The effects of language learning and math mindsets on academic success in an engineering program

Background: Mindsets are based on two basic assumptions: some people think that their intellectual abilities can be developed through hard work and instruction (i.e., a growth mindset), whereas others believe that nothing can change their level of intellectual ability (i.e., a fixed mindset). The association between mindsets and academic achievement has been examined in different academic subjects, such as biology and math. However, no previous study has examined the effects of language learning mindsets (LLMs) and math mindsets (MMs) on academic success in an English medium instruction (EMI) setting in which English, rather than the first language of the students, is used for teaching content (e.g., mechatronics engineering). Purpose/Hypothesis: This study explores the relationship between Turkish mechatronics engineering undergraduate students' domain-specific mindsets, LLMs and MMs, and their academic success. Design/Method: Student test scores for English medium and first-language medium courses were collected from fourth-year students studying mechatronics engineering (n = 68) at a public university in Turkey. Students also completed the LLM and MM inventories. Results: Regression analyses revealed that growth LLM and MM were positive predictors of EMI and Turkish medium of instruction (TMI) academic success, whereas fixed LLM and MM were negative predictors of EMI and TMI academic success. Conclusions: In both EMI and TMI courses, a growth mindset in math and language learning can profoundly predict students' academic achievement in a mechatronics engineering program. We argue that domain-specific mindsets can effectively explain the self-theories of intelligence and achievement.