Intelligent Support for Practice Goal Setting to Enhance Learning

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Bibliographic Details
Title: Intelligent Support for Practice Goal Setting to Enhance Learning
Language: English
Authors: Conrad Borchers (ORCID 0000-0003-3437-8979), Kenneth R. Koedinger (ORCID 0000-0002-5850-4768), Vincent Aleven (ORCID 0000-0002-1581-6657)
Source: Grantee Submission. 2025.
Peer Reviewed: Y
Page Count: 7
Publication Date: 2025
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305A220386
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Junior High Schools
Middle Schools
Secondary Education
Descriptors: Goal Orientation, Active Learning, Rewards, Academic Achievement, Feedback (Response), Middle School Students, Tutoring, Blended Learning, Artificial Intelligence, Individualized Instruction
DOI: 10.1007/978-3-031-99261-2_43
Abstract: Setting practice goals, which helps students regulate their effort toward achieving engagement and mastery, can enhance the benefits of active learning. However, traditional goal-setting approaches, such as homework contingency contracts, often lack frequent feedback and require substantial human intervention. The presented research investigates integrating intelligent and scalable goal-setting support within active learning environments. In recent research, we have evaluated the impact of goal-setting contracts, performance feedback, and scalable goal support with rewards on student effort and learning. The proposed research aims to study student achievement trajectories related to achievement and the distinct impact of adaptive goal feedback. To that end, we propose developing an adaptive goal-setting dashboard that automates feedback and recommendations to support students in setting and refining their goals. Findings from a 12-week study with 110 middle school students in a hybrid tutoring program show that data-supported goal setting led to a about 25% increase in weekly practice time and a about 40% increase in skills mastered per week. These results indicate that intelligent goal setting can enhance engagement and learning while minimizing teacher workload. This research contributes to practical advancements in AI-assisted active learning and theoretical insights into self-regulatory processes related to student effort in active learning. [Additional funding provided by Learning Engineering Virtual Institute.]
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2025
Accession Number: ED674425
Database: ERIC
Description
Abstract:Setting practice goals, which helps students regulate their effort toward achieving engagement and mastery, can enhance the benefits of active learning. However, traditional goal-setting approaches, such as homework contingency contracts, often lack frequent feedback and require substantial human intervention. The presented research investigates integrating intelligent and scalable goal-setting support within active learning environments. In recent research, we have evaluated the impact of goal-setting contracts, performance feedback, and scalable goal support with rewards on student effort and learning. The proposed research aims to study student achievement trajectories related to achievement and the distinct impact of adaptive goal feedback. To that end, we propose developing an adaptive goal-setting dashboard that automates feedback and recommendations to support students in setting and refining their goals. Findings from a 12-week study with 110 middle school students in a hybrid tutoring program show that data-supported goal setting led to a about 25% increase in weekly practice time and a about 40% increase in skills mastered per week. These results indicate that intelligent goal setting can enhance engagement and learning while minimizing teacher workload. This research contributes to practical advancements in AI-assisted active learning and theoretical insights into self-regulatory processes related to student effort in active learning. [Additional funding provided by Learning Engineering Virtual Institute.]
DOI:10.1007/978-3-031-99261-2_43