Intelligent Tutoring Systems Need Teachers.
Background: The development and distribution of digital learning software, such as intelligent tutoring systems (ITSs), has evolved into a billion‐dollar industry, impacting a vast number of students worldwide. A large number of studies on ITSs have focused on their effects on learning outcomes. How...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 1; pp. 1 - 12 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191181611&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191181611 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Feb2026 vid: 42 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 191181611 191181611 191181611 10.1002/jcal.70159 191181611 ppf: 1 ppct: 11 formats: tig: atl: Intelligent Tutoring Systems Need Teachers. aug: au: Bardach, Lisa Moeller, Korbinian Ruiz‐Garcia, Miguel Strittmatter, Younes Meyer, Jennifer Musslick, Sebastian Spitzer, Markus affil: Department of Psychology, University of Giessen, Giessen, Germany sug: subj: Computer-Assisted Instruction Teachers Student Dropouts Student Attitudes Teaching Methods Intelligent Systems Utilization Mathematics Education Faculty Role Educational Technology Utilization Human Germany Netherlands Male Female Child Adolescence Retrospective Design Record Review Nonexperimental Studies Survival Analysis Cox Proportional Hazards Model Linear Regression Probability Self-Directed Learning Faculty-Student Relations Learning Methods Motivation Academic Performance Course Content Child: 6-12 years Adolescent: 13-18 years Male Female ab: Background: The development and distribution of digital learning software, such as intelligent tutoring systems (ITSs), has evolved into a billion‐dollar industry, impacting a vast number of students worldwide. A large number of studies on ITSs have focused on their effects on learning outcomes. However, less is known about student engagement and dropout when ITSs are used in real classroom settings over extended periods, particularly with regard to how these patterns may be linked to different assignment scenarios within ITSs. Objective: The present study aimed to explore whether student engagement and dropout varied based on whether mathematics problems within the ITS were assigned by teachers or self‐assigned by students. Methods: We evaluated rich data from an ITS for learning mathematics used in Germany and the Netherlands (~139,000,000 problems; n ~ 194,000 students) between 2016 and 2023. To examine whether students' engagement and dropout, both within and between students, varied based on the two assignment scenarios (teacher assigned vs. self‐assigned problems), we employed regression and survival analyses. Results and Conclusions: Our results revealed that, in both Germany and the Netherlands, students with teacher‐assigned problems consistently (i) dropped out later, (ii) were active for significantly more weeks and (iii) worked through more mathematics problems each week than those who self‐assigned problems. The results were robust across academic school years in the examined period. Overall, our study raises questions about the use of digital learning software as a stand‐alone solution and suggests embedding such software in real‐life learning scenarios involving teachers. Lay Summary: What is currently known about this topic? ○Digital tools like intelligent tutoring systems (ITSs) have been developed to support student learning.○Despite large investments, real‐world use of ITSs is not yet fully understood.○Student dropout and disengagement limit the benefits of digital tools.○There is a need to better understand factors linked to dropout and engagement.What does this paper add? ○We examine links between assignment scenarios in ITSs and student engagement/dropout using data from real classroom settings.○Students drop out earlier and engage less when they self‐assign problems in the ITS than when teachers assign problems to them.○We show that these effects appear in both Germany and the Netherlands.Implications for practice and/or policy ○Teachers may need to stay involved when students use ITSs over extended periods.○ITSs may be better integrated into classroom practices rather than used in isolation.○Involving educators in the design of ITSs may help align these tools with classroom realities. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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