What is scaffolded teaching in science?

Answer from top 2 papers

Scaffolded teaching in science is an instructional strategy that provides temporary support to students as they learn new concepts, with the ultimate goal of fostering independent learning. Research has shown that scaffolded teaching can significantly improve students' attitudes towards science and their learning outcomes ( and ). For instance, students taught using scaffolding strategies exhibited a more positive attitude towards learning science compared to those taught with conventional methods (). Additionally, integrating scaffolding into digital game-based learning and computer-based environments has been found to enhance learning outcomes in scientific inquiry and STEM education ((Kim et al., 2017) and ).
Interestingly, while scaffolded teaching generally has a strong effect across student populations and STEM disciplines, there are exceptions. For example, the effectiveness of scaffolding varies with different problem-centered instructional models and is less pronounced in secondary education (). Moreover, the impact of computer-based scaffolding on cognitive outcomes does not significantly differ based on the customization of the scaffolding or the context-specificity of the support provided ().
In summary, scaffolded teaching is a powerful educational strategy in science education that supports students' cognitive development and fosters positive attitudes towards learning. The research underscores the effectiveness of scaffolding across various instructional models and educational levels, although its impact may vary depending on specific contexts and student populations. Future research could explore the nuances of scaffolded teaching to optimize its application in diverse learning environments ( and ).

Source Papers

198
10.1007/s10648-017-9419-1

Effectiveness of Computer-Based Scaffolding in the Context of Problem-Based Learning for Stem Education: Bayesian Meta-analysis

Jul 29, 2017
Educational Psychology Review
Nam Ju Kim + 2 more +2

Computer-based scaffolding plays a pivotal role in improving students’ higher-order skills in the context of problem-based learning for Science, Technology, Engineering and Mathematics (STEM) education. The effectiveness of computer-based scaffolding has been demonstrated through traditional meta-analyses. However, traditional meta-analyses suffer from small-study effects and a lack of studies covering certain characteristics. This research investigates the effectiveness of computer-based scaffolding in the context of problem-based learning for STEM education through Bayesian meta-analysis (BMA). Specifically, several types of prior distribution information inform Bayesian simulations of studies, and this generates accurate effect size estimates of six moderators (total 24 subcategories) related to the characteristics of computer-based scaffolding and the context of scaffolding utilization. The results of BMA indicated that computer-based scaffolding significantly impacted (g = 0.385) cognitive outcomes in problem-based learning in STEM education. Moreover, according to the characteristics and the context of use of scaffolding, the effects of computer-based scaffolding varied with a range of small to moderate values. The result of the BMA contributes to an enhanced understanding of the effect of computer-based scaffolding within problem-based learning.

10.15354/bece.22.ab006

An Empirical Study on the Data Analytics-based Self-Regulated Learning Scaffolding Model for Primary Students

Jul 30, 2022
Best Evidence in Chinese Education
Tao Huang

In the age of Internet Plus, the deep integration of information technology into education and individualized instruction have become a growing trend in education development. Self-regulated learning is a key element of student core competence, but easy to be overlooked in basic education. The purpose of this study is to establish the data analytics-based self-regulated learning scaffolding model for primary students and test its results in teaching practice, citing Scaffolding Theory and Zone of Proximal Development Theory as its rationale. Research findings demonstrate that learning data analytics-enabled self-regulated after-class learning can help enhance learning outcomes and develop student learning strategies.