Conducted by the Education & Technology Desk

Elmoon Akhter is a Bangladesh-based English educator and applied researcher whose work explores how educational-psychology principles can be integrated with artificial intelligence to personalize language learning. Her research focuses on learner differences, motivation, feedback, adaptation, engagement, and AI-supported tools for more responsive learning experiences. She earned a BA (Hons) in English and an MA in English Literature from the State University of Bangladesh and is associated with Monipur Uchcha Vidyalaya & College. Her publications examine adaptive learning, intelligent tutoring, AI speech assistants, automated feedback, human-machine interaction, and personalized English instruction. Her current research profile records 153 citations, an h-index of 4, and an i10-index of 3.

Q. How can educational psychology and artificial intelligence work together to personalize language learning?
A. Educational psychology helps us understand how learners differ in motivation, confidence, attention, prior knowledge, and learning pace. AI can translate some of these principles into more individualized learning experiences. My interest is not simply in adding technology to the classroom, but in examining how AI can respond to learner needs in psychologically informed ways. A system may adjust difficulty, provide timely feedback, or recommend practice, while the teacher provides judgment and human guidance.

Q. Your most-cited research focuses on adaptive learning systems. Why is learner variability so important?
A. Students enter language classrooms with different levels of vocabulary, reading ability, confidence, learning speed, and prior experience. Educational psychology shows that one pathway may not serve every learner equally well. Adaptive systems can use performance data to modify content, pacing, and practice. In English language and literature learning, this may help prevent students from becoming overwhelmed or disengaged while maintaining meaningful teacher involvement.

Q. How can AI support motivation and reduce anxiety in English learning?
A. Language learning is strongly affected by emotion and confidence. Some learners understand the material but hesitate to speak because they fear making mistakes. AI speech assistants can provide a lower-pressure environment for repeated pronunciation and fluency practice. A learner can repeat an activity, receive feedback, and try again before speaking in front of others. From an educational-psychology perspective, the important issue is whether technology increases confidence, persistence, and willingness to participate.

Q. What role does feedback play in your work on automated essay scoring and AI-supported learning?
A. Feedback is one of the most important mechanisms in learning because students need to understand how to improve. Automated systems can provide rapid formative feedback on grammar, organization, vocabulary, or recurring writing patterns. Used carefully, this can support self-correction and self-regulated learning. Teachers remain essential for evaluating argument, creativity, and individual development. I see AI as a way to make feedback more immediate while educators provide deeper interpretation and personal support.

Q. How does educational psychology shape your work with multilingual learners and intelligent tutoring systems?
A. Multilingual learners differ in prior language exposure, cultural background, confidence, and the kinds of errors they make. Intelligent tutoring systems can provide scaffolding by breaking complex tasks into manageable steps, offering examples, and adapting explanations to performance. This connects closely with educational psychology because effective learning depends on matching support to the learner's current level and gradually reducing that support as independence develops.

Q. Human-machine interaction is another theme in your publications. What matters most when learners interact with AI?
A. The quality of interaction also matters. Learners need to understand what the system is asking, trust the feedback, and remain cognitively engaged rather than simply accepting machine-generated answers. Good AI integration should encourage thinking, reflection, and active participation. I am interested in designs that preserve learner agency and make AI a partner in practice, while teachers remain responsible for pedagogy, context, and the social dimensions of education.

Q. What direction would you like your future research to take?
A. I would like to develop a more psychologically informed model of AI-supported language education. Future research could examine how adaptive systems affect motivation, metacognition, confidence, persistence, cognitive load, and long-term learning. I am also interested in responsible uses of large language models for personalized instruction. My broader goal is evidence-based AI integration that responds to individual needs and strengthens learner independence without reducing education to automation.

Elmoon Akhter is a Bangladesh-based English educator and applied researcher with a BA (Hons) in English and an MA in English Literature from the State University of Bangladesh. Her work centers on integrating educational psychology and AI to personalize language learning, including adaptive learning, intelligent tutoring, multilingual education, AI speech assistants, automated feedback, human-machine interaction, and personalized English instruction. She is associated with Monipur Uchcha Vidyalaya & College. Her current research profile shows 153 citations, an h-index of 4, and an i10-index of 3.
Email: elmoonshimu@gmail.com

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