In November of last year, the New York Times published an article that attempted to answer the question of “why science majors change their minds.” The author cited the results of a UCLA-led study that found that across the nation, freshmen originally intending to major in engineering or follow the pre-med route switch to non-STEM majors at alarmingly high rates.

 

Almost invariably, Stanford students know at least a few peers who changed their minds about being a chemist or engineer after taking inorganic chemistry, linear algebra or some other difficult introductory class. Indeed, the author of the Times piece concludes that attrition rates in engineering and sciences are higher than that in other disciplines because STEM classes are “so darn hard.”  While true to an extent, we do not think this accurately portrays the whole picture.

Take the introductory sequence in computer science at Stanford, for instance (CS 106A and B/X). According to CourseRank, the average grade and hours of work per week in these classes are comparable to introductory classes in other STEM fields.

 

If, as the Times article suggests, high attrition rates are due to the rigor of such classes, we would expect Stanford freshmen intending to major in computer science to change their minds as often as their peers in other STEM fields.  But the opposite seems to be the case; from many accounts, the introductory CS sequence actually attracts students to the major who, prior to Stanford, had scarcely entertained the thought of being a programmer.  Is Computer Science simply a more interesting subject than, say, mechanical engineering?  Perhaps.  But this Board believes that variations in attrition rates among similarly rigorous STEM disciplines are more a result of differences in the presentation of course content and its application in homework.

 

In a landmark piece on engineering education, chemical engineering professor and STEM-education expert Richard Felder argues that induction—also called inquiry or discovery learning—is the most effective method of teaching applied science to undergraduates. An example of inductive learning, defined broadly, is the trial and error in designing a computer program to complete a certain task; over time, the student learns which approaches work and utilizes these effective practices when confronted with similar problems in the future. According to Felder, this type of learning leads to “increased academic achievement and enhanced abstract reasoning skills; longer retention of information; and improved ability to apply principles” (among other benefits).  According to Worcester Polytechnic Institute, incorporating inductive learning into its freshman year curriculum has served to “hook” its students into STEM majors.

 

We would hope, then, that inductive learning is fundamental to Stanford’s science and engineering curriculums. On the contrary, it seems that Stanford is more aligned with what Felder labels the “traditional college teaching method [of] deduction, starting with ‘fundamentals’ and proceeding to applications.” Although it is beyond the scope of this editorial to study the content of every STEM class at Stanford, the standard problem-set model is certainly deductive; theory presented in lecture must be applied to solve homework problems that generally have only one correct solution. The inductive element is often lacking.

 

Certainly, there are classes at Stanford that incorporate an inductive approach to learning.  Introductory design and computer science classes, for instance, assign tangible problems where the desired result can be reached in various ways. It should come as no surprise that these classes tend to be significantly more popular than their purely deductive counterparts.

 

Although focusing on technical fundamentals is crucial to many STEM classes, there are various ways in which some aspect of inductive learning can be introduced. This fusion, however, demands that professors adopt less straightforward methods of presenting the material and, when formulating homework, assign more than just conventional textbook problems. It is certainly no easy task for professors, especially those with limited formal training in education. Accordingly, this Board recommends that STEM departments work with professors to incorporate more inductive elements in their coursework. It is imperative, especially in disciplines that attempt to either explain the world or design solutions to improve it, that classes at Stanford and across the nation engage students in truly understanding what lies at the heart of these disciplines.