Blockly-DS: Blocks Programming for Data Science with Visual, Statistical, Descriptive and Predictive Analysis

Luiz Barboza, Rafael Mello, M. Modell, E. Teixeira
{"title":"Blockly-DS: Blocks Programming for Data Science with Visual, Statistical, Descriptive and Predictive Analysis","authors":"Luiz Barboza, Rafael Mello, M. Modell, E. Teixeira","doi":"10.1145/3576050.3576097","DOIUrl":null,"url":null,"abstract":"Interest in data science has been growing across industries - both STEM and non-STEM. Non-STEM students often have difficulties with programming and data analysis tools. These entry barriers can be minimized, and these concepts can be easily absorbed when using visual tools. Thus, for this specific audience, the use of visual tools has been essential for teaching data science. Several of these tools are available, but they all have limitations. This work presents Blockly-DS: a new tool capable of assisting in teaching data science to a non-STEM audience. The Blockly-DS tool is being tested in two Brazilian higher education institutions, one, IBMEC, a business undergraduate university, and the other, FIAP, a STEM school that offers an MBA as well as corporate and undergraduate courses. The preliminary results presented in this article refers to a validation with two groups of training sessions for junior financial analysts of a major Brazilian bank in partnership with FIAP.","PeriodicalId":394433,"journal":{"name":"LAK23: 13th International Learning Analytics and Knowledge Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"LAK23: 13th International Learning Analytics and Knowledge Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3576050.3576097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Interest in data science has been growing across industries - both STEM and non-STEM. Non-STEM students often have difficulties with programming and data analysis tools. These entry barriers can be minimized, and these concepts can be easily absorbed when using visual tools. Thus, for this specific audience, the use of visual tools has been essential for teaching data science. Several of these tools are available, but they all have limitations. This work presents Blockly-DS: a new tool capable of assisting in teaching data science to a non-STEM audience. The Blockly-DS tool is being tested in two Brazilian higher education institutions, one, IBMEC, a business undergraduate university, and the other, FIAP, a STEM school that offers an MBA as well as corporate and undergraduate courses. The preliminary results presented in this article refers to a validation with two groups of training sessions for junior financial analysts of a major Brazilian bank in partnership with FIAP.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
block - ds:基于可视化、统计、描述和预测分析的数据科学块编程
各行各业(包括STEM和非STEM行业)对数据科学的兴趣一直在增长。非stem学生通常在编程和数据分析工具方面有困难。这些进入障碍可以被最小化,当使用可视化工具时,这些概念可以很容易地被吸收。因此,对于这一特定受众,可视化工具的使用对于数据科学教学至关重要。这些工具中有几个是可用的,但它们都有局限性。这项工作提出了block - ds:一个能够协助向非stem受众教授数据科学的新工具。block - ds工具正在两所巴西高等教育机构进行测试,一所是商科本科大学IBMEC,另一所是FIAP,一所提供MBA以及企业和本科课程的STEM学校。本文中提出的初步结果涉及与FIAP合作的巴西一家主要银行初级金融分析师的两组培训课程的验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Blockly-DS: Blocks Programming for Data Science with Visual, Statistical, Descriptive and Predictive Analysis Instructor-in-the-Loop Exploratory Analytics to Support Group Work How to Build More Generalizable Models for Collaboration Quality? Lessons Learned from Exploring Multi-Context Audio-Log Datasets using Multimodal Learning Analytics Fostering Privacy Literacy among High School Students by Leveraging Social Media Interaction and Learning Traces in the Classroom Predicting Students’ Algebra I Performance using Reinforcement Learning with Multi-Group Fairness
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1