Expectancy-Value Theory, Goals, Instrumentality & Motivation

Will Hunting's motivation for math can be analyzed from various perspectives, including Expectancy-Value Theory, goals, and instrumentality. For him, the value of solving math questions was mostly intrinsic interests and reasons. Although intrinsic interests fuel motivation, intrinsic reasons are one of the four reasons that contribute to the value of the motivation. Will was not seeing the external rewards (extrinsic reasons), or felt guilt for not working on the math problems (introjected reasons), or realized the benefits of solving math questions to his life (identified reasons). Moreover, Will didn't have goals for how he could utilize his math skills present or in the future. Instead, he thought that doing concrete work was more meaningful, felt tangible, and contributed more to other people's lives than some prestigious intellectual job. For example, Will told Dr. Sean Maguire, his counselor, that he enjoyed construction work. He worked as a janitor at MIT, as well as a construction worker alongside his best friends. He asked his friend to pretend to be him to attend the job interview, turned down the research project, and rejected the job offer from the NSA. His goals of working some "real work" were not in agreement with his interests, while he didn't have any goals in the math field. 

Additionally, as discussed in my last post, Will didn't develop mastery or performance goals toward math. However, according to Harackiewicz & colleagues, the co-existence of both mastery and performance goals helped college students obtain the highest levels of performance. In this sense, Will's motivation for math was low, which in turn hindered his performance in continuing or taking a job that required math. On the ther hand, based on the 3 x 2 achievement goal model, Will's goal focus was on the task, specifically whether he had the competence to meet the task's demands and provide a solution. It was extrinsically driven, without comparison to others. 

However, Will's situation can be viewed as benefiting his motivation based on John Keller's ARCS Model of Instruction, as his condition embodies all four categories that help promote students' motivation. For example, he received attention, the math questions themselves, and numerous opportunities for him to engage with math problems, promoted by Professor Gerald Lambeau, were ideal. Besides, his actions were relevant to his interests and his prior knowledge and experience in math learning. Moreover, he had the confidence to achieve his expectations of success and could attribute success to his personal skills and effort. Finally, he felt a sense of satisfaction after solving the math questions and received fair recognition from Lambeau and his colleagues. 

Nevertheless, one of the pitfalls of Will's motivation was the perceived lack of instrumentality in math. He didn't connect his math skills to any of his current or future goals, nor did he value the utility math can bring to him, as demonstrated by his view of the destructive effects of using math to work for the NSA and his goals of doing everyday work, not related to math. Additionally, he didn't place value on the future or how he could improve his future life with his skills, as if he could continue to work as a construction worker and spend his time with his friends all the time.