## 2 Materials and Methods
### MuLiMi Platform and Tasks
#### 2.2.4 Dynamic Novel Word Learning  
In the dynamic novel word learning (DNWL) task, three auditorily presented LS NWs (for procedure of construction and selection, see [12]; for the Italian version [galpo], [domjo], and [fe:jjo]; for the Spanish task [mokal], [flado], and [lepon]) were associated with one character displayed on the screen that did not resemble existing creatures or objects (see Figure 2). It was carefully avoided to use words that could easily be associated with any distinctive feature of the characters. This task involves four phases: presentation, consolidation, test, and naming phase. Task instructions and stimuli were recorded by native speakers. In the **presentation phase**, the characters are displayed one by one on the screen. Upon the auditory presentation of the corresponding \"name\", the child is asked (by a pre-recorded audio by native speakers of the language of assessment) to click on the character that was just introduced to encourage their active engagement with this task. Corrective feedback is provided upon an incorrect selection, but responses are neither collected nor analysed. In the **consolidation phase**, all characters were displayed on the screen and children were asked to select each character one by one when it was named. When selecting the target at first attempt, corroborative, pre-recorded auditory feedback is provided and the next name is presented. Having selected the wrong character instead, upon auditory corrective feedback, the child is asked the same question again until the correct figure has been identified. The system uses two variables to manage this phase: \(c\) and \(c_{err}\), tracking,  
Figure 2: Examiner interface during remote administration of the DNWL consolidation phase. respectively, the next character to be presented and the number of errors in the current execution of the phase. After all the characters have been presented, if \(c_{err}\) is greater than zero, the phase is repeated (see Figure 3). The frequency of correct character identification along with the total number of attempts is automatically recorded, and the ratio is derived and recorded. Figure 3: Flow diagram of the DNWL task. In the **test phase**, the NWs associated with characters are embedded within semantic contexts, visually supported by coloured line drawings depicting the scene. In these scenes, each character requests an object (high-frequent nouns, selection based on CDI database) [71]. A pre-recorded audio is played introducing the scene (e.g., \"Now they go out.\"), the condition of a certain character is described (e.g., \"[PERSON] notices the rain.\"), and a question is posed that requires the association between the information in the scene and the character's name (e.g., \"Whom do you give the umbrella to?\"). Upon the child selecting the corresponding character, a subtle audio signal indicates that the answer has been recorded, irrespective of the accuracy of the child's response. This subtest consists of a minimum of two and maximum of three scenes, depending on the child's performance. The state of this phase is represented by four variables: \(t\) and \(o\) represent the current scene and the current object within the scene, \(t_{err}\) counts the number of incorrect answers given within the current scene, and \(t_{cons}\) counts the number of consecutive scenes completed with no errors before the current one. If in the first or second scene the participant answers incorrectly to one or more of the questions proposed, the consolidation phase is repeated. The test phase resumes from the mistaken object. If the examinee provides exclusively correct answers in the first two scenes (having \(t_{cons}\) reaching a value of 2), the phase ends skipping the third scene (see Figure 3). Again, the frequency of correct character identification and the amount of attempts are automatically recorded. In each scene, all three characters are addressed once in a random order, so this phase consists of a maximum \(n=9\) items.