In this interview with Amal Dimashki – Regional Director, MENAT & Pakistan, Turnitin explores how institutions can balance AI adoption with critical thinking, meaningful assessment and the development of essential learning skills.

Students are becoming increasingly comfortable prompting AI, but how can universities ensure they are still developing independent reasoning and critical thinking rather than simply producing better AI-assisted answers?

Prompting is becoming an important skill, but being able to write a sophisticated prompt is not the same as being able to think critically.

AI can be a very effective learning partner. It can help students brainstorm, explore different perspectives, challenge an argument or receive feedback on something they have written. But students still need to do the cognitive heavy lifting. If they simply prompt AI for an answer and then refine that answer until it looks better, we may improve the quality of the output without necessarily developing the student’s thinking.

This is why AI literacy needs to go beyond teaching students how to prompt. Students need to learn how to critically evaluate AI-generated content, verify information and sources, question what they are given and make their own judgments about the output. Turnitin’s guidance on responsible prompting encourages students to engage with AI iteratively and interrogate its responses rather than simply accepting what it produces.

We want students to use AI as a learning partner while remaining actively engaged in the learning process and taking ownership of the work they produce. Turnitin’s guidance to students reinforces this by encouraging them to ensure that the majority of their work remains their original thinking.

Universities therefore need to develop AI literacy alongside critical thinking and independent judgment, so that becoming better at using AI does not come at the expense of developing the skills students are there to learn.

What should a modern assessment look like if institutions want to measure a student’s actual understanding rather than just the quality of the final submitted work?

In an AI-enabled environment, assessing only the final product gives us a limited view of whether learning actually took place. A polished final submission does not necessarily tell us how the student arrived there.

This is where a process-based approach to assessment becomes increasingly important. Educators can build meaningful checkpoints into the learning journey through outlines, drafts, formative feedback, revisions and reflection. This allows them to see how the student’s thinking developed, how they responded to feedback and where they may need additional support. Turnitin’s multipart assignments, for example, are designed around structured checkpoints for guidance and reflection throughout the writing process.

At Turnitin, we refer to the broader framework behind this as learning integrity. It expands traditional academic integrity by placing greater emphasis on the integrity of the learning process and ensuring that students are doing the work necessary to learn and develop.

It brings us back to a familiar principle: “show your work.” Greater visibility into drafts, revisions and the development of ideas gives educators richer evidence of how a student approached the assignment rather than relying on a single snapshot at the end. Turnitin Clarity, for example, provides visibility into how students develop their work from ideation through to final submission.

This does not mean making every assessment more complicated. It means designing assessment around the learning objective and creating opportunities for students to demonstrate that they have developed the skills being assessed.

The final submission will continue to matter, but it can be considered alongside evidence of the learning process that produced it.

AI makes it possible to get answers, summaries and explanations almost instantly. Do you worry that this could reduce students’ ability to sustain attention, read deeply and work through difficult material without immediate assistance?

There is certainly a risk, and students themselves recognise it. Turnitin’s research found that 64% of students are concerned that the use of AI in education may be shortcutting their learning.

Learning should not become a completely frictionless process. Researching a subject, developing a point of view, articulating ideas with evidence, editing and working through something difficult all require effort, and some of that effort is where learning happens.

Turnitin refers to this through the concept of “productive struggle.” Cognitive growth and long-term retention require students to engage with difficulty rather than having every challenge immediately removed for them.

That does not mean students should struggle without support. AI can provide guidance and feedback throughout the learning process. Turnitin Clarity’s AI Assistant, for example, is designed to prompt reflection and support students throughout their writing without generating the full response for them.

As AI becomes more capable, preserving productive struggle will become increasingly important. We want students to benefit from the support AI can provide without removing the effort involved in developing knowledge and skills.

4. Looking ahead, how do you see the role of academic integrity evolving as AI becomes embedded in writing, research and learning, and what will universities need to change over the next few years?

Academic integrity will remain fundamental, but its role is expanding as AI becomes embedded in learning.

At Turnitin, we describe this evolution through learning integrity, a proactive expansion of traditional academic integrity that places greater emphasis on the integrity of the learning process. It reflects the need to understand how students are developing their work and ensure they are developing the skills their education is intended to build.

Over the next few years, universities will need to translate this into practice. AI governance needs to provide educators with clear guidance, while recognising that responsible AI use will not look the same across every subject or assessment. Turnitin’s learning integrity framework recognises a spectrum ranging from no AI in some contexts to defined AI use cases and more open use in others.

Educators will also need greater agency over how AI is introduced into teaching and assessment. Turnitin’s latest Learning Integrity Insights found that AI decision-making is moving closer to faculty and teaching and learning leaders, while educators are asking for education-specific AI that is flexible enough to reflect how they actually teach and design assignments.

Technology therefore needs to adapt to pedagogy, rather than pedagogy adapting to the technology. This is the principle behind Turnitin Clarity’s configurable AI settings, which allow educators to determine the level and type of AI support appropriate for an individual assignment.

Over the next few years, universities will need to bring these pieces together: clear AI governance, greater educator agency, assessment practices that support learning integrity, and technology designed around the needs of teaching and learning.