MOOCs – Models for Learning in the 21st Century: Part 2

MOOCs – Models for Learning in the 21st Century:
Part 2

Mary Harrsch
Networks and Management Information Systems (Retired)
University of Oregon College of Education

This is a cross-post from the Information Age Education newsletter

In the previous newsletter, I described my experience as a learner in a MOOC hosted by FutureLearn, a UK distance education provider. MOOCs are now being used to teach both pre-college and higher education students. In this newsletter, we will explore the science behind MOOCs as evolving models for learning. 

Working Memory Capacity

Back in the 1960s, psychologists George Armitage Miller, Eugene Galanter, and Karl Pribram coined the term “working memory” to describe the human brain’s cognitive system used for temporarily holding information available for processing (Pribram, et al., 1960). Since each human being’s physical traits are determined by a unique combination of genes in their DNA sequence, each human brain has a unique capacity of working memory. However, some psychologists think genetics is only responsible for about half of this attribute. (Engelhardt, et al., 2016)

According to developmental psychologists, the developing brain’s working memory capacity (WMC) increases gradually over the course of childhood, reaches its mature level (unique to each individual) in their early twenties (American Psychological Association), then gradually decreases in old age (Salthouse, 1994).

Working memory capacity is most commonly tested by a dual-task paradigm invented by Daneman and Carpenter in 1980. (Daneman & Carpenter, 1980) Subjects read a number of sentences (usually between two and six) and try to remember the last word of each sentence. At the end of the list of sentences, they repeat back the memorized words in their correct order.

In an academic setting, WMC has been shown to be an important predictor of learning, reasoning, and comprehension (Conway, et al., 2007). But, a human’s working memory, a finite resource, is cluttered with both task-related and unrelated information at any given time. If a student is juggling multiple commitments requiring executive thought processes—processes necessary for the cognitive control of behavior—a student's ability to absorb large amounts of new information may be compromised. The increasing cost of higher education has likely increased this probability. A large majority of college students are now dependent on employment to finance their education. Based on a report released by the Center on Education and the Workforce of Georgetown University, 70% of college students (including myself at the time!) now work while enrolled (Carnevale, et al., 2015). This certainly must have an impact on their ability to maintain focus in the classroom.

So, task performance, in this case learning, is dependent upon an individual’s executive-control ability to keep the learning material being presented mentally active and accessible enough to influence the individual’s behavior (Kane & McVay, 2012).

The Importance of Attention

Proponents of executive-attention theory claim that, although individuals with lower WMC appear to suffer more from distractions created by thoughts unrelated to the task at hand, termed mind wandering, goal achievement is ultimately a product of an individual’s attention control system (Engle & Kane, 2004).

So, what is the average attention span of an adult learner?

Current researchers argue that the average attention span of American adults has dropped and it is now limited to 20, 10, or even five minutes,” says award-winning instructional designer Art Kohn. “The late educator Neil Postman believed that modern technologies such as television and the Internet are actually reducing people’s attention span. He proposed that our frantic world has somehow rewired the human brain, making us less able to attend to things for long periods. In fact, there is precedent for such a view. For example, the human eyeball, which is a sensory outgrowth of the brain, actually changes shape because of early visual experience. For instance, if a child engages in close-up activities like reading or playing computer games for prolonged periods, the human eyeball develops into a more oval shape to better accommodate these close-up images. The downside of this reshaping, however, is that the children then become myopic (nearsighted) and have difficulty focusing on distant objects.

Researchers propose a similar process to explain the shortening of adults’ attention spans (and perhaps the epidemic of attention deficit disorders in children). The theory states that because of exposure to our frantic world with its persistent thrills, challenges, and competition, a person’s brain somehow rewires itself to better accommodate this rapid pace. The downside is that same brain has difficulty focusing on the more mundane experiences of everyday life (Kohn, 2014).

Kohn also points to a new theory that claims learners, especially Millennials, have become accustomed to seeking information on an as-needed basis and are unwilling to attend to material that is not perceived as being immediately interesting and valuable. Quoting again from Kohn, “The advent of instant information has made people impatient with traditional spoon-fed training. Instead, they want to guzzle knowledge when, but only when, they need it.”

How MOOCs Address Learning Challenges

I am hardly a Millennial and not even technically a digital native. However, I think these psychological factors clearly explain my own inability to stay focused for an hour of passive listening in a traditional classroom, and also the apparent inattention of many of my much younger classmates. Like 65% of all adults, I am predominantly a visual learner. So, a lecture that has few visual components would not be presenting information in a format that I would assimilate easily.

