地学大数据背景下的矿床统计预测教学方法探讨  

The Teaching Methods of Ore Deposit Statistical Prediction under the Background of Geology Big Data

作　　者：赵江南[1] 

机构地区：[1]中国地质大学资源学院,湖北武汉430074

出　　处：《教育教学论坛》2018年第11期153-154,共2页Education And Teaching Forum

基　　金：中国地质大学(武汉)教学研究立项项目(2017A07);中国地质大学(武汉)优秀青年教师资助计划资助项目(26420160123)联合资助成果

摘　　要："矿床统计预测"是中国地质大学(武汉)开设历史较长的一门综合性学科交叉课程,目的是让学生掌握数学地质基本理论、基本方法,并应用这些理论与方法进行矿产资源定量预测,并培养数学地质专业青年人才。通过在近两年的教学实践及对学生的调查中,笔者认为加强本课程教学可以考虑从以下几个方面进行:(1)结合地学大数据为背景,完善授课内容设置,提高授课针对性,培养应用型人才;(2)构建多学科交叉融合的教学模式,培养学生的定量地学思维与系统思维;(3)通过优化课程考核评价体系,积极发挥考核的引导和激励作用。The ore deposit statistical prediction （ODSP） is a comprehensive frontier interdisciplinary course. Thepurpose is to promote students master the basic theories and methods of mathematical geology,understand theapplication of these theories and methods for quantitative prediction of mineral resources. It also strengthens the trainingof young professional mathematics geological talent. Through the teaching practice in recent years and the survey of thestudents,I think this can be considered to strengthen the ODSP teaching from the following aspects： （1） under thebackground of the geology big-data,improve the teaching content and teaching aim; （2） constructing amulti-disciplinary and cross linking teaching model to train students＇ quantitative thinking and systematic thinking;（3） optimize the evaluation system to play a guiding and incentive effect assessment.

关 键 词：教学方法 地学大数据 交叉学科 矿床统计预测 

分 类 号：G642.41[文化科学—高等教育学]