{"title":"Investigating learning processes through analysis of navigation behavior using log files.","authors":"Kerstin Huber, Maria Bannert","doi":"10.1007/s12528-023-09372-3","DOIUrl":null,"url":null,"abstract":"<p><p>The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining can predict learning outcomes. This work aims to provide support for learners and instructors regarding efficient learning with computer-based learning environments (CBLEs). We evaluated log file and questionnaire data from students (<i>N</i> = 58) who used a CBLE for two weeks. Results show a significant learning increase after studying with the CBLE with a very high effect size (<i>p</i> < .001, <i>g</i> = 1.71). A cluster analysis revealed two groups with significantly different learning outcomes accompanied by different navigation patterns. The time spent on learning-relevant pages and the interactivity with a CBLE are meaningful indicators for Recall and Transfer performance. Our results show that navigation behaviors indicate both beneficial and detrimental learning processes. Moreover, we could demonstrate that navigation behaviors impact the learning outcome. We present an easy-to-use approach for learners as well as instructors to promote successful learning by tracking the duration spent in a CBLE and the interactivity.</p>","PeriodicalId":15404,"journal":{"name":"Journal of Computing in Higher Education","volume":" ","pages":"1-19"},"PeriodicalIF":4.5000,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134688/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing in Higher Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s12528-023-09372-3","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}
引用次数: 0
Abstract
The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining can predict learning outcomes. This work aims to provide support for learners and instructors regarding efficient learning with computer-based learning environments (CBLEs). We evaluated log file and questionnaire data from students (N = 58) who used a CBLE for two weeks. Results show a significant learning increase after studying with the CBLE with a very high effect size (p < .001, g = 1.71). A cluster analysis revealed two groups with significantly different learning outcomes accompanied by different navigation patterns. The time spent on learning-relevant pages and the interactivity with a CBLE are meaningful indicators for Recall and Transfer performance. Our results show that navigation behaviors indicate both beneficial and detrimental learning processes. Moreover, we could demonstrate that navigation behaviors impact the learning outcome. We present an easy-to-use approach for learners as well as instructors to promote successful learning by tracking the duration spent in a CBLE and the interactivity.
期刊介绍:
Journal of Computing in Higher Education (JCHE) contributes to our understanding of the design, development, and implementation of instructional processes and technologies in higher education. JCHE publishes original research, literature reviews, implementation and evaluation studies, and theoretical, conceptual, and policy papers that provide perspectives on instructional technology’s role in improving access, affordability, and outcomes of postsecondary education. Priority is given to well-documented original papers that demonstrate a strong grounding in learning theory and/or rigorous educational research design.