In educational research, nonessential factors are commonly ignored and when accounted for, they are often treated statistically as fixed effects. Yet many researchers in these situations generalize their findings beyond the specific levels selected; however, the analyses may require treating the factor as a random effect. Such inappropriate analyses create the potential for an "education-as-fixed-effect fallacy." The present paper takes Clark's (1973) comments on the "language as fixed-effect fallacy" and applies them to educational research. The distinction between fixed and random models and the use of the quasi-F statistic are reviewed. Examples of commonly used mixed models with derivation of expected mean squares are provided and general guidelines for defining factors as fixed or random are suggested. (Contains 30 references.) (Author)