(Why) Are Open Research Practices the Future for the Study of Language Learning?

Abstract

Open Research practices are relevant to all stages of research, from conceptualisation through to dissemination. Here, we discuss key facets of Open Research, highlighting its rationales, infrastructures, behaviours, and challenges. Part I conceptualizes Open Research and its rationales. Part II identifies challenges, such as the speed and cost of Open Research; the usability of open data and materials; the difficulties of conducting replication research; and the economics and sustainability of open access and Open Research generally. In discussing these challenges, we seek to provide examples of good practice, describe and evaluate emerging innovations, and envision change. Part III considers ongoing co-evolutions of culture, infrastructure, and behaviours, and acknowledges the limitations of our review and of Open Research practices. We argue that Open Research is indeed a large part of our future, and most—if not all—challenges are surmountable, but doing so requires significant changes for many aspects of the research process.

A Context-Aligned Two Thousand Test: Towards estimating high-frequency French vocabulary knowledge for beginner-to-low intermediate proficiency adolescent learners in England

“…Finally, the open accessibility of the tool can, we hope, widen the scope of research producers and consumers (Marsden & Morgan-Short, 2023), adding to the numerous options already available in English. We hope that the CA-TTT inspires the development of equivalent tests for other languages and proficiency levels thus far underrepresented in the literature.…”

“…Finally, we investigated the extrapolation inference by examining the extent to which CA-TTT estimates correlated with performance in high-stakes and standardised testing. Our research questions (RQs), generated from the validation framework proposed in Table 1, In the past decade, open research practices have been gaining traction in the language sciences (Liu et al, 2022;Marsden & Morgan-Short, 2023), with an increasing number of materials, data, and analysis code being made Findable, Accessible, Interoperable, and Reusable (FAIR; GO FAIR, n.d.). Exemplifying these FAIR principles, this article shares the materials, data, and analysis code used to partially validate the CA-TTT via our Open Science Framework repository (https://osf.io/k4y7p/) and on Instruments and Data for Research in Language Studies (IRIS, n.d.).…”

Diamond is a scientist’s best friend

“…While laudable for making research open, Green publishing disincentives change towards better systems if it acts as a license for closed publishing. Marsden and Morgan-Short (2023) highlight other problems of Green publishing: the circulation of multiple versions of papers and the absence of peer-review quality checks. Thus, Green open access publishing merely treats the symptoms of closed access publishing, it makes research openly available that otherwise would not have been, but it does nothing to treat the causes.…”

Enhancing Self-Explanation Learning through a Real-Time Feedback System: An Empirical Evaluation Study

“…In the realm of intelligent tutoring systems (ITSs), several platforms have established a significant presence by catering to various facets of educational needs. Table 1 offers a comprehensive overview of the features and functionalities related to self-explanation across four distinguished ITS platforms: SEAF, Mathia [32,33], Assessment's [34,35], and I-START. The table elucidates the varying degrees to which each system emphasizes selfexplanation, shedding light on the nuances of their approaches.…”