The term "education for all" in the context of inclusive schooling describes the aim that children with identified special/additional needs are fully included in education together with their typically developing peers. However, this is easier said than done as there are few easy-to-use methods that teachers can use while at the same time teaching the approbate curriculum to children with a full range of different abilities. The Good Inclusion Game (GIG) is a group contingency-based tool to create inclusive classrooms that utilizes principles of the applied branch of the science of behavior analysis (applied behavior analysis) and can be used across settings and academic subjects. The GIG was evaluated across nine classrooms including 93 boys and girls aged between 9 and 15 years of age, including 20 children with identified special educational needs. Findings show that the GIG reliably led to a significant increase of inclusive curriculum-focused activities with the collateral effect of decreasing disruptive behaviors for all children. Findings are discussed in the context of inclusive schooling and evidence-based education.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

The studies reported here examine how participants distribute resources to arbitrary stimuli in an equivalence class after one stimulus is given a social label. In Experiment 1, two 3-member equivalence classes were established with nonsense syllables (Class 1: A1 (ZID), B1 (YIM), C1 (FAP) and Class 2: A2 (VEK), B2 (RIX), C2 (KUD)) using matching-to-sample training. A social function was then assigned to B1 only, using the simple verbal statement "YIM is a Good person." Next, participants were instructed to allocate tokens to stimuli in whatever way they consider appropriate. In general, the percentage distribution of tokens allocated to Class 1 was greater than those allocated to Class 2. Participants were then informed that a mistake had been made “Sorry I have made a mistake. YIM was actually a bad person not a good person.” Participants were again asked to allocate tokens. In general, results showed a reduction in the distribution of tokens allocated to Class 1, with a relatively higher decrease for B1, and an increase in the distribution allocated to Class 2. Experiment 2 replicated Experiment 1 with the addition of a baseline assessment of token distribution prior to examining the effects of adding a social function to B1. During this baseline, the distribution of tokens was relatively similar across both classes. When social functions were added, marked differences occurred in the distribution depending on whether YIM was described as a “Good” or a “Bad” person. Results are discussed regarding transfer of function and its relevance to experimental social psychology.