Evaluating Classroom Potential for Card-it: Digital F lashcards for Studying and Learning I talian Morphology (2023)

Abstract: This paper presents Card-it, a web-based application for learning Italian verb conjugation. Card-it integrates a large-scale finite-state morphological~(FSM) analyzer and a flashcard application as a user-friendly way for learners to utilize the analyzer. While Card-it can be used by individual learners, to support classroom adoption, we implemented simple classroom management functionalities such as sharing flashcards to a class and tracking students’ progression. We evaluated Card-it with teachers of Italian. Card-it was reported as engaging and supportive, especially by featuring two different quiz types combined with a verb form look-up feature. Teachers were optimistic about the potential of Card-it as a classroom supplementary tool for learners of Italian as L2. Future work includes sample sentences and a complete learners evaluation.

## introduction learning verb morphology plays a crucial role in the acquisition of morphologically rich languages @xcite , such as italian and french. thus, learners of italian deal with the acquisition of a rich system of verbal inflections (e.g., @xcite . explicit morphological instructions and training have been shown to help students on acquiring new words as well as to improve their syntactic knowledge @xcite . similarly, raising meta-linguistic awareness improves the learners' production and competence in second language (l2) acquisition @xcite . to support learners of italian as l2, we designed, implemented, and evaluated cardit with the help of experts: teachers of italian as a foreign language. card-it fosters meta-linguistic knowledge when presenting linguistic information on the analysis of verb forms (i.e., for the verb mangiare (to eat) "prima persona singulare presente indicativo" → (io) mangio) along with additional explanations of linguistic categories related to verb morphology that are displayed on demand. in addition, meta-linguistic information is also used to present corrective feedback (see sec. 4.2). card-it is an online application for teachers and learners of italian to create collections of digital flashcards -based on a semi-automatic approachwith which they can study and test themselves on verb morphology explicitly. our choice for using a digital flashcard design reflects a traditional way of learning vocabulary explicitly, which has been shown to be a successful learning method that is perceived well by students @xcite . while some flashcard systems may support verb morphology with pre-defined cards and modules, they do not allow for the customization of cards or decks (e.g., memrise foot_0 ). other systems support custom card collections, but they require manual input of the card information (e.g., anki foot_1 ). yet, these systems do not enable teachers to track and analyze their students' progress over time. in addition, card-it's learner-centred design embeds corrective feedback, meta-linguistic information, and different study modes. this paper introduces the system's architecture, the fsm implementation, and card-it's iterative design and features. lastly, we report the results of a brief evaluation with italian teachers which indicates card-it's potential for their classroom and outlines our future steps towards a learners evaluation. ## related work traditionally, natural language processing (nlp) tools like an fsm are a component of larger pipelines, for example, as a tokenizer (e.g., jurafsky and martin, 2009). as a result, using these tools is often not intuitive or easy for users unfamiliar with nlp. however, since these tools can work with text, nlp has become an integral part of the field of computer-assisted language learning (call), with several systems using nlp tools in a language-learning context. examples include e-tutor @xcite , an intelligent tutoring system for learners of german that is fully incorporated into the german curriculum at simon fraser university; tagarela (amaral and meurers, 2011), a system for portuguese that includes exercises on vocabulary; and feedbook @xcite , an intelligent tutoring system for english that can be fully integrated into regular classes. similarly, google-assisted language learning (gall), corpus-based or data-driven learning (ddl) are increasing in popularity as language learning tools (conroy, 2010; pérez-paredes, 2022). while gall refers specifically to learners using tools provided by google, both gall and ddl happen when learners take advantage of online access and text processing power to use corpus tools, such as dictionaries and linguistic corpora. furthermore, @xcite verified that ddl was an effective cognitive tool for helping people with their lexical and grammatical problems while dealing with concordance tasks; for example, learning frequent word pairs such as to take instead of to eat a [medicine] pill. however, he suggests that some of the available resources are not user-friendly and difficult to use, such as functions for linguistic resources applied for stemming. that said, card-it's design uses a learner-centred approach with teacher support features; it provides a user-friendly interface to leverage an fsm to power a semi-automatic generation of flashcards that can be used to study and self-assess italian verb conjugations. related to using fsm in card-it, @xcite used a finite-state transducer to power a turkish word synthesis system and a word-level translation system between turkish and english. another