Rosy Tsopra
email: rosy.tsopra@nhs.net

Mélanie Courtine

Karima Sedki

David Eap

Manon Cabal

Samuel Cohen

Olivier Bouchaud

Frédéric Mechaï

Jean-Baptiste Lamy

AntibioGame®: A serious game for teaching medical students about antibiotic use

Keywords:

Introduction: Measures for controlling antimicrobial resistance are urgently required. We describe here AntibioGame®, a serious game for improving the training of medical students in antibiotic use in primary care. Objective: We aimed to design a serious game for antibiotics teaching and to evaluate its usability and playability by medical students. Methods: We used various gamification techniques (e.g. use of mascots, avatars, rewards, leader board) and cartoon graphics in the design of AntibioGame®. This game implements clinical case templates built from a list of learning goals defined by a medical team through an analysis of clinical practice guidelines. The game was evaluated by asking medical students to rate their satisfaction and the usability and playability of the game on an electronic form and through group discussions. The electronic form was derived from the MEEGA + scale, a fivepoint Likert scale including 32 items for assessing both usability and playability. Results: AntibioGame® is a case-based game in which students play the role of a doctor meeting patients in consultation and helping other health professionals to solve their problems, as in real life. The scenarios are realistic and cover situations frequently encountered in primary care. The 57 medical students enrolled found the game attractive, usable, fun, and appropriate for learning. Game quality was considered "good" (score = 60 on the MEEGA + scale). All the students said they would recommend the game, 96 % liked it and 81 % would use it for revision. Conclusion: AntibioGame® is a promising tool for improving knowledge in antibiotic prescription that could easily be included in multifaceted programs for training medical students.

Introduction

The WHO has warned that "the world urgently needs to change the way it prescribes and uses antibiotics" [START_REF]Antibiotic Resistance[END_REF]. Indeed, antibiotics are currently widely misused and overused, accelerating the development of bacterial resistance, and leading to complications, death, extended hospital stays and higher medical costs [START_REF] Davey | Appropriate vs. inappropriate antimicrobial therapy[END_REF].

Most antibiotics are prescribed in primary care. Physicians have to decide "empirically" (i.e. without knowledge of the causal pathogen) whether or not to prescribe antibiotics [START_REF] Gupta | International clinical practice guidelines for the treatment of acute uncomplicated cystitis and pyelonephritis in women: A 2010 update by the Infectious Diseases Society of America and the European Society for Microbiology and Infectious Diseases[END_REF][START_REF] Woodhead | Guidelines for the management of adult lower respiratory tract infections-full version[END_REF]. This requires clinical skill, but also a knowledge of epidemiology, pharmacology, and microbiology [START_REF] Leekha | General principles of antimicrobial therapy[END_REF]. This knowledge is developed during medical training, including lectures on the basics of antibiotic treatment and textbooks on infectious diseases. However, despite this intensive training, many physicians continue to prescribe antibiotics inappropriately [START_REF] Van Den Broek D'obrenan | Antibiotic use in Dutch primary care: relation between diagnosis, consultation and treatment[END_REF][START_REF] Steinman | PRedictors of broad-spectrum antibiotic prescribing for acute respiratory tract infections in adult primary care[END_REF][START_REF] Linder | Antibiotic treatment of adults with sore throat by community primary care physicians: a national survey, 1989-1999[END_REF]. One of the reasons for this may be that current teaching approaches and textbooks do not adequately prepare medical students for this task [START_REF] Miles | Medical graduates' preparedness to practice: a comparison of undergraduate medical school training[END_REF][START_REF] Illing | Perceptions of UK medical graduates' preparedness for practice: a multi-centre qualitative study reflecting the importance of learning on the job[END_REF][START_REF] Monrouxe | How prepared are UK medical graduates for practice? A rapid review of the literature 2009-2014[END_REF]. Indeed, these methods have limitations: (i) the learning process is passive and students are not encouraged to develop critical thinking [START_REF] Schmidt | On the use and misuse of lectures in higher education[END_REF]; (ii) students memorize theoretical medical concepts, rather than learning to solve the practical problems that arise in medical practice; (iii) students focus on clinical situations encountered in hospitals, but not in primary care; (iv) students focus on a single patient, whereas, in real life, they often have to manage several patients simultaneously; (v) students often miss lectures due to the constraints of their work shifts at the hospital; (vi) students may find the format of current teaching methods unattractive, boring and outdated relative to the new technologies developed in other domains.

Serious games may provide a solution to these issues [START_REF] Wang | A systematic review of serious games in training health care professionals[END_REF]. These interactive computer applications aim to facilitate "learning through the game" [START_REF] Bergeron | Developing Serious Games[END_REF]. They propose an entertaining learning environment in which students are exposed to various medical problems, as in real life. Students can formulate hypotheses and suggest solutions, in conditions in which they can make and learn from errors, without fatal consequences for real patients [START_REF] Buttussi | Evaluation of a 3D serious game for advanced life support retraining[END_REF]. They are, thus, encouraged to develop analytical and synthetic skills [START_REF] Bonwell | Active Learning: Creating Excitement in the Classroom, ASHE-ERIC Higher Education Reports[END_REF]. Serious games also make learning fun, challenging and exciting. Moreover, with their digital format, they allow students to play "anytime anywhere". They are, therefore, much appreciated by students [START_REF] Kron | Medical student attitudes toward video games and related new media technologies in medical education[END_REF], who recommend their use in medical training [START_REF] Jeffres | A study assessing the educational value of serious games in infectious diseases -going beyond memorization[END_REF].

A few serious games relating to antibiotic use have already been developed. Some, such as e-Bug games [START_REF] Farrell | Developing e-Bug web games to teach microbiology[END_REF][START_REF] Hale | Can gaming increase antibiotic awareness in children? A mixed-methods approach[END_REF], aim to educate young children about antibiotic use and resistance. Others, such as Bacteria Combat [START_REF]Bacteria Combat[END_REF], and Superbugs [START_REF]Superbugs[END_REF], aim to teach microbiological concepts. A few, such as Septris [START_REF] Evans | Septris: a novel, mobile, online, simulation game that improves sepsis recognition and management[END_REF], a case-based online game for teaching sepsis management, or "On call antibiotics" [START_REF] Castro-Sánchez | On call: antibiotics"-development and evaluation of a serious antimicrobial prescribing game for hospital care[END_REF], a mobile case-based game for teaching antibiotic prescription, aim to teach medical students about antibiotics. However, these games are based on clinical cases in hospitals, whereas antibiotics are mostly prescribed in primary care. The underlying learning goals of these games are also not always clearly defined, and it may be difficult for medical teachers without specialist computer engineering skills to update the clinical cases. Finally, their graphic design may not have appealed to young people.

We tried to overcome these limitations by designing AntibioGame®, a case-based game for teaching students about antibiotics in primary care. The student plays the role of a doctor meeting patients in consultation and helping other health professionals to solve their problems, as in real life. The scenarios are realistic and cover the learning goals defined by a medical team on the basis of an analysis of clinical practice guidelines. The scenarios are displayed through a graphical interface with a cartoon design.

We describe here the design of AntibioGame® and the evaluation of its usability and playability.

Materials and methods

Design of AntibioGame®

We aimed to design a serious game:

• To teach students how to manage infected patients in primary care.

We therefore defined a list of learning goals adapted to primary care;

• That could be easily updated by the medical education team without the need for computer engineers. We therefore chose to create clinical case templates;

• To make the learning process fun, exciting and challenging through a pleasant graphical interface. We therefore used gamification techniques and cartoon design;

• That could be made available on different digital supports, to fa- cilitate its use by students.

Definition of a list of learning goals adapted to primary care

A medical team defined a list of learning goals based on an analysis of three clinical practice guidelines concerning the management of respiratory and urinary infections in primary care.

Creation of clinical case templates

The medical team built clinical case templates based on the preestablished learning goals. These templates were designed to be (i) generic, to allow adjustment for a large range of medical cases, (ii) realistic, to motivate students, (iii) short, to make it possible for students to play "anywhere anytime", (iv) varied, to ensure that the game did not become monotonous. These templates were then implemented in the game.

