Online Collaborative Translation in Massive Open Online Courses (MOOCs): Policy, Collaborators and Work Models
dc.contributor.advisor | Washbourne, Richard Kelly | |
dc.contributor.author | Aldrees, Mohammed H. | |
dc.date.accessioned | 2024-08-04T07:50:44Z | |
dc.date.available | 2024-08-04T07:50:44Z | |
dc.date.issued | 2024-07-22 | |
dc.description.abstract | Online participatory translation and localization spread widely with the advent of Web 2.0, and various collaborative translation practices continue to emerge in different contexts (e.g., the entertainment, technology, and software development industries). Collaborative translation also continues to evolve in online education, particularly in massive open online courses (MOOCs), most of which are delivered in English. Therefore, a range of opportunities must be provided to learners with relatively low English language proficiency. Online collaborative translation has been utilized by several prominent platforms such as Coursera, Khan Academy, and edX to increase linguistic diversity and the use of MOOCs in international development. This study explores the online collaborative translation practices evident on educational platforms, with a particular focus on the translation policies of MOOCs’ providers, the motivations driving collaborators to engage in these participatory translation initiatives, and the work models implemented by the platforms. Two MOOC providers were identified as case studies, namely Coursera and Khan Academy. This research investigates their respective translation policies, drawing on González Núñez’s (2013) systematic approach to translation policy as a complex concept that encompasses management, practice, and beliefs. Additionally, this research adopts Engeström’s (1987) activity system model to explain the technologically mediated collaborative translations involving diverse participants and tools on Coursera and Khan Academy, and to identify contradictions within and between the components of their activity system models. It also explores collaborators’ motivations through the functional approach, which identifies specific motives driving participation in collaborative translation, alongside demotivating factors. The research employs a combination of methods, including document analysis, observation, questionnaires, and follow-up interviews. The findings indicate that Coursera and Khan Academy adopt distinct translation policies that influence user practices. Coursera relies on a structured digital platform and predefined roles and tasks, while Khan Academy employs a more decentralized approach that allows flexibility and adaptation to local contexts. Moreover, collaborators are driven by a combination of intrinsic and extrinsic motivations, with intrinsic motivations, such as the desire to contribute to education accessibility, enhance native language content, and engage in personal learning and skill development, being more prevalent. The work model of online collaborative translation in this study is a dynamic and complex activity system model with opportunities for improvement and innovation in areas such as platform technologies, communication tools, and participant recruitment. | |
dc.format.extent | 268 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14154/72762 | |
dc.language.iso | en_US | |
dc.publisher | Kent State University | |
dc.subject | Online collaborative translation | |
dc.subject | translation crowdsourcing | |
dc.subject | MOOCs | |
dc.subject | Khan Academy | |
dc.subject | Coursera | |
dc.subject | educational translation | |
dc.subject | volunteer motivations | |
dc.subject | translation policy | |
dc.subject | activity theory | |
dc.subject | gamification | |
dc.title | Online Collaborative Translation in Massive Open Online Courses (MOOCs): Policy, Collaborators and Work Models | |
dc.type | Thesis | |
sdl.degree.department | Modern and Classical Language Studies | |
sdl.degree.discipline | Translation Studies | |
sdl.degree.grantor | Kent State | |
sdl.degree.name | Doctor of Philosophy |