scholarly journals Learning Self-regulated L2 WritingUnder a Cognitive Model

Author(s):  
Mrs Manashi Gogoi Dutta, Et. al.

This innovative approach of teaching L2 writing was experimentedbelieving that using a fewer self-regulated learning strategymay lead toweakmetacognitive learning attitude resulting in low proficiency.This research wasconducted to investigate the consequences of instructionally aroused cognitive involvement load for using self-regulated and metacognitive learning strategies to improve L2 writing skills. The innovative L2 writing instructional model of this study has been named as Strategic Self-Regulated Metacognitive Activities or S2RMCA.The approach of this model is to promoteself-regulated learning managementby learners. Forarousing the use of learning strategies, a set of self-monitoring and self-evaluatingassessment rubric namedStrategy Inventories for Learning L2 Writing(SILL2W)has also been designed. For collecting and analyzingthe data a questionnaire, pre-post-tests, checklist, and interviews wereutilized. Outcomes of data analyses have shownusefulness and practicality ofthe S2RMCA model for teaching self-regulated L2 writing. Acceptable resultshave also beenshownby participants intheir L2 writing skills. In research studies conducted on cognitive load, accurate measurement of load viaself-reporting has been a persistingquestion and this study has notbeen different from the onesthat have faced the challenge.

2021 ◽  
Author(s):  
Manashi Gogoi Dutta ◽  
Uthaivan Danvivath

Abstract This research study has been conducted to experiment an innovative teaching approach believing that when less use of self-regulated learning strategy leads to lower metacognitive learning attitude which results in low proficiency. This study has investigated the consequences of instructionally aroused cognitive involvement load for self-monitoring and self-assessment through facilitation of metacognitive learning strategy use for improving L2 writing skills of Thai undergraduate students. This innovative instructional model for teaching self-regulated L2 writing has been named as Strategic Self-Regulated Metacognitive Activities or S2RMCA. The approach of this model has been developed to promote self-regulated learning management. For stimulating the use of learning strategies, a set of self-monitoring and self-evaluating assessment rubric named Strategy Inventories for Learning L2 Writing (SILL2W) has also been devised. A set of questionnaire, pre-post-tests, checklist, and interviews were employed for collecting and analyzing the data. Results of data analyses have shown effectiveness and feasibility of the S2RMCA model for teaching self-regulated L2 writing. Satisfactory results have also been shown by participants in their L2 writing skills. So far, research studies conducted on cognitive involvement load, a continuing challenge has always been there regarding the accurate measurement of load via self-reporting and this study has also faced that challenge.


2019 ◽  
Vol 11 (2) ◽  
pp. 99
Author(s):  
Siew Siew Kim ◽  
Mariani Md. Nor

To enhance the will and the skills to express thoughts explicitly and effectively in early writing among preschool children, self-regulated learning (SRL) was suggested for preschool children as one of the effective learning approaches. This quasi-experimental study involved seventy-five preschool children (5-6 years old) from two public preschools in Selangor, Malaysia. This study investigated the effects of SRL strategies on early writing self-efficacy and early writing performance among preschool children. Interview data was engaged and supported the quantitative result to obtain a deep insight of the findings. Two-way Repeated Measure ANCOVA was employed and confirmed the effectiveness of self-regulated learning intervention with an interaction effect between the test and group for early writing self-efficacy being statistically significant (F(1, 72) = 12.665; p = 0.001, 2= 0.150), with Cohen’s d = 0.84;  and early writing performance statistically significant (F(1, 72) = 110.801; p < 0.001, 2= 0.606), with Cohen’s d = 2.84. The result also confirmed that self-monitoring and controlling (F (5, 69) = 17.934, p < 0.001), with an adjusted R² = 0.534, was a strong predictor for early writing self-efficacy, and planning and goal setting (F(5, 69) = 12.706, p< 0.001), with an adjusted R² = 0.442, were a strong predictor for early writing performance. Eleven self-regulated learning strategies used emerged from the interviews’ data pertaining to different contexts. According to the participant children, planning and goal setting, self-monitoring, and self-evaluation were the strategies that will assure their writing quality. These responses supported the results produced by the quantitative data. The findings of this research provide a useful insight into early writing and self-regulated learning instructions in the Malaysian preschool context.


2020 ◽  
Vol 25 ◽  
pp. 1
Author(s):  
Liz Cristiane Dias ◽  
Evely Boruchovitch

Este artigo objetiva averiguar, com base em uma revisão sistemática de literatura, o investimento em estratégias de ensino e aprendizagem autorregulada em cursos de Licenciatura em Geografia. Os dados foram coletados nas bases de dados Scientific Electronic Library Online, Red de Revistas Cientificas de America Latina y el Caribe, España y Portugal e na Plataforma Sucupira da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior em periódicos da Geografia com classificação Qualis A1, A2 e B1 dos últimos cinco anos. A busca pelos trabalhos teve como resultado o total de 154 artigos. Destes, apenas 25 tratavam especificamente da formação inicial de professores e, dentre estes, apenas 8 atendiam às demandas da pesquisa. Os resultados revelaram a necessidade de mais investimento em programas de intervenção em estratégias de aprendizagem e a necessidade de pesquisas futuras que disseminem na Geografia a temática da autorregulação.


2020 ◽  
Vol 32 (4) ◽  
pp. 1055-1072 ◽  
Author(s):  
Tamara van Gog ◽  
Vincent Hoogerheide ◽  
Milou van Harsel

Abstract Problem-solving tasks form the backbone of STEM (science, technology, engineering, and mathematics) curricula. Yet, how to improve self-monitoring and self-regulation when learning to solve problems has received relatively little attention in the self-regulated learning literature (as compared with, for instance, learning lists of items or learning from expository texts). Here, we review research on fostering self-regulated learning of problem-solving tasks, in which mental effort plays an important role. First, we review research showing that having students engage in effortful, generative learning activities while learning to solve problems can provide them with cues that help them improve self-monitoring and self-regulation at an item level (i.e., determining whether or not a certain type of problem needs further study/practice). Second, we turn to self-monitoring and self-regulation at the task sequence level (i.e., determining what an appropriate next problem-solving task would be given the current level of understanding/performance). We review research showing that teaching students to regulate their learning process by taking into account not only their performance but also their invested mental effort on a prior task when selecting a new task improves self-regulated learning outcomes (i.e., performance on a knowledge test in the domain of the study). Important directions for future research on the role of mental effort in (improving) self-monitoring and self-regulation at the item and task selection levels are discussed after the respective sections.


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