支持学生在建模活动中的知识转移

IF 4 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
J. Piksööt, T. Sarapuu
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引用次数: 8

摘要

本研究旨在探讨如何透过问题提示来促进中学生在复杂科学领域的知识转移。两个学生样本应用了两个基于网络的模型来研究分子遗传学——遗传密码模型(n = 258)和翻译模型(n = 245)。对于每个模型,样本随机分为实验组和对照组,并提供相同的任务-通过增加或改变模型中的对象来构建复杂的生物过程。实验组在每次建模活动后被提示回答一个问题,以促进他们的知识从对象的本体论类别转移到过程类别,而对照组在没有问题提示的情况下工作。研究结果表明,实验组学生在建模活动中的错误明显少于对照组学生。此外,问题提示的额外支持对学生在前测和后测中的答案所显示的知识转移有统计学上显著的影响。因此,该研究提供了强有力的证据,表明在学习复杂学科时,通过采用适当的提问策略,引导学生注意所描述过程的相关特征,可以提高学生从一个本体论类别到另一个本体论类别的知识转移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supporting Students' Knowledge Transfer in Modeling Activities
This study investigates ways to enhance secondary school students' knowledge transfer in complex science domains by implementing question prompts. Two samples of students applied two web-based models to study molecular genetics—the model of genetic code (n = 258) and translation (n = 245). For each model, the samples were randomly divided into experimental and control groups and were provided with the same tasks—to construct a complex biological process by adding or changing objects in the model. The experimental group was prompted to answer a question after each modeling activity in order to facilitate their knowledge transfer from the ontological category of objects to the category of processes, whereas the control group worked without question prompts. The results of the study indicated that the students of the experimental group made significantly fewer mistakes in modeling activities than their peers in the control group. Moreover, the additional support by question prompts had a statistically significant influence on the students' knowledge transfer as indicated by their answers in the pre- and post-tests. Therefore, the study provides strong evidence that students' knowledge transfer from one ontological category to another can be improved by applying an appropriate questioning strategy that guides attention to the relevant features of the depicted processes while studying a complex subject.
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来源期刊
Journal of Educational Computing Research
Journal of Educational Computing Research EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
11.90
自引率
6.20%
发文量
69
期刊介绍: The goal of this Journal is to provide an international scholarly publication forum for peer-reviewed interdisciplinary research into the applications, effects, and implications of computer-based education. The Journal features articles useful for practitioners and theorists alike. The terms "education" and "computing" are viewed broadly. “Education” refers to the use of computer-based technologies at all levels of the formal education system, business and industry, home-schooling, lifelong learning, and unintentional learning environments. “Computing” refers to all forms of computer applications and innovations - both hardware and software. For example, this could range from mobile and ubiquitous computing to immersive 3D simulations and games to computing-enhanced virtual learning environments.
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