<![CDATA[Graduate students in Educational Technology require learning resources that move beyond describing online-learning design frameworks to support evidence-based interpretation, design decision-making, documentation, and revision. This study conducted a 2020–2025 Scopus-based systematic mapping review with bibliometric analysis and a focused qualitative synthesis to derive evidence-informed requirements for a digital workbook for learning the Integrative Learning Design Framework for Online Learning (ILDF) through Case-Based Learning (CBL), while defining a bounded role for artificial intelligence (AI). Three complementary search blocks addressed digital workbooks and related resources, CBL, and online/instructional learning design; no dedicated AI search block was conducted. RStudio, Bibliometrix, and Biblioshiny supported deduplication, descriptive science mapping, and conceptual-structure analysis. Of 1,147 retrieved records, 26 duplicates were removed, 1,121 records were screened, and 26 studies were retained for the focused synthesis. Structured digital resources were associated with guided task completion, documentation, reflection, and formative feedback, whereas CBL was associated with knowledge application, reasoning, decision-making, and theory–practice transfer. The evidence base was heterogeneous and concentrated outside instructional-design education, and the ILDF was rarely represented as explicit student-facing content. AI-related literature was therefore used contextually to define governance and support boundaries rather than treated as a comprehensively searched evidence strand. The synthesis supports a role-based design logic rather than a claim of product effectiveness: the ILDF is the framework to be learned, CBL is the instructional approach, the digital workbook is the process scaffold, and AI is a bounded authoring or learner-support aid whose actor, purpose, and outputs require human oversight. These requirements provide a defensible basis for prototype development and staged empirical validation.]]>
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