When the medical team wishes to add a new clinical case, one of these templates is completed (Table 1), and the clinical case is automatically saved in the game database, without the need for reprogramming.

Use of gamification techniques and cartoon design

Various gamification techniques [START_REF] Maheu-Cadotte | Effectiveness of serious games and impact of design elements on engagement and educational outcomes in healthcare professionals and students: a systematic review and meta-analysis protocol[END_REF] were used (Table 2): a mascot represented by a superhero called Antibioman appears throughout the game, and helps students if necessary; an avatar with badges personalized according to the student's achievements is displayed in the student's profile; hints and recaps are provided on request; a scoring system, with rewards, points, levels and a leader board, is displayed at the end of each clinical case.

The interface is based on a cartoon design. Some of the characters are reminiscent of well-known cartoon characters. They ask the

Table 1

Example of a clinical case written by the medical team based on the template "consultation in the GP's office" (R: Response). students questions and respond enthusiastically or sarcastically, depending on the correctness of the answers supplied by the students. The decor corresponds to various medical contexts, and various meaningful icons are used (Fig. 1).

Technical implementation

AntibioGame® is implemented in PHP 7.0 and MySQL 5.7. It is a web application available for personal computers and smartphones. Firefox Mozilla is required for its optimal use.

Various tests were performed during the development process, to check software quality and playability. First, all functions were tested by three students from different backgrounds (video games, computer sciences, and biology). This made it possible to fix 47 problems (e.g. interaction problem with some icons). Second, playability was assessed by seven people from different backgrounds (video games, medical). This made it possible to fix 22 problems (e.g. incomprehensibility of some icons, leading to the addition of information bubbles). Third, medical relevance was assessed by the educational team of the university, including two specialists in antibiotics, the educational director, and the head of a hospital infectious diseases department. This made it possible to fix two problems (e.g. the addition of a "key point" at the end of each clinical case).

AntibioGame® evaluation

We evaluated student satisfaction and the usability and playability of the game, by organizing several evaluation sessions. Each session began with a presentation of AntibioGame®. The students then played games for three clinical cases on computer tablets, at the end of which, they could compare their results with those of their peers on a leader board. At the end of the evaluation period, we collected their opinions on the game through group discussions and the completion of an electronic form. Rewards are given at the end of clinical cases, depending on the accuracy of the answers given by the student

Table 3

Clinical cases played in AntibioGame® with their learning goals.

Recruitment of medical students

Students were notified of the existence of this study through social networks, the faculty of medicine, and the hospital. For participation, students had to have completed at least two years of a medicine degree and had to sign a consent form. They were not remunerated for their participation, but received a small gift in the form of chocolate at the end of the evaluation.

Electronic form and open discussion

The electronic form included:

• Demographic questions • 36 questions assessing student satisfaction and the usability and playability of the game. We used the MEEGA + scale [START_REF] Petri | MEEGA+: A Method for the Evaluation of Educational Games for Computing Education[END_REF][START_REF] Meega+ Team | MEEGA+ a Model for Evaluating Educational Games -GQS -Software Quality Group[END_REF], which assesses 9 items for usability and 23 items for playability on a fivepoint Likert scale extending from "strongly disagree" to "strongly agree" for each item. The scores for these items yield an overall score for game quality (low quality for scores < 42.5, good quality for scores between 42.5 and 65, and excellent quality for scores > = 65)

• Three questions assessing the students' appreciation of the game, its use for study purposes and areas for improvement

• Additional free comments

At the end of the session, students were encouraged to exchange views concerning their overall opinion of the game during a free discussion.

Quantitative and qualitative analyses of the free comments of the students are presented together in the results section.

Results

AntibioGame® design

Clinical case templates

Ten clinical case templates were created to cover the 16 learning goals defined on the basis of an analysis of clinical practice guidelines (Table 3):

• Four were main scenarios corresponding to GP appointments with patients.

• The other six were secondary scenarios corresponding to phone calls from other health professionals asking for advice. These scenarios were presented only at higher levels in the game and aimed to teach students how to manage two patients simultaneously, as in real life.

Game play

Students first log in with their alias and password. Once logged onto the system, they can see their avatar, personalized with three badges summarizing their achievements in the game.

On the homepage, the mascot asks students to choose a theme for training (e.g. respiratory infections). Once the theme has been chosen, the game starts with a first clinical case (Fig. 2). Students have to read the patient record, and then answer the patient's questions. The student selects the answer from a list of responses proposed by the system and displayed in random order. Once students have validated their answers, they receive a response from the patient, which may be pleasant or sarcastic, depending on the accuracy of their answers. If students answer a question incorrectly they can ask for a hint and try again. They have only two chances to answer the question correctly. Once the question has been completed, the student can choose to read a recap of the medical knowledge related to the question. This recap includes web links to online materials.

At higher levels, the game may involve the student receiving a phone call. These calls occur without warning, briefly interrupting the main clinical case game played by the student. Students are notified by a graphical representation of a phone vibrating and an audio ringtone. They have a short time in which to pick up the phone. The person at the other end of the phone is another health professional asking for some quick advice. Once the students have answered the question posed by the health professional, they receive a reward or a punishment (e.g. a sweet or a bottle of poison) depending on whether they answered the question correctly or not. When they hang up, they return to the main clinical case.

At the end of each main clinical case, a score window is displayed (Fig. 3). It contains (i) an image of the mascot with an encouraging or sarcastic message, depending on the student's achievements, (ii) some "key points to remember" highlighted in yellow, (iii) a syringe, which fills up progressively depending on the student's score, (iv) the learning goals of the medical case played and (v) the three scores assessed:

• The "experience score" increases with the number of clinical case games played and determines the avatar badge "school year" (e.g. at the beginning, the avatar has a badge proclaiming "first year of medicine school").

• The "degree score" is calculated from the number of correct answers provided for main scenarios and determines the "degree" badge of the avatar (e.g. the avatar wears the badge "serial killer" if the student answers incorrectly).

• The "popularity score" is calculated from the number of correct answers provided during phone calls and determines the "popularity with health professionals" badge (e.g. the avatar wears the badge "charming" if the student responds correctly to phone calls).

Each of these scores may increase or decrease as the game progresses. When the students have completed all the clinical cases for a given topic, they can compare themselves with others on the leader board, which ranks students according to their degree score.

AntibioGame® evaluation

In total, 57 students assessed AntibioGame® (Table 4). They had a mean age of 23 years, and two were "Erasmus students" from other countries. Very few were in the habit of frequently playing video games.

Quality

AntibioGame® was considered to be of "good" quality according to the MEEGA++ scale (score was 60).

Usability (Fig. 4)

Overall, 91 % of the students felt that the AntibioGame® design was attractive. Some described the design as original, captivating and pleasant (Table 5, Ex1), and one felt that it made the discipline of infectious diseases easier to approach. Moreover, 89 % of students found the game easy to play, and 98 % found the rules easy to understand (Table 5, Ex2).

In terms of possible improvements, a few students suggested improving interactions with some icons, or improving readability by the use of other text fonts.

Player experience (Fig. 4)

AntibioGame® provided relevant medical content and made it easier to learn about antibiotic use according to 93 % and 98 % of students, respectively. The game was perceived as "instructive", thanks to the explanations displayed after each question, but also as "professionalizing", thanks to the various realistic clinical cases. AntibioGame® was also seen as promoting competition, cooperation and challenging activities, for 87%-89% of students (Table 5,Ex10). The students saw the phone calls, for example, as an exciting challenge (Table 5,Ex13). 98 % of the students felt that AntibioGame® was fun (Table 5, Ex11-12). Many of the students liked the responses of the game characters to their answers (Table 5,Ex4), but one of the students reported being upset by some sentences.

In terms of possible areas for improvement, the game does not currently engage the full attention of students (only 56 % lost track of time when playing). The students also suggested that the clinical cases could be improved by: adding more questions and icons (e.g. imagery), adding questions from other medical specialties, adapting the level of difficulty according to the number of years of medical training already completed by the student, and extending the learning goals to other aspects of antibiotic therapy (e.g. mechanisms of bacteria resistance), and to other medical contexts (e.g. intensive care units).

