{"title":"支持学生在建模活动中的知识转移","authors":"J. Piksööt, T. Sarapuu","doi":"10.2190/EC.50.2.d","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2190/EC.50.2.d","citationCount":"8","resultStr":"{\"title\":\"Supporting Students' Knowledge Transfer in Modeling Activities\",\"authors\":\"J. Piksööt, T. Sarapuu\",\"doi\":\"10.2190/EC.50.2.d\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":47865,\"journal\":{\"name\":\"Journal of Educational Computing Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2014-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2190/EC.50.2.d\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Educational Computing Research\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://doi.org/10.2190/EC.50.2.d\",\"RegionNum\":2,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational Computing Research","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.2190/EC.50.2.d","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
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.
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.