K. Koedinger, Elizabeth Mclaughlin, J. Z. Jia, Norman L. Bier
{"title":"Is the doer effect a causal relationship?: how can we tell and why it's important","authors":"K. Koedinger, Elizabeth Mclaughlin, J. Z. Jia, Norman L. Bier","doi":"10.1145/2883851.2883957","DOIUrl":null,"url":null,"abstract":"The \"doer effect\" is an association between the number of online interactive practice activities students' do and their learning outcomes that is not only statistically reliable but has much higher positive effects than other learning resources, such as watching videos or reading text. Such an association suggests a causal interpretation--more doing yields better learning--which requires randomized experimentation to most rigorously confirm. But such experiments are expensive, and any single experiment in a particular course context does not provide rigorous evidence that the causal link will generalize to other course content. We suggest that analytics of increasingly available online learning data sets can complement experimental efforts by facilitating more widespread evaluation of the generalizability of claims about what learning methods produce better student learning outcomes. We illustrate with analytics that narrow in on a causal interpretation of the doer effect by showing that doing within a course unit predicts learning of that unit content more than doing in units before or after. We also provide generalizability evidence across four different courses involving over 12,500 students that the learning effect of doing is about six times greater than that of reading.","PeriodicalId":343844,"journal":{"name":"Proceedings of the Sixth International Conference on Learning Analytics & Knowledge","volume":"02 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International Conference on Learning Analytics & Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2883851.2883957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 54
Abstract
The "doer effect" is an association between the number of online interactive practice activities students' do and their learning outcomes that is not only statistically reliable but has much higher positive effects than other learning resources, such as watching videos or reading text. Such an association suggests a causal interpretation--more doing yields better learning--which requires randomized experimentation to most rigorously confirm. But such experiments are expensive, and any single experiment in a particular course context does not provide rigorous evidence that the causal link will generalize to other course content. We suggest that analytics of increasingly available online learning data sets can complement experimental efforts by facilitating more widespread evaluation of the generalizability of claims about what learning methods produce better student learning outcomes. We illustrate with analytics that narrow in on a causal interpretation of the doer effect by showing that doing within a course unit predicts learning of that unit content more than doing in units before or after. We also provide generalizability evidence across four different courses involving over 12,500 students that the learning effect of doing is about six times greater than that of reading.