priming of autonomous motivation
At three secondary schools, we divided the same group task into classes with a group self-evaluation protocol (experimental) and classes without (control). The total involved 355 students with an average age of 16.25. At the end of the project, when handing in the workpiece, the students completed a motivation survey known as the “intrinsic motivation inventory” (IMI). It measures (self-reported) feelings of choice, interest & enjoyment, competence, effort & importance, pressure & tension, value & usefulness and relatedness. Each question has a Likert scale of 1-7, going from “not-at-all-true” to “very-true”. Values below 4 indicate negative sentiments of choice, enjoyment, etc., whereas values above 4 indicate positive sentiments. We have calculated mean values for each subscale (“choice”, “interest & enjoinment”, etc.) of the control and experimental classes. There is no absolute scale: what matters here is that higher the values, with the exception of pressure & tension, indicate a higher degree of internalization of motivation (more autonomous motivation or, conversely, less controlled motivation). We show the results in two ways: first, in the form of a boxplot (figure 1), so that you can clearly see the distribution of student responses, and second, as a simple table with mean values and standard deviations (table 1). For more information about boxplots
With respect to the control classes, whereas the mean values are above the middle (or neutral) point of the Likert scale, some 25% of the students had nevertheless not perceived much “choice”, “value/usefulness” and “interest/enjoyment”. For pressure/tension, nearly half the population had selected values above the middle point. As examples, whereas the project really offers lots of choice, the students hardly perceive it as such (M = 4.90, SD = 1.387). The project was meant to prepare students for a more self-regulated learning attitude for the University but they saw little value or usefulness in the exercise M = 4.73, SD = 1.353) and they only moderately enjoyed the project (M = 4.71, SD = 0.993). The perception was considerably better in the experimental classes where we used the group self-evaluation procedure. When accumulating the results of all control (7 classes, n = 224) and experimental classes (5 classes, n = 131), we observed important (significant) increases in the outcome of the IMI with the exception of “pressure/tension”, which was reduced.
Besides significant differences in mean values we also noted a systematic reduction in standard deviation (SD) values of the IMI scales from the experimental classes (the boxes are much smaller in figure 1 and the values are much smaller in table 2, row 4 (SD)). We therefore calculated the significance of differences in variance for each subscale with the Brown-Forsythe test. We observed a significant reduction in variance in the experimental classes for subscales “choice” (p < .01), “value/usefulness” (p < .01), “relatedness” (p < .01), “effort” (p = .020) and “pressure/tension” (p < .01), but not “interest/enjoyment” (p = .08) and “competence”(p = .17) (table 1, row 6).
Table 2. Effect Size of Group Self-Evaluation on the Response Scores of the Intrinsic Motivation InventoryPositive Hedge’s g values indicate an increase in the values for the experimental classes, and negative values indicate a decrease for the experimental classes.
We next applied Hedges’ calculations to estimate the effect size and found large and medium effects for all subscales, with “interest/enjoyment”, “choice” and “value/usefulness” ranking in the top 3 (table 2).
These results imply that the students not only had a better appreciation, they also had a more homogeneous appreciation of the collaborative project under the condition of self-evaluation; as if they were all aligned.
Statistical analyses (not shown here) revealed that these results are not the consequence of the variation in years, teachers or schools. When corrected for teachers and years, which substantial reduction in the size of the populations, we remain a significant change for all subscales, with the exception of “effort” and “relatedness”. Their values were already very high in the control condition, so little room for improvement. In conclusion, we measure a true positive effect of the experimental intervention. In this respect we do not distinguish between the impact of the voting of ground rules (mid- and end-of-project) and the impact of the progress-report checklist (mid-project): it is the effect of the sum of the two events that we measure.
Details: description of the collaborative project and experimental condition
We have tested the group self-evaluation protocol in three high schools where students worked on a group-based exam project that counted toward their school diploma (a high stakes project in a real educational setting). The participants had an average age of M = 16.25 (SD = 0.5) and the population comprised 53.8% women and 46.2% men. They were in their 2nd year (K11) of preparation of the “scientific baccalauréat” a diploma equivalent of an American High School diploma or an English GCE A-levels. In total, 355 participants were involved, separated over 12 classes: 7 control classes (control condition, n = 224, without intervention) and 5 experimental classes (experimental condition, n = 131, with whom we carried out a group self-evaluation procedure) (table 1). The group self-evaluation procedure employed in the experimental classes qualifies as an “informational external-intervention” (Deci & Ryan, 1980; Deci & Ryan, 1985; described in Chapter 6, p130, Ryan & Deci, 2017). It is an experimental manipulation without randomization (American Psychology Association, 2020).
