Claudia Leopold

Self-Regulated Learning with a Text-Highlighting Strategy

Abstract. Forty-five university students participated in a computer-based training program on self-regulated learning from expository text. The training program introduced students to a learning strategy helping them identify and highlight important text information. Students were randomly assigned to three treatment groups: (1) no training at all, (2) training in highlighting only, or (3) combined training in both highlighting and self-regulation. After completing the training, students were instructed to read an instructional text and apply the trained strategies. The extent to which they applied the strategies while reading the text was assessed, and the amount of knowledge and comprehension they had acquired and recalled from the text was measured. Results show that students in the combined training condition outperformed their counterparts in the learning strategy training condition, who in turn outperformed those with no training at all. The results are in line with recent self-regulated learning th...

Self-explaining steps in problem-solving tasks to improve self-regulation in secondary education

The ability to learn in a self-regulated way is important for adolescents’ academic achievements. Monitoring one’s own learning is a prerequisite skill for successful self-regulated learning. However, accurate monitoring has been found to be difficult for adolescents, especially for learning problem-solving tasks such as can be found in math and biology. This study investigated whether a self-explaining strategy, which has been found effective for improving monitoring accuracy in learning from text, can improve monitoring and regulation-choice effectiveness, and problem-solving performance in secondary biology education. In 2 experiments, one half of the participants learned to solve biology problems by studying video-modeling examples, and the other one half learned by giving step-by-step self-explanations following the video-modeling examples (Experiment 1) or by following the posttest problem-solving tasks (Experiment 2). Results showed that in contrast to earlier studies, self-explaining did not improve monitoring and regulation-choice effectiveness. However, the quality of self-explanations was found to be related to monitoring accuracy and performance. Interestingly, the complexity of the problem-solving tasks affected monitoring and regulation-choice effectiveness, and problem-solving performance. These results are discussed in relation to the cognitive demands that monitoring and regulating learning to solve problems combined with self-explaining pose on learners.