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Education in the age of AI should not choose between ignoring the technology and handing
learning over to it. The professional path is to integrate it where it increases human capacity,
to set limits where it threatens independence, integrity, or rights, and to review the effect

continuously. It is not enough to ask whether users liked the tool; we must ask whether they
learned more, whether they could transfer what they learned, and whether the opportunity

stayed fair and safe.

Having discussed the support of teaching and learning and classroom integrity, the next
chapter moves to evidence-based research use, where the quality of sources, citation,
authorship, and research integrity become a subject in their own right.

“The best educational use of AI is the one that leaves the learner more able to think
without it.”

Chapter Glossary
TABLE 6-23: GLOSSARY OF ESSENTIAL TERMS

Common
Term Plain-language explanation
abbreviation

An observable statement of what the learner will be
Learning outcome -
able to do.

Constructive Agreement among the outcome, the activity, and the
-
alignment assessment.

Planning from the desired result and its evidence
Backward design -
back to the activity.

The product or performance that shows the outcome
Evidence of learning -
was achieved.

What the learner must already know before the new
Prior knowledge -
learning begins.

A held idea that is incorrect and blocks new
Misconception -
understanding.

Example and non- A case the rule applies to, and a near case it does
-
example not, used to mark the boundary.

A solved problem that explains the reason for each
Worked example -
step.

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