GARNET: Geoscience Affective Research Network







Approximately 40-50% of STEM majors transfer into non-STEM programs during their college experience (Strenta and others, 1994; Seymour and Hewitt, 1997). Seymour and Hewitt (1997) reported that the principal reasons given by students for switching out of STEM programs were:

  1. Students became unmotivated as they lost the feeling that STEM disciplines were interesting or enticing;
  2. Students became more interested in other majors.

In Spring, 2008, I asked students in my introductory Earth Science class the following question: Consider a class that resulted in a lot of new learning, and one where you didn’t learn much at all.  Why did you think you learned a lot in one class and relatively little in the other? Take a moment and think about the question. Can you predict the most common answers?

why did you learn graph
Half of the students provided answers indicating that they learned more in classes that provided them with interesting information. Further, another third of the class was influenced by how the class was taught (things the instructor was doing or activities the students completed in class).

Clearly, if we are to attract and retain greater numbers of students to STEM disciplines, we need to be more intentional about addressing the affecting elements of learning in STEM classrooms. Interest and motivation have been examined only tangentially in college science education research, which has instead focused largely on targeting inaccurate student alternative conceptions through the use of effective pedagogical methods (Sinatra, 2005).  Ormrod (2006) described six overlapping theories that are individually or in some combination, responsible for motivating student learning and are the focus for ongoing psychological research:

  1. Social-cognitive theory – students who are confident that they can do well (self-efficacy), make more effort to learn, persist to overcome obstacles, and use effective cognitive strategies.  These strategies are more likely to be used when encouragement is received from peers or instructors.
  2. Attribution theory – students who believe that they have some personal control of their learning environment and that they can learn how to understand the course material, work harder, are more engaged and employ better cognitive strategies than those that do not feel in control. 
  3. Goal theory – students may employ achievement goals that target mastery (understanding concepts and developing skills) and/or performance (achieving high scores, avoiding low scores).  Mastery goals are often driven by intrinsic factors such as interest (and are more frequently correlated with improved scores) while performance goals are often related to extrinsic drivers such as the need to please others. 
  4. Expectancy value theory – students are more likely to study longer and persist at tasks when they have high expectations of their performance.  In addition, students do better when they see some value to succeeding in a particular task beyond the completion of the task itself (e.g., learning a new skill). 
  5. Self-determination theory – students are more motivated to learn when they believe they can competently complete assignments, when they have some control over the outcome of their work, and when they can develop close working relationships with peers. 
  6. Self-worth theory – students may either work to be successful to enhance their sense of self-worth or may deliberately engage in ineffective behaviors to provide an explanation for potential failure.

Wolters and Pintrich (1998) linked many cognitive and affective factors together when they stated that “interest and value can help a student chose to become involved in a task, somewhat like the ‘starter’ for a car, but once involved, the self-regulation process of strategy use and adaptive efficacy beliefs (the potential for a change of student self-efficacy beliefs) are more important for ‘steering’ and controlling actual performance” (p. 44).  

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