Educational software based on teachable agents has repeatedly proven to have positive effects on students’ learning outcomes. The strongest effects have been shown for low-performers. A number of mechanisms have been proposed to explore this outcome, in particular mechanisms that involve attributions of social agency to teachable agents. Our study examined whether an expression of high versus low self-efficacy in a teachable agent would affect low- performing students with respect to their learning outcomes and with respect to a potential change in their own self- efficacy. The learning domain was mathematics, specifically the base-ten system. Results were that the learning outcomes of low-performers who taught a low self-efficacy agent were significantly better than the learning outcomes of low- performers who taught a high self-efficacy agent. There were no effects from the manipulation of self-efficacy expressed by the teachable agent on changes of the low-performing students’ own self-efficacy.

Number-line estimation tasks (NLETs) have been used to assess symbolic numerical skills (SNS; Booth & Siegler, 2008; Lyons & Ansari, 2015) and have also been associated with the approximate number system (ANS; Khanum et al., 2016; Wong et al., 2016). A recent study with 6–7-year-old children in Sweden (Morell-Ruiz et al., 2025) provided evidence that training NLE abilities can help bridge these two numerical systems, suggesting that the ANS may actively scaffold the development of the SNS. Building on this, we designed a novel two-choice NLET compatible with Drift Diffusion Model (DDM) fitting, allowing us to decompose children's estimation processes into interpretable parameters. Our results show that DDM parameters significantly correlate with performance in both symbolic and nonsymbolic tasks, and that performance on the two-choice and standard NLETs is strongly correlated. These findings validate our paradigm, offering new insights into the cognitive mechanisms linking numerical representations via number-line estimation.