This study examined the motives and drives of adult students during online degree completion, including the commonalities among and differences between Hispanic and non-Hispanic adult students.... Show More

This study examined the motives and drives of adult students during online degree completion, including the commonalities among and differences between Hispanic and non-Hispanic adult students. Participants included 364 adult students at a Hispanic-serving institution (HSI) who completed a series of reflective writing assignments, generating over 15,000 pages of data. After linguistic and statistical data analysis, results identified the drives and motives common to all adult students and significant differences between Hispanic and non-Hispanic adult students. Some merit little or no action, while three offer opportunities—achievement and affiliation as drives, the states of acquire and lack, and allure as motive. These results offer implications for Hispanic and non-Hispanic adult students and those in higher education who serve or teach such students—academic advisors, instructional designers, instructors, and program administrators—and inform how technology can support such efforts.

Power distance (PD), a cultural value denoting acceptance of asymmetrical power relationships, influences the force of rhetoric used by a writer to address their reader. However, AI technologies... Show More

Power distance (PD), a cultural value denoting acceptance of asymmetrical power relationships, influences the force of rhetoric used by a writer to address their reader. However, AI technologies such as ChatGPT lack an explicit awareness of PD, which could affect the quality of AI-generated persuasive texts used for language learning. To investigate this issue, 200 persuasive essays written by ChatGPT were compared to 200 essays written by L1-English university learners. Three elements of formulaic language related to PD were examined: stances, modals, and pronoun deixis. Differences in stances (z = -3.411; p = .001) and modals (z = -2.100; p = .036) were both significant according to the Wilcoxon signed ranks formula, whereas differences in pronoun deixis were nearly significant (z = -1.917; p = .055). Overall, language of ChatGPT appears generic and incomplete, suggesting that consistent and uniform expressions are being borrowed from an LLM training corpus to mimic aspects of PD. Limitations of AI highlight a need for pedagogical emphasis of culturally imbued discourse.

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a... Show More

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of student comments is being undertaken. The first and simplest use of big data analytics is for the identification of high frequency keyword groups, which, without big data analytics, would be extremely time consuming. However, the lack of context surrounding keyword groups severely limited the ability to draw meaningful conclusions and highlighted the need for human intervention in the analysis process. Future work includes sentiment analysis. This initial work is an impetus for further exploration of big data analytics methods in qualitative contexts, especially in dynamic contexts where rapid data analysis can form a basis for timely interventions.

With the enhancement of internet medium and development of science and technology, interactive technologies have gradually emerged in the field of language education. However, previous empirical... Show More

With the enhancement of internet medium and development of science and technology, interactive technologies have gradually emerged in the field of language education. However, previous empirical studies and meta-analyses have focused on the impact of specific types of technologies. Therefore, this study aims to comprehensively synthesize the effect of overall interactive technologies on language education through meta-analysis. The results revealed that interactive technologies could exert a substantial influence on learning attitudes, self-efficacy, listening, reading, writing skills, vocabulary and grammar level, and overall learning outcomes. Additionally, numerous types of interactive technologies have demonstrated potential in language education, such as mobile apps, multimedia, technology-assisted tools, etc. In future research, educators should judiciously apply interactive technologies to different language educational processes according to their unique features, and researchers should expand their survey scope to ensure data validity.