Detailed Conceptual Framework Diagram (University Level) — an alternative version of the Conceptual Framework: Technology Acceptance Model, generated by AI and fully editable. Download the PNG for quizzes, homework or slides.
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OUTPUT · 16:9 · PNGThis Detailed Conceptual Framework Diagram (University Level) expands the standard Technology Acceptance Model beyond its six familiar components: external variables, perceived usefulness, perceived ease of use, attitude toward use, behavioral intention, and actual use. It adds system quality, information quality, social influence, facilitating conditions, digital literacy, trust, perceived risk, and demographic controls. Unlike the standard main diagram, which introduces TAM through a small set of causal arrows, this version distinguishes independent, mediating, moderating, control, and dependent variables. Use it when students must move from recognizing a theory to specifying a researchable model.
Read the solid arrows as proposed direct effects and the dashed arrows as moderation paths. Hypotheses H1–H5 identify testable relationships, while construct labels indicate measurement dimensions such as usefulness for performance, ease of learning, attitudinal evaluation, intention frequency, and observed usage. Mediators explain how an external factor influences adoption; moderators indicate when or for whom an effect changes. Control variables are grouped at the bottom to separate background influences from the focal theory. This version is preferable to the standard main diagram for operationalization, hypothesis development, survey design, and statistical analysis, but not for a brief first introduction to TAM.
The standard diagram is best for learning the core adoption sequence, whereas this version supports research design by separating variable roles, measurement dimensions, hypotheses, and controls. Use the detailed version when the task requires operationalization or empirical testing rather than simple theory recognition.
No. Constructs should be retained only when theory, prior evidence, and the research question justify them; unnecessary variables reduce parsimony and may create identification or multicollinearity problems. The expanded diagram is a planning template, not a requirement to estimate every possible relationship.