example is the icall system for two saami languages that is based on finite-state transducers @xcite . ## card-it: system architecture card-it is a web-based application consisting of two components: back-end and front-end. back-end: the fsm analyzer. the main component of the back-end is our fsm, containing over 5000 verb lemmata and their conjugations @xcite . it was created by extracting verb roots from free resources, the morph-it! lexicon by @xcite and the online dictionary provided by one of italy's leading news magazines, corriere della sera foot_2 . fsms are usually part of a text processing pipeline within nlp tools. here, we leveraged our fsm as a dynamic form generator and analyzer in a language-learning context. the fsm ties a verb form to its linguistic analysis: it may analyze a verb form and return its linguistic tags (analysis) or generate a verb form given its linguistic tags (generation) -see fig. 1 . in our case, the fsm consists of a lexicon that contains verb stems, their inflectional paradigms and the appropriate morphological analysis. the lexicon of the fsm creates all verb forms following the regular pattern of concatenating stems with their respective inflectional endings. with the use of regular expressions the fsm is able to manipulate those regular forms of the lexicon on the basis of phonological rules. for example, some forms require the insertion of an -h to retain certain pronunciation patterns. consider the verb mancare ("to miss"): the regular inflection paradigm in the lexicon creates the incorrect form manci ("you miss"), for the second person singular present indicative. however, to retain the correct pronunciation, the correct form is manchi. whenever the fsm is run, it first creates all forms in the lexicon and then applies regular expressions to manipulate these forms based on phonological rules of the language. this architecture allows us to build a powerful and large morphological resource since it automatically creates verb forms on the basis of their stems. if we were to add new verbs to our tool, it simply requires to manually add verb stems into the fsm lexicon. verbs generated by the fsm, user accounts, flashcards and classroom organization are stored in a mysql database. a flask middleware is responsible for querying changes users request from the front-end. these changes are related to flashcard, classroom, and account organization. the main advantage of this back-end architecture is to scale the system for multiple users simultaneously; this integration approach has been taken by others @xcite . a set of python scripts are responsible for parsing and updating the database with any changes to the fsm; currently, these updates are triggered manually whenever the list of verbs or morphology is altered. front-end: user interface. the user interface front-end of card-it is developed with react.js. the main function of the front-end is the flashcard design for users to study and be assessed from. sec. 4 explains card-it's digital flashcards design and interaction. ## card-it design and features card-it can be used for autonomous learners who may interact with the app to study italian conjugations on their own. in addition, card-it can also be integrated by teachers in the classroom. in either case, learners interact with verbs and conjugations via digital flashcards. ## evaluation we took an iterative design approach for implementing card-it, where we performed a preliminary expert evaluation (@xmath0. based on this preliminary evaluation, we determined the fitness of the flashcards and the quiz formats and iterated over the application. the teachers responded positively to card-it as a digital version of their current classroom practices, such as verb conjugation worksheets. we also learned that card-it could be adopted as a supplemental tool to the classroom, which led us to implement the classroom features. the following section describes our second expert evaluation. ## future work and conclusion this paper discussed the power of the adequate use of nlp tools in language learning, including designing appropriate interfaces. we presented card-it as a user-friendly app for learning italian verb conjugation using digital flashcards; we also described card-it's classroom management and analytics features (more details in app. a). lastly, we discussed our iterative approach to design, which combined expert evaluations between iterations of card-it. the results of the expert evaluation show that according to their expertise, card-it is an appropriate conjugation tool for autonomous learning and for classroom integration as a supplementary resource. card-it's usability and different quiz functions were positively evaluated. nonetheless, we also learned that card-it might be further improved by adding example sentences. the most promising result from the evaluation is the experts' expression of interest in using card-it in their classrooms. despite asking for the experts' perspectives as students, it would be more reliable to run a user study with learners of italian as a second language. we are designing a remote longitudinal study with 3 weekly sessions. at the end of each session, participants are invited to submit a card-it quiz and a short usability survey. we also plan on testing their knowledge of a set of verb conjugations before and after their study period of 3 weeks. other future directions may include gamification of cardit's quizzes and quiz modes that can support live classroom exercises such as kahoot @xcite .