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- PaperOpenAlex — TESOL research22 Jul 2026
ENHANCING FOREIGN LANGUAGE TEACHING METHODOLOGY THROUGH ARTIFICIAL INTELLIGENCE: A CASE STUDY OF ENGLISH LANGUAGE LEARNING
Farmonova Naimakhon Furkat kizi
AI tools like intelligent tutoring systems and adaptive learning platforms significantly improve vocabulary acquisition, communicative competence, and learner autonomy in English language teaching, though challenges such as teacher readiness and ethical concerns persist.
Original abstract
Artificial Intelligence (AI) is rapidly transforming educational practices, particularly in the field of foreign language teaching. This study explores how AI can enhance English language teaching methodology in higher education. Using a mixed-method research design, the study evaluates the impact of AI-based tools such as intelligent tutoring systems, natural language processing applications, and adaptive learning platforms on students’ language proficiency. The findings reveal that AI significantly improves vocabulary acquisition, communicative competence, and learner autonomy. However, challenges related to teacher readiness, infrastructure, and ethical considerations remain. The study contributes to the development of modern AI-based pedagogical frameworks.
- NewsEdSurge13 Jul 2026
Study: The National AI Policy Landscape in K–12 Education
A study of 122 US K-12 districts and schools found that most have reactive AI policies, with many restricting or prohibiting AI use and only a small fraction taking proactive approaches. The dominant posture is conditional permission and teacher-delegated decision-making, reflecting a field managing uncertainty rather than leading.
Original abstract
<p>In the span of just two years, artificial intelligence has moved from an emerging curiosity to an operational reality in American K–12 classrooms. Students are using it to draft essays and build interactive study apps. Teachers are using it to generate lesson plans, differentiate instruction and develop assignments. Administrators are using it to summarize data, create chatbots and organize teams. And most school districts are scrambling to update or create policies that reflect the ever-changing world of AI. But what does an AI policy landscape look like? How many districts have formal AI policies at all? What do those policies say? And what does the distribution of approaches reveal about the state of readiness, equity and strategic thinking in K–12 education? To answer those questions, we built the<a href="https://policy.aiandeducationstudio.com/"> <u>AI School Policy Database</u></a> by using a five-level AI policy continuum to code 122 districts and schools across 38 states and then analyzed the results. What we found is a snapshot of a field that is neither panicking nor confidently leading: it is waiting, watching and managing uncertainty one teacher-directed decision at a time.</p><h2>What This Snapshot Tells Us</h2><p>The dataset does not capture every district/school in America; it is a structured sample. But the patterns it reveals are consistent and interpretable. Taken together, they point in the same direction.</p><ul><li><p><strong>Most districts/schools are reactive. </strong>The dominant posture is conditional permission, teacher-delegated decision-making and a wait-and-see attitude toward systemic AI integration.</p></li><li><p><strong>Some districts/schools are still trying to stop the clock. </strong>Nearly 30% are actively restricting or prohibiting AI use, an approach that is increasingly difficult to sustain as student access to AI tools extends far beyond school networks.</p></li><li><p><strong>Only a small fraction is daring to lead.</str
- NewsEdSurge10 Jul 2026
In Rural Districts, AI Resources for Educators Are Scarce
A recent study from Texas Tech University found that rural schools lack professional development resources for AI, limiting teachers' ability to effectively use the technology. Rural students also scored lower in ICT access and literacy compared to urban peers. Experts note that AI could benefit rural education by providing instructional support and expanding students' horizons, but gaps in expertise and resources persist.
Original abstract
<p>Professional development is crucial in ensuring teachers can put AI to work effectively. But a <a href="https://journals.sagepub.com/doi/10.1177/87568705251387039?__cf_chl_f_tk=CAZIy4i9YfjGxGZv7zfF4.IgSEpqSim3svGIjQdwFNE-1783002978-1.0.1.1-oZKjnpZ6Usv2XLN4p44VfwNtT9YFjnueGWjzNT3pBX8">recent study</a> from Texas Tech University found that PD around AI may not be readily available in rural schools. Another <a href="https://www.mdpi.com/2071-1050/17/6/2748#Results">study</a> compared elementary school students in rural areas to students in urban areas and found that rural students scored “statistically significantly lower” in Information and Communications Technology access and literacy, resilience, and online learning capabilities.</p><p>“The resources are limited. There is not much support out there for our rural educators,” says Nikkolina Prueitt, a co-author of the study. For rural schools to get the most out of AI, “we will need to build that knowledge base.”</p><h2>Closing the Gap</h2><p>AI has the potential to give rural teachers a pedagogical boost. It can provide instructional support, “like creating differentiated instruction, adapting lessons, drafting individualized education plans,” Prueitt says.</p><p>And AI can expand rural students’ understanding of the world, says Amanda Robinson, an elementary teacher at Pikeville Elementary, a Title I school in Eastern Kentucky. “AI opens the students’ horizons.”</p><p>In a rural community, AI can students to “experience new learning, outside of their communities,” said Dr. LeeAnn Lindsey, director of edtech and innovation at Northern Arizona University. But she sees rural schools struggle to embrace that potential, due in part to a lack of in-house expertise. “Our big urban and suburban school districts, they have technology integration coaches who have been diving into the AI work for the past three years,” she says. “Rural school districts often don’t.”</p><p>To help close the gap, Northern Arizona last fall le
- NewsEdSurge8 Jul 2026
How a Vinyl Record Resurgence Helped Me Understand the Future of AI in Education
The author draws a parallel between the vinyl record revival and AI integration in education, arguing that as technology makes tasks easier, it forces educators to reconsider what students must still learn to do independently. The piece reflects on a capstone project involving English, science, and global studies to illustrate the tension between convenience and meaningful engagement.
