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Description
Guided by four review questions (RQs), this critical narrative review examines how translation strategy teaching is changing as neural machine translation and large language models enter digital higher education. The RQs address shifts in the conceptualization of strategy, the strength and limits of effectiveness evidence, changes in instruction and assessment, and implications for Vietnamese higher education. It synthesizes 69 works published from 2023 to 11 October 2026, spanning system evaluation, human assessment, translation-process research, classroom studies, and Vietnam-focused evidence, and uses one earlier Vietnamese study as historical context. The analysis identifies four shifts: from decontextualized sentence conversion to brief-driven task design; from one-shot prompting to the orchestration of examples, context, terminology, and candidate versions; from generic correction to error-led post-editing and bilingual verification; and from product-only grading to assessment of process, rationale, and AI literacy. Gains are conditional: results vary by language pair, genre, domain, prompt, and model version, and fluent output does not warrant trust. Evidence from Vietnam remains limited and methodologically heterogeneous. The review proposes a Context–Strategy–Evidence–Agency (CSEA) framework for Vietnamese higher education. CSEA stages learner analysis, purposeful strategy trials, source-grounded verification, reflective revision, and risk-tiered assessment, while identifying priorities for validation.