The Science of Learning in a Social Science Context

Melinda Messineo

Perhaps you have heard the quote attributed to William Glasser suggesting that we learn 10 percent of what we read, 20 percent of what we hear, 80 percent of what we experience, and 95 percent of what we teach others. Possibly an adaptation of Dale's Cone of Experience (1969), the percentages are merely symbolic and are meant to illustrate the importance of engagement in the learning process. Research shows that the more active you are in the learning process, the more it "sticks" and the more capable you are at applying and adapting what you have learned to other contexts (Meyers and Jones 1993). The last 30 years have witnessed a significant push for higher education to employ active-learning strategies (Pascarella and Terenzini 2005; see also the journal Active Learning in Higher Education). Instructors in higher education have moved toward highly diverse delivery formats that involve a myriad of assessment strategies (Angelo and Cross 1993; Barkley and Major 2016). At the heart of these approaches is active learning.

ACTIVE LEARNING

Active learning is an umbrella term that describes a variety of learning experiences in which the learner demonstratively engages in the learning process (Bonwell and Eison 1991; ERIC thesaurus). Active learning focuses more on what the student is doing in the learning process as opposed to the behaviors of the instructor. If the instructor is the most active person in the classroom, the odds are that the students are at risk of being disengaged from the learning experience. As a result, learner-centered pedagogies that increase the engagement of students have emerged as the most effective for learning and retention. Research across many fields documents the positive impact that active strategies have on student engagement and learning outcomes (Michael 2006; Prince 2004). Learner-centered strategies are more likely to lead to active learning. As a result, the justification for the shift toward learner-centered strategies is based on evidence that active learners learn more (Bransford, Brown, and Cocking 2000).

The challenge of interpreting learning outcome data, however, lies in deciding how to actually measure improvement. Some studies focus on the degree to which students master objective exams (Hake 1998; Martin, Grimbeek, and Jamieson-Proctor 2014). Other studies focus on more subjective measures of improvement (see examples in Prince 2004). In many cases, typical assessments are ill equipped to measure the value added through these more complex approaches. For example, cooperative and problem-based strategies often create benefits in students in terms of teamwork and improved interpersonal skills. However, change in these areas is difficult to measure (Terenzini et al. 2001). Despite these challenges, research shows that active-learning strategies increased learning and affective outcomes. Specifically, the active student engaging in more authentic learning experiences learns and retains more (Fink 2013). Changes in brain scanning technology and cognitive science can now provide an explanation for why it is that student-centered active learning works.

THE SCIENCE BEHIND ACTIVE LEARNING — HOW THE BRAIN LEARNS

Recording, Sorting, and Storing

Learning involves change in the learner's brain, and this change occurs through electrical and chemical processes (Clay 2007; Ford 2011; Learner Centered Teaching n.d.; Stroman 2016). External stimuli activate specific patterns in the brain that allow for the recording and storage of information. We are generally aware that different parts of the brain do different things and that the reactivation of patterns strengthens the pathways across these parts and assists in recall. Learning occurs through the development of connections between existing patterns and new patterns. As babies, our brains have no established patterns or constructs. However, once we have some existing patterns, it is easier to store new information because we have something to attach it to. The more the pathways are fired or activated, the stronger the paths and patterns become, and the learner has an easier time with future recall and connections (Ford 2011). This explains why older memories are the most stable patterns in the brains of individuals with dementia and Alzheimer's disease. Having been fired the most, they are the strongest and most stable in the brain (Smith and Squire 2009). The challenge with learning is that you can only fire neural pathways for a brief period of time before the brain fatigues. Involving other parts of the brain can extend the learning time block, but a very narrow, focused task usual tires the brain in four to eight minutes (Perry 2000). The brain needs to rest for a few minutes and then can work on finding patterns and making connections again. This intense firing of...