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Higher education professionals may have a bit of AI-related homework to do. Otherwise, you may miss opportunities and lose touch with your students.
As a recent Tyton Partners study showed, students are using generative AI solutions at a much faster pace than instructors. How wide will this disparity become? Only 22% of faculty use AI regularly, compared to 49% of students.
Of course, this does not mean that AI is not being used at an organizational level. According to Intelligent 2023 research, 82% of participating institutions plan to incorporate AI into their admissions workflows this year. In other words, while progress is occurring, campuses lag significantly behind corporate campuses in widespread friendliness to experimentation and adoption of AI products.
Part of the problem with the hesitancy to adopt AI across the higher education ecosystem may be related to confusion about when, where, and how to adopt AI. Additionally, many college, university, and graduate program leaders may not realize that AI is not all bad. Yes, generative AI has facilitated a new era of plagiarism warnings. However, just because some students are abusing AI does not mean we should shun it.
On the contrary, higher institutions that actively want to explore AI's broader capabilities can reap several benefits. These include doing more with limited resources, providing a more personalized experience for students, and leveraging the predictive power of AI to attract more relevant and diverse campus applicants. Includes encouragement.
What are some areas where AI can be an asset to higher education institutions and programs?
1. AI frees administrative staff from manual tasks.
Companies around the world are discovering important facts. That means repetitive tasks are taking up a significant amount of employee time. According to her 2021 UiPath study, employees lose approximately 4.5 hours each week on mundane, routine tasks that can be automated. This is not great for any department's budget and certainly requires a rethinking of AI technology.
There is no shortage of AI tools, software, and plugins that can competently and effortlessly take on simple, repetitive responsibilities. At an administrative and 'back office' level in higher education, this means deploying paperwork after a student receives an acceptance letter, identifying students at risk of dropping out, and encouraging increased recruitment of institutional staff. could mean. In real-world classrooms and learning environments, AI can provide assistive functions to free teachers from manual processes, such as transferring grades to spreadsheets and organizing reports.
The key to implementing AI as an automation solution within your company is to first find out where repetition is occurring. From that point on, AI advances can be piloted in controlled settings and small groups to establish which ones will be of most value to the organization and its people.
2. AI can facilitate holistic and unbiased applications.
The admissions process remains one of the most talked about areas in higher education. When the Supreme Court ruled against affirmative action in college admissions, it sent shockwaves through universities. Many wondered whether it was still possible to set up a fair application process. That's also true for educational institutions leveraging AI for holistic admissions.
How does a holistic admissions process work? Andy Hanna, president of Liaison International's Osot division, says schools first need to align their holistic approach with their overarching mission. I'm explaining. Institutions and programs will then be able to identify the demographic and behavioral variables that most closely match the objectives that define the qualities and experience they seek in candidates. Factors such as grit and empathy can be quantified. Although difficult to do, it is now possible to navigate organizational and programmatic missions by mapping them to specific variables, allowing machines to optimize the composition of diverse student populations.”
By allowing AI to evaluate applicants on multiple unique criteria, not just standardized test scores, GPAs, and other numeric rankings, admissions officers can reduce the potential for non-diverse student populations. You can avoid bias, Hanna argues. This type of “non-linear” model allows schools to be more nuanced and responsible when considering what really matters, and allows admissions teams to recognize excellence in all its forms.
3. AI allows students to have more customized learning.
At the consumer level, personalization is becoming just a gamble. As Insider Intelligence points out, 73% of people expect personalization from brands. This naturally extends to interactions between students and higher education institutions.
AI can enable personalization at scale in ways never before possible. An example of this happened just recently at Ivy Tech. The community college has developed a proprietary algorithm to help identify students who are statistically less likely to pass their classes or graduate. A Google Cloud article about the project explains, “By the second week of the semester, this algorithm could predict a student's final grade in a course with 60% to 70% accuracy.” I am. result? All 3,000 students received the intervention they needed to pass their classes.
Of course, this is just one use case for AI-enhanced personalization in higher education. Other possibilities include using AI to provide corrective and instructional writing feedback, set personalized study plans, and help first-semester students get through their first few weeks on campus. This includes supporting the
Learning is at the heart of higher education. Now is the time for educational institutions to better understand AI and put it to work for them and their students.
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