The students also suggested that the scoring system could be improved by specifying whether each question has one or more answers, adding a correction of each question, providing more hints, and attributing more points for responses that are partially correct.

Finally, some students recommended adding functions such as a multiplayer mode, a timer, daily rewards, and tutorials.

Use for revision

All students said they would recommend AntibioGame® to their colleagues; 96 % liked the game, and 81 % said they would play the game for the purposes of revision ( Once students have validated their answers, they can read the patient's comment, which may be pleasant or sarcastic, depending on the accuracy of the answer. In the lower panel, the patient givens a sarcastic comment because the answer given was incorrect. Students can request hints by clicking on the "help" icon on the left of the desk.

Discussion

We present here AntibioGame®, a serious game for teaching medical students about the use of antibiotics in primary care. AntibioGame® is a case-based game in which students are asked to manage patients suffering from various infectious diseases and to help other healthcare professionals encountering difficulties with their own patients. The scenarios are realistic and cover the learning goals defined by a medical team based on an analysis of clinical practice guidelines. Gamification techniques and carton design were used in the development of this game, which can easily be updated by the educational team through the use of clinical case templates. The game was found to be of "good" quality. Medical students found AntibioGame® attractive, fun and appropriate for learning about antibiotics. They all said that they would recommend the game to their colleagues, and 81 % said that would use it for revision.

AntibioGame® design

We chose to design a case-based game, to get as close as possible to medical reality. However, other types of serious games exist [START_REF] Wang | A systematic review of serious games in training health care professionals[END_REF][START_REF] Gorbanev | A systematic review of serious games in medical education: quality of evidence and pedagogical strategy[END_REF]: (i) adventure games, in which students complete a series of quests [START_REF] Elderquest | Adventures in Geriatrics!, ElderQuest: Adventures in Geriatrics![END_REF]; (ii) quizzes, in which students answer series of questions [START_REF] Jirasevijinda | Jeopardy!: an innovative approach to teach psychosocial aspects of pediatrics[END_REF]; (iii) board or card games adapted from well-known existing games [START_REF]Bacteria Combat[END_REF]; (iv) puzzles in which students manipulate visual objects [START_REF]Superbugs[END_REF]. In the future, we aim to add a mixture of different types of games to AntibioGame®, to increase its chances of adoption by students. Other gamification elements exist but were not used here [START_REF] Maheu-Cadotte | Effectiveness of serious games and impact of design elements on engagement and educational outcomes in healthcare professionals and students: a systematic review and meta-analysis protocol[END_REF]: time pressure, difficulty adaptation, content unlocking, evolution of performance score, and multiplayer modes. In the future, we aim to add some of these gamification elements to increase student motivation and make the learning process more enjoyable [START_REF] Boendermaker | Exploring elements of fun to motivate youth to do cognitive Bias modification[END_REF]. Finally, we chose to use a 2D frozen cartoon design to reduce cost development. However, other types of design could make the game more realistic, attractive and fun, such as a 3D design with human characters [START_REF] Buttussi | Evaluation of a 3D serious game for advanced life support retraining[END_REF], or the adaptation of the interface according to student score [32,[START_REF] Brown | NightShift Simulation to Train Newly Qualified Doctors in Non-technical Skills: a Feasibility Study[END_REF]. In the future, we aim to Fig. 3. AntibioGame® Gameplay. At the end of the clinical case, students can see the score window including: (i) the Antibioman mascot, (ii) an amusing picture, depending on student achievement, (iii) the key points highlighted in yellow, (iv) a syringe that gradually fills up as the student's achievements increase, (v) the number of points acquired for each of the three scores and (vi) the learning goals. Ex3: "I love it!" Ex4: "When the characters make a pleasant comment (e.g. "you are a great doctor"), it makes me more confident" Ex5: "I wanted to do more clinical cases and I was disappointed that the evaluation ended" Ex6: "I am disappointed that we have to wait to play the game. I hope it will be ready before the end of the medical school" Learning, Relevance

Ex7: "When we learn about classic clinical cases, we don't always have the explanations. Here, I really liked reading the explanations" Ex8: "The hints encourage us to think actively rather than looking directly for the answers" Ex9: "With the game, I can learn without feeling that I am studying" Interaction, Challenge Ex10: "The scoring and the leader board motivate me to study" Fun Ex11: "Very good fun; I really like the game play" Ex12: "Great. The game play is fun and helps you to learn in another format" Reality Ex13: "I really like the phone calls because it makes me feel like a real doctor" Ex14: "There is a gap between what I learn from my books and reality. With the game, I felt like a junior doctor who has to treat the patient" Use for revision Ex15: "When will this game be available?" Ex16: "I will tell all my friends about this game" improve the design by displaying an interface adapted to student score (e.g. changes in the faces of the characters according to the accuracy of answers).

AntibioGame® evaluation

We chose to assess AntibioGame® with the MEEGA + method [START_REF] Petri | MEEGA+: A Method for the Evaluation of Educational Games for Computing Education[END_REF]. Other methods exist, but, as pointed out in a systematic literature review, they were developed in an ad-hoc manner, and do not provide an definition of the goal, measurements or data collection methods used [START_REF] Petri | How to Evaluate Educational Games: a Systematic Literature Review[END_REF]. They also differ considerably in terms of the quality factors assessed [START_REF] Petri | How to Evaluate Educational Games: a Systematic Literature Review[END_REF][START_REF] Akl | An educational game for teaching clinical practice guidelines to Internal Medicine residents: development, feasibility and acceptability[END_REF][START_REF] Duque | Learning while having fun: the use of video gaming to teach geriatric house calls to medical students[END_REF][START_REF] Vallejo | Evaluation of a novel Serious Game based assessment tool for patients with Alzheimer's disease[END_REF]. We chose the MEEGA + method [START_REF] Petri | MEEGA+: A Method for the Evaluation of Educational Games for Computing Education[END_REF] because it is appropriate for evaluations of educational games, it assesses both usability and player experience from the student's perspective, it uses an explicit scale assessing various quality factors, it provides a global score quality, and it is easy to use and free of charge [START_REF] Meega+ Team | MEEGA+ a Model for Evaluating Educational Games -GQS -Software Quality Group[END_REF]. However, according to the four-level model of training evaluation developed by Kirkpatrick et al. [START_REF] Kirkpatrick | Evaluating Training Programs: the Four Levels[END_REF], we assessed only the "reaction" level (i.e. the degree to which students find the game beneficial, engaging and relevant to their jobs). Further evaluations are required to assess the other three levels: "learning", "behavior", and "results". To this end, we plan to introduce AntibioGame® into the training program for medical students, and to assess its impact on student learning [START_REF] Buttussi | Evaluation of a 3D serious game for advanced life support retraining[END_REF][START_REF] Telner | Game-based versus traditional case-based learning: comparing effectiveness in stroke continuing medical education[END_REF].

