## 4 Case Study  
The Italian company Mega Italia Media is the owner of the e-learning platform Dyn-Device. This software helps companies, mainly in Italy but also in the rest of Europe, to  
Figure 2: Schematic representation of a BERT encoding layer. The input vectors, \(X\), are processed by a self-attention mechanism, by two add and normalize layers and a feed-forward neural network. The encoder also contains two skip connections from \(X\) to the first add and normalize layer and from its output to the second add and normalize layer. provide business training to their employees. Since 2011, Mega Italia Media has opened more than 300 platforms and trained approximately 800,000 workers, mostly through courses on workplace health and safety. At the end of the course, the worker has to take an assessment test to determine whether he or she has understood the concepts presented in the courses. These tests are composed of two kinds of questions: _multiple-choice_ and _open-ended_ ones. Although an automatic algorithm is already used to process and correct a multiple-choice question, human intervention is necessary to check open-ended questions. As stated by the domain experts who perform the correction of the open-ended question-based tests, it takes 10 to 15 min to correct one; therefore, if the number of these tests is particularly high, it will require a very significant effort from the experts. Moreover, the latter are also involved in other duties, such as providing real-time assistance to the users on many platforms. This issue has become more prominent over the past three years; in fact, as we can see in Figure 3, the number of tests has significantly increased over the years, from 123 in 2012, the year when this service was launched, to 1430 in 2014, up to more than 5000 in 2020 and 6570 last year. Please note that these numbers also include the multiple-choice questions, which are the majority. This growth in numbers is probably due to the major increase in growth of the e-learning sector during the COVID-19 pandemic [36; 37; 38]. Therefore, providing a system to help domain experts and speed up the correction process has become a company priority. Each test is on average composed of five questions that require different kind of answers. Some questions require a short yes or no answer with a brief motivation, others ask for a simple definition, or require articulate thinking on a general topic. In the following, we show some examples of the original questions in Italian. For clarity, we also provide a translation. 1. _Qual e la definizione di lavoro elettrico?_ What is the definition of electrical work? 2. _Spiegare le differenze tra \"lavoro softo tensione\", \"lavoro fuori tensione\" e \"lavoro in prossimitu\" come definiti dalla Norma CEI 11-27 in relazione all'escuzione di lavori elettrici._ Explain the differences between \"live work\", \"off-voltage work\", and \"proximity work\", as defined in CEI 11-27 in relation to the performance of electrical work. Figure 3: Number of tests from January 2012 to January 2023 (in green). The red dashed line represents the distribution trend, which is a linear increase over the last decade. 3. _Quali sono i DPI necessari per eseguire un lavoro sotto tensione (bassa tensione)? E per un lavoro in prossimita (bassa tensione)?_ What PPE is required for performing live work (low voltage)? What about for proximity work (low voltage)? For each question, the teacher or the creator of the course also provides a _reference answer_ to the experts in the domain to speed up the correction process; this sentence contains all the information that users' answers have to include in order to achieve the maximum score. However, a reference answer can be very complex and long, slowing the correction process. In fact, for domain experts, it is quite difficult to compare the two answers and figure out whether the users wrote all the important information.