) by Ajay et al. (1973). To grade the essay, PEG evaluates the writing characteristics, such as grammar, diction, construction, etc.
Most US states use AES systems in school education, like Utah compose tool and the Ohio standardized test (an updated version of PEG), evaluating millions of students’ responses yearly. These systems work for formative and summative assessments and give feedback to students on the essay.
Other notable AI education examples that transform student learning include information visualization and digital lesson generation.
In information visualization, AI innovative content creation stimulates the real-life experience of visualized web-based study environments. The technology helps with 2D-3D visualization, where students can perceive information differently.
In digital lesson generation, students can leverage the entire study material without taking up much space in the digital system. And these materials are accessible from any device.
AI in Education Assists Teachers
More than 50% of schools and universities rely on AI for administrative assistance, with a rising emphasis on improved higher education quality.
AI trends fuel growth rapidly in EdTech by improving student engagement with customized courses, interactive lectures, gamified classrooms for skill gain, etc. A March 2022 study found that the AI education market is predicted to cross 20 billion by 2027.
Teachers can leverage AI in the classroom to help with tedious tasks that are repetitive and time-consuming, such as lesson planning. These duties can now be automated, making the planning lesson process easier and more efficient while optimizing the actual quality of lesson plans.
Additionally, AI-powered devices have the potential to provide much-needed support and boost teachers’ bandwidth. For example, AI chatbots allow for 24/7 learning from anywhere and anytime.
These chatbots can interact with students and are critical in helping provide students with a more effective and engaging learning experience. Likewise, educators can focus on other needs as chatbots simultaneously engage with a few students.
Conversational AI systems also deliver intelligent tutoring by closely observing the content consumption pattern and catering to their needs accordingly. In this way, teachers’ ability to nurture multiple learning styles is a crucial benefit of leveraging AI in the classroom.
Teachers must understand students' emotions, behavior, and engagement levels and respond accordingly. But it is also essential for the classroom itself to serve as a great learning environment.
Teachers can deploy AI in the classroom by using technology to actively monitor classroom conditions and then become alerted about any problems or areas where improvement is possible. For example, students may be uncomfortable, distracted, or less engaged if a room is too warm or cold.
Similarly, University of Mississippi research found a significant effect between light quality and student academic performance. Artificial light settings vary greatly in classrooms, leading to questions of how constituents in the educational process select lighting for optimizing teaching and learning.
AI can potentially resolve both issues by training systems to learn the ideal room conditions and automatically adjusting heating, air conditioning, and lights.
The adoption of AI in education has faced some resistance, and even now, discussions will often center around how students can use AI. However, AI can greatly assist teachers as well.