Connecting teachers' classroom instructions with children's metacognition and learning in elementary school

The structure of metacognition in middle childhood: Evidence for a unitary metacognition-for-memory factor

It has been debated whether children's metacognitive monitoring and control processes rely on a general resource or whether metacognitive processes are task specific. Moreover, findings about the extent to which metacognitive processes are related to first-order task performance are mixed. The current study aimed to uncover the relationships among children's monitoring (discrimination between correct and incorrect responses), control (accurate withdrawal of wrong answers), and performance across three memory-based learning tasks: Kanji learning, text comprehension, and secret code learning. All tasks consisted of a study phase, a test phase, monitoring (confidence judgments), and control (maintaining/withdrawing responses). Participants were 325 children (151 second graders [Mage = 8.12 years] and 174 fourth graders [Mage = 10.20 years]). Confirmatory factor analyses showed that a model in which monitoring and control loaded on a joint factor and performance on a separate factor provided the best fit to the data. Fourth graders had better monitoring and control accuracy than second graders. However, the factor structure of metacognition was similar for both age groups, contradictory to the assumption that metacognition generalizes across tasks as children grow older. After accounting for task-specific processes, monitoring and control skills for language-based memory tasks appear to be generalizable in middle childhood. In sum, children's monitoring and control for three separate memory tasks appear to reflect a unitary metacognition-for-memory factor related to, but distinguishable from, performance.

From the lab to the classroom: Improving children's prospective memory in a natural setting

BACKGROUND

Laboratory-based studies have shown that children's ability to remember intentions (i.e., prospective memory; PM) can be improved by asking them to imagine performing the PM task beforehand (i.e., episodic future thinking; EFT) or to predict their PM performance. Moreover, combining the two strategies resulted in an additional improvement in children's PM performance. However, the effectiveness of these encoding strategies on real-life PM tasks is still unknown.

AIMS

The aim of the present study was to evaluate the effect of EFT instructions, performance predictions, and of their combination on children's PM in a natural setting, namely in the classroom.

SAMPLE

Twelve classes composed by a total of 121 children (53% females) aged between seven and 9 years participated to the study.

METHODS

As a PM task, children were asked by their teachers to deliver a letter to their parents and to bring it back to school the next day. Children were divided into four groups: control, prediction, EFT, and the EFT + prediction group. Parent reports on children's everyday prospective and retrospective memory failures were also collected.

RESULTS

Results showed that encoding strategies were effective in enhancing children's PM performance. However, differences compared to previous laboratory-based findings emerged since predicting PM performance resulted to be most effective in enhancing real-life PM performance. Moreover, parent reports were related to children's PM performance.

CONCLUSIONS

These novel findings highlight the importance of studying PM interventions in natural settings in order to increase their ecological validity and inform educational practices.

Construction of self-learning classroom history teaching mode based on human-computer interaction emotion recognition

Due to the continuous epidemic in recent years, the traditional teaching mode of history classroom has been gradually replaced by the teaching mode of self-learning classroom. The teaching mode of autonomous learning classroom has become a popular teaching mode in recent years. However, in the autonomous learning classroom under the current history teaching mode, the lecturer cannot always pay attention to the various states of the students. It is also difficult to understand and receive the information the teacher wants to convey in real time. For this reason, human-computer interaction emotion recognition technology has been proposed and developed. In order to construct and realize the teaching mode of self-learning classroom history, this paper studies the emotion recognition technology of human-computer interaction. The research results show that the introduction of human-computer interaction emotion recognition technology into the construction of autonomous learning classroom teaching mode can fully understand students' emotional behavior. It improves the accuracy of students' emotion recognition by 2.67%, enables students to maintain a good learning motivation, and make reasonable plans and arrangements for the historical time and progress of learning. At the same time, it enhances the history teaching intensity and autonomous learning ability, and improves the original single learning mode. By establishing a new teaching-teacher-student relationship, it creates a good and active autonomous classroom atmosphere.