تقييم دور الذكاء الاصطناعي في دعم المناهج القائمة على الاستخدام في دراسة النحو
DOI:
https://doi.org/10.31185/eduj.Vol64.Iss1.5133الكلمات المفتاحية:
متعلمو اللغة الإنجليزية كلغة أجنبية ، تأثيرات التكرار، القياس، تحليل الأخطاء، التعلم البنائي، اللغة الوسيطة.الملخص
تستقصي هذه الدراسة الاتجاهات النحوية في النصوص التي تُنتجها تطبيقات الذكاء الاصطناعي مقارنة بتلك التي يكتبها المتعلمون من البشر. تختبر الدراسة مبدأً أساسياً من مبادئ النحو القائم على الاستخدام (usage-based grammar)، والذي يفترض أن اللغة تُكتسب من خلال التعرض المتكرر للأنماط اللغوية. ولتحقيق ذلك، تم إجراء مقارنة مباشرة بين نصوص الذكاء الاصطناعي ومقالات متعلمي اللغة. تعتمد الدراسة على منهجيات كمّية (quantitative approaches) لعدّ الكلمات والجمل، ورصد الأخطاء النحوية. كما تستخدم مناهج نوعية (qualitative analysis) للكشف عن الاتجاهات العامة في بناء الجملة، وخصائص محددة مثل استخدام صيغة الماضي (past tense). الهدف الأساسي هو معرفة ما إذا كانت نماذج الذكاء الاصطناعي تلتزم بقواعد النحو القائم على الاستخدام، إضافة إلى مقارنة أنماط الأخطاء (mistake types) بين المجموعتين. تُظهر النتائج تبايناً واضحاً؛ فبينما يتسم إنتاج الذكاء الاصطناعي بثبات كبير، تميل النصوص البشرية إلى التنوع والتفاوت. وقد كشفت الدراسة عن خلُوّ نصوص الذكاء الاصطناعي تقريباً من الأخطاء النحوية، في المقابل، احتوت النصوص البشرية على أخطاء متوقعة مثل الحذف (omissions) والتعميم المفرط (overgeneralizations). كما تشير النتائج إلى أن الذكاء الاصطناعي يوظف بعض العناصر اللغوية، كصيغة الماضي وصيغ الجمع (plurals)، بشكل أكثر كثافة. تخلص هذه التحليلات إلى أن أداء الذكاء الاصطناعي يحاكي عملياً نتائج التعلّم القائم على الاستخدام. فنتائج تدريب هذه النماذج على كميات هائلة من البيانات تتسم بالاتساق والدقة. في المقابل، يعكس الإنتاج البشري الطبيعة المستمرة والمتطورة لعملية اكتساب اللغة. تستنتج الدراسة أن الذكاء الاصطناعي يمثل أداة قوية للتحقق من النظريات اللغوية القائمة على التكرار (frequency-based linguistic theory)، إلا أنه لا يمثل نموذجاً محاكياً للرحلة المعرفية البشرية. توصي الدراسة بإجراء أبحاث مستقبلية تتناول نماذج مختلفة من الذكاء الاصطناعي ومستويات متنوعة من كفاءة المتعلمين.
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