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As Internet became more widespread, the use of printed dictionaries decreased. However, users’ abilities to consult online dictionaries are still not adequately developed. The project Esplorare (con) i Dizionari Digitali – through Moodle platform – allows users to carry out online exercises in order to develop both their linguistic knowledge and their ability to consult online dictionaries of different languages. We present the results of an study that involved around 300 students of Italian secondary schools, showing how the structure of the platform and the exercises, common to all languages, leads to transfer of skills. The exercises were created using Möbius Assessment, an automatic assessment system, already tested for scientific subjects.

This paper is concerned with lexical competence in the study of Italian for academic purposes, notably learned words formed with Greek/Latin elements. To improve and check receptive knowledge of such “difficult” vocabulary both by native and by L2 learners, a number of exercises are made available, and can be actually done and evaluated, at https://esploradizionari.i-learn.unito.it/. This is a technology enhanced learning environment integrating Moodle with the Automatic Assessment System Maple®, a software of Canadian origin already successfully used for teaching STEM disciplines. The specific features of the exercises are discussed, along with early results by Italophone and non-Italophone learners.

Because of the Covid-19 pandemic, the need to promote digital education has been felt even more, bringing the DELTA Research Group to reflect on how digital education could optimally facilitate the creation of an educating community able to promote and support educational success exclusively through distance learning. In order to answer, in this paper the experience of the 2019/2020 edition of “Scuola dei Compiti” (a recovery project for secondary schools of the poorest suburbs of Turin) is analysed in the perspective of the priority strategies illustrated in the Digital Education Action Plan for the period 2021-2027. Results will show that this was a forerunner experience perfectly in line with the principles and directions outlined in the document. Moreover, thanks to digital education, even a peculiar edition of the project such as this one has been a success: in fact, it has allowed students to improve from a cognitive and metacognitive point of view, even during a time that was very difficult for some families.

The transition between different levels of education is delicate, especially when mathematics is concerned; could a digital learning environment and new technologies help and support students in it? In this paper, we discuss the efficiency of a technology-enhanced learning environment for facilitating the transition between lower and upper secondary school. This Online Path regards the review and the enhancement of the main mathematical topics that are fundamental for beginning the upper secondary school. This educational path has been implemented in a Virtual Learning Environment (VLE) integrated with an Advanced Computing Environment (ACE) and with an Automatic Assessment System (AAS); in this way, it is always available and accessible and the educational materials in it are interactive and adaptive. Moreover, the system allows the adoption of a model of formative automatic assessment and interactive feedback that has already been proven to be effective when self-paced learning is concerned. Students could consult the material and self-assess their abilities through those summer holidays between the lower and the upper secondary school but the course is always available during the whole year allowing a perpetual support in the main mathematical concepts studied in class. So far, a total of 500 students have been involved, around two hundred students during the summer of 2018 and three hundred during the summer of 2019. Data analysis shows that students, who have been more involved in this online path, have also achieved a better performance in mathematics at the beginning of the scholastic year in the upper secondary school, proving that methodologies and technologies adopted were successful. For the summer of 2020, we are planning to enlarge the project with two more online paths: one for Latin and one for English language.

Enhancing language skills is a duty for many institutions, schools and universities; Information and Communications Technology is nowadays supporting language teaching, heading also to the integration of foreigners. According to previous studies, the use of a Technology Enhanced Learning Environment can foster language competences through online tests. The goal of this paper is to show and discuss different typologies of automatically evaluated questions useful to learn languages and designed with an Automatic Assessment System, already successfully used for teaching STEM disciplines: Science, Technology, Engineering and Mathematics. This work has been carried out thanks to the collaboration between the Department of Mathematics and the Department of Foreign Languages. Five different typologies of questions are analysed: "Combining sentence elements" asks to combine given elements to form at least three correct and meaningful sentences; "Find the mistake" asks whether a sentence is grammatically correct and to explain why; "The Target puzzle" asks to join words together using precise links; "Scrambled text" asks the student the correct sequence of sentences in a scrambled text; "The Encrypted Crossword puzzle" is a crossword puzzle without definition clues. Linguists consider these question types effective to develop language competences and have already used them profitably in traditional teaching and language learning. To engage the learner and increase motivation, we will develop an implementation where the questions are self-evaluated, always available, with immediate and interactive feedback. These tools could be used in online language courses and in all those teaching activities that are carried out remotely by the student alone. All questions are outlined with the explanation of the grading code and a triplet of descriptors; they describe the Performance, Requirements and Objectives of each question and allow further studies on automatic detection of the relatedness between different language learning objects, in order to construct adaptive language tests.