The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Claudia M. Roebers - One of the best experts on this subject based on the ideXlab platform.
-
Comparing Metacognitive Monitoring between native and non-native speaking primary school students
Metacognition and Learning, 2021Co-Authors: Florian J. Buehler, Mariëtte H. Loon, Natalie S. Bayard, Martina Steiner, Claudia M. RoebersAbstract:Metacognitive Monitoring is a significant predictor of academic achievement and is assumed to be related to language competencies. Hence, it may explain academic performance differences between native and non-native speaking students. We compared Metacognitive Monitoring (in terms of resolution) between native and non-native speaking fourth graders (~ 10 year olds) in two studies. In Study 1, we matched 30 native and 30 non-native speakers and assessed their Monitoring in the context of a paired-associates task, including a recognition test and confidence judgements. Study 1 revealed that recognition and Monitoring did not differ between native and non-native speaking children. In Study 2, we matched 36 native and 36 non-native speakers and assessed their Monitoring with the same paired-associates task. Additionally, we included a text comprehension task with open-ended questions and confidence judgments. We replicated the findings of Study 1, suggesting that recognition and Monitoring do not necessarily differ between native and non-native speakers. However, native speaking students answered more open-ended questions correctly than non-native speaking students did. Nevertheless, the two groups did not differ in Monitoring their answers to open-ended questions. Our results indicate that native and non-native speaking children may monitor their Metacognitive resolution equally, independent of task performance and characteristics. In conclusion, Metacognitive Monitoring deficits may not be the primary source of the academic performance differences between native and non-native speaking students.
-
the development of Metacognitive Monitoring and control in second graders a short term longitudinal study
Journal of Cognition and Development, 2017Co-Authors: Claudia M. Roebers, Manuela SpiessAbstract:Although metacognition is considered a central aspect of self-regulated learning and is often linked to learning outcomes, little is known about the intraindividual development and factors that lead to developmental improvement over time. This longitudinal study investigated 2nd graders’ (N = 119, aged 8–9 years) Metacognitive Monitoring and control abilities in the context of spelling. Children were tested at the beginning (T1) and at the end of their 2nd school year (T2). The study focused on the development of Monitoring and control, their interplay at both measurement points and across time, and the cross-sectional and longitudinal impact of 1st-order task performance (here, spelling) on the 2 Metacognitive processes. Results revealed substantial developmental progression in most Monitoring and control measures. Monitoring and control were interrelated cross-sectionally only at T2, but longitudinally, control predicted Monitoring. Interestingly, earlier spelling performance predicted not only later sp...
-
Metacognitive Monitoring and control in elementary school children their interrelations and their role for test performance
Learning and Individual Differences, 2014Co-Authors: Claudia M. Roebers, Saskia S Krebs, Thomas RodererAbstract:Contemporary models of self-regulated learning emphasize the role of distal motivational factors for student's achievement, on the one side, and the proximal role of Metacognitive Monitoring and control for learning and test outcomes, on the other side. In the present study, two larger samples of elementary school children (9- and 11-year-olds) were included and their mastery-oriented motivation, Metacognitive Monitoring and control skills were integrated into structural equation models testing and comparing the relative impact of these different constituents for self-regulated learning. For one, results indicate that the factorial structure of Monitoring, control and mastery motivation was invariant across the two age groups. Of specific interest was the finding that there were age-dependent structural links between Monitoring, control, and test performance (closer links in the older compared to the younger children), with high confidence yielding a direct and positive effect on test performance and a direct and negative effect on adequate control behavior in the achievement test. Mastery-oriented motivation was not found to be substantially associated with Monitoring (confidence), control (detection and correction of errors), or test performance underlining the importance of proximal, Metacognitive factors for test performance in elementary school children.
-
The Impact of Retrieval Processes, Age, General Achievement Level, and Test Scoring Scheme for Children's Metacognitive Monitoring and Controlling.
Metacognition and Learning, 2011Co-Authors: Saskia Krebs, Claudia M. RoebersAbstract:This multi-phase study examined the influence of retrieval processes on children’s Metacognitive processes in relation to and in interaction with achievement level and age. First, N = 150 9/10- and 11/12-year old high and low achievers watched an educational film and predicted their test performance. Children then solved a cloze test regarding the film content including answerable and unanswerable items and gave confidence judgments to every answer. Finally, children withdrew answers that they believed to be incorrect. All children showed adequate Metacognitive processes before and during test taking with 11/12- year-olds outperforming 9/10-year-olds when considering characteristics of on-going retrieval processes. As to the influence of achievement level, high compared to low achievers proved to be more accurate in their Metacognitive Monitoring and controlling. Results suggest that both cognitive resources (operationalized through achievement level) and mnemonic experience (assessed through age) fuel Metacognitive development. Nevertheless, when facing higher demands regarding retrieval processes, experience seems to play the more important role.
