Metacognition in the Teaching and Learning of Mathematics

Lee, Ngan Hoe; Ng, Kit Ee Dawn; Yeo, Joseph B. W.

doi:10.1007/978-981-13-3573-0_11

Cited by 5 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Singaporean students with high intrinsic motivation could still obtain high mathematics performance, though they used memorization strategies. These results could indicate that Singaporean teachers do not have concrete concepts between metacognition and cognition learning strategies to teach students (Lee et al, 2019). In turn, students might not understand how to use appropriate learning strategies during learning mathematics, though they have high intrinsic motivation.…”

Section: Discussionmentioning

confidence: 99%

Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis

Chen

Kiefer

et al. 2021

SAGE Open

View full text Add to dashboard Cite

This study applied a three-step latent class analysis (LCA) approach to explore latent classes of learning strategy use and their moderation effects on the relationships between motivation and mathematics performance. The data of 15-year-old students from five East Asian educational systems related to Chinese culture in the Programme of International Student Assessment (PISA) in 2012 were analyzed. The findings indicated that Shanghai, Singapore, Taiwan, and Macau showed three latent classes of learning strategies, whereas Hong Kong had two latent classes. Most students in the five educational systems reported to use the control strategy, some students reported the use of combined learning strategies, and few students reported the use of memorization except for students in Shanghai. Furthermore, we found the moderation effects of learning strategy use on mathematics performance depended on the types of motivation and educational systems. This study provides insights into the advantages of a three-step LCA approach in educational research.

show abstract

Section: Discussionmentioning

confidence: 99%

Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis

Chen

Kiefer

et al. 2021

SAGE Open

View full text Add to dashboard Cite

show abstract

“…Differences in metacognitive skills can be explained by examining variations in the knowledge of a learner and the learning tasks (Livingston, 2003). For example, differences in metacognitive skills were due to learners’ differences in language learning (Goh & Vandergrift, 2021; Kessler, 2021), mathematic problem-solving (Lee et al, 2019; Tian et al, 2018), and programming (Chetty & van der Westhuizen, 2014; Prather et al, 2020). Metacognition comes to fruition when a learner is strategic in learning new knowledge (knowing how ) and has an understanding of when and why certain behaviours are to be selected (Paris et al, 1983).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Metacognitive skills in low-code app development: Work-integrated learning in information systems development

Matook

Wang

KÃ¶ppel

et al. 2023

Journal of Information Technology

View full text Add to dashboard Cite

Low-code platforms can provide a learning environment that integrates academic theory with practical experiences, allowing students to experience real-world ISD projects. Such a pedagogy is known as work-integrated learning (WIL). In a low-code WIL course, the focus is on the practical development experiences and the delivery of a business application based on client’s requirements. Yet, the real-world ISD experiences may inhibit metacognition, which is essential for students to succeed in future learning of digital innovations. Without metacognition, students struggle to learn how to learn and be reflective about their learning. This study uses a mixed-method design and draws on Flavell’s (1979) theoretical framework to examine metacognition in the context of low-code WIL. In particular, the study examines the effect of learner-oriented factors and task-oriented factors on metacognition and its impact on learning outcomes, such as knowledge confidence, app delivery, and grade. The quantitative results indicate that metacognition is influenced by motivation, the strategic approach, and autonomy, whereas self-efficacy beliefs have no effect. The learning outcomes are also achieved. Qualitative results (students’ essays and apps) corroborate the quantitative results while also providing additional insights into the learning in low-code WIL showing the impact of the platform and agile ISD practices on metacognition. Overall, this study offers IS educators a better understanding of how low-code platforms can foster learning-to-learn while providing real-world practical experiences.

show abstract

“…In science education, current literature has not achieved a consensus regarding the construct of online metacognitive skills (Desoete, 2001;Desoete & Roeyers, 2002;Efklides, 2002;Lee et al, 2019). According to Chen and Goverover (2021), online metacognition skills comprise the abilities of monitoring (e.g., identifying mistakes) and regulation (e.g., correcting responses).…”

Section: Online Metacognitive Skillsmentioning

confidence: 99%

Developing and Validating an Instrument to Assess Ninth-Grade Students’ Online Metacognitive Skills in Solving Chemistry Problems

Zeng

Chi

Wang

et al. 2023

JBSE

View full text Add to dashboard Cite

Online metacognitive skills are the real-time awareness of cognition, which can effectively promote science learning and improve performance in solving scientific problems. Therefore, it is important to enhance and diagnose students’ online metacognitive skills in science education. This study aimed to evaluate ninth-grade students’ online metacognitive skills while processing chemistry problems. To achieve this goal, this study constructed a framework for guiding the development of an instrument comprising 12 two-tier items. A total of 258 ninth graders took part in the field testing in Jiangsu, China. A partial credit Rasch model analysis was employed to inform instrument development and evaluation. The results revealed that this instrument was valid and reliable for assessing students’ online metacognitive skills. Nearly 70% of the ninth-grade students in this sample were able to monitor their own thought processes or evaluate their own cognitive performance in processing chemistry problems. About one-third of the students could regulate their thought processes. However, less than 4% of the students could make attributions about their cognitive performance. Keywords: assessment instrument, problem-solving skills, Rasch measurement model, chemistry education

show abstract

Metacognition in the Teaching and Learning of Mathematics

Cited by 5 publications

References 18 publications

Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis

Learning Strategies as Moderators Between Motivation and Mathematics Performance in East Asian Students: Latent Class Analysis

Metacognitive skills in low-code app development: Work-integrated learning in information systems development

Developing and Validating an Instrument to Assess Ninth-Grade Students’ Online Metacognitive Skills in Solving Chemistry Problems

Contact Info

Product

Resources

About