Do working memory capacity and test anxiety modulate the beneficial effects of testing on new learning?

Abstract

Although testing has repeatedly been shown to be one of the most effective strategies for consolidating retention of studied information (the backward testing effect) and facilitating mastery of new information (the forward testing effect), few studies have explored individual differences in the beneficial effects of testing. The current study recruited a large sample (1,032 participants) to explore the potential roles of working memory capacity and test anxiety in the enhancing effects of testing on new learning, and the converse influence of testing on test anxiety.The results demonstrated that administering interim tests during learning appears to be an effective technique to potentiate new learning, regardless of working memory capacity and test anxiety. At a final test on all studied materials, individuals with low working memory capacity benefited more from interim testing than those with high working memory capacity. These testing effects are minimally modulated by levels of trait/state test anxiety, and low-stake interim testing neither reduced nor increased test anxiety. Overall, the results imply that low-stake interim tests can be administered to boost new learning irrespective of learners' level of WMC, test anxiety, and of possible reactive effects of testing on test anxiety. Public Significance StatementAlthough testing is frequently regarded as an assessment tool, the current study demonstrates that it also appears to be an effective technique to boost new learning across individuals with different levels of working memory capacity and test anxiety. In addition, retrieval practice can more effectively consolidate retention of studied information for individuals with low working memory capacity. Regardless of the concern that frequent tests may increase text anxiety, this research finds that frequent tests tend to exert minimal influence on test anxiety.

Testing potential mechanisms underlying test-potentiated new learning.

“…Output order can explain Pastötter et al’s serial position results equally well as the reset-of-encoding account. For instance, according to Yang et al (2020), Pastötter et al’s Test group might have initiated List 3 recall with primacy items (i.e., Items 1–4) whereas the Restudy group might have primarily recalled the recency items first (i.e., Items 9–12; to foreshadow, this assumption is corroborated in the current study). According to the output interference effect (that is, first-recalled items impair subsequent recall of others; A.…”

“…Given that the current study is focused on the FTE, we do not discuss the cumulative test results further. Interested readers can consult Yang et al (2020).…”

“…Although Pastötter et al’s (2018) serial position results suggest a selective enhancement effect of interpolated testing on new learning, they cannot be taken as direct evidence supporting the reset-of-encoding theory for at least two reasons. The first is that the selective enhancement effect on new learning can be readily accounted for by another explantion – output order (Dalezman, 1976; Yang et al, 2020). Yang et al (2020) recently reported that interpolated testing significantly affects output order.…”

“…Yang et al (2019; experiment 3) observed that testing on memory for statements about artists’ contributions facilitated subsequent learning of different artists’ painting styles. The FTE is observed among different populations, such as older adults (Pastötter & Bäuml, 2019), patients suffering from traumatic brain injury (Pastötter et al, 2013), older elementary school children (Aslan & Bäuml, 2016), and college students with different levels of working memory capacity and test anxiety (Yang et al, 2020).…”

“…2Another reason for recruiting a large number of participants was that this project also aimed to investigate individual differences in the FTE. Because previous studies observed inconsistent findings about individual differences in test-enhanced learning, we decided to employ a large sample size to obtain more robust findings (for detailed discussion, see Yang et al, 2020). …”