Comparison with other teaching methods

We chose to use an approach aiming at "learning through the game" [START_REF] Bergeron | Developing Serious Games[END_REF]. However, other teaching methods exist. Conventional lecturebased teaching is the most widespread teaching method. It allows students to learn theoretical medical concepts, but also to benefit from the clinical experience of senior doctors. However, this approach may suffer from a lack of practical training, and of attractiveness for new generations of students at ease with technology. MOOCs [START_REF] Rocha-Pereira | Educating healthcare professionals in antimicrobial stewardship: can online-learning solutions help?[END_REF][START_REF] Sneddon | Development and impact of a massive open online course (MOOC) for antimicrobial stewardship[END_REF] are lecture-based resources available online that allow students to learn remotely, but do not provide practical training. Several MOOCs relating to antibiotic therapy are available for free [START_REF] Sneddon | Development and impact of a massive open online course (MOOC) for antimicrobial stewardship[END_REF][START_REF]Massive Online Open Course (MOOC) on Antimicrobial Stewardship[END_REF]. Manikin-based simulations [START_REF] Lateef | Simulation-based learning: just like the real thing[END_REF][START_REF] Liaw | Comparison of virtual patient simulation with mannequin-based simulation for improving clinical performances in assessing and managing clinical deterioration: randomized controlled trial[END_REF] provide students with the opportunity to practice technical gestures, but are difficult to organize. Virtual reality techniques [START_REF] Liaw | Comparison of virtual patient simulation with mannequin-based simulation for improving clinical performances in assessing and managing clinical deterioration: randomized controlled trial[END_REF][START_REF] Li | Application of virtual reality technology in clinical medicine[END_REF][START_REF] Youngblood | Design, development, and evaluation of an online virtual emergency department for training trauma teams[END_REF] provide practical training in which the students are immersed in a real world in which they can interact with characters and objects presented in a 3D virtual environment, but such techniques are expensive and require complex software [START_REF] Samadbeik | The applications of virtual reality technology in medical groups teaching[END_REF]. A few courses based on virtual techniques have been developed for antibiotic treatment [START_REF] Pan | The responses of medical general practitioners to unreasonable patient demand for antibiotics -a study of medical ethics using immersive virtual reality[END_REF]. We decided to develop a serious game to overcome these limitations: this game exposes students to real clinical situations, it is low-cost (estimated cost: 6000 to 10,000 euros), and it is a flexible teaching method that can be associated with other teaching methods.

Expected potential impact on student learning

Limited evidence is available concerning the efficacy of serious games for promoting knowledge retention [START_REF] Akl | Educational Games for Health Professionals[END_REF][START_REF] Bhoopathi | Educational Games for Mental Health Professionals[END_REF][START_REF] Blakely | Educational gaming in the health sciences: systematic review[END_REF][START_REF] Akl | The effect of educational games on medical students' learning outcomes: a systematic review: BEME Guide No 14[END_REF], but we expect AntibioGame® to have a positive impact on student learning. Systematic reviews and meta-analyses [START_REF] Akl | Educational Games for Health Professionals[END_REF][START_REF] Bhoopathi | Educational Games for Mental Health Professionals[END_REF][START_REF] Blakely | Educational gaming in the health sciences: systematic review[END_REF][START_REF] Akl | The effect of educational games on medical students' learning outcomes: a systematic review: BEME Guide No 14[END_REF] have concluded that serious games are a viable teaching strategy, but their impact in terms of efficacy has yet to be demonstrated. However, these conclusions are based on only a few randomized controlled trials, because of the limited number of available trials with a methodology of sufficiently high quality for inclusion in such analyses. A few trials have reported that serious games are as effective as traditional methods for promoting student knowledge [START_REF] Dankbaar | Comparative effectiveness of a serious game and an emodule to support patient safety knowledge and awareness[END_REF][START_REF] Tubelo | Serious game is an effective learning method for primary health care education of medical students: a randomized controlled trial[END_REF], whereas others have reported serious games to be more effective [START_REF] Boeker | Game-based e-learning is more effective than a conventional instructional method: a randomized controlled trial with third-year medical students[END_REF]. Further research is required to determine the impact of serious games on the acquisition of knowledge by students. We show here that serious games have the potential to increase enjoyment and motivation in the student's learning process. Students are also encouraged to interact with each other, challenging each other, to obtain higher scores through the gamification elements, such as leader board and awards. We hypothesize that motivated students excited by the game are more likely to spend longer revising, thereby increasing their medical knowledge. In the future, we will perform a randomized control trial to investigate the impact of AntibioGame® on learning outcomes.

Expected potential impacts on antibiotic resistance

We propose a serious game for improving the training of medical doctors in antibiotic use. We expect to see an impact on the quality of antibiotic prescriptions in primary care, and, consequently, a decrease in antimicrobial resistance. Antimicrobial resistance is a worrying phenomenon that could lead to critical situations in which no effective antibiotic is available for the treatment of common infectious diseases [START_REF] Harbarth | Antimicrobial resistance determinants and future control[END_REF][START_REF] Carlet | Save antibiotics: a call for action of the world alliance against antibiotic resistance (WAAAR)[END_REF]. It is becoming urgent to take action against this phenomenon. However, no single action in isolation would be sufficient [START_REF] Arnold | Interventions to Improve Antibiotic Prescribing Practices in Ambulatory Care, Cochrane Database Syst Rev[END_REF]. The teaching action described here should be incorporated into multifaceted interventions at different levels [START_REF] Arnold | Interventions to Improve Antibiotic Prescribing Practices in Ambulatory Care, Cochrane Database Syst Rev[END_REF][START_REF] Davey | Interventions to Improve Antibiotic Prescribing Practices for Hospital Inpatients[END_REF][START_REF] Krishnakumar | What rationale do GPs use to choose a particular antibiotic for a specific clinical situation?[END_REF]. The WHO has proposed a global action plan with five types of intervention [START_REF]WHO, Global Action Plan on AMR[END_REF]: increasing awareness and understanding of antimicrobial resistance (e.g. through educational programs); improving knowledge of antibiotics (e.g. through surveillance and research programs); decreasing the incidence of infections (e.g. through lifestyle habits); optimizing antibiotic use [START_REF] Barlam | Implementing an antibiotic stewardship program: guidelines by the infectious diseases society of america and the society for healthcare epidemiology of america[END_REF] (e.g. through clinical decision support systems [START_REF] Tsopra | Comparison of two kinds of interface, based on guided navigation or usability principles, for improving the adoption of computerized decision support systems: application to the prescription of antibiotics[END_REF][START_REF] Tsopra | Using preference learning for detecting inconsistencies in clinical practice guidelines: methods and application to antibiotherapy[END_REF][START_REF] Tsopra | Helping GPs to extrapolate guideline recommendations to patients for whom there are no explicit recommendations, through the visualization of drug properties. The example of AntibioHelp® in bacterial diseases[END_REF]); and supporting economic investment in the development of new therapies or diagnostic tools. This multifaceted intervention should target not only doctors, but also other healthcare professionals and the general population. Thus, although serious games are a promising tool for improving medical training in antibiotics, other actions are required to achieve a significant impact on antimicrobial resistance.

Fig. 1 .

 1 Fig. 1. AntibioGame® interface. Here, a little girl, "Candy", has come to consult her GP. Various interactive and meaningful icons are displayed through the interface.

  prescriptions Secondary scenarios Call from a pharmacist to check antibiotic dose Call from a nurse concerning antibiotic side effects x x Call from a nurse concerning signs of severity for an infection x x x x Call from a nurse concerning paraclinical examinations to be performed to monitor antibiotic dose Call from a junior doctor concerning the prescription of an Patient consultation in the GP's office x Patient consultation for a second time for the same reason x x Review of paraclinical examinations performed on patient Review of drug prescriptions Call from a pharmacist to check antibiotic dose x Call from a nurse concerning antibiotic side effects x x Call from a nurse concerning signs of severity for an infection Call from a nurse concerning paraclinical examinations to be performed to monitor antibiotic dose x Call from a junior doctor concerning the prescription of an antibiotic Call from a microbiologist for pathogen identification

Fig. 2 .

 2 Fig. 2. AntibioGame® gameplay. At the beginning of the game, the patient record is displayed on the left. The patient asks the medical student a question, and the student responds by selecting one or more of the responses displayed (upper panel). Once students have validated their answers, they can read the patient's comment, which may be pleasant or sarcastic, depending on the accuracy of the answer. In the lower panel, the patient givens a sarcastic comment because the answer given was incorrect. Students can request hints by clicking on the "help" icon on the left of the desk.

Fig. 4 .

 4 Fig. 4. Usability and playability of AntibioGame®. Graphical results. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

Table 2

 2 List of gamification techniques used in AntibioGame® design.

	Gamification techniques	Effects on AntibioGame® design	Anticipated benefits for medical students
	used [25]
			Learning Challenge Confidence Ease of	Attractiveness Fun
				use
	Challenge/Quests	Challenges are proposed in the form of various clinical cases that must be solved	x	x	x	x
	Mascot	A mascot, "Antibioman", is symbolized by a superhero appearing throughout				x	x
		the game
	Avatar with badges	An avatar is displayed in the student's profile, associated with badges		x		x	x
		symbolizing the student's achievements
	Hints	Hints are provided on request when the student gives an incorrect answer to a	x	x		x
		question
	Feedback	Medical knowledge is updated on request at the end of each question	x	x		x
	Rewards

Table 5 ,

 5 . All the students said they would like to have training sessions with the game; 79 % said these training sessions should be remote and 78 % said they should include debriefing by a teacher.

