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ASSISTments

Product or Programme · All products and programmes
Evidence · 10 claims (9 for, 1 mixed) · 7 studies (3 causal, 2 qualitative, 1 associational, 1 design), q2–q3 · 3 of 7 report an effect size · 10 claims rest on one study

Description

ASSISTments is a free web-based platform developed and operated by the ASSISTments Project for assigning mathematics practice, providing feedback, and reporting student-performance data to teachers.

Components

  • ASSISTments online math homework platform: ASSISTments is a free, web-based platform used in the study as an online tool for math homework, with many teachers also using it for classwork. It "provided students with instant feedback on their math work, while teachers received real-time data and progress reports on student learning." The platform contains textbook-based problems from schools' existing curricula plus prebuilt content, and developers built teacher-created practice problems into it on request. No specialized hardware or software was required beyond existing devices. (Feng et al. (2024))
  • ASSISTments platform with the four steps of formative assessment: ASSISTments is "a free, web-based formative assessment platform for teachers and students in grades 3 through 12" that delivers immediate feedback, hints, explanations, and step-by-step scaffolds while generating color-coded class- and student-level reports. Its use is standardized into four steps of formative assessment: Assign standards-aligned problem sets, Practice with immediate feedback, Assess reports to identify patterns and errors, and Review selected problems using anonymized projected data. The intervention paired the platform with a virtual professional learning community to train rural middle school teachers. (Feng et al. (2025))
  • Four-step formative assessment loop for technology-supported math homework: The ASSISTments intervention is organized around "a four-step loop that can be readily integrated into day-to-day instructional practices." Teachers (1) find and assign standards-aligned content, (2) students work with instant feedback and support, (3) teachers examine performance data to inform instructional decisions, and (4) teachers share and review data with students, discussing common misconceptions. Teachers were expected to assign 20–30 minutes of assignments at least twice a week and regularly review data reports. (Feng et al. (2023))
  • ASSISTments/E-TRIALS: free A/B testing platform integrated with a K-12 math practice platform: E-TRIALS is described as "a free learning science A/B testing platform that allows researchers to conduct randomized controlled trials," integrated with ASSISTments, "a free online K-12 math learning platform supporting millions of students." Teachers assign problems from open educational resources; the platform randomly assigns students to study conditions unobtrusively and supplies datasets covering performance, hint requests, log data, and school demographics. The article uses it to illustrate a four-condition study of hints and explanations with and without SEL language. (Language and Mathematics Learning: A Comparative Study of Digital Learning Platforms)
  • ASSISTments E-Trials A/B test dataset with remnant log data (68 tests, 227 contrasts, 38,035 experimental students, 193,218 remnant students): A dataset assembled for testing remnant-based estimators, drawn from the ASSISTments online tutor's E-Trials experimentation platform. It comprises, in the article's words, "a collection of 68 multi-armed A/B tests run on the ASSISTments TestBed (Ostrow et al., 2016, now called "E-Trials"), which together include 227 different two-way comparisons and 38,035 students." Alongside it, log data were collected for 193,218 remnant students who worked on similar skill builders but participated in no experiment, with no overlap in students or skill builders between the two sets. The outcome analyzed was binary assignment completion, with nine student-level aggregated predictors used for within-RCT a (Adam C. Sales et al. (2023))
  • ASSISTments online math homework platform: ASSISTments is an online homework tool coupled with teacher training that "provid[es] students with math assistance and teachers with assessments of student progress." It has two content types: problem sets linked to existing textbook homework, giving teachers flexibility in assignment, and mastery-oriented skill practice content. The web-based platform is available at no cost to schools, but students need computer access at home. (ASSISTments evidence summary (2020))
  • ASSISTments Skill Builders with the ARRS delayed reassessment system: ASSISTments is a free online formative assessment and tutoring system for middle school mathematics, used by 650 teachers with over 5,000 student users a day. Within its Skill Builder problem sets, students master a skill by answering three questions correctly in a row, after which "a single -item test is administered after a pre -defined period of time, with a gradually increasing space in between reassessments" through the Automatic Reassessment and Relearning System (ARRS). This study used ARRS test outcomes to define productive persistence versus wheel-spinning. (Kai et al. (2018))
  • QUICK-Comments teacher-augmentation tool in ASSISTments: QUICK-Comments is a teacher-augmentation tool within the ASSISTments web-based K-12 mathematics platform that supports teachers in assessing open-ended student responses. The article describes that "this tool allows teachers to select from a repository of pre-authored comments, which has been tailored to address common student errors or misconceptions." By streamlining feedback selection, it lets teachers deliver personalized, timely feedback efficiently; the feedback messages analyzed in this study were drawn from its use. (Seiyon M. Lee et al. (2025))

