Spacing, Feedback, and Testing Boost Vocabulary Learning in a Web Application

Abstract

As information and communication technology (ICT) becomes more prevalent in education its efficacy in general and that of specific learning applications in particular has not been fully established yet. One way to further improve learning applications could be to use insights from fundamental memory research. We here assess whether four established learning principles (spacing, feedback, testing, and multimodality) can be translated into an applied ICT context to facilitate vocabulary learning in a self-developed web application. Effects on the amount of newly learned vocabulary were assessed in a mixed factorial design (3×2×2×2) with the independent variables Spacing (between-subjects; one, two, or four sessions), Feedback (within-subjects; with or without), Testing (within-subjects, 70% or 30% retrieval trials), and Multimodality (within-subjects; unimodal or multimodal). Data from 79 participants was analyzed and revealed significant main effects for Spacing (F[2, 76] = 8.51, p = 0.0005, η^2p = 0.18) and Feedback (F[1, 76] = 21.38, p < 0.001, η^2p= 0.22), and a significant interaction between Feedback and Testing (F[1, 76] = 14.12, p = 0.0003, η^2p = 0.16). Optimal Spacing and the presence of corrective Feedback in combination with Testing together boost learning by 29% as compared to non-optimal realizations (massed learning, testing with lack of corrective feedback). Our findings indicate that established learning principles derived from basic memory research can successfully be implemented in web applications to optimize the acquisition of new vocabulary.

A Meta-Analysis on Mobile-Assisted Language Learning Applications: Benefits and Risks

“…It will thus be an interesting endeavour for future studies to incorporate and manipulate learning principles to directly assess the relative contribution of each principle on learning and their interactions on L2 learning with a MALL-application. Such studies would be interesting in their own rights for the field of memory research more generally because our current knowledge on the interaction of different learning principles is extremely limited (Belardi et al, 2021;Weinstein et al, 2018). Given how easy it is to collect large amounts of data across extended time periods with MALL-application, such studies therefore offer a unique opportunity to advance current knowledge in the field of basic memory research beyond mere L2 learning.…”

A Meta-Analysis on Mobile-Assisted Language Learning Applications: Benefits and Risks

“…We therefore cannot conclude that the learning outcomes observed were a direct result from the implementation of learning principles. Given the wealth of prior data revealing the benefit of these principles on learning in the classroom or experimental setting (Belardi et al, 2020;Butler et al, 2014;Dempster, 1987;Karpicke & Bauernschmidt, 2011;Metcalfe, 2017;Reber & Rothen, 2018;Smith et al, 2016;Soderstrom et al, 2016), we can surmise that learning principles could be successfully implemented and utilized in a digital learning setting, and this appears to have a benefit over the traditional approaches. But why might this be so?…”

“…Previous meta-analyses on the topic have not focused strictly on mobile applications designed for second language learning, rather assessing multiple mobile solutions together in the same analysis such as text messaging (SMS) or social networking sites (Afzali et al, 2017;Cho et al, 2018;Mahdi, 2018), making it difficult to distinguish which type of mobile learning specifically impacts language performance. The literature also does not address which elements within mobile applications could deliver optimal benefit for language learning (Belardi et al, 2020). The broader research community believes while these mobile technologies are being implemented and utilized in the educational setting, there is an overall lack of empirical validations of these applications (Bano et al, 2018;Heil et al, 2016;Zydney & Warner, 2016).…”