Table 4

 4 Demographic characteristics of medical students.

	Characteristics	Percentage (number of
		students)
	Sex
	Female	56 % (32/57)
	Male	44 % (25/57)
	Age (mean)	23 years
	Location of the university of origin of the
	student
	France	96 % (55/57)
	Germany	2 % (1/57)
	Romania	2 % (1/57)
	School year
	2 nd year completed	14 % (8/57)
	3 rd year completed	21 % (12/57)
	4 th year completed	25 % (14/57)
	5 th year completed	33 % (19/57)
	6 th year completed	7 % (4/57)
	Frequency with which the student plays
	video games
	Never	28 % (16/57)
	Rarely/sometimes	37 % (21/57)
	At least once a month	11 % (6/57)
	At least once a week	18 % (10/57)
	Every day	7 % (4/57)

Table 5

 5 Extracts from the students' comments (Ex: Extract).

			Students' comments
	Usability	Design	Ex1: "Beautiful design"
		Use	Ex2: "It is intuitive and you can rapidly understand how it works"
	Player experience	Satisfaction, Confidence

Acknowledgments

We thank all the medical students for taking the time to participate in this study.

We thank Karny BEDIKIAN, Françoise JAUREGUY, Dr Warda KHAMIS, Prof. Bertrand DEGOS and Prof. Jean-Ralph ZAHAR, for encouraging medical students to participate in this study.

We thank Dr Hugues CORDEL and Thomas PLANQUES for their advice.

We thank Bernard VIRGINIE for his technical support. We thank Giani PETRI for his advice regarding the use of the MEEGA + scale.

Authors' contributions

Summary points

• Antimicrobial resistance is a worrying phenomenon • Serious games could help to improve antibiotic prescription and, thus, to decrease antimicrobial resistance • There was no serious game for teaching students about anti- biotics in primary care

• AntibioGame® is a case-based game for teaching antibiotics to medical students

• AntibioGame® has the potential to make the learning process more fun, interactive and enjoyable for students • AntibioGame® is a promising tool that could easily be in- corporated into multifaceted programs for medical students R. Tsopra, et al. International Journal of Medical Informatics 136 (2020) 104074

Declaration of Competing Interest

None.

Appendix A. Supplementary data

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.ijmedinf.2020. 104074.


W303-1A KNR4 SLT2 448 HM13 knr4D SLT2 44 JF1366 rlm1D SLT2 434 W303Dslt2 slt2D < 1
Assay of Rlm1 activity : Use of a reporter plasmid containing a lexA-RLM1DN fusion and a lacZ reporter gene with lexA binding sites in the promoter.

Rom2/ GEF

SBF

Rho1/

Rom2 Rho1

Part 2: Knr4 is involved in Slt2-cell wall integrity pathway

Rlm1

Cell wall remodeling genes G/S transition ; bud emergence

Bck1

Pkc1

Mkk1/2

Mid2

Cell wall

Wsc1 Wsc2 Wsc3

membrane Knr4 Knr4 Hsp90 Hsp90 (Martin-Yken, Mol Microbiol, 49, 23, 2003;Millson, Eukayot.cell, 4, 849, 2005)

Mpk1/Slt2

T-OP

Y-OP

Mpk1/Slt2

HO-Y HO-T Three strategies

Synthetic Lethal

Two Hybrid TAP-Tag

• genetic • functional • not temporal • not spatial • not [prot] • no false +/- • physical • not temporal • spatial • not [prot]
• some false +/-

• physical • functional • temporal • spatial • [protein] • lot false +
The 'most probable interaction maps'

✓Membrane

  single gene, not essential ✓ specific to fungal kingdom ❖ At the gene level ➢ Hypersensitive to cell wall drugs ➢ Hypersensitive to caspofungin and cercosporamide ➢ Stop growth > 38°C as with small buds, osmotically remediable ➢ 50% reduction of cell wall b-1,3 glucans in vegetative cells ➢ Synthetic lethal with pkc1D, slt2D, rlm1D……. ▪ main phenotypes of knr4D mutant ▪ main phenotypes of KNR4 overexpression ➢ supress several cwh mutants ➢ repression CHS1, CHS2, CHS3 is involved in Mpk1-cell wall integrity pathwayRlm1Cell wall remodeling genes G1/S transition, bud emergence is required for the heat shock activation Mpk1/Slt2Part 2: Knr4 is involved in Mpk1-cell wall integrity pathway

➢Synthetic interactions with knr4D: 82 Lesage et al., Genetics, 167, 35-49, 2004) Cell wall 33%

Cell Others/Unknown (Ymr262c, Rpc40) (From Uetz et al.,Nature,403, 2000;Ito et al., PNAS, 98, 2001;Dagkessamanskaia et al. FEMS Lett, 2001;Martin-Yken et al., Mol. Microbiol., 2003;Basmaji et al., 2006) Bni1 Mid2

Jnm1

Cla4 Bni4 E,K,R,G,Q,S;I,L,V,W,F,Y ) -relatively unstable protein /high turnover (From A.L.Fink. Natively Unfolded proteins, Curr. Op. Struct.Biol., 15, 35-41, 2005) Hypothesis:

Gvp36

Unfolded /unstructured proteins have lots of partners, are often implicated in regulatory aspect and get their folding upon binding to their partners or substrates Knr4 may be such a protein, since :


A Structural Approach to Discover an

Achilles'heel of fungi : the case of Knr4/Smi1

Hélène Martin-Yken 1,2,3 , Didier Zerbib 1,2,3, , Sylviane Julien

Background Disordered domains of Knr4

Intrinsically disordered proteins (IDPs) are involved in numerous essential biological processes. Their conformational flexibility gives them the ability to be involved in one-to-many binding (a single disordered domain is able to bind several structurally diverse partners). Highly connected proteins located at nodes in interactions networks or "Hubs" are significantly enriched in disordered domains which allow them to fulfil their multiple interactions.

4,5 , Lionel Mourey 4,5 , Laurent Maveyraud 4,5 , and Jean-Marie François 1,2,3 . 1-Université de Toulouse, INSA, UPS, INP, LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France, 2-INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France, 3-CNRS, UMR5504, F-31400 Toulouse, France, 4-Institut de Pharmacologie et de Biologie Structurale (IPBS), CNRS, 205 route de Narbonne, BP 64182, Toulouse, F-31077, France 5-Université de Toulouse, Université Paul Sabatier, IPBS, Toulouse, F-31077, France

Conclusions and outlook

3D structure of fungal Knr4 is unknown to date. In silico, biophysical and biochemical methods have shown that it contains large disordered Nterminal (1-80) and C-terminal (341-505) parts and a structured and globular central core, which holds the essential of the biological functions of the protein 2 . The disordered N and C parts control the interactions of the protein with its partners.

We have found crystallization conditions allowing the identification of secondary structure elements of S. cerevisiae Knr4 central core domain 3 . Recently, we obtained new Knr4 crystals diffracting at 2.5 Å, a resolution which should allow us to rapidly decipher the 3D structure of the protein core of this unique fungal IDP. Our goal is to finally decipher the global 3D structure of the complete protein, in complex with relevant essential proteins partners, in order to later define targetable regions for complex formation inhibition.

We have expressed in E. coli , purified and crystallized this core domain, as well as a modified Selenomethionine containing corresponding protein 3 .

Knr4/Smi1 : a S. cerevisiae hub protein

-functions in signaling, gene transcription, cell cycle progression and morphogenesis 1 ;

-knr4D : hypersensitive to stress conditions (high q, SDS, caffeine, CFW, …); -multiple physical interacting partners; -over 280 synthetic lethal or sick interactions.

