APLUS (Artificial Peer Learning Using SimStudent)

Product or Programme · All products and programmes
Evidence · 1 claim (1 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

APLUS is an online learning-by-teaching environment developed by its researchers in which students tutor the SimStudent virtual agent to solve algebraic equations through guided problem solving.

Components

• APLUS: a learning-by-teaching environment in which students tutor SimStudent to solve algebraic equations: APLUS (Artificial Peer Learning Using SimStudent) is an online learning-by-teaching environment in which students, acting as tutors, "teach a virtual agent named SimStudent to solve algebraic equations through guided problem solving". SimStudent learns production rules via programming by demonstration (inductive logic programming), proposes solution steps, and asks focal questions when the tutor disagrees or lacks a production. Tutors can quiz SimStudent across four quiz levels and access a Problem Bank, Unit Overview, Introduction Video, worked Examples, and a meta-tutor agent, Mr. Williams, who gives voluntary metacognitive hints. (Fathima Ameen et al. (2026))

Claims

• Tutors' proportion of knowledge-building responses to an agent's adaptive follow-up questions predicts conceptual and procedural post-test scores [+W]

Related Products and Programmes

• Math with Matt

Key Sources

• Fathima Ameen, Tasmia Shahriar, Aditi Mallavarapu, Shiyan Jiang, Noboru Matsuda. (2026). Beyond prior knowledge: the predictive role of knowledge-building in tutor learning. Behaviormetrika. https://doi.org/10.1007/s41237-026-00294-9

Page metadata

Field	Value
type	product
id	aplus-artificial-peer-learning-using-simstudent
title	APLUS (Artificial Peer Learning Using SimStudent)
description	APLUS is an online learning-by-teaching environment developed by its researchers in which students tutor the SimStudent virtual agent to solve algebraic equations through guided problem solving.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-11
trust	unverified — no one has confirmed this page's content

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