Library Science Teachers, Postsecondary

Many routine tasks in teaching have already been eased by software. For example, professors use online systems (like Blackboard or Canvas) to track attendance and grades ^{[1] [2]}. These tools automatically record who is in class and store scores, which cuts down paperwork.

AI is also helping grade some exams: for simple quizzes or short answers, programs can score tests quickly and consistently ^{[3] [2]}. Research also suggests AI tools can cluster student responses or check assignments for fairness ^[3]. Other tasks, like writing grant proposals or doing deep research, remain mostly human jobs.

However, AI can lend a hand. A recent survey found about 15% of researchers already use AI (for example, ChatGPT) to help draft parts of research grants ^{[4] [4]}. Librarians and professors can use AI-powered assistants (such as Elicit or research chatbots) to gather articles and summarize literature for bibliographies ^{[5] [5]}.

In summary, AI and software can take over many repetitive duties (attendance logs, basic grading, data lookup), which saves time so teachers can focus on students ^[6]. But work that needs a human touch – teaching in person, mentoring students, creative planning – still needs people ^{[3] [3]}.

Whether colleges adopt AI quickly or slowly depends on several factors. In favor of AI, many helpful tools are already available. Learning-management systems, scheduling software, and free AI models like ChatGPT or Perplexity can be used right away by teachers ^{[1] [4]}.

ChatGPT, for instance, is easy to try and it can save time writing or brainstorming. This “makes it easier to write long applications,” one researcher noted ^[4]. On the other hand, higher education often has tight budgets and slow tech roll‐out.

A review of academic libraries found that nearly half of the studies cited funding as a major barrier to using AI ^[7]. In addition, education is still viewed as a human-centered field. Many librarians and teachers feel some tasks require personal judgment and care ^{[3] [7]}.

They may be cautious about trusting AI for things like grading or advising. Finally, staff need training to use new AI tools (for example, learning how to work with chatbots) ^[7]. In sum, colleges can save money on routine work and make research easier with AI, but high costs, ethics, and the need for human skills mean change will likely be gradual ^{[7] [4]}.