Crystals First structural elements solved


Hélène Martin-Yken

Cécile Formosa

Marion Schiavone

Jean Marie François

Etienne Dague

Stress, Drug resistance and Adhesion: a closer look at the dark side of the wall

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Stress, Drug resistance and Adhesion:

a closer look at the dark side of the wall. Stress conditions and antifungal drugs induce significant changes in the cell wall composition of yeasts and fungi. They cause modifications of the cell wall molecular architecture, including nature, repartition and attachment of cell wall proteins to the cell surface. Atomic Force Microscopy (AFM) is a powerful tool for studying the morphology, nanomechanical and adhesive properties of live microorganisms under physiological conditions. We imaged and measured the biophysical consequences of various stresses on both S. cerevisiae and C. albicans cell morphology at the nanoscale, focusing on changes in cell surface aspect and characteristics: roughness, elasticity, and adhesive properties.

AFM allowed us to unravel the morphologic effect on yeast cells of Heat Shock, Osmotic Shock, exposure to toxins and drugs. Moreover, using Single Molecule Force Spectroscopy (SMFS) we can now explore the organization of adhesins, map them on the cell surface and quantify their adhesion forces. Altogether, our studies establish the great interest of AFM to explore molecular mechanisms occurring on the cell surface of live fungal cells.

Conclusions and outlook

Measuring and mapping Cellular Adhesion

Adhesion force

Maps of 1µm 2 , corresponding histograms representing the adhesion force repartition, and a few representative force curves.

Molecular Biology tools and AFM established the contribution of previously uncharacterized PGA proteins to C. albicans adhesion mechanism

Caspofungin induces a deep cell wall remodeling, evidenced by nanomechanichal properties and dramatic chitin increase 2 . A low dose of Caspofungin (0.5 x MIC) results in adhesins expression on the cell surface

Nanoscale effects of Caspofungin on Yeast cell wall

Elasticity maps (z range = 0.5 MPa)

Adhesion Maps

Heat Shock

AFM deflection images of surface topology of living yeast cell at 30°C (unstressed, A, A') or exposed to heat shock for 1 h at 42°C (B, B').

BS: Bud scar, CS: circular structure.

Cell's relief (= 3D Image)

HS induces formation at the cell surface of a circular structure that takes its origin at a single punctuate source and propagates in a concentric manner to reach a diameter of 2-3 μm 1 .

Our results suggest that this singular morphological event occurring at the cell surface is due to a dysfunction in the budding machinery and that this phenomenon is controlled by the CWI pathway.

1.

  Pillet et al. Uncovering by A F M of an original circular structure at the yeast cell surface in response to heat shock. BMC Biology 2014, 12:6 2. Formosa C. et al., (2013), Nanoscale effects of Caspofungin against two yeast species; S. cerevisiae and C. albicans, AAC, 57, 3498. 3. Cabral V. et al., (2015),Targeted changes of the cell wall proteome influence C. albicans ability to form single-and multi-strain biofilms. PloS Pathog. 2014 Dec 11;10(12).

Hélène Martin-Yken, Cécile Formosa, Marion Schiavone, Jean Marie François and Etienne Dague. 1-Université de Toulouse; INSA, UPS, INP; LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France, 2-INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France, 3-CNRS, UMR5504, F-31400 Toulouse, France


Mireille Babineau
email: mireillebbineau@gmail.com

Alex A De Carvalho

John Trueswell

Anne Christophe

Familiar words can serve as a semantic seed for syntactic bootstrapping

Keywords: Word learning, Language development, Language processing, Syntactic bootstrapping, Eye movements

Familiar words can serve as a semantic seed for syntactic bootstrapping

Research on language development has provided abundant evidence on how children learn the meaning of new words by relying on the other words in the sentence (the syntactic context), a mechanism called syntactic bootstrapping (e.g., [START_REF] Arunachalam | Preschoolers' Acquisition of Novel Verbs in the Double Object Dative[END_REF][START_REF] Bernal | Syntax Constrains the Acquisition of Verb Meaning[END_REF][START_REF] Fisher | Syntactic bootstrapping[END_REF][START_REF] Gillette | Human simulations of vocabulary learning[END_REF][START_REF] Gleitman | The Structural Sources of Verb Meanings[END_REF]Landau & Gleitman, 1985). For instance, when hearing "It's a pratch!" 18-month-olds can infer that pratch refers to an object, while upon hearing "It's pratching!," they can infer that it refers to an action (de Carvalho, [START_REF] De Carvalho | Prosody and Function Words Cue the Acquisition of Word Meanings in 18-Month-Old Infants[END_REF][START_REF] He | Verb Learning in 14-and 18-Month-Old English-Learning Infants[END_REF]. Syntactic contexts are often revealed by functional elements, such as function words and morphemes (e.g., "the", "a", "she", "he", "-ing"), which are so frequent that infants store and recognize them before the age of one (e.g., in English: Shi et al., 2006;in French: Shi & Lepage, 2008). Crucially, function words can be exploited during syntactic and semantic acquisition, since they provide useful information about the cooccurring content words, first enabling infants to assign words that they do not know yet to grammatical categories (e.g., Babineau, Shi & Christophe, under review;[START_REF] Höhle | Functional elements in infants' speech processing: The role of determiners in the syntactic categorization of lexical elements[END_REF][START_REF] Shi | Syntactic Categorization in French-Learning Infants[END_REF] and then to infer their probable meanings (e.g., [START_REF] Bernal | Syntax Constrains the Acquisition of Verb Meaning[END_REF]de Carvalho et al., 2019a;[START_REF] He | Verb Learning in 14-and 18-Month-Old English-Learning Infants[END_REF]. That is, young children expect a novel word following determiners to be a noun (i.e. mapping it to an object), and a novel word following pronouns to be a verb (i.e. mapping it to an action). It is clear that children can make use of the syntactic contexts that they already know to speed up their acquisition of vocabulary very early in their development, but it is less clear how they have gotten to this point.

The question of how children learned which syntactic contexts correspond to which semantic features is still unanswered. Recent findings about infants' abilities can give us an insight on the learning mechanism at play. On the one hand, infants are known to have the ability to track statistical regularities, which should help them to learn some aspects of the grammar of their native language, as they can do after a brief exposure to an artificial language (e.g. between the age of 12-18 months [START_REF] Gerken | Infants can use distributional cues to form syntactic categories[END_REF][START_REF] Gòmez | Artificial grammar learning by one-year-olds leads to specific and abstract knowledge[END_REF]. Distributional patterns are present in natural languages, i.e. specific functional elements tend to co-occur with content words from specific word classes. For instance, articles tend to precede nouns while personal pronouns tend to precede verbs in languages such as English and

French. Attempts at modeling the distributional learning of syntactic categories via the cooccurrences of content words with specific function words have consequently been successful (e.g., [START_REF] Chemla | Categorizing words using "frequent frames": What cross-linguistic analyses reveal about distributional acquisition strategies[END_REF]Mintz, Newport, & Bever, 2002;[START_REF] Mintz | Frequent frames as a cue for grammatical categories in child directed speech[END_REF][START_REF] Weisleder | What's in the input? Frequent frames in childdirected speech offer distributional cues to grammatical categories in Spanish and English[END_REF]. On the other hand, rudimentary knowledge of the meaning of words develops early during infancy: preverbal infants have managed to learn something about the meaning of frequent and concrete words (e.g. "banana", "feet"; [START_REF] Bergelson | At 6 -9 months, human infants know the meanings of many common nouns[END_REF][START_REF] Tincoff | Some beginnings of word comprehension in 6-montholds[END_REF], possibly through their multimodal daily experience, in addition to noticing the semantic relatedness between those words [START_REF] Bergelson | Nature and origins of the lexicon in 6-mo-olds[END_REF]. By the end of their first year, they even group concepts into basic semantic categories (e.g., object, action, agent;Carey, 2009). Given these results in the domain of early syntactic and semantic acquisition, and the possible synergies between these two during language development, researchers that have modeled distributional learning of categories have proposed that children may be using their knowledge of a handful of word meanings as a seed for future syntactic categories (e.g., [START_REF] Christophe | Bootstrapping the syntactic bootstrapper[END_REF][START_REF] Gutman | Bootstrapping the Syntactic Bootstrapper: Probabilistic Labeling of Prosodic Phrases[END_REF]; see also [START_REF] Christodoulopoulos | An incremental model of syntactic bootstrapping[END_REF][START_REF] Connor | Starting from scratch in semantic role labeling: Early indirect supervision[END_REF][START_REF] Connor | Starting from Scratch in Semantic Role Labeling[END_REF][START_REF] Fisher | Language acquisition[END_REF][START_REF] Gleitman | Hard words[END_REF]. Based on the semantic seed hypothesis, young children would track the syntactic contexts in which known familiar words occur through a distributional analysis (e.g., "the car"; "the ball"), then use this information to infer some semantic properties of novel words that they encounter in the same syntactic contexts: "the dax" -> "dax" shares some characteristics with "car" and "ball" (and possibly refers to an object). This mechanism would enable the creation of syntactic categories, which in turn would guide children's interpretation of novel word meanings.

