higher-education
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- PaperTESOL Quarterly24 Jul 2026
Mixed‐Methods Research on English‐Medium Instruction in Higher Education: A Systematic Review
Haemin Kim, Keith M. Graham
This systematic review of 136 studies on English-medium instruction (EMI) in higher education reveals significant methodological gaps in mixed-methods research: only seven studies explicitly stated an epistemological orientation, six presented an integrative mixed-methods research question, and no study specified sampling procedure terminology. Questionnaires and interviews were the most common instruments. The authors provide recommendations for strengthening future EMI mixed-methods research.
Original abstract
With the rapid growth of research in English‐medium instruction (EMI) in higher education, much research has been conducted through qualitative and quantitative approaches. Yet, little attention was paid to the use of mixed‐methods research (MMR) in this field. Therefore, this systematic review aims to examine previous literature that adopted MMR in EMI research, specifically evaluating the methodology across three aspects: epistemological orientation and purpose, MMR question formulation, and MMR design. Among 136 studies identified, substantial methodological gaps were found across all three aspects. First, only seven studies explicitly stated an epistemological orientation whereas 27 studies provided explicit purpose terminology. Second, only six studies explicitly presented an integrative MMR question, while 112 studies provided qualitative and/or quantitative research questions, and 18 studies lacked explicit research questions. Finally, MMR design characteristics were rarely described: (1) nearly half of the studies did not specify a design, (2) no study used specific sampling procedure terminology, and (3) questionnaires and interviews were the most frequently used instruments. Based on these methodological gaps, this study offers recommendations for strengthening future EMI studies that employ a mixed‐methods approach.
- NewsEdSurge22 Jul 2026
What Does AI Cost When We Skip the Work?
This EdSurge podcast episode discusses the enduring value of a college degree and writing skills in the age of AI, featuring guests who argue that the benefits of these experiences—such as personal growth and deep learning—cannot be replicated by artificial intelligence.
Original abstract
<p>Every few months, another headline declares the college degree dead. <strong>This Week with EdSurge</strong> examines what still holds up when artificial intelligence moves fast, through two guests who are both defending something slow against something fast.</p><h2>A Four Year Degree in the Age of AI</h2><p><a href="https://www.edsurge.com/author/rita-finkel--9b5e61f9-c70d-441e-b13a-0c1a116d3d60"><u>Rita Finkel</u></a>, co-president of the Armory Foundation and director of the Armory College Prep program, argues that a college degree was never just about a technical skill. She says the data tells a different story than the headlines suggest, and that the value of a degree comes from something artificial intelligence cannot replicate.</p><h2>The Fourth Essay</h2><p><a href="https://www.edsurge.com/author/cobretti-williams"><u>Cobretti Williams</u></a> of the <strong>EdSurge</strong> Voices of Change Fellowship makes a similar case for writing. He talks about the beauty in imperfection, and how a fellow's fourth essay reads nothing like the first, growth that only comes from doing the work yourself.</p><p><a href="https://www.edsurge.com/podcasts"><u>Listen to the episode</u></a>.</p><h2>Stories Mentioned in This Episode</h2><p><a href="https://www.edsurge.com/news/2026-05-28-why-college-degrees-matter-in-the-age-of-ai"><u>Why College Degrees Matter in the Age of AI</u></a></p><p>by Rita Finkel</p><p><a href="https://www.edsurge.com/collections/edsurge-voices-of-change-writing-fellowship"><u>EdSurge Voices of Change Writing Fellowship</u></a></p><p>by EdSurge</p><p><strong>This Week with EdSurge</strong> is a weekly podcast from <strong>EdSurge</strong>. Subscribe to the <a href="https://www.edsurge.com/newsletters"><u>EdSurge newsletters</u></a> for more news and analysis on education and technology.</p><p> </p>
- PaperOpenAlex — TESOL research21 Jul 2026
The Impact of AI Empowerment on the Development of College Students' English Speaking Skills: A Mixed-Methods Analysis Based on Speech Competence Assessment and Self-Directed Learning Efficiency
Jian Li, Luo ZhiYao
A mixed-methods study with 20 Chinese college students found that using the Doubao AI platform for autonomous speaking practice significantly improved fluency, pronunciation, and lexical resources. AI empowerment enhanced self-directed learning efficiency through synergy between self-determination theory and self-regulated learning, though a 'situational gap' between virtual practice and real interaction persisted.
Original abstract
In the context of the digital transformation of global education, artificial intelligence (AI) has become a transformative force in the field of second language acquisition. This study explores the impact of AI empowerment on the development of Chinese college students’ oral English competence and the efficiency of self-directed learning (SDL). The core of the research is to explore the synergy between the self-determination theory (SDT) and the self-regulated learning (SRL) model to clarify the interaction between technology empowerment and psychological mechanisms. Under this framework, SDL is the main learning mode, while SDT provides motivational basis (answering students “why” initiates SDL), and SRL provides strategic guarantee (answering students “how” manages learning process). This study adopts a mixed research method and conducts a six-week quasi-experiment with 20 International Business English majors students from Guangdong University of Foreign Studies. During the winter vacation, participants used the Doubao AI platform for autonomous speaking practice and received instant, data-driven feedback. The data were comprehensively analyzed through pre-test and post-test (measuring fluency, lexical resources, accuracy and pronunciation), validated questionnaires and qualitative interviews. The results show that AI empowerment significantly improves objective speaking ability, especially in terms of fluency, pronunciation and lexical resource. More importantly, the study found that there is a deep synergistic effect between the learner’s motivation process and the strategy process: the satisfaction of the two basic psychological needs of autonomy and ability (SDT) provides the internal motivation for students to enter the three cycle stages of SRL; the effective strategy execution guided by the role of AI “virtual supervisor” further strengthens the learners’ sense of achievement, thus jointly improving the overall SDL efficiency. Despite these advances, the study also found a “situational gap” between virtual practice and real social interaction. This study highlights the importance of an AI-supported teaching model that combines technical efficiency with human-led strategic guidance to optimize the self-directed development of oral English in the digital age.