Claims

Key Sources

  • Feng, M., Weiser, G., & Collins, K. (2024). Cost and cost effectiveness of ASSISTments online math support: Analysis from a randomized controlled study in middle school. WestEd. https://www.wested.org
  • Feng, M., Li, L., Brezack, N., & Schneider, M. (2025). Scaling teachers' professional development for ASSISTments companion report: Implementation analysis of the ASSISTments intervention. WestEd. https://www.wested.org
  • Feng, M., Li, L., Brezack, N., Huang, C.-W., Luttgen, K., Grady, J., Yang, S., Lavine, A., Collins, K., & Schneider, M. (2025). Scaling teachers' professional development for ASSISTments: Evaluation final report. WestEd. https://WestEd.org
  • Feng, M., Huang, C.-W., & Collins, K. (2023). Technology-based support shows promising long-term impact on math learning: Initial results from a randomized controlled trial in middle schools. WestEd. https://osf.io/exqpn
  • Wei, X., Wortman, A., Cheng, L., Heffernan, N., Heffernan, C., Murphy, A., Zepeda, C., Motz, B., Jankowski, H., & Roschelle, J. (2024, March). Language and mathematics learning: A comparative study of digital learning platforms. Digital Promise. https://doi.org/10.51388/20.500.12265/206
  • Adam C. Sales, Ethan B. Prihar, Johann A. Gagnon-Bartsch, Neil T. Heffernan. (2023). Using Auxiliary Data to Boost Precision in the Analysis of A/B Tests on an Online Educational Platform: New Data and New Results. Journal of Educational Data Mining, Volume 15, No 2. https://osf.io/k8ph9/
  • ASSISTments evidence summary. (2020). https://www.assistments.org
  • Kai, S., Heffernan, C., Almeda, M. V., Heffernan, N., & Baker, R. S. (2018). Decision Tree Modeling of Wheel-Spinning and Productive Persistence in Skill Builders. Journal of Educational Data Mining, Volume 10, No 1. https://jedm.educationaldatamining.org/index.php/JEDM/article/view/210
  • Seiyon M. Lee, Sami Baral, Hongming Chip Li, Li Cheng, Shan Zhang, Carly S. Thorp, Jennifer St. John, Tamisha Thompson, Neil Heffernan, Anthony F. Botelho. (2025). Developing Feedback Taxonomy for Math: A Synergy of Perspectives through Data Mining Methods. Journal of Educational Data Mining, Volume 17, No 2. https://osf.io/puhyr/?view_only=514d8534e9be41d9a57ad82e9efb3249
Page metadata
Field Value
type product
id assistments
title ASSISTments
description ASSISTments is a free web-based platform developed and operated by the ASSISTments Project for assigning mathematics practice, providing feedback, and reporting student-performance data to teachers.
status review
moved_from element/assistments-e-trials-platform, element/assistments-etrials-68-test-remnant-dataset, element/assistments-online-homework-platform, element/assistments-skill-builders-arrs-element, element/quick-comments-assistments-tool
product_kind software
generated by process:settle-candidates on 2026-10-09
trust unverified — no one has confirmed this page's content
sources 5 — wei-x-wortman-a-cheng, adam-c-sales-2023, assistments-evidence-summary-2020, kai-2018, seiyon-m-lee-2025

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