How accurately can learners discriminate their comprehension of texts? A comprehensive meta-analysis on relative metacomprehension accuracy and influencing factors

Prinz, Anja; Golke, Stefanie; Wittwer, Jörg

doi:10.1016/j.edurev.2020.100358

Cited by 34 publications

(53 citation statements)

References 87 publications

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“…This suggests that the connection of monitoring activities with other activities (i.e., what students monitor) led to differential transfer performance. In tasks which require text comprehension, monitoring is a core skill but metacomprehension (accuracy) tends to be underdeveloped ( Prinz et al, 2020 ) and poor monitoring accuracy have consequential effects on the use of effective control and remediation measures ( Serra and Metcalfe, 2009 ). The present study’s learning task involved intensive text reading and comprehension through which students had to make decisions on what to read, how to read, how to proceed with the materials they have read.…”

Section: Discussionmentioning

confidence: 99%

Temporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols

et al. 2021

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It has been widely theorized and empirically proven that self-regulated learning (SRL) is related to more desired learning outcomes, e.g., higher performance in transfer tests. Research has shifted to understanding the role of SRL during learning, such as the strategies and learning activities, learners employ and engage in the different SRL phases, which contribute to learning achievement. From a methodological perspective, measuring SRL using think-aloud data has been shown to be more insightful than self-report surveys as it helps better in determining the link between SRL activities and learning achievements. Educational process mining on the basis of think-aloud data enables a deeper understanding and more fine-grained analyses of SRL processes. Although students’ SRL is highly contextualized, there are consistent findings of the link between SRL activities and learning outcomes pointing to some consistency of the processes that support learning. However, past studies have utilized differing approaches which make generalization of findings between studies investigating the unfolding of SRL processes during learning a challenge. In the present study with 29 university students, we measured SRL via concurrent think-aloud protocols in a pre-post design using a similar approach from a previous study in an online learning environment during a 45-min learning session, where students learned about three topics and wrote an essay. Results revealed significant learning gain and replication of links between SRL activities and transfer performance, similar to past research. Additionally, temporal structures of successful and less successful students indicated meaningful differences associated with both theoretical assumptions and past research findings. In conclusion, extending prior research by exploring SRL patterns in an online learning setting provides insights to the replicability of previous findings from online learning settings and new findings show that it is important not only to focus on the repertoire of SRL strategies but also on how and when they are used.

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Section: Discussionmentioning

confidence: 99%

Temporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols

et al. 2021

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“…It also provides comprehensive and accurate skills and development for the students. It assesses their level of learning that explores and influences the factors of their knowledge and level (Prinz, Golke, & Wittwer, 2020). On the other hand, it shows that the analysis and comprehension level of students show skills in creative thinking, can learn, and can communicate with passion and ideas based on their lesson.…”

Section: Discussionmentioning

confidence: 99%

Structural Domain of Learning and Teaching Strategies in the Academic Performance of Students

Mallillin¹,

Cabaluna

Laurel

et al. 2021

EJES

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The study aims to describe the profile of the respondents in terms of age, gender, educational attainment, and number of years in teaching and to understand the structural domain of learning among the students in their academic performance in the area of cognitive domain of learning, affective domain of learning, and psychomotor domain of learning to include the approach on the teaching strategies of the students in their school achievement along the area of analysis and comprehension level, attitude towards the lesson, and academic performance. The quantitative research design is utilized in the study because it attempts to quantify and collect the statistical analysis on the various measures set in the research questions in the study. The purposive sampling technique is utilized in the study. This type of sampling is non-probability which is very effective in the domain of learning and expert knowledge on the needs of the study. The study comprised thirty (30) respondents only. Results show that structural cognitive domain of learning reveals the ability to construct meaning from their lesson as to function and activities in their module, structural affective domain of learning reveals that students have the active attention and proper motivation to learn, willingness to respond, and feeling of satisfaction, and students have the attitude of worth, beliefs, acceptance, preference, and commitment to values, and structural psychomotor domain of learning reveals that students can express their learning through gestures, posture, facial expression, and/or creative movement. On the other hand, approach to teaching strategies as to comprehension and analysis levels shows innovation, creativity, competition, and have the ability to present concepts in their outline lesson, approach to teaching strategies as to the attitude of students toward the lesson shows that students display strict compliance toward their lessons and activities, and approach to teaching strategies as to academic performance shows that students focus on their lessons and provides output in the learning process, and students pay close attention to the direction in their lesson set up by. Findings of the study show that there is no significant agreement between the structural domain of learning among the students in their academic performance and the approach on the teaching strategies of the students in their school achievement among the respondents. Article visualizations:<img src="/-counters-/edu_01/0855/a.php" alt="Hit counter" />

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“…For example, overestimation entails that learners likely overlook underdeveloped aspects of their text representation, and hence, their efforts in regulating their understanding will very likely be insufficient (e.g., skip rereading, miss relevant parts during rereading). Accordingly, poor accuracy and overestimation in particular, which are a widespread phenomenon (Lin & Zabrucky, 1998;Maki & McGuire, 2002;Prinz et al, 2020a;Thiede et al, 2009), have been shown to result in underachievement (Dunlosky & Rawson, 2012).…”

Section: Metacomprehension Accuracy and Its Relevance For Learningmentioning

confidence: 99%

“…Learners are usually poor at accurately monitoring and judging their text comprehension (Maki & McGuire, 2002;Prinz et al, 2020a;Thiede et al, 2009). This poor accuracy, often reflected in overestimations but also in underestimations of comprehension, hampers learning (Dunlosky & Rawson, 2012).…”

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confidence: 99%

What Makes Learners Overestimate Their Text Comprehension? The Impact of Learner Characteristics on Judgment Bias

2022

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It is frequently assumed that learner characteristics (e.g., reading skill, self-perceptions, optimism) account for overestimations of text comprehension, which threaten learning success. However, previous findings are heterogenous. To circumvent a key problem of previous research, we considered cognitive, metacognitive, motivational, and personality characteristics of learners (N = 255) simultaneously with regard to their impact on the judgment biases in prediction and postdiction judgments about factual and inference questions. The main results for the factual questions showed that men, lower reading skill, working memory capacity, and topic knowledge, yet higher self-perceptions of cognitive and metacognitive capacities yielded stronger overestimations for prediction judgments. For inference questions, a lower reading skill, higher self-perceptions of metacognitive capacities, and a higher self-efficacy were related to stronger overestimations for prediction and postdiction judgments. A higher openness was a risk factor for stronger overestimations when making predictions for the inference questions. The findings demonstrate that learner characteristics are a relevant source of judgment bias, which should be incorporated explicitly in theories of judgment accuracy. At the same time, fewer learner characteristics were actually relevant than previous research suggests. Moreover, which learner characteristics impact judgment bias also depends on task requirements, such as factual versus inference questions.

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How accurately can learners discriminate their comprehension of texts? A comprehensive meta-analysis on relative metacomprehension accuracy and influencing factors

Cited by 34 publications

References 87 publications

Temporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols

Temporal Assessment of Self-Regulated Learning by Mining Students’ Think-Aloud Protocols

Structural Domain of Learning and Teaching Strategies in the Academic Performance of Students

What Makes Learners Overestimate Their Text Comprehension? The Impact of Learner Characteristics on Judgment Bias

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