MOOCs and Motivation

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Addressing learner motivation in self-directed open learning environments

Reading about motivation and volition in instructional design, I contextualized the ideas within self-directed open learning models, like MOOCs, which reflect social constructivism. Here, participants join large groups working toward a common goal, but pursuing their goals in smaller self-selected learning communities.

For most participants, MOOCs are voluntary and pursued independently. Often loosely structured, these courses allow individuals meet their own learning goals in contexts that are interesting to them while connecting with others of similar mind. This embodies Keller’s (Simsek, 2014) first two principles of motivation: attention and relevance .

MOOCs can draw thousands of participants suggesting that many people are highly motivated to learn. However, with completion rates averaging only 13% (Jordan, n.d.) there seems to be a lack of volition to see the program through to the end.

Learning systems such as this, Bouchard (2009) suggests, create a pedagogical void; the learner herself is both learner and educator. Pedagogical tasks such as sequencing, pacing, formulating objectives, finding resources, following up, and evaluating may or may not be part of the learners’ skill set. In their absence, learners may feel overwhelmed, experience failure, and lose the will to continue (Knox, 2014). These three outcomes reflect the absence of Keller’s (Simsek, 2014) last three principles of motivation: confidence, satisfaction, and volition.

Clarà & Barberà (2014) suggest that MOOCs represent a way of being, rather than a way of learning. That technology-enabled ubiquitous connection and constant engagement reflect the practice behind an attitude of life-long learning rather than the rigor required for formal education. In this respect, MOOC participants neither fail nor succeed, they just make more or less progress to achieving a learning goal.

Instructional planning for MOOCs and social constructivism with autonomous learners has to address the pedagogical void. While learners are highly motivated to begin with, and can act on their own curiosity, instructional designers have to consider developing the metacognitive processes that increase confidence, lead to success, and sustain learner volition.

Additionally, the connectivist learning approach, an offshoot of social constructivism, approaches learning differently through a process of aggregation, remixing and reflecting, re-purposing, and sharing (Kop & Fournier, 2011), very different from experiences these learners may have had in the past. Orienting learners to the big pedagogical picture may also contribute to success.


Bouchard, P. (2009). Pedagogy without a teacher: What are the limits? International Journal of Self-Directed Learning, 6(2), 13–22.

Clarà, M., & Barberà, E. (2014). Three problems with the connectivist conception of learning. Journal of Computer Assisted Learning, 30(3), 197–206. doi:10.1111/jcal.12040

Jordan, K. (n.d.). MOOC Completion Rates: The Data. Retrieved from

Knox, J. (2014). Digital culture clash: “Massive” education in the e-learning and digital cultures MOOC. Distance Education, 35(2), 164–177. Retrieved from

Kop, R., & Fournier, H. (2011). New dimensions to self-directed learning in an open networked learning environment. International Journal of Self-Directed Learning, 7(2), 1–20. Retrieved from

Simsek, A. (2014). Interview with John M . Keller on Motivational Design of Instruction, 5(1), 90–95.

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