Throughout the 21st century colleges, universities and the state legislatures that support them have dedicated millions of dollars to merit-based scholarships aimed at recruiting "high ability" students and preventing brain drain (when said students leave home for an out of state institution). While this idea has a net benefit on the surface level, it has actually caused some disruption in the ability for low-income students, from rural and urban settings alike, to attend and finish college. By taking a look at America's past we can see viable solutions that should inform our future and one of those solutions includes redesigning state and local aid packages to focus on students of high-need first.

This study investigates the comparative effects of computer-based and paper-based data-driven learning (DDL) on learning new vocabulary. In both of these methods, learners engage with real-world examples of language use in corpora to discover patterns, rules, and meanings through exploration and analysis of the language. The participants in the current study are 52 university prep students who are randomly assigned to one of the experimental conditions as computer-based DDL and paper-based DDL. Participants in the computer-based DDL group study the twenty target words inductively using online corpora, whereas the participants in the paper-based DDL group study the same target words inductively on paper-based concordances pre-selected from corpora by teachers. Adopting a quasi-experimental mixed methods design, the study utilizes pre-tests and post-tests, individual think-aloud protocol, and focus group interviews to collect data. The collected data is analyzed to explore how paper-based DDL compares to computer-based DDL on (1) vocabulary recall and recognition, (2) students’ constructing vocabulary knowledge behaviors using corpus data, (3) pair work and individual work, and (4) students’ attitudes. The study fills in the gap in the literature by concluding that there is no significant difference between paper-based DDL and computer-based DDL on students’ vocabulary gains according to pre-test and post-test results. Qualitative data obtained from think-aloud protocols and focus group interviews reveals notable differences and similarities between the two groups regarding the challenges they encountered with the two types of DDL tasks, the advantages they derived from these experiences, and their expectations.

Translanguaging, defined as "the dynamic process whereby multilingual language users mediate complex social and cognitive activities through the strategic use of multiple semiotic resources to act, to know, and to be" (García & Li, 2014), has gained prominence as a transformative concept in language education. While extensively explored in the fields of linguistics, sociolinguistics, applied linguistics, and education (Lewis et al., 2012; García et al., 2015; Jaspers, 2018; Li, 2011, 2023; MacSwan, 2017, 2022), there remains a notable gap in understanding bilingual individuals’ perspectives on how translanguaging functions in their everyday social interactions. This qualitative study aims to bridge this gap by examining the attitudes and experiences of bilinguals regarding translanguaging in daily social communication. Using semi-structured interviews with four Chinese bilinguals, the research identifies two primary scenarios where translanguaging is commonly employed: interacting with diverse communities and conveying nuanced contextual meanings. The findings reveal a duality in the effects of translanguaging practices. On the positive side, translanguaging enhances communication experiences, promotes deeper engagement with language and cultural learning, and fosters inclusivity in social contexts. On the negative side, participants reported reduced personal confidence, decreased communication influence, and challenges in establishing strong interpersonal relationships when translanguaging was perceived as inappropriate or ineffective. These findings not only deepen the theoretical understanding of translanguaging but also offer practical implications for language education. They emphasize the importance of integrating translanguaging pedagogy into classrooms to create inclusive, adaptive learning environments that reflect the complexities of multilingual realities, enhancing both social and academic outcomes.

This empirical study responds to student engagement with GAI in L2 writing, because the emergence of Generative Artificial Intelligence (GAI) technologies for everyday users has drawn widespread attention, particularly for these technologies’ potential to transform the processes and products of writing (e.g., Yan, 2023). In pedagogical contexts, instructors and scholars have raised concerns surrounding potential ethical issues in using GAI in writing for academic purposes (Barrot, 2023). However, less is known about students' perspectives, including international and L2 students, who have the most to lose if GAI technologies are misused or misunderstood in teaching and learning. To respond to this gap, the present study takes up Sociocultural Theories of learning to examine multilingual university students’ perceptions of ChatGPT as a scaffold for writing academic essays. Participants were 11 international students enrolled in a developmental composition course for undergraduate L2 writers at a mid-sized U.S. university in the Midwest, and whose exam scores upon enrollment indicated they needed additional writing instruction before enrolling in the university’s introductory composition course. Via a classroom intervention utilizing ChatGPT, a pre- and post-intervention questionnaire, semi-structured interviews, and student writing samples, the researcher sheds light on the ways students’ perceptions of using ChatGPT for academic writing remained static, shifted, or other as they were taught various strategies for integrating AI into their writing processes. The researcher discusses the study’s findings and provides implications for further research.