Why students need to be prepared to cooperate: a cooperative nudge in statistics learning at university

Abstract

Despite the potential benefits of cooperative learning at university, its implementation is challenging. Here, we propose a theory-based 90-min intervention with 185 first-year psychology students in the challenging domain of statistics, consisting of an exercise phase and an individual learning post-test. We compared three conditions that manipulated the exercise phase: individual work, cooperative dyadic instructions (structuring three basic components of cooperative learning: positive goal interdependence, individual responsibility and promotive interactions) and cooperative dyadic interactions (the three basic components with an additional cooperative nudge, namely explaining why and how to cooperate in this task) in order to test whether a progressive increase in benefits occurs as the cooperative structure is reinforced. Results indicated a linear trend in individual post-test learning and competence perception, from individual work to cooperative instructions to cooperative interactions. Competence perception mediated the effect of experimental conditions on learning. The results highlight the benefits of the cooperative nudge.

Keywords:

• cooperative learning
• cooperative skills
• preparation for cooperation
• competence perception
• statistics learning

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The three conditions were designed to range from lower to higher involvement in learning statistics. However, one might argue that they also range from lower to higher cognitive demand, to the extent that the individual condition contains fewer elements to attend to than does the cooperative instructions condition, which in turn contains fewer elements than the cooperative interactions condition; in this respect, we checked students’ involvement during their exercises. Results showed that students’ involvement linearly increased from individual work to cooperative instructions to cooperative interactions.

2. In order to be fully transparent, we also present the results for all hypotheses with all participants (N = 187) and no transformation. For learning outcomes, the L1 contrast showed that individual learning outcomes progressed linearly and significantly from the individual work condition (M = 2.51) to the cooperative instructions condition (M = 2.65) to the cooperative interactions condition (M = 2.98), b = .24, t(184) = 1.99, p = .05. The deviation from linearity D2 was not significant: b = .03, t(184) = .42, p = .67. For competence perception, one student did not answer the questions (N = 186). Competence perception progressed linearly from the individual work condition (M = 4.50) to the cooperative instructions condition (M = 4.86) to the cooperative interactions condition (M = 5.03), b = .26, t(183) = 2.48, p = .01, whereas the deviation D2 was not significant, b = −.03, t(183) = −.48, p = .63. When students’ competence perception was entered as a mediator, the effect of the linear contrast L1 was reduced and became non-significant, b = .17, t = 1.42, p = .15, while the effect of students’ competence perception remained significant (b = .26, t = 3.33, p < .01). Regarding the manipulation check for the two cooperative conditions (N = 112 but one participant did not answer, final N = 111), students who did the exercises in the cooperative interactions condition reported more cooperation (M = 5.99) than did students in the cooperative instructions condition (M = 5.53), b = .46, t(109) = 2.26, p < .03. Students reported less competitive social comparison activities when they did the exercises in the cooperative interactions condition (M = 2.58) than they did in the cooperative instructions condition (M = 3.06), b = −.49, t(109) = −2.41, p < .02.