However, FutureLearn and other organizations are now using the model of interleaved lessons, often rich with graphics and video clips, coupled with discussion forums and computerized assessment tools that provide immediate feedback. I find this format meets my needs. In addition, students can easily pause or replay segments of recorded information to review and reinforce their understanding of the information presented.

Furthermore, the chunking of information into learning experiences that incorporate a variety of activities requiring about 15 - 20 minutes of concentration per exercise, like those I encountered in my FutureLearn course, also more closely approximates the average adult attention span. In addition, the discussion questions and interactions with classmate responses provide an opportunity to reflect on the information provided and correlate it with previous learning and experiences.

Smallwood and Schooler have asserted that tasks requiring controlled processing are less likely to support mind-wandering. The rationale behind this assertion is that the scarcity of executive resources makes it hard for a person to divert actions to task-unrelated thoughts. Hence, tasks requiring a maximum degree of cognitive control are less prone to mind-wandering than those requiring minimal cognitive control (James, 2018).

The peer-to-peer discussion forums surrounding open essay-type answers used with humanities courses also provide much quicker feedback than you would get from an instructor, even one assisted by three to five teaching assistants. Daphne Kohler, co-founder of U.S.-based MOOC provider Coursera, reports that in their courses, the median response to a question posted in a lesson's global discussion forum was 22 minutes (coursera, 2018). She attributes this to the worldwide nature of student enrollments. She pointed out that, regardless what time of the day you were working on a class unit, someone somewhere else in the world was often working on that same class unit at the same time. So, students often help each other much more quickly than the faculty facilitators (Kohler, 2012).

Anant Agarwhal is another U.S.-based MOOC developer, founder of EdX, and a MOOC instructor. He agrees with Kohler, pointing out that the first peer answer may not be totally correct but, as more and more students join the discussion, a correct answer usually surfaces. Agarwhal also agrees with an MIT colleague who says timely feedback turns teachable moments into positive learning outcomes (Agarwhal, 2013).

The 5-stage Process of Learning

In fact, the process of reflection and discussion is so important to refine a learner's understanding of new material that it is included in Taylor and Hamdy's proposed 5-stage process of learning as outlined in their paper, Adult Learning Theories: Implications for Learning and Teaching in Medical Education. The quote below and the following diagram come from this article (Taylor & Hamdy, June, 2013). Notice the centrality of feedback in the diagram.

[A] discussion between individuals will increase the amount of practical knowledge, and that some things remain a mystery until we talk to someone else with a different range of knowledge or understanding. It follows that the more diverse a learning group's membership is, the more likely the individuals within the group are to learn.

Taylor and Hamdy argue that the feedback phase, where students reflect on new information, compare it to their existing knowledge and, through discussion, with the knowledge of other students, is arguably the most crucial phase. Continuing to quote from Taylor & Handy:

…it is where the learner articulates their newly acquired knowledge and tests it against what their peers and teachers believe. The feedback will either reinforce their schema, or oblige the learner to reconsider it in the light of new information.

I believe that choosing a MOOC that supports a dynamic environment for discussion and feedback with course peers is essential to gaining the most out of the learning experience.

My first MOOC was the FutureLearn course, Superpowers of the Ancient World. I have since taken seven other MOOC courses from FutureLearn and one online course from ArcGIS, a software firm that develops mapping applications for geographic information systems. The ArcGIS class was taught by software developers rather than by academic faculty and included only a single discussion pool not related to specific course exercises. I learned the material because I am particularly adept at learning to use software and also had twenty years of database design experience. But, the course itself offered little opportunity to learn from others with different backgrounds or ideas. I sorely missed the exchange of ideas and inspiration I received in the FutureLearn environment.

Summary and Final Remarks

The importance of in-depth mental processing to learning retention was recognized as far back as 1972 by psychologists Fergus I. M. Craik and Robert S. Lockhart in their foundational paper, Levels of Processing: A Framework for Memory Research, published in the Journal of Verbal Learning and Verbal Behavior (Craik & Lockhart, 1972). Their research found that information with strong visual images or many associations with existing knowledge would be processed at a deeper level and would therefore be retained much longer.

They also acknowledged that retention is further aided by recirculating information to extend attention on the new material coupled with analysis. comparisons, and elaboration. They emphasized that these processes are really necessary for students to understand and remember content.

