Brief Reflection on Past and Present

When this issue on ancient languages was suggested, certain members of our editorial team wondered whether we weren't venturing into something dry and elitist as generally, we try to stick to issues that speak to a large readership and cross many domains. Thus, we suggested that the link between the teaching of ancient languages and modern languages be made explicit with the intent of breaking down “stuffy old” barriers. And as the contributions came rolling in, we realized that there are clear benefits for “Old” meeting “New” and for “Ancient” and “Modern” to learn from one another! One aspect that kept cropping up throughout the editing of this issue was the use of generative artificial intelligence. If you ask Claude “Can AI write in ancient and modern Greek?” it says that it can, but it does state “Ancient Greek may have more inconsistencies since there's less digital training data” and that it sometimes has a hard time “Understanding of archaic grammar and syntax”. And then this ability of AI to actually be decent in giving any type of answer even in and about ancient and modern languages is cause for concern in evaluating student work. Consequently, several of us have made steps backwards, proposing written examinations that test specific knowledge, or facts, instead of more modern exams testing the transfer and application of knowledge. No longer can a BYOD mode or the writing of reflective portfolios be used in class as such things were too often used by students and though such AI produced texts that are sometimes convincing, they are rarely interesting. If the thinkers of antiquity were teacher trainers in the modern era, they would undoubtedly be surprised by the speed with which students delegate their learning to a machine. Socrates, for example, did not transmit ready-made answers: he questioned, provoked, forced his interlocutors to think. Generative artificial intelligences, on the contrary, provide instant and polite responses, but without the intellectual journey that leads to understanding. Therein lies the risk, according to us: replacing reflection with automation. The teaching of languages, both ancient and modern, must therefore continue to evolve. Since machines already translate faster than humans, the challenge is no longer only the accumulation of vocabulary or mastery of grammar, or even the development of communicative competence. The acquisition of a critical stance about learning language is in question: questioning meaning, comparing contexts, understanding nuances, and inferring meaning. In other words, cultivating Socratic skills through both modern language teachings as well as the teaching of ancient languages. Χαίρων ἀνάγνωθι!

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Publication Details

Journal
Babylonia Journal of Language Education
Published
2025-09-29
DOI
https://doi.org/10.55393/babylonia.v2i.840
Primary Topic
Digital Humanities and Scholarship
Type
article
Field-Weighted Citation Impact
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article

Brief Reflection on Past and Present

Editorial Team of Babylonia
Babylonia Journal of Language Education
Digital Humanities and Scholarship
article

Brief Reflection on Past and Present

Editorial Team of Babylonia
article en

Abstract

When this issue on ancient languages was suggested, certain members of our editorial team wondered whether we weren't venturing into something dry and elitist as generally, we try to stick to issues that speak to a large readership and cross many domains. Thus, we suggested that the link between the teaching of ancient languages and modern languages be made explicit with the intent of breaking down “stuffy old” barriers. And as the contributions came rolling in, we realized that there are clear benefits for “Old” meeting “New” and for “Ancient” and “Modern” to learn from one another! One aspect that kept cropping up throughout the editing of this issue was the use of generative artificial intelligence. If you ask Claude “Can AI write in ancient and modern Greek?” it says that it can, but it does state “Ancient Greek may have more inconsistencies since there's less digital training data” and that it sometimes has a hard time “Understanding of archaic grammar and syntax”. And then this ability of AI to actually be decent in giving any type of answer even in and about ancient and modern languages is cause for concern in evaluating student work. Consequently, several of us have made steps backwards, proposing written examinations that test specific knowledge, or facts, instead of more modern exams testing the transfer and application of knowledge. No longer can a BYOD mode or the writing of reflective portfolios be used in class as such things were too often used by students and though such AI produced texts that are sometimes convincing, they are rarely interesting. If the thinkers of antiquity were teacher trainers in the modern era, they would undoubtedly be surprised by the speed with which students delegate their learning to a machine. Socrates, for example, did not transmit ready-made answers: he questioned, provoked, forced his interlocutors to think. Generative artificial intelligences, on the contrary, provide instant and polite responses, but without the intellectual journey that leads to understanding. Therein lies the risk, according to us: replacing reflection with automation. The teaching of languages, both ancient and modern, must therefore continue to evolve. Since machines already translate faster than humans, the challenge is no longer only the accumulation of vocabulary or mastery of grammar, or even the development of communicative competence. The acquisition of a critical stance about learning language is in question: questioning meaning, comparing contexts, understanding nuances, and inferring meaning. In other words, cultivating Socratic skills through both modern language teachings as well as the teaching of ancient languages. Χαίρων ἀνάγνωθι!

Babylonia Journal of Language EducationVol. 2
Openalex Percentile: Top 71%
Digital Humanities and Scholarship
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