My research examines how learners monitor, interpret, and control their own learning. Successful learning requires students to decide what they know, what to study, how to study, and when to stop. Yet learners often rely on imperfect cues—such as fluency, effort, confidence, or recent test performance—that can lead them to misjudge how well they have learned. Across laboratory, online, and classroom-based studies, I investigate how metacognition shapes learning and how educational activities can be designed to support more accurate, strategic, and durable learning.
Metacognitive Monitoring and Memory
One line of our research examines how metacognitive judgments influence memory. Although judgments of learning are often used to measure students’ predictions about future performance, our work shows that making these judgments can also change what students remember. In particular, judgments of learning can improve later recall when they strengthen cue–target relationships that are useful for later retrieval (Janes, Rivers, & Dunlosky, 2018; Rivers, Janes, & Dunlosky, 2021; Rivers, Dunlosky, Janes, Witherby, & Tauber, 2023). This work helps clarify when monitoring is merely diagnostic and when it becomes part of the learning process itself.
We also study confidence and prediction in broader learning and problem-solving contexts. For example, our work has examined gender differences in confidence during number-line estimation (Rivers, Fitzsimmons, Fisk, Dunlosky, & Thompson, 2020) and how people predict their ability to solve insight problems after exposure to misleading or fixating information (Storm & Hickman [Rivers], 2015). Together, these projects ask when learners’ confidence accurately reflects their performance and when it does not.
Beliefs About Effective Learning Strategies
A second major focus of our research is learners’ beliefs about effective study strategies. Practice testing, or retrieving information from memory, is a powerful way to promote long-term retention, but learners often underestimate its benefits and view testing mainly as a way to check what they know (Rivers, 2021). Our work examines why these misconceptions persist and how they can be corrected through task experience, feedback, direct instruction, and other forms of support (Rivers, Dunlosky, & McLeod, 2022; Rivers, 2023).
This work also examines how test experience shapes future learning. Learners can adapt their encoding strategies based on the type of test they expect (Rivers & Dunlosky, 2021), and taking tests can improve how learners encode new material later on (Storm, Hickman [Rivers], & Bjork, 2016). These projects show that tests can influence not only what students remember, but also how they approach future learning.
Designing Learning Activities That Work
Our research also investigates how specific learning activities can be designed to improve memory and metacognitive accuracy. In work on pretesting and prequestioning, we have shown that learners often fail to appreciate the benefits of attempting to answer questions before learning, but their awareness can improve with appropriate support (Pan & Rivers, 2023; Pan, Chua, Rivers, & Teo, under review). More recent work shows that covert and overt prequestioning can similarly benefit learning from text, suggesting that prequestions may work partly by directing attention to important information (Rivers, Berdelis, Pan, & Tauber, 2026).
In related work on retrieval practice, we examine when students benefit most from overt retrieval, such as typing an answer, versus covert retrieval, such as mentally recalling an answer. Overt retrieval appears especially useful for complex material, whereas covert retrieval may offer a more efficient, though sometimes less thorough, alternative (Rivers, Northern, & Tauber, 2025).
Assessment, Feedback, and Educational Contexts
A final theme of our work concerns how educational environments shape students’ judgments and study decisions. Classroom exams can provide formative feedback, but students do not always use exam experience accurately to evaluate their concept-level knowledge (Rivers, Dunlosky, & Joynes, 2019). Assessment design can also improve learning; for example, requiring students to justify their answers during multiple-choice testing can enhance performance and may support metacognitive accuracy (Clark, Rivers, & Overono, 2025; Hardy, Kostal, Nayak, & Rivers, under review).
We also study how instructional materials and educational systems guide self-regulated learning. Rubric point values can influence how students allocate study effort to STEM concepts (Shumaker, Rivers, & Tauber, 2025), and metacognitive knowledge, monitoring, and control can be measured in authentic educational settings such as pharmacy education (Rivers, Dunlosky, & Persky, 2020). Our work also examines how students and faculty interpret student evaluations of teaching, including whether evidence-based practices such as daily quizzing are recognized in evaluations (Rivers, Babineau, Neely, & Tauber, 2023).