The traditional lecture model, used for centuries in higher education as the primary teaching format, simply does not provide these opportunities. First, the length of the information presentation, usually 45 minutes to an hour, exceeds the average adult’s attention span. In addition, non-course related urgent tasks like employment or family responsibilities that are a factor for more than 70% of modern students often can compete with the learning task for a student’s attention. Craik and Lockhart point out that studies of selective attention and sensory storage have shown that non-attended verbal material is lost within a few seconds.

An effective model developed for MOOCs, on the other hand, can offer an alternative experience that addresses the restrictions of a human brain’s limited working memory capacity and individual differences in ability to sustain executive control in a distracted state. Since all participants are equipped with a computer, key concepts can easily be illustrated with multimedia, increasing the visual content for visual learners (65% of all adult learners). The computer connectives can provide forums where course material can be analyzed and compared with the existing knowledge of both the individual student, and of large numbers of classmates with vastly different life experiences.

Critics of MOOCs point to the huge number of enrollees who fail to complete their courses. But, Anant Agarwhal, founder of EdX and a MOOC instructor, explained in his June, 2013, TED Talk that even though only a little more than 7,000 out of 150,000 students who signed up for one of his classes completed it, he would have had to have taught 40 years in a traditional classroom to reach those 7,000 students (Agarwal, June, 2013). 

References and Resources

Agarwal, A. (June, 2013). Why massive open online courses (still) matter. TED Talks. (Video file.) Retrieved from https://www.ted.com/talks/anant_agarwal_why_massively_open_online_courses_
still_matter.

American Psychological Association (n.d.). Memory and aging. Retrieved from https://www.apa.org/pi/aging/memory-and-aging.pdf.

Baddeley, A. (October, 2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience. 4 (10): 29-39. Commercially available online from doi:10.1038/nrn1201. PMID 14523382.

Carnevale, A., Smith, N., Melton, M., & Price, E. (2015). Learning while earning: The new normal. Retrieved from https://cew.georgetown.edu/cew-reports/workinglearners/.

Conway, A.R., Kane M.J., & Engle, R.W. (December, 2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences. 7 (12): 547-552. Commercially available online from doi:10.1016/j.tics.2003.10.005. PMID 14643371.

coursera (2018). Take the world's best courses, online. Retrieved from https://www.coursera.org/.

Craik, F.I.M., & Lockhart, R.S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior. 11: 671-684.

Daneman, M., & Carpenter, P.A. (August ,1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior. 19 (4): 450-466. Commercially available online from doi:10.1016/S0022-5371(80)90312-6.

Engelhardt, L.E., Mann, F.D., Briley, D.A., Church, J.A, Harden, K.P., & Tucker-Drob, E.M.  (September, 2016). Strong genetic overlap between executive functions and intelligence. Journal of Experimental Psychology: General. 145 (9): 1141-1159. Commercially available online from http://psycnet.apa.org/doiLanding?doi=10.1037%2Fxge0000195.

Engle, R.W,, & Kane, M.J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. In B. Ross (ed.), The psychology of learning and motivation. New York: Academic.

James, H.J. (n.d.). Attention span in adults. Academia.edu. Retrieved from https://www.academia.edu/8749503/Attention_Span_in_Adults.

Kane, M, & McVay, J. (2012). What mind wandering reveals about executive-control abilities and failures. Current Directions in Psychological Science. 21 (5): 348-354. Retrieved from http://www.jstor.org.libproxy.uoregon.edu/stable/44318607.

Kohn, A. (2014). Brain science: focus – Can you pay attention? Learning Solutions. Retrieved from https://www.learningsolutionsmag.com/articles/1440/brain-science-focuscan-you-pay-attention.

Koller, D. (June, 2012). What we're learning from online education. TED Talks. [Video file.] Retrieved from https://www.ted.com/talks/daphne_koller_what_we_re_learning_from_online_
education.

Pribram, K.H., Miller, G.A., & Galanter, E. (1960). Plans and the structure of behavior. New York: Holt, Rinehart & Winston.

Salthouse, T.A. (1994). The aging of working memory. Neuropsychology. 8 (4):535-543. Retrieved from https://www.researchgate.net/publication/232504870_The_Aging_of_Working_
Memory.

Smallwood, J., & Schooler, J. (2006). The restless mind. Psychological Bulletin. 132: 946-958. Retrieved from https://themindwanders.files.wordpress.com/2010/09/mind-wandering1.pdf.

Taylor, D.C., & Hamdy, H. (September 4, 2013). Adult learning theories: Implications for learning and teaching in medical education. AMEE Guide No. 83. Med Teacher. Retrieved from https://www.tandfonline.com/doi/full/10.3109/0142159X.2013.828153?scroll=top&needAccess=true.