20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
A typical day mixes class time, research, and meetings. Mornings often mean preparing or delivering lectures with PowerPoint, grading, and answering student emails in Microsoft Outlook or the school's LMS (Blackboard Learn).
Afternoons are for research: reading journals, running analyses in SAS or SQL, writing grant proposals, and meeting colleagues or students. Evenings or one day a week are for committee work, advising student groups, and campus events.
You will use Microsoft Outlook for email and scheduling, Word and Google Docs for reports and papers, and PowerPoint for lectures. Blackboard Learn or another LMS hosts assignments and grades.
If you do research you may use SAS or SQL for data analysis, and Excel for simple datasets. Committees and grants use Word/Google Docs; collaboration often happens in shared cloud drives.
According to the U.S. Bureau of Labor Statistics (BLS), there were about 47,670 postsecondary professors employed and the median pay was $79,940 per year. The lowest tenth earned about $49,180 and the top tenth about $139,340.
Pay varies by institution, discipline, grant income, and geographic region; research-active professors at research universities often earn more, especially with external grants.
Professors teach undergraduates and graduates, plus conduct original research and write grant proposals. They spend more time on research, publishing, and service like committees and faculty evaluations.
High-school teachers focus more on daily classroom management, standardized curricula, and direct classroom supervision. Professors also advise student organizations and mentor graduate students.
You can use AI to draft lecture outlines, generate quiz items, or summarize articles, but always check accuracy and bias. Cite sources and tell students when AI helped create materials. Don't use AI to assess students without human review.
For research, use AI to clean data or explore ideas, but validate results with SAS/SQL or statistical checks. Follow university policies on AI, data privacy, and plagiarism.
You need clear teaching skills: preparing lectures, facilitating discussions, demonstrating concepts, and monitoring student progress using the LMS and assessments. Advising and managing student relationships are also essential.
Research skills matter: designing studies, using SAS or SQL for data, writing grants, and staying current in your field. Collaboration skills for committees and peer evaluation complete the picture.