What I mean by readiness
I use readiness to describe a learner’s ability to act with reasons within a defined scope. In software engineering, I want a student to connect a requirement to a design choice, anticipate a relevant failure and explain what evidence would change that choice. I would not infer readiness for every professional setting from success in one classroom task. The scope of the claim should match the scope of the evidence.
I still consider disciplinary knowledge essential. A student cannot reason well about reliability without understanding the mechanisms and assumptions involved. I want explanations, examples and diagrams to make those mechanisms accessible, followed by opportunities to use them. I become concerned when completing content replaces checking what a learner can do with it, or when a visually impressive lesson leaves the important technical reasoning implicit.
The smallest useful change in an assessment
I would begin with a manageable task and then change one consequential condition. In a hypothetical architecture exercise, a student might first explain a proposed redundancy design. I might then reveal a shared power dependency and ask the student to reassess it. I learn more from the resulting revision than from another repetition of the original explanation, because the student has to connect a changed fact to its engineering consequence.
I would not make difficulty itself the objective. I want an explicit progression from identifying a mechanism, to applying it in a supported example, to comparing alternatives, and finally defending a choice under a changed constraint. I would provide feedback along that progression and allow revision. My purpose is to make developing judgment visible while students still have a realistic opportunity to improve it.
What AI changes in the evidence
I welcome AI assistance when its role is explicit and consistent with the learning task. If a tool helps produce an artifact, I need evidence of the learner’s contribution and understanding before drawing conclusions about individual capability. I might ask for a short explanation, a modification to the solution or a test of an assumption. I would choose the method to fit the discipline, access needs and available teaching time.
I connect this position to my educational design work across CIMT, IMAM and the iSCARB teaching system. I use these efforts to investigate how instructional structure, interaction and evidence can remain visible when AI helps produce learning materials. I do not regard a prescribed slide count or a completed design checklist as proof of learning. I would want evidence from student reasoning and performance, interpreted with the limitations of the study or classroom context.
What I mean by sovereignty in AI-enabled education
I connect the identity question in IMAM to who defines the purpose of learning, selects the knowledge and judges the evidence of readiness. I believe a university should be able to explain and revise those choices in its own language and disciplinary context, even when it uses external AI tools. I would judge that control by visible authority over curriculum, assessment and revision; an Arabic interface alone would not establish it.
A claim I am prepared to revise
I would reconsider an assessment if it rewards fluent performance without improving the evidence of understanding, imposes excessive workload or disadvantages learners for reasons unrelated to the intended capability. My commitment is to justified inferences about learning. I want students to know what counts as evidence, teachers to see where reasoning breaks down, and institutions to explain what their claims of readiness actually mean.