Description:

Co-Principal Investigator: Kali Trzesniewski (University of California – Davis)

Original Grant: R305A130239: Florida State University

Purpose: Maximizing a child's opportunity to learn and succeed academically requires confronting at least two types of challenges. First, one must determine which strategies best foster learning. Second, one must determine how best to motivate students to take advantage of those strategies. This project will focus on whether a belief that one can improve one's intelligence leads students to use self-regulated learning strategies more often and to use those strategies in more effective ways. The researchers will focus on the use of two self-regulated learning strategies in particular—spacing one's studying and monitoring one's level of understanding—and will explore the consequences of adopting these strategies for metacognitive accuracy and sustained learning in mathematics. The researchers propose that the belief that intelligence is changeable (incremental view) leads students to more often engage in self-regulated learning strategies which, in turn, leads to greater metacognitive accuracy, additional effort toward mastery of material, and consequently, superior math learning, compared to a view of intelligence as fixed (entity view).

Project Activities: The research team will conduct three pairs of studies that capitalize on different research designs. Within each pair, one study will explore the effects of naturally held theories of intelligence while the other study will involve random assignment to experimental conditions that convince students of a particular view of intelligence (incremental, entity, or a control). The first pair of studies will focus on whether students with stronger incremental views of intelligence use self-regulated learning strategies more often than those with stronger entity views, and consequently, show superior learning. The second pair of studies will focus on whether students with incremental views of intelligence continue to use self-regulated learning strategies when facing difficulty. The third pair of studies will focus on whether students with incremental views of intelligence will use self-regulated strategies in more effective ways than students with an entity view of intelligence.

Products: The products of this project will be preliminary evidence about whether students' views of intelligence can be altered and lead them to more often adopt and use self-regulated strategies for learning, and as a result, improve learning outcomes. Peer-reviewed publications will also be produced.

Structured Abstract

Setting: Participating schools will be located in urban and suburban settings in Florida and California. Studies will take place in multi-purpose rooms at the schools or in the researchers' laboratories at Florida State University and University of California, Davis.

Sample: Participants include freshmen and sophomore high school students recruited in California and Florida, approximately 13–16 years old, 50 percent male and 50 percent female, and diverse with respect to ethnicity and SES. For each of the six studies within this project, between 140–250 students will be recruited depending on the research design of the experiment.

Intervention: The outcome of this project will be a better understanding of whether believing one can improve one's intelligence leads students to more often adopt and use self-regulated strategies for learning, and consequently leads to improved student learning outcomes. The findings from this study can be used to inform the development of interventions.

Research Design and Methods: The research team will conduct three pairs of studies to explore the ways in which students prepare for tests of their learning using a mathematics tutorial developed within Plato Learning Environment, a web-based educational program. Each pair of studies examines a research question by measuring (the first study in the pair) or manipulating (the second study in the pair) students' beliefs about intelligence. For all studies that will measure students' intelligence beliefs, all students will complete the same tasks. For all studies that will manipulate students' intelligence beliefs, students will be randomly assigned (using a between-subjects design) to one of the three intelligence conditions (entity, incremental, or control) and will complete tasks meant to induce an intelligence belief prior to interacting with the mathematics tutorial. The first two pairs of studies will explore the relationship between students' measured or manipulated intelligence beliefs and the use of self-regulated learning strategies for tasks of varying difficulty. For the final two studies, students will be randomly assigned to study through spacing or massing (using a between-subjects design), and the researchers will investigate how measured or manipulated theories of intelligence influence the manner in which these strategies are used.

Control Condition: For the studies that will measure intelligence beliefs, there is no control condition due to the nature of the studies. For the studies that will manipulate intelligence beliefs, students in the control condition will engage in tasks that will not convince them to believe in one view of intelligence over another.

Key Measures: The studies will focus primarily on students' intelligence beliefs, their use of self-regulated learning strategies, and the consequences of those learning strategies for metacognitive accuracy and learning. To measure students' intelligence beliefs, students will complete the Theories of Intelligence scale. Students will also be asked to complete the 2x2 Achievement Goal Orientation scale, the Motivated Strategies for Learning scale and its Metacognitive Self-Regulation subscale, and the Effort Beliefs scale. To measure students' use of self-regulated learning strategies, the researchers will log information about students' actions while using the Plato Learning Environment. To measure students' learning outcomes and metacognitive accuracy, the researchers will administer researcher-designed pre-tests and post-tests.

Data Analytic Strategy: Data will be analyzed using a combination of Hierarchical Linear Modeling (HLM) and Structural Equation Modeling (SEM) techniques. For studies measuring students' intelligence beliefs, the researchers will use SEM with latent variables to test the process model. For studies manipulating students' intelligence beliefs, the researchers will use a set of one-way analyses of variance to examine the effect of the experimental condition on participants' theories of intelligence.

Products and Publications

Book chapter

Ehrlinger, J., and Shain, A. (2014). How Accuracy in Students' Self Perceptions Relates to Success in Learning. In V.A. Benassi, C.E. Overson, and C.M. Hakala (Eds.), Applying Science of Learning in Education: Infusing Psychological Science Into the Curriculum (pp. 142–151). Washington, DC: Society for the Teaching of Psychology, American Psychological Association.

Journal article, monograph, or newsletter

Ehrlinger, J., Mitchum, A.L., and Dweck., C.S. (2016). Understanding Overconfidence: Theories of Intelligence, Preferential Attention, and Distorted Self-Assessment. Journal of Experimental Social Psychology, 63: 94–100.