Exercise 2 - Part 3
You are going to read an article about the same topic with various authors' perspectives. Then you are given 10 statements, decide which author (A to D) fits the best with each statement. Choose the best answer for each question.
A: Professor Aris (The Traditionalist)
The uncritical integration of generative AI into university classrooms threatens the very foundations of critical thought and intellectual development. Higher education should be an exercise in human cognitive struggle, where students learn to synthesize complex ideas through rigorous reading and essay writing. Outsourcing these tasks to algorithms creates a generation of dependent thinkers unable to formulate original arguments. Furthermore, university assessments must return entirely to supervised pen-and-paper examinations to guarantee academic honesty. Allowing digital proxies to draft responses undermines the validation of a student's actual capabilities. Technology should serve exclusively as an administrative utility, not as a substitute for human evaluation, dialogue, and mentorship. If we surrender the core educational experience to machine learning models, we permanently devalue the meaning of a university degree.
B: Dr. Benson (The EdTech Pioneer)
Resisting technological advancement in modern academia is a futile endeavor that ultimately disadvantages students entering a highly digitized workforce. Artificial intelligence functions as an incredible equalizer, providing personalized, round-the-clock tutoring tailored directly to an individual's specific learning pace. Classrooms should pivot completely toward AI-assisted project frameworks, where students learn to prompt and refine algorithmic outputs effectively. Traditional methods like lengthy essays and standardized testing are archaic relics that measure memorization rather than actual competence. Furthermore, automated grading platforms can evaluate student submissions with absolute objectivity, eliminating human bias and reducing administrative burdens for professors. Higher education must evolve from a system of knowledge transmission into an dynamic laboratory of human-machine collaboration.
C: Clara (The Student Advocate)
While administrative bodies focus on productivity metrics, students are caught in an exhausting crossfire of shifting academic integrity policies. Generative tools offer invaluable support for non-native speakers needing assistance with formatting and language mechanics, yet their use is frequently penalized disproportionately. Completely banning these platforms is an unrealistic approach that ignores how my generation actually interacts with technology daily. However, relying blindly on automated grading algorithms is an incredibly dangerous alternative that strips empathy and nuance from academic evaluation. Essays are deeply personal expressions, and receiving a machine-generated score feels deeply alienating. We need clear guidelines that permit constructive digital assistance while preserving human evaluation and authentic professor-student relationships as the absolute cornerstone of our learning journey.
D: Dr. Davies (The Sociologist)
The current debate surrounding academic AI focuses too narrowly on cheating while ignoring broader socio-economic disparities. Institutions must realize that premium algorithmic tools are expensive, meaning wealthy students access superior research assistants while disadvantaged peers rely on basic, outdated models. This economic divide exacerbates existing educational inequalities. Regarding assessment frameworks, a balanced approach is necessary; while traditional essays still hold significant value for developing cognitive synthesis, they should be supplemented by interactive oral defense presentations. Automated grading systems should be rejected outright, as they replicate historical data biases and lack the cultural awareness needed to judge diverse student perspectives fairly. Our priority must be closing the digital access gap, ensuring equitable resources for everyone before restructuring curricula.