Abstract
Implementation intentions have been proven to be effective to help individuals reaching their goals in medical interventions. The current study investigated whether this is true as well for individuals who enrolled in MOOCs. Implementation intentions are concerned with planning where, when, and how learning will take place as well as planning how much time will be allocated to the learning and determining how potential problems will be resolved (referred to as shielding behavior). The current study investigated the relationship between the degree to which implementation intentions were formed and the degree to which goals were achieved, thereby taking the time spent for studying MOOCs and the number of barriers encountered into account. Goal achievement was taken relative to the intended goal achievement (more than intended, all as intended, less than intended).
The results, based on a small sample of MOOC learners enrolled a single MOOC, revealed that the two latent classes of implementation intentions (representing the group of MOOC learners with strong and the group with weak implementation intentions) were completely determined by whether these MOOC learners were time planning or not. The results also revealed limited influence of implementation intentions on relative goal achievement and no influence on the time spent for studying MOOCs. Implementation intentions negatively influenced the impact of the number of barriers on relative goal achievement but this finding was not significant which also means that there was no impact of the number of barriers on this relative goal achievement. But there was a direct effect of time spent for studying MOOCs on relative goal achievement, suggesting that the more time was spent on studying MOOCs the higher the probability was that intended goal achievement would be realized. In sum, we found some indications that implementation intentions can be as effective on relative goal achievement in MOOCs as they are in medical interventions. However, much stronger evidence is needed.
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Notes
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The Bonferroni adjustment means that the normal alpha values of .05 and .01 were divided by three as there were three related variables: ‘time spent,’ ‘number of barriers,’ and ‘relative goal achievement;’ resulting in the values .017 and .0034 after rounding respectively.
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Kreijns, K., Kalz, M., Castaño-Muñoz, J., Punie, Y. (2017). Implementation Intentions and How They Influence Goal Achievement in MOOCs. In: Delgado Kloos, C., Jermann, P., Pérez-Sanagustín, M., Seaton, D., White, S. (eds) Digital Education: Out to the World and Back to the Campus. EMOOCs 2017. Lecture Notes in Computer Science(), vol 10254. Springer, Cham. https://doi.org/10.1007/978-3-319-59044-8_28
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