The present study investigated whether text structure inference skill (i.e., the ability to infer overall text structure) has unique predictive value for expository text comprehension on top of the variance accounted for by sentence reading fluency, linguistic knowledge and metacognitive knowledge. Furthermore, it was examined whether the unique predictive value of text structure inference skill differs between monolingual and bilingual Dutch students or students who vary in reading proficiency, reading fluency or linguistic knowledge levels. One hundred fifty-one eighth graders took tests that tapped into their expository text comprehension, sentence reading fluency, linguistic knowledge, metacognitive knowledge, and text structure inference skill. Multilevel regression analyses revealed that text structure inference skill has no unique predictive value for eighth graders’ expository text comprehension controlling for reading fluency, linguistic knowledge and metacognitive knowledge. However, text structure inference skill has unique predictive value for expository text comprehension in models that do not include both knowledge of connectives and metacognitive knowledge as control variables, stressing the importance of these two cognitions for text structure inference skill. Moreover, the predictive value of text structure inference skill does not depend on readers’ language backgrounds or on their reading proficiency, reading fluency or vocabulary knowledge levels. We conclude our paper with the limitations of our study as well as the research and practical implications.
Digital support during self-regulated learning can improve metacognitive knowledge and skills in learners. Previous research has predominantly focused on embedding metacognitive support in domain-specific content. In this study, we examine a detached approach where digital metacognitive support is offered in parallel to ongoing domain-specific training via a digital tool. The primary support mechanism was self-explication, where learners are prompted to make, otherwise implicit, metacognition concrete.In a controlled pre-test/post-test quasi-experiment, we compared domain-specific and domain-general support and assessed the effects, use, and learners' perceptions of the tool. The results showed that self-explication is an effective mechanism to support and improve metacognition during self-regulated learning. Furthermore, the results confirm the effectiveness of offering detached metacognitive support. While only domain-specific metacognitive support was found to be effective, quantitative and qualitative analysis warrant further research into domain-general and detached metacognitive support.The results also indicated that, while students with higher metacognition found a lack of relevance of using the tool, students with lower metacognition are less likely to make (structural) use of the available support. A key challenge for future research is thus to adapt metacognitive support to learner needs, and to provide metacognitive support to those who would benefit from it the most. The paper concludes by formulating implications for future research as well as design of digital metacognitive support.
Learner metacognition is one of the most influential factors that positively affects learning. Previous work shows that game-based learning can contribute to supporting and developing metacognitive knowledge and skills of learners. While there are many specific examples of such games, it remains unclear how to effectively design game-based learning environments to achieve this in an effective way. In other words: there is sufficient case-specific evidence, but limited design knowledge derived from such cases. In this paper, we attempt to identify such intermediary design knowledge that resides between specific games and generalized theory. We present three design experiments where game-based metacognitive training is evaluated in real-world educational settings. We collected insights regarding usefulness, motivation, usage, effort, and metacognition among participating students. From these experiments we identify what was learned in the form of design recommendations and, as such, contribute to collecting intermediary design knowledge for designing game-based metacognitive training.
How do learners understand, monitor, and regulate their own learning? A question of metacognition. Improving metacognitive knowledge and skills contributes too learning effectiveness and effiency. The goal of this PhD project is to study in what ways metacognitive training can be supported and facilitated trhough game-based learning.
