Effective Metaheuristic Assignment to Improve Equivalence in Small Experimental Pedagogical Groups
We propose a new metaheuristic algorithm to find “good” solutions for the assignment of small treatment-control groups, minimising the random resource. Using simulated cases, we achieved 100% groups with equivalence levels equal to or higher than those generated with the simple random assignment, complete random assignment and block random assignment designs. In addition, as a secondary objective to test the new algorithm, we found that short out of-class essays implied that treatment group marks were 14% higher than in the control group.
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