The present study tested for the first time whether young children can indeed learn about syntactic categories by paying attention to the contexts in which familiar words appear. To do so, we taught children a novel function word embedded in sentences containing known content words (the seed). A new function word, "ko", was introduced as a novel syntactic context during a short familiarization phase (i.e. a 5-minute training video). The goal was to assess whether children can use their ability to compute distributional regularities to track the cooccurrence of this new function word with a specific type of familiar words (either nouns or verbs, in a between-participants design), and then use this information when encountering novel words co-occurring with the newly-learned function word. To test this, we relied on an experimental design recently developed by [START_REF] De Carvalho | Studying the Real-Time Interpretation of Novel Noun and Verb Meanings in Young Children[END_REF], who showed that 3-to-4-year-olds can use known function words in realtime to predict the syntactic category of novel content words. In this task participants saw two videos side-by-side on a TV-screen: one showing a person performing a novel action, and the other a person passively holding a novel object. At the same time, participants heard a novel word preceded either by a determiner (e.g., Regarde! Une dase! -"Look! A dase!") or a pronoun (e.g., Regarde! Elle dase! -"Look! She's dasing!"). Three-to-4-year-olds exploited function words online to categorize novel words and infer their meanings: they looked more to the novel action in the Verb condition, while participants in the Noun condition looked more to the novel object.

In the current experiment, we inquired whether 3-4 year-olds could use what they learned of the novel function word "ko" to narrow down the probable meaning of a novel content word, e.g. dase in ko dase, referring either to a novel object (if "ko" was heard in a noun context) or a novel action (if "ko" was heard in a verb context). We hypothesized that children's training condition would influence their implicit visual attention during the test trials. That is, children in the Verb condition would learn to attend to actions after hearing the novel word (e.g. "ko", such as while children in the Noun condition would attend to objects.

Hence, when listening to a test sentence in which a novel content word (e.g. dase) is preceded by the novel function word (e.g., Regarde! Ko dase! "Look! Ko dase"), participants who heard "ko" before verbs (Verb condition) should look more to the novel action, while participants who heard "ko" before nouns (Noun condition) should look more to the novel object.

Moreover, we recorded participants' pointing responses, as a measure of their explicit guesses regarding the meaning of the novel words. We also tested adult university students as a control group.

Method

The method, analyses and criteria for exclusion of participants were pre-registered on the OSF (Open Science Framework) database before running the experiment (the formal preregistration can be accessed with the following link: https://osf.io/6s9eh/?view_only=c65b329b9b2548309114548c2b87b8d7). The materials, collected data, and data analyses are freely available to readers through the following link: https://osf.io/79j53/?view_only=0197429abd4e4bd5b451bd127911f642.

Participants

Preschoolers. Sixty 3-to 4-year-old monolingual French-speaking children (3;3 to 4;4, M age = 3;8, 33 females) participated to the study (30 in each condition). A total of 25 children were tested at the laboratory and the remaining 35 were tested in two public preschools in Paris.

Parents signed an informed consent form. The study was approved by the local ethics committee (CER Paris Descartes), as well as by the school boards.

An additional 27 children were tested, but not included in the final analysis because they failed to comply during the experiment, e.g. fussing, not pointing or taking off the headphones [START_REF] Fisher | Language acquisition[END_REF], because they were bilingual (6), or because of technical problems (4). As stated in the pre-registration, we removed from the statistical analyses test trials with more than 25% missing data frames. If a participant had more than two excluded trials (out of 4), she was excluded from eye-tracking data analysis (eight children). Four additional participants had corrupted eye-tracking files. Hence, a total of 12 children were excluded from the eye-tracking analyses, resulting in 48 children remaining for those analyses. The preregistered number of participants sufficient for the eye-tracking analyses was based on de Carvalho et al. (2019), which found a medium-size effect with a final sample of 48 children. Note that in our study, pointing responses were kept for subjects with low-quality/corrupted eye-tracking data. In fact, in order to complete the experiment and to be included in the final sample, children had to be engaged in the task and point toward one of the still videos on every trial when the experimenter prompted them to do so. Hence, there are no pointing data missing in the final sample of 60 children.

Adults. Forty-nine native French-speaking adults (18 to 34 years of age, M age = 23; 28 females) participated in the control study (25 in the noun condition, 24 in the verb condition).

They were tested in the laboratory, where they signed an informed consent form.

Five additional participants were tested, but not included in the final analysis. Three were excluded based on their poor eye-tracking data (see the description of the criteria above), and two participants were not included in the final analysis because they had seen the novel animals or heard about the training videos before the experiment.

Stimuli and design

In a between-subject design, participants were assigned to one of two conditions (Noun vs Verb condition). In the first part of the experiment, they watched a training video showing a female native French speaker (last author) using child-friendly speech as she acted out scenarios with stuffed animals and toys. We created two versions of the training video (see Figure 1). In both videos, the same script was used with the exception that articles un/une/le/la (feminine and masculine forms of "a"/"the") were replaced by "ko" in the video assigned to the Noun Condition ("e.g., "ko pretty turtle", "ko pig"), while pronouns elle/il ("she"/ "he") were replaced by "ko" in the video assigned to the Verb Condition (e.g. "ko will play", "ko rolls"; see Figure 1). The new function word "ko" was presented 60 times in total in each of the videos, co-occurring with 14 different familiar nouns in the Noun condition (e.g. biberon "bottle", chat "cat", cochon "pig", livre "book") and with 17 different familiar verbs in the Verb condition (e.g. donner "to give", jouer "to play", regarder "to look", tomber "to fall").

To facilitate the segmentation of the new function word and the recognition of the familiar cooccurring words, syntactic contexts varied for both noun and verb contexts. Specifically, to avoid perceiving the Article + N sequence as a whole new word (e.g., kochat '"kocat" as a word), both Article+N and Article+Adj+N structures were used in the Noun condition (e.g. ko joli chat 'ko pretty cat') for 10 of the 14 familiar nouns. For the same reason, different verb tenses were used for 14 of the 17 familiar verbs, with 11 verbs appearing in two verb tenses (either present and past or present and future), and 3 appearing in the present, future, and past tense (e.g. danser 'to dance' appeared in ko va danser 'ko will dance', ko danse 'ko dances', ko a dansé 'ko danced'). The full script of the videos along with summary tables are available on the OSF page, as well as the entire training videos. In both conditions, the novel function word "ko" shared similar acoustic properties as the replaced real function words. For instance, although "ko" tended to be shorter in duration than real function words (both articles and pronouns), it was not significantly so (p >.1). Note that the short duration of "ko" might be due to the fact that the closure before [k] was not counted as part of the word since it was not possible to distinguish it from a pause. The detailed results of the speech analysis done on half of the training videos can be found in the additional material section of the OSF.

In the second part of the experiment (i.e., the test phase), participants were tested with two videos displayed side-by-side on a TV-screen: one video showing an agent performing an intransitive action, and the other video showing an agent passively holding an object (the same videos used in de Carvalho et al., 2019, but with new sound tracks recorded by the last author).