-
the effects of summary production and encoding condition on children s Metacognitive Monitoring
Metacognition and Learning, 2011Co-Authors: Nicole Von Der Linden, Wolfgang Schneider, Claudia M. RoebersAbstract:Two studies were conducted to investigate whether context variations were suitable to improve Metacognitive judgments in children in a complex, everyday memory task. In the first phase of each experiment, participants were shown a short event (video) and gave judgments-of-learning (JOLs), that is, rated their certainty that they would later be able to recall specific details correctly. In the second phase of the experiments, participants took part in a memory interview about the memory event and gave confidence judgments (CJs), that is, rated their certainty that the provided answers to the memory questions were correct. Study 1 specifically investigated the potential positive influence of giving a verbal summary before the JOL-interview on Metacognitive Monitoring, whereas Study 2 had a closer look on the effect of intentional versus non-intentional encoding on JOL and CJ accuracy. Results revealed no significant influence of giving a summary and hardly any effect of encoding condition on metamemory Monitoring although children from age 6 on showed adequate Monitoring performance. JOL accuracy appears to be a complex process, which is even more difficult to influence in children than in adults.
Mark Brosnan - One of the best experts on this subject based on the ideXlab platform.
-
supporting Metacognitive Monitoring in mathematics learning for young people with autism spectrum disorder a classroom based study
Autism, 2019Co-Authors: Katie Maras, Tim Gamble, Mark BrosnanAbstract:Previous research suggests impaired Metacognitive Monitoring and mathematics under-achievement in autism spectrum disorder. Within educational settings, Metacognitive Monitoring is supported through the provision of feedback (e.g. with goal reminders and by explicitly correcting errors). Given the strength of the relationship between metacognition, learning and educational attainment, this research tested new computer-based Metacognitive support (the 'Maths Challenge') for mathematics learners with autism spectrum disorder within the context of their classroom. The Maths Challenge required learners to engage in Metacognitive Monitoring before and after answering each question (e.g. intentions and judgements of accuracy) and negotiate with the system the level of difficulty. Forty secondary school children with autism spectrum disorder and 95 typically developing learners completed the Maths Challenge in either a Feedback condition, with Metacognitive Monitoring support regarding the accuracy of their answers, goal reminders and strategy support, or with No Feedback. Contrary to previous findings, learners with autism showed an undiminished ability to detect errors. They did, however, demonstrate reduced cohesion between their pre- and post-test intentions. Crucially, support from the Feedback condition significantly improved task performance for both groups. Findings highlight important implications for educational interventions regarding the provision of Metacognitive support for learners with autism to ameliorate under-performance in mathematics within the classroom.
-
deficits in Metacognitive Monitoring in mathematics assessments in learners with autism spectrum disorder
Autism, 2016Co-Authors: Mark Brosnan, Hilary Johnson, Beate Grawemeyer, Emma Chapman, Konstantina Antoniadou, Melissa HollinworthAbstract:Children and adults with autism spectrum disorder have been found to have deficits in metacognition that could impact upon their learning. This study explored Metacognitive Monitoring in 28 (23 males and 5 females) participants with autism spectrum disorder and 56 (16 males and 40 females) typically developing controls who were being educated at the same level. Participants were asked a series of mathematics questions. Based upon previous research, after each question they were asked two Metacognitive questions: (1) whether they thought they had got the answer correct or not (or ‘don’t know’) and (2) whether they meant to get the answer correct or not (or ‘don’t know’). Participants with autism spectrum disorder were significantly more likely than the typically developing group to erroneously think that they had got an incorrect answer correct. Having made an error, those with autism spectrum disorder were also significantly more likely to report that they had meant to make the error. Different patterns i...
Roger Azevedo - One of the best experts on this subject based on the ideXlab platform.
