Let them choose: Optional assignments and online learning patterns as predictors of success in online general chemistry courses

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Internet and Higher Education Pub Date : 2022-10-01 DOI:10.1016/j.iheduc.2022.100867

Yael Feldman-Maggor , Ron Blonder , Inbal Tuvi-Arad

{"title":"Let them choose: Optional assignments and online learning patterns as predictors of success in online general chemistry courses","authors":"Yael Feldman-Maggor , Ron Blonder , Inbal Tuvi-Arad","doi":"10.1016/j.iheduc.2022.100867","DOIUrl":null,"url":null,"abstract":"<div><p>This study examined learning processes in undergraduate online general chemistry courses. The study aimed to characterize learners according to their learning patterns and to identify indicators that predict students' success in an online environment. Specifically, we focused on the role of a central factor affecting success in online courses: self-regulated learning and learner engagement. To this end, we used a mixed methods approach that combines semi-structured interviews and statistical analysis. We applied two logistic regression models and a decision tree algorithm and found two parameters that can predict completion of the course: the submission status of an optional assignment and the students' cumulative video opening pattern (SCOP). Recommendations for institutions and lecturers regarding the benefits of implementing these models to identify self-regulated learning patterns in online courses and to design future effective interventions are discussed. Regarding students, we emphasize the importance of time management and how choices they make with respect to their learning process affect their potential for success.</p></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"55 ","pages":"Article 100867"},"PeriodicalIF":6.4000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet and Higher Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1096751622000239","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}

引用次数: 8

Abstract

This study examined learning processes in undergraduate online general chemistry courses. The study aimed to characterize learners according to their learning patterns and to identify indicators that predict students' success in an online environment. Specifically, we focused on the role of a central factor affecting success in online courses: self-regulated learning and learner engagement. To this end, we used a mixed methods approach that combines semi-structured interviews and statistical analysis. We applied two logistic regression models and a decision tree algorithm and found two parameters that can predict completion of the course: the submission status of an optional assignment and the students' cumulative video opening pattern (SCOP). Recommendations for institutions and lecturers regarding the benefits of implementing these models to identify self-regulated learning patterns in online courses and to design future effective interventions are discussed. Regarding students, we emphasize the importance of time management and how choices they make with respect to their learning process affect their potential for success.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

让他们自己选择:可选作业和在线学习模式作为在线普通化学课程成功的预测因素

本研究考察了本科在线普通化学课程的学习过程。该研究旨在根据学习者的学习模式来描述他们的特征，并确定预测学生在在线环境中取得成功的指标。具体来说，我们关注的是影响在线课程成功的一个核心因素:自主学习和学习者参与。为此，我们采用了半结构化访谈和统计分析相结合的混合方法。我们应用了两个逻辑回归模型和决策树算法，并找到了两个可以预测课程完成情况的参数:可选作业的提交状态和学生的累积视频开放模式(SCOP)。针对实施这些模式的好处，对机构和讲师提出了建议，以确定在线课程中自我调节的学习模式，并设计未来有效的干预措施。对于学生，我们强调时间管理的重要性，以及他们在学习过程中所做的选择如何影响他们成功的潜力。

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

Internet and Higher Education EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

19.30

自引率

4.70%

发文量

审稿时长

40 days

期刊介绍： The Internet and Higher Education is a quarterly peer-reviewed journal focused on contemporary issues and future trends in online learning, teaching, and administration within post-secondary education. It welcomes contributions from diverse academic disciplines worldwide and provides a platform for theory papers, research studies, critical essays, editorials, reviews, case studies, and social commentary.