What I mean by readiness
I use readiness to describe a learner’s ability to make and defend a judgment 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 also want the student to identify what remains uncertain. I would limit any claim about professional readiness to what the assessed task and its evidence can support.
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 put this position to work through iSCARB. I want a learning sequence to connect the initial problem, the relevant mechanisms, a defensible choice and evidence of the learner’s reasoning. I would examine how the learner responds when an assumption fails or a constraint changes. A completed lecture, a prescribed slide count or a polished submission cannot by itself establish that the learner can make that judgment.
How context belongs inside the learning design
I place IMAM within iSCARB as a contextual design layer. I want language, local examples and educational purpose to make the disciplinary problem meaningful without weakening its technical substance. I would ask whether a contextual choice helps students explain an assumption, examine evidence or defend a revision. I keep responsibility for curriculum and assessment with the educational institution, and I would review any design choice that makes the evidence of learning harder to interpret.
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.