-
using sequence mining to analyze Metacognitive Monitoring and scientific inquiry based on levels of efficiency and emotions during game based learning
Educational Data Mining, 2018Co-Authors: Michelle Taub, Roger AzevedoAbstract:Self-regulated learning conducted through Metacognitive Monitoring and scientific inquiry can be influenced by many factors, such as emotions and motivation, and are necessary skills needed to engage in efficient hypothesis testing during game-based learning. Although many studies have investigated Metacognitive Monitoring and scientific inquiry skills during game-based learning, few studies have investigated how the sequence of behaviors involved during hypothesis testing with game-based learning differ based on both efficiency level and emotions during gameplay. For this study, we analyzed 59 undergraduate students’ (59% female) Metacognitive Monitoring and hypothesis testing behavior during learning and gameplay with CRYSTAL ISLAND, a game-based learning environment that teaches students about microbiology. Specifically, we used sequential pattern mining and differential sequence mining to determine if there were sequences of hypothesis testing behaviors and to determine if the frequencies of occurrence of these sequences differed between high or low levels of efficiency at finishing the game and high or low levels of facial expressions of emotions during gameplay. Results revealed that students with low levels of efficiency and high levels of facial expressions of emotions had the most sequences of testing behaviors overall, specifically engaging in more sequences that were indicative of less strategic hypothesis testing behavior than the other students, where students who were more efficient with both levels of emotions demonstrated strategic testing behavior. These results have implications for the strengths of using educational data mining techniques for determining the processes underlying patterns of engaging in self-regulated learning conducted through hypothesis testing as they unfold over time; for training students on how to engage in the self-regulation, scientific inquiry, and emotion regulation processes that can result in efficient gameplay; and for developing adaptive game-based learning environments that foster effective and efficient self-regulation and scientific inquiry during learning.
-
how do different levels of au4 impact Metacognitive Monitoring during learning with intelligent tutoring systems
Intelligent Tutoring Systems, 2018Co-Authors: Michelle Taub, Roger Azevedo, Nicholas V MudrickAbstract:We investigated how college students’ (n = 40) different levels of action unit 4 (AU4: brow lowerer), Metacognitive Monitoring process use and pre-test score were associated with Metacognitive Monitoring accuracy during learning with a hypermedia-based ITS. Results revealed that participants with high pre-test scores had the highest accuracy scores with low levels of AU4 and use of more Metacognitive Monitoring processes, whereas participants with low pre-test scores had higher accuracy scores with high levels of AU4 and use of more Metacognitive Monitoring processes. Implications include designing adaptive ITSs that provide different types of scaffolding based on levels of prior knowledge, use of Metacognitive Monitoring processes, and emotional expressivity keeping in mind that levels of emotions change over time, and therefore must be monitored to provide effective scaffolding during learning.
-
using sequence mining to reveal the efficiency in scientific reasoning during stem learning with a game based learning environment
Learning and Instruction, 2017Co-Authors: Michelle Taub, Roger Azevedo, Garrett C Millar, Amanda E Bradbury, James C LesterAbstract:Abstract The goal of this study was to assess how Metacognitive Monitoring and scientific reasoning impacted the efficiency of game completion during learning with Crystal Island, a game-based learning environment that fosters self-regulated learning and scientific reasoning by having participants solve the mystery of what illness impacted inhabitants of the island. We conducted sequential pattern mining and differential sequence mining on 64 undergraduate participants’ hypothesis testing behavior. Patterns were coded based on the relevancy of what items were being tested for, and the items themselves. Results revealed that participants who were more efficient at solving the mystery tested significantly fewer partially-relevant and irrelevant items than less efficient participants. Additionally, more efficient participants had fewer sequences of testing items overall, and significantly lower instance support values of the PartiallyRelevant -- Relevant to Relevant -- Relevant and PartiallyRelevant -- PartiallyRelevant to Relevant--Partially Relevant sequences compared to less efficient participants. These findings have implications for designing adaptive GBLEs that scaffold participants based on in-game behaviors.
-
using multi level modeling with eye tracking data to predict Metacognitive Monitoring and self regulated learning with crystal island
Intelligent Tutoring Systems, 2016Co-Authors: Michelle Taub, Roger Azevedo, Nicholas V Mudrick, Garrett C Millar, Jonathan P Rowe, James C LesterAbstract:Studies investigating the effectiveness of game-based learning environments GBLEs have reported the effectiveness of these environments on learning and retention. However, there is limited research on using eye-tracking data to investigate Metacognitive Monitoring with GBLEs. We report on a study that investigated how college students' eye tracking behavior ni?ź=i?ź25 predicted performance on embedded assessments within the Crystal Island GBLE. Results revealed that the number of books, proportion of fixations on book and article content, and proportion of fixations on concept matrices--embedded assessments associated with each in-game book and article--significantly predicted the number of concept matrix attempts. These findings suggest that participants strategized when reading book and article content and completing assessments, which led to better performance. Implications for designing adaptive GBLEs include adapting to individual student needs based on eye-tracking behavior in order to foster efficient completion of in-game embedded assessments.
