In a conversation with one of the principals featured in a forthcoming Apex Learning case study, the principal noted that males under the age of 16 ½ in his school struggle with Apex’s online curriculum. Females do much better with it.
His assertion left me wondering about this observed gender difference. Is Apex’s content biased toward female brains? Is online learning in general, regardless of content provider, more suited toward a gender-based mental or personality predisposition?
In the children’s book How many seeds in a pumpkin?, by Margaret McNamara, the fictitious science teacher Mr. Tiffin asks his students to guess the number of seeds in a small, medium and large pumpkin. The children then carve into the pumpkins, scoop out the seeds and tally them. Turns out, much to the children’s surprise, that the small pumpkin has the most seeds, followed by the large and then the medium. Mr. Tiffin teaches the puzzled kids that size is not the important categorization for predicting number of seeds. Instead, pollination, pumpkin variety, and time on the vine determine how many lines are on a pumpkin, which in turn indicates how many seeds are inside. If you like pumpkin seeds, buy a darker, riper one with the most grooves on the outside.
The key to developing useful theory is getting the categories right. Mr. Tiffin’s class erroneously sorted pumpkins based on one attribute—their size, but found that the small pumpkin presented an anomaly to this theory. They then learned that if they sorted the pumpkins based on different categories—pollination, variety and time on vine—they could predict quite perfectly which pumpkin would have the most seeds. In The Innovator’s Solution, Clayton Christensen and Michael Raynor explain that researchers need to categorize in order to highlight the most meaningful differences in a complex array of phenomena. As researchers begin to identify the causal mechanism behind the phenomena (e.g. time on vine produces more pumpkin seeds), they then can improve their theory by noting anomalies. These anomalies prompt them to identify what circumstances produce a different outcome than their initial theory suggests. For example, if a pumpkin has been on the vine the longest AND is a Jumping Jack or Big Tom, it will grow more seeds than a similarly ripe Aspen.
So back to Apex Learning. Are young males less suited for Apex? My hunch is that this categorization is not an adequate description of the causal mechanism behind the observed phenomenon. A useful study would be to analyze the success of young males with Apex, then note the anomalies—the young men who actually perform well with the program. What circumstances produce this success? Conversely, what females are failing with the content, and what circumstances might explain their falling below the norm?
This thought process, applied to education research, will produce a better set of theories for educators to use when deciding which content and learning modalities to apply to each student. As researchers produce better circumstance-contingent theories, educators will be able to predict with high accuracy when a provider like Apex Learning will work and for whom.