Sunday, April 26, 2026

Maybe Engineers Don’t Hate English - They Just Need Better Tools to Learn It

Let’s be honest! Most civil engineering students don’t wake up excited to study English. For many of them, language learning feels like a side quest that has nothing to do with bridges, concrete, or structural analysis. But here’s the uncomfortable truth: English is everywhere in engineering. From textbooks and research papers to technical manuals and global collaboration, it’s basically unavoidable. The problem isn’t that students don’t need English. It’s that the way we teach it often feels disconnected from their real world. And that’s where things start to fall apart.

Interestingly, research has long emphasized how critical English is in academic and professional settings, especially in globalized fields like engineering (Khan & Ali, 2010). Students are expected to read complex materials, understand technical terms, and communicate ideas clearly. Yet, many still struggle, not because they lack ability, but because they lack motivation. Traditional teaching methods, dominated by lectures and textbooks, don’t exactly spark excitement. So the real question becomes: what if the issue isn’t the students, but the tools we’re using?

This is where digital technology starts to change the conversation. Over the past decade, learning has shifted from rigid, classroom-centered systems to more flexible and interactive environments. Students today can access materials anytime, anywhere, which fits much better with their busy academic lives. Technology also encourages more active participation instead of passive listening, which has been shown to improve engagement and learning outcomes (Shadiev & Wang, 2022). In short, learning doesn’t have to feel like a chore anymore, it can actually be part of daily life.

One approach that stands out is Mobile-Assisted Language Learning (MALL). It sounds fancy, but the idea is simple: using your phone to learn a language. And honestly, it makes perfect sense. Students already spend hours on their phones, why not turn some of that time into something productive? Mobile learning allows for short, flexible learning sessions that can happen anytime, whether you’re waiting for a class or commuting. Studies show that this kind of accessibility can significantly improve consistency in learning (Akram et al., 2021).

Now let’s talk about Duolingo, probably the most recognizable language-learning app out there. What makes it interesting isn’t just its content, but how it delivers it. Instead of traditional lessons, it uses gamification points, levels, streaks to keep users engaged. This simple design trick turns learning into something that feels more like playing a game than studying. And surprisingly, it works. Research shows that Duolingo is particularly effective in helping learners build vocabulary and basic grammar skills through repetition and immediate feedback (Loewen et al., 2019).

But Duolingo isn’t perfect. While it’s great for beginners, it doesn’t fully prepare students for real-world communication. Engineering students, for example, need to understand technical discussions, write reports, and present ideas. These are complex skills that go beyond tapping answers on a screen. Some studies even point out that Duolingo lacks depth in developing speaking and writing abilities (Kazu & Kuvvetli, 2025). So while it’s a great starting point, it shouldn’t be the only tool in the toolbox.

Friday, January 2, 2026

Enhancing Assessment With AI: Strategies for Complementing Teacher Expertise


Authors:
Andi Asrifan (Universitas Negeri Makassar, Indonesia), Rismawati Sudirman (Universitas Muhammadiyah Palopo, Indonesia), Rusdiana Junaid (Universitas Cokroaminoto Palopo, Indonesia), and Juvrianto Chrissunday Jakob (Politeknik Negeri Ambon, Indonesia)


Abstract
This chapter examines the revolutionary impact of Artificial Intelligence (AI) on educational evaluation, highlighting how AI tools can enhance, rather than supplant, teacher ability. In response to the changing requirements of 21st-century education, AI provides avenues for individualized learning, immediate feedback, and effective performance monitoring. Grounded in cognitive and constructivist learning theories, the book delineates various AI-driven assessment models, encompassing rule-based grading and adaptive analytics. It emphasizes the pedagogical, ethical, and technical aspects of AI integration by utilizing empirical research and practical case studies. The debate emphasizes promoting a human-centered approach that maintains teacher autonomy, guarantees equity, and fosters inclusivity. The book advocates for a collaborative future where instructors and AI synergistically enhance assessment processes and student results.

Chapter Description:

Enhancing assessment with artificial intelligence (AI) means using technology to support teachers in evaluating student learning more effectively. AI does not replace teachers, but helps them work more efficiently and make better decisions. By combining AI tools with teacher expertise, assessment can become more accurate, fair, and supportive of student development.

One important strategy is using AI to assist with grading routine tasks. For example, AI can quickly check multiple-choice tests, short answers, or basic language exercises. This saves teachers time, allowing them to focus more on giving meaningful feedback and supporting students who need extra help.

AI can also help teachers understand student learning patterns. By analyzing student responses and performance over time, AI can identify strengths, weaknesses, and common mistakes. This information helps teachers adjust their teaching strategies and design assessments that better match students’ needs.

Another way AI complements teacher expertise is through personalized feedback. AI systems can provide instant feedback on assignments, such as writing or quizzes, based on clear criteria. Teachers can then review this feedback, add their professional judgment, and give more personal and encouraging guidance to students.

AI can also support fairness and consistency in assessment. By using the same standards for all students, AI can reduce bias in scoring. However, teachers still play a key role in interpreting results, understanding student context, and ensuring that assessments remain ethical and meaningful.

In conclusion, enhancing assessment with AI is about partnership, not replacement. When AI is used as a supportive tool, it helps teachers save time, understand students better, and improve the quality of assessment. Teacher expertise remains essential to guide, interpret, and humanize the assessment process.