A total of six trials were presented to each participant: two practice trials followed by four test trials. The practice trials included two pairs of videos referring to familiar words (une voiture "a car" vs elle dort "she is sleeping"; un ballon "a ball" vs il mange "he is eating"). Every participant had one practice trial in which the target was a familiar verb and one in which the target was a familiar noun. The new function word "ko" replaced the article in the Noun condition and the pronoun in the Verb condition (e.g. a participant in the Noun condition might hear ko voiture "ko car" for the first practice trial and il mange "he is eating" for the second one; while a participant in the Verb condition might hear ko dort "ko is sleeping" for the first practice trial and un ballon "a ball" for the second one). The practice trials not only aimed at familiarizing participants with the structure of the test phase (e.g. two videos would be presented side-by-side and only one of them would be the target), but also to extend the teaching period of the novel function word by presenting simple visual scenes with restricted mappings. The test trials included four pairs of videos referring to novel words (i.e., dase, nuve, rane, fome). Note that a third-person singular verb is unmarked in French (e.g., elle marche "she is walking"), as is a singular noun (e.g., une marche "a step") making it possible to create ambiguous novel words that could be either a noun or a verb.

All trials followed the same structure (see Figure 2), aimed at familiarizing participants with the content of the videos, and to reduce their novelty and potential biases. Each of the two videos were presented alone on each side of a TV-screen during an inspection period. Note that the practice trials contained an informative audio prompt such as "Oh regarde! Il mange. Tu as vu ça?" -"Oh look! He's eating. Did you see that?" during the inspection period, whereas the test trials contained uninformative audio prompts such as "Oh regarde! Tu as vu ça?" -"Oh look! Did you see that?". Then, during the contrast period, both videos were presented side-by-side during 10 sec along with an uninformative audio prompt (e.g. Et voilà les deux! "And here's the two of them"). Subsequently, a fixation point was presented during 6 sec along with an informative audio prompt in which the target was named once (e.g., Oh regarde! Ko dase! "Oh look! Ko dase!"). The two videos finally reappeared side-by-side during 10 sec together with two more repetitions of the target (e.g., Tu vois? Ko dase! Wow regarde! Ko dase. "Do you see that? Ko dase! Wow look! Ko dase.") meant to attract the participant's attention toward one of the videos. The two videos would freeze after 10 sec, indicating to the participant that she needed to point towards the video that the woman referred to. After each trial, a picture of a baby (along with a sound of laughter) would appear in the center of the screen (5 sec). Note that the test phase with novel content words presented the exact same stimuli (videos and sentences) to all participants, in both conditions (Noun and Verb). Hence, the only difference between these two conditions was the training phase and the practice trials.

Apparatus and Procedure

Participants were tested individually, with children being tested either in a soundattenuated booth in the laboratory (with their caregiver sitting behind them) or in a quiet room at their preschool, and adults in the control group being tested at the laboratory. Participants sat in front of a 27-in TV-screen positioned approximately 70 cm away from them. Their eyegaze towards the videos was recorded by an Eyelink-1000, with a time-sample collected every 2 ms. A 5-point calibration procedure was used. Children were given verbal instructions before starting the task. They were told that they would need to wear headphones so that they could hear a woman tell them a story. After the stories, they would watch videos and the woman would tell them where to look. Since the experimenter would not have headphones, she would not know which video the woman talked about. Hence, children were asked to point to the correct video (left vs right) to let the experimenter know what the woman talked about. The experimenter reminded children to point during the first practice trial. She gave no feedback about whether their answer was correct or not (and she did not herself know which answer was correct). Adults were told that they were participating in an experiment intended for children, and they received the same instructions as the children. The first fourteen adults tested were not asked to point after the end of each trial (only their eye-gaze was recorded). For the remaining participants, the experimenter gathered pointing responses after each trial, just as for children. At the end of the experiment, adult participants answered questions regarding their degree of awareness and knowledge of the novel function word's usage.

The experiment was composed of two phases: a familiarization phase in which a training video was presented (either the version for the Noun condition or the one for Verb condition), and a test phase including two practice trials with familiar words, and four test trials with novel words. During the test phase, participants needed to point toward the target video in order to proceed to the next trial. The experimenter recorded participants' choice by pressing a key on the keyboard of the computer.

Data processing and analyses

We report our three pre-registered analyses looking at (1) the time-course of participants' eye-gaze, reflecting their real-time interpretation of test sentences, (2) the looking times averaged over the entire duration of the test trials, reflecting their overall interpretation of test sentences and (3) the pointing responses, reflecting participants' final interpretation of the target novel words. Additional analyses which were not preregistered or which look at various subsets of the data (such as practice trials) can be found on OSF following this link: https://osf.io/79j53/?view_only=0197429abd4e4bd5b451bd127911f642. We used the package eyetrackingR (Dink & Ferguson, 2016) to conduct the analyses, and the ggplot2 package (Wickham, 2009) to plot the eye-gaze data and the pointing responses. We down-sampled the eye-tracking data (initially collected every 2 ms) by averaging to one sample every 20 ms. We removed from the statistical analyses test trials with more than 25% missing data frames, i.e. 30 trials for preschoolers (out of 192) and 27 trials for adult participants (out of 196).

To test the effect of Condition (Noun vs Verb), we ran a cluster-based permutation analysis for each group (as in de Carvalho, Dautriche, & [START_REF] De Carvalho | Phrasal prosody constrains online syntactic analysis in two-year-old children[END_REF][START_REF] Hahn | Rapid Linguistic Ambiguity Resolution in Young Children with Autism Spectrum Disorder: Eye Tracking Evidence for the Limits of Weak Central Coherence[END_REF][START_REF] Von Holzen | Language nonselective lexical access in bilingual toddlers[END_REF]; see [START_REF] Maris | Nonparametric statistical testing of EEG-and MEG-data[END_REF] for a formal presentation of this analysis), to find whether there were time-windows (i.e. clusters) during which the two conditions were significantly different from each other. This conservative analysis has the advantage of avoiding fixing a time-window arbitrarily beforehand. Since the fixations to the two videos were complementary (apart from the time spent looking away, which is not significantly different between conditions), the analysis used the proportion of fixations toward the action video as the dependent variable. The analysis was conducted on the entire test trial (0-10s), since participants heard the target words once before the beginning of the test trials (during the period with the fixation point), which could already have an impact on their eye-gaze. The steps of the analysis are as follows. For each time point, a t-test testing for the effect of Condition (Noun vs Verb condition) was conducted on the proportion of looks toward the action video. Adjacent time points that have a t-value greater than our predefined threshold (t = 1.5) form a cluster, and its size is the sum of the t values at each time point within this cluster. Crucially, to test the probability of observing a cluster of that size by chance, we Error bars represent the standard error of the mean. A cluster-based permutation test revealed significant difference between the Verb and the Noun conditions for both age groups (grey time-windows). For preschoolers, the significant time-window started 307 ms after the first occurrence of the novel function word 'ko'. For adults, the significant time-window started slightly after the onset of the trial. Note that a first sentence containing the novel word preceded by 'ko' was played during the blank interval.

conducted 1000 simulations where we randomly shuffle the conditions (Noun, Verb). For each simulation, the same procedure mentioned above was used to calculate the size of the biggest cluster. Finally, the cluster found with our real data is considered significant if its size is greater than the size of the largest cluster found in 95% of the simulations (ensuring a p-value of .05).

Results

Results of the eye-tracking data

Figure 3 shows children's average proportion of looks toward the action video in the Verb condition (purple curve) and in the Noun condition (orange curve), time-locked to the beginning of trial onset. Visual inspection of the data reveals that overall children tended to look more toward the action videos, most probably due to the movements in these videos, which might have attracted their attention. In the action videos (illustrating the verb interpretation), the actors were moving their body and/or arms to perform a novel action, whereas in the object videos (illustrating the noun interpretation), the actors were simply holding novel objects and looking at them. Crucially, after processing the first occurrence of "ko" during the test