-
adolescents use of self regulatory processes and their relation to qualitative mental model shifts while using hypermedia
International Conference of Learning Sciences, 2006Co-Authors: Jeffrey A Greene, Roger AzevedoAbstract:This study examined 148 adolescents' use of self-regulated learning (SRL) processes when learning about the circulatory system using hypermedia. All participants scored in the lowest category on a measure of conceptual understanding regarding their mental model. We examined participants' verbal protocols to determine the relationship between SRL processes and qualitative shifts in students' mental models from pretest to posttest. Results indicated that participants who exhibited a qualitative shift in their mental models, pretest to posttest, displayed differential use of six SRL processes. These SRL processes included Metacognitive Monitoring activities, learning strategies, and indications of task difficulty. We propose that these SRL processes can account for the participants' shift in mental model. Implications for the design of hypermedia learning environments are presented.
Bert De Smedt - One of the best experts on this subject based on the ideXlab platform.
-
the neural basis of Metacognitive Monitoring during arithmetic in the developing brain
Human Brain Mapping, 2020Co-Authors: Elien Bellon, Wim Fias, Daniel Ansari, Bert De SmedtAbstract:In contrast to a substantial body of research on the neural basis of cognitive performance in several academic domains, less is known about how the brain generates Metacognitive (MC) awareness of such performance. The existing work on the neurobiological underpinnings of metacognition has almost exclusively been done in adults and has largely focused on lower level cognitive processing domains, such as perceptual decision-making. Extending this body of evidence, we investigated MC Monitoring by asking children to solve arithmetic problems, an educationally relevant higher-order process, while providing concurrent MC reports during fMRI acquisition. Results are reported on 50 primary school children aged 9-10 years old. The current study is the first to demonstrate that brain activity during MC Monitoring, relative to the control task, increased in the left inferior frontal gyrus in children. This brain activity further correlated with children's arithmetic development over a 3-year time period. These data are in line with the frequently suggested, yet never empirically tested, hypothesis that activity in the prefrontal cortex during arithmetic is related to the higher-order process of MC Monitoring.
-
metacognition across domains is the association between arithmetic and Metacognitive Monitoring domain specific
PLOS ONE, 2020Co-Authors: Elien Bellon, Wim Fias, Bert De SmedtAbstract:Metacognitive Monitoring is a critical predictor of arithmetic in primary school. One outstanding question is whether this Metacognitive Monitoring is domain-specific or whether it reflects a more general performance Monitoring process. To answer this conundrum, we investigated Metacognitive Monitoring in two related, yet distinct academic domains: arithmetic and spelling. This allowed us to investigate whether Monitoring in one domain correlated with Monitoring in the other domain, and whether Monitoring in one domain was predictive of performance in the other, and vice versa. Participants were 147 typically developing 8-9-year-old children (Study 1) and 77 typically developing 7-8-year-old children (Study 2), who were in the middle of an important developmental period for both Metacognitive Monitoring and academic skills. Pre-registered analyses revealed that within-domain Metacognitive Monitoring was an important predictor of arithmetic and spelling at both ages. In 8-9-year-olds the Metacognitive Monitoring measures in different academic domains were predictive of each other, even after taking into account academic performance in these domains. Monitoring in arithmetic was an important predictor of spelling performance, even when arithmetic performance was controlled for. Likewise, Monitoring in spelling was an important predictor of arithmetic performance, even when spelling performance was controlled for. In 7-8-year-olds Metacognitive Monitoring was domain-specific, with neither correlations between the Monitoring measures, nor correlations between Monitoring in one domain and performance in the other. Taken together, these findings indicate that more domain-general Metacognitive Monitoring processes emerge over the ages from 7 to 9.
Michelle Taub - One of the best experts on this subject based on the ideXlab platform.
