What term describes a design where more than one independent variable is manipulated?

What term describes a design where more than one independent variable is manipulated?

• A. Multi-factorial design
• B. Single-factor design
• C. Blocked design
• D. Randomized factorial design

Answer: (A)

The design tested is one in which more than one independent variable is actively varied across conditions, allowing you to look at both the separate effects of each variable and how they combine to influence outcomes. This is the essence of a multi-factorial (factorial) design: you cross levels of each factor so the effects of one variable can interact with another. For example, you might test two factors—dosage level (high vs. low) and method of presentation (visual vs. auditory)—to see not only their individual impacts on learning but also whether the effect of dosage depends on the presentation method. This differs from a single-factor design, which manipulates only one variable. A blocked design organizes participants to control variance due to nuisance factors but doesn’t focus on manipulating multiple independent variables. A randomized factorial design is still a factorial design, with random assignment, but the key idea remains the manipulation of more than one factor.

The design tested is one in which more than one independent variable is actively varied across conditions, allowing you to look at both the separate effects of each variable and how they combine to influence outcomes. This is the essence of a multi-factorial (factorial) design: you cross levels of each factor so the effects of one variable can interact with another. For example, you might test two factors—dosage level (high vs. low) and method of presentation (visual vs. auditory)—to see not only their individual impacts on learning but also whether the effect of dosage depends on the presentation method.

This differs from a single-factor design, which manipulates only one variable. A blocked design organizes participants to control variance due to nuisance factors but doesn’t focus on manipulating multiple independent variables. A randomized factorial design is still a factorial design, with random assignment, but the key idea remains the manipulation of more than one factor.