The collaborative project (named TPE) was designed and planned in the French national curriculum by the Ministry of National Education (Ministère de l’Education Nationale) with the intention to give students the opportunity to work autonomously in small groups on a project of their choice (chosen from a large list of social themes formulated in the government instructions) with an additional requirement that they had to integrate biology with one other discipline (physics, chemistry, mathematics or social sciences). According to the instructions of the Ministry the project is meant to be autonomy-supportive and serves to prepare students for a more self-regulating learning style that would be necessary to succeed in higher education. The project groups can be described as “student project groups” with the characteristics of: low authority differentiation, moderate temporal stability (one semester), and, at the onset, member interchangeability and a lack of skill differentiation (Hollenbeck et al., 2012).
A large majority of groups (86%) consisted of 3 members. Groups worked on their project throughout the autumn semester, corresponding to 15 weeks, with formal work sessions of 2 hours held in computer-cluster rooms each week. These dedicated work sessions were accompanied by one biology and one physics teacher of the school. These teachers provided the necessary cognitive scaffolding in scheduled bi-weekly get-togethers with the groups (discussed in “setting the ground rules” and “assessment of group member engagement”.)
Details: Measuring the quality of motivation with an intrinsic motivation inventory
In order to answer our research question, whether the group self-evaluation procedure impacts on the quality of motivation, we asked students to complete a paper-version of a full scale Intrinsic Motivation Inventory (IMI) (Deci et al., 1994; McAuley et al., 1989) when they handed in their project reports. The IMI is a multidimensional scale survey intended to measure the subjective experiences of participants following task participation (Ryan, 1982). Various iterations of the IMI have been in use for more than 30 years, with well-established validity and subscale reliability across tasks, conditions, and settings (McAuley et al., 1989). The scale has seven primary subscales, detailed below (table 2), that can be mixed and matched to suit research needs. Although referred to as the Intrinsic Motivation Inventory, the survey measures more than just intrinsic motivation; it covers a range of criteria that indicate whether or not students adopted a self-determined learning approach (autonomous or internalized regulation of behavior).
For a brief explanation of regulation of behavior we refer to Self-Determination Theory, autonomy and collaborative attitude (it concerns figure 1. Taxonomy of human motivation).
The original questionnaire, developed by Ryan and Deci, and relevant literature can be retrieved from the Self Determination Theory website. If you require more experimental detail, click here.
References
American Psychology Association. (2020). Publication Manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000
Deci, E. L., Eghrari, H., Patrick, B. C., & Leone, D. R. (1994). Facilitating internalization: The self-determination perspective. Journal of Personality, 62, 119–142. https://doi.org/10.1111/j.1467-6494.1994.tb00797.x
Deci, E.L., & Ryan, R.M. (1980). The empirical exploration of intrinsic motivational processes.In L. Berkowitz (Ed). Advances in experimental social psychology (Vol.13, pp. 39-80). Academic Press. https://doi.org/10.1016/S0065-2601(08)60130-6
Deci E.L., & Ryan, R.M. (1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109-134. https://selfdeterminationtheory.org/SDT/documents/1985_DeciRyan_GCOS.pdf
Hollenbeck, J.R., Beersma, B., & Schouten, M.E. (2012). Beyond team types and taxonomies: a dimensional scaling conceptualization for team description. Academy of Management Review, 37(1), 82-106. https://doi.org/10.5465/amr.2010.0181
Kramer, I.M., Franc, N., Maricourt, F., Cohen, M., Fau, T., Nogues, X., van der Velden, W. & Kusurkar, R. (2021). Group Self-Evalulation Primes for Autonomous Motivation in Collaborative Learning. Advance. Preprint. https://doi.org/10.31124/advance.17105573.v1
McAuley, E., Duncan, T., & Tammen, V. V. (1989). Psychometric properties of the intrinsic motivation inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60(1), 48–58. https://doi.org/10.1080/02701367.1989.10607413
Ryan, R. (1982). Control and information in the intrapersonal sphere an extension of cognitive evaluation theory. Journal of Personality and Social Psychology, 43, 450-461. https://doi.org/10.1037/0022-3514.43.3.450
Ryan, R.M., & Deci, E.L. (2017). Self-determination theory: basic psychological needs in motivation, development, and wellness. The Guilford Press. ISBN 9781 4625 2876 9. https://doi.org/10.1521/978.14625/28806
group working and motivation 