-
using sequence mining to analyze Metacognitive Monitoring and scientific inquiry based on levels of efficiency and emotions during game based learning
Educational Data Mining, 2018Co-Authors: Michelle Taub, Roger AzevedoAbstract:Self-regulated learning conducted through Metacognitive Monitoring and scientific inquiry can be influenced by many factors, such as emotions and motivation, and are necessary skills needed to engage in efficient hypothesis testing during game-based learning. Although many studies have investigated Metacognitive Monitoring and scientific inquiry skills during game-based learning, few studies have investigated how the sequence of behaviors involved during hypothesis testing with game-based learning differ based on both efficiency level and emotions during gameplay. For this study, we analyzed 59 undergraduate students’ (59% female) Metacognitive Monitoring and hypothesis testing behavior during learning and gameplay with CRYSTAL ISLAND, a game-based learning environment that teaches students about microbiology. Specifically, we used sequential pattern mining and differential sequence mining to determine if there were sequences of hypothesis testing behaviors and to determine if the frequencies of occurrence of these sequences differed between high or low levels of efficiency at finishing the game and high or low levels of facial expressions of emotions during gameplay. Results revealed that students with low levels of efficiency and high levels of facial expressions of emotions had the most sequences of testing behaviors overall, specifically engaging in more sequences that were indicative of less strategic hypothesis testing behavior than the other students, where students who were more efficient with both levels of emotions demonstrated strategic testing behavior. These results have implications for the strengths of using educational data mining techniques for determining the processes underlying patterns of engaging in self-regulated learning conducted through hypothesis testing as they unfold over time; for training students on how to engage in the self-regulation, scientific inquiry, and emotion regulation processes that can result in efficient gameplay; and for developing adaptive game-based learning environments that foster effective and efficient self-regulation and scientific inquiry during learning.
-
how do different levels of au4 impact Metacognitive Monitoring during learning with intelligent tutoring systems
Intelligent Tutoring Systems, 2018Co-Authors: Michelle Taub, Roger Azevedo, Nicholas V MudrickAbstract:We investigated how college students’ (n = 40) different levels of action unit 4 (AU4: brow lowerer), Metacognitive Monitoring process use and pre-test score were associated with Metacognitive Monitoring accuracy during learning with a hypermedia-based ITS. Results revealed that participants with high pre-test scores had the highest accuracy scores with low levels of AU4 and use of more Metacognitive Monitoring processes, whereas participants with low pre-test scores had higher accuracy scores with high levels of AU4 and use of more Metacognitive Monitoring processes. Implications include designing adaptive ITSs that provide different types of scaffolding based on levels of prior knowledge, use of Metacognitive Monitoring processes, and emotional expressivity keeping in mind that levels of emotions change over time, and therefore must be monitored to provide effective scaffolding during learning.
-
using sequence mining to reveal the efficiency in scientific reasoning during stem learning with a game based learning environment
Learning and Instruction, 2017Co-Authors: Michelle Taub, Roger Azevedo, Garrett C Millar, Amanda E Bradbury, James C LesterAbstract:Abstract The goal of this study was to assess how Metacognitive Monitoring and scientific reasoning impacted the efficiency of game completion during learning with Crystal Island, a game-based learning environment that fosters self-regulated learning and scientific reasoning by having participants solve the mystery of what illness impacted inhabitants of the island. We conducted sequential pattern mining and differential sequence mining on 64 undergraduate participants’ hypothesis testing behavior. Patterns were coded based on the relevancy of what items were being tested for, and the items themselves. Results revealed that participants who were more efficient at solving the mystery tested significantly fewer partially-relevant and irrelevant items than less efficient participants. Additionally, more efficient participants had fewer sequences of testing items overall, and significantly lower instance support values of the PartiallyRelevant -- Relevant to Relevant -- Relevant and PartiallyRelevant -- PartiallyRelevant to Relevant--Partially Relevant sequences compared to less efficient participants. These findings have implications for designing adaptive GBLEs that scaffold participants based on in-game behaviors.
-
using multi level modeling with eye tracking data to predict Metacognitive Monitoring and self regulated learning with crystal island
Intelligent Tutoring Systems, 2016Co-Authors: Michelle Taub, Roger Azevedo, Nicholas V Mudrick, Garrett C Millar, Jonathan P Rowe, James C LesterAbstract:Studies investigating the effectiveness of game-based learning environments GBLEs have reported the effectiveness of these environments on learning and retention. However, there is limited research on using eye-tracking data to investigate Metacognitive Monitoring with GBLEs. We report on a study that investigated how college students' eye tracking behavior ni?ź=i?ź25 predicted performance on embedded assessments within the Crystal Island GBLE. Results revealed that the number of books, proportion of fixations on book and article content, and proportion of fixations on concept matrices--embedded assessments associated with each in-game book and article--significantly predicted the number of concept matrix attempts. These findings suggest that participants strategized when reading book and article content and completing assessments, which led to better performance. Implications for designing adaptive GBLEs include adapting to individual student needs based on eye-tracking behavior in order to foster efficient completion of in-game embedded assessments.