Original abstract
<p>A few months ago, I found myself standing in the vinyl record section of a bookstore with my children.</p><p>“What even is a record?” one of them asked.</p><p>After a quick explanation, another question followed.</p><p>“Why would anyone buy one when you can stream everything?”</p><p>I laughed. Then I realized, I wasn't entirely sure how to answer that question.</p><p>After all, they weren’t wrong. Streaming gives us access to nearly every song ever recorded. It’s cheaper, faster, more portable, and infinitely more convenient than vinyl. By almost every measure, it is better technology. Which makes the resurgence of vinyl so unexpected.</p><p>What struck me wasn’t that my children didn’t know what a record was. It was that they couldn’t imagine why someone would want one.</p><p>To them, music is immediate. Infinite. Effortless. The idea of listening to an album from beginning to end seemed almost irrational. This friction between convenience and engagement is exactly what I’ve been wrestling with as AI has become more prevalent in the classroom.</p><p>Vinyl records and AI are actually similar technologies. Both seem to provoke a human response to technology: the easier something becomes via technology, the more we begin questioning what was valuable about the underlying use in the first place.</p><p>In my own experience with AI, I can’t remember another issue that has prompted so many conversations about what learning is actually for. But as I listen to educators wrestle with these questions, I increasingly hear another one emerging beneath them.</p><p>It’s not a question about technology. Rather, it’s a question about learning: What should students still need to do themselves?</p><p>I found myself thinking about that question recently while sitting in on rehearsals for our ninth grade capstone presentations.</p><p>This capstone project brings together English, science, and global studies and asks students to partner with local nonprofits, investigate real-world c
- NewsEdSurge24 Jun 2026
Who Is Really in Charge When Tech Enters the Classroom?
Two educators share experiences with technology outpacing institutional readiness: one observes student teachers referencing TikTok for professional knowledge, while another builds an AI grading assistant that returns accurate feedback but raises questions about teacher ownership of grades.
Original abstract
<p>What happens when the tools teachers build start making decisions teachers have not reviewed? And what happens when the knowledge shaping future educators does not come from research or curriculum, but from a social media feed? On <strong>This Week with EdSurge</strong>, two educators are wrestling with technology that is moving faster than their institutions are prepared to handle.</p><h2><strong>When TikTok Becomes the Teacher</strong></h2><p><a href="https://www.edsurge.com/author/evi-wusk"><u>Evi Wusk</u></a>, Ed.D., teaches the people who will become teachers, and she noticed something during final exams that she could not ignore: her students kept referencing TikTok videos and social media reels, then apologizing for it. Wusk wrote about the experience for <strong>EdSurge</strong>, and her conclusion is not what you might expect. She is not calling for a ban or a warning label. Rather, she is asking whether teacher prep programs need to reckon with where professional knowledge is actually forming right now, and what it means if those teaching are the last ones to find out.</p><h2><strong>The Grader Who Was Not in the Room</strong></h2><p><a href="https://www.edsurge.com/author/steven-swanson"><u>Steven Swanson</u></a> teaches high school engineering, and after two consecutive days of field trips he came back to 450 ungraded assignments. So he built a solution: an AI grading assistant that drafted grades, generated comments against his rubrics, and returned everything to students automatically. Then a student thanked him for feedback he had never read. Swanson wrote about what happened next for <strong>EdSurge</strong>, and the story is less about the technology malfunctioning than about what it revealed: even when the AI is accurate, the grade still needs to belong to someone.</p><p>Join us on <strong>This Week with EdSurge</strong> where we dig into what both of these educators decided to do next, and what their answers might mean for every teacher feeling
- NewsEdSurge24 Jun 2026
Outgrowing the Chromebook: Why Advanced STEM Demands Better Student Tech
K-12 schools' one-to-one Chromebook programs support basic digital literacy but lack the computing power needed for advanced STEM coursework like engineering CAD and data science, prompting districts to evaluate more capable student devices.
Original abstract
<p>Across the United States, K-12 schools have spent the past decade building one-to-one device programs. These initiatives have established an essential baseline for digital access, making it easier for students to complete daily schoolwork across grade levels and subjects. By putting a device in the hands of every learner, districts have created a standard foundation for digital literacy, research and everyday classroom engagement.</p><p>As STEM programs continue to grow and mature, however, school leaders are beginning to encounter new questions about how well those devices support more advanced coursework. Pathways in fields like robotics, engineering, cybersecurity and data science increasingly rely on specialized professional applications that reach well beyond general-purpose classroom software.</p><p>In many cases, students can successfully complete introductory work on school-issued devices. But as instruction progresses, the tools required for STEM programs place different demands on student computing resources. As a result, educators and technology directors are taking a closer look at how hardware capacity can keep pace with shifting curricular needs.</p><h2>STEM Tools and Computing Demands</h2><p>While web-based applications work well for introductory coursework and daily assignments, many expanding STEM pathways introduce entirely different technical requirements. Courses in engineering, 3D modeling, cybersecurity and data science rely on industry-standard applications that demand substantial local computing capacity, robust memory and dedicated graphics processing.</p><p>A prime example is <a href="https://www.solidworks.com/"><u>SolidWorks</u></a>, a professional computer-aided design (CAD) platform used in both higher education and engineering industries. When students build detailed, multi-part models or run stress-test simulations, the performance of the device they’re using directly affects how efficiently they can work. Insufficient hardware can