Testing the Agenda-Based Regulation Model With Worked Examples and Problem-Solving

• In Event: AERA Roundtable Session Sunday 1:30 pm Four Seasons Ballroom 2-3
  In Roundtable Session: Self-Regulated Learning Strategies and Academic Performance (Table 7)

Abstract

Do students study math effectively? Prior research found novices benefit from studying worked examples but tend to use them less than problem-solving (Foster et al., 2018). We explored this further using the agenda-based regulation model (ABR) (Ariel et al., 2009), manipulating assigned posttest values. Participants (n=36) learned to solve four types of probability problems assigned high- or low-point values. They chose between worked examples or problem-solving for each problem. Despite using worked examples at a similar rate (43.52%), students switched strategies more for higher-value content and had different primary reasons for using each. They reported using worked examples to improve/check their understanding and problem-solving to monitor learning. Findings indicate students select learning strategies based on their agendas and progress.

Authors

• Xinran Wang, Vanderbilt University

• Rebecca Adler, Vanderbilt University

• Cristina D. Zepeda, Vanderbilt University

• Bethany Rittle-Johnson, Vanderbilt University