ENG2612
EXAM PORTFOLIO
2025
CHOOSE ESSAY 1 OR 2
(DON’T INCLUDE SUBHEADINGS)
LOOK AT WORD COUNT
ESSAY 1
Should UNISA Disable AI Detection
Software?
(I disagree – UNISA should NOT disable AI detection
software.)
Introduction
I disagree with the suggestion that UNISA should disable its AI
detection software. From my perspective, keeping this system is
necessary to uphold the credibility of UNISA’s degrees, maintain
academic honesty, and protect the university’s reputation. Although
Extract A (McKenna & Kramm) highlights the stress and frustration
caused by AI detection software, I think these issues can be
addressed by making the process fairer and more transparent, not
by removing the technology entirely. As supported by the ENG2612
study guide and scholars such as Bailey (2015) and Leland et al.
(2013), academic integrity relies on reliable checks and a balance
between trust and accountability.
, Protecting the Value of UNISA Degrees
One of the strongest reasons to keep AI detection is to protect the
value of UNISA’s qualifications. The ENG2612 study guide
emphasises that academic integrity is essential in building a
university’s reputation and the value of its degrees
(ENG2612/501/0/2025). Bailey (2015) further argues that without
strong systems to check for authenticity, the meaning of a
qualification can be easily questioned. If UNISA were to remove all
forms of detection, it would risk being seen as a university where
cheating is possible and even easy. This could lead employers and
other academic institutions to doubt the reliability of UNISA
graduates, harming all students—including those who have worked
honestly for their degrees.
From my own experience, I have seen how potential employers
sometimes question the quality of distance learning qualifications. If
UNISA cannot provide clear evidence that its assessments are
original and fair, our degrees might even be compared to “fake”
qualifications from unregistered colleges. The ENG2612 guide
reminds us that “students need to be proactive in the decisions
about learning” and that universities should “encourage agency and
accountability” (ENG2612/501/0/2025: 18). Without strong, fair
checks, the achievements of honest students would be
overshadowed by the actions of a dishonest few.
Problems with Detection Must Be Solved, Not Avoided
Extract A (McKenna & Kramm) describes real challenges with AI
detection, such as students being wrongly accused and made to
prove their innocence, and software that flags genuine writing as
suspicious. These issues are serious and can undermine student
confidence. As Wallace (1995) explains, critical reading is about
“distinguishing between facts and opinions, and questioning the
intention of the author” (Wallace, 1995: 335; ENG2612/501/0/2025:
6). In the same way, AI detection systems must be questioned and
improved, not simply removed.
Instead of getting rid of detection tools, UNISA should focus on
making their use transparent, fair, and educational. Janks (2010)
suggests that we can either “read with a text or against a text” to
challenge or accept the assumptions in a given situation (Janks,
2010; ENG2612/501/0/2025: 10). In this context, I choose to read
against the idea that removing AI detection is the best answer.
Instead, I believe UNISA should use the technology as a starting
point for honest conversations between students and lecturers,
allowing for appeals and explanations whenever flags are raised.
EXAM PORTFOLIO
2025
CHOOSE ESSAY 1 OR 2
(DON’T INCLUDE SUBHEADINGS)
LOOK AT WORD COUNT
ESSAY 1
Should UNISA Disable AI Detection
Software?
(I disagree – UNISA should NOT disable AI detection
software.)
Introduction
I disagree with the suggestion that UNISA should disable its AI
detection software. From my perspective, keeping this system is
necessary to uphold the credibility of UNISA’s degrees, maintain
academic honesty, and protect the university’s reputation. Although
Extract A (McKenna & Kramm) highlights the stress and frustration
caused by AI detection software, I think these issues can be
addressed by making the process fairer and more transparent, not
by removing the technology entirely. As supported by the ENG2612
study guide and scholars such as Bailey (2015) and Leland et al.
(2013), academic integrity relies on reliable checks and a balance
between trust and accountability.
, Protecting the Value of UNISA Degrees
One of the strongest reasons to keep AI detection is to protect the
value of UNISA’s qualifications. The ENG2612 study guide
emphasises that academic integrity is essential in building a
university’s reputation and the value of its degrees
(ENG2612/501/0/2025). Bailey (2015) further argues that without
strong systems to check for authenticity, the meaning of a
qualification can be easily questioned. If UNISA were to remove all
forms of detection, it would risk being seen as a university where
cheating is possible and even easy. This could lead employers and
other academic institutions to doubt the reliability of UNISA
graduates, harming all students—including those who have worked
honestly for their degrees.
From my own experience, I have seen how potential employers
sometimes question the quality of distance learning qualifications. If
UNISA cannot provide clear evidence that its assessments are
original and fair, our degrees might even be compared to “fake”
qualifications from unregistered colleges. The ENG2612 guide
reminds us that “students need to be proactive in the decisions
about learning” and that universities should “encourage agency and
accountability” (ENG2612/501/0/2025: 18). Without strong, fair
checks, the achievements of honest students would be
overshadowed by the actions of a dishonest few.
Problems with Detection Must Be Solved, Not Avoided
Extract A (McKenna & Kramm) describes real challenges with AI
detection, such as students being wrongly accused and made to
prove their innocence, and software that flags genuine writing as
suspicious. These issues are serious and can undermine student
confidence. As Wallace (1995) explains, critical reading is about
“distinguishing between facts and opinions, and questioning the
intention of the author” (Wallace, 1995: 335; ENG2612/501/0/2025:
6). In the same way, AI detection systems must be questioned and
improved, not simply removed.
Instead of getting rid of detection tools, UNISA should focus on
making their use transparent, fair, and educational. Janks (2010)
suggests that we can either “read with a text or against a text” to
challenge or accept the assumptions in a given situation (Janks,
2010; ENG2612/501/0/2025: 10). In this context, I choose to read
against the idea that removing AI detection is the best answer.
Instead, I believe UNISA should use the technology as a starting
point for honest conversations between students and lecturers,
allowing for appeals and explanations whenever flags are raised.
