Article describes how Machine Translation Post-Editing has emerged as a productivity-enhancing practice in the language service industry, where human editors correct the output of machine translation systems. this research paper aims to assess students' self-efficacy in translation learning, specifically in the context of MTPE, and explore the factor structure, psychometric properties, and internal associations of their self-efficacy.

Data management plan for the grant, "Distributed Learning for Undergraduate Programs in Data Science at Diverse Universities." Here, we propose to expand on our previous NSF-supported work in developing a suite of courses in data science (DS) that were taught across a network of 4 undergraduate institutions in a distributed learning (DL) format. The current proposal seeks to expand the size and diversity of our network while adapting the advanced distributed learning (ADL) technology of the U.S. military to an academic setting to harness the power of AI in tailoring optimal learning experiences for individual students.

Data management plan for the grant, "Improving Student Learning While Decreasing Bias in Teaching Through Simulation." Research on the simEquity project which will implement a scalable model for developing equitable, culturally responsive teaching practices through simSchool, a simulated teaching environment. The project will identify best practices to help teachers recognize and mitigate implicit biases that often impact student success. The project team will iteratively develop and test a Teaching without Bias curriculum and an AI-driven set of bias reduction tools that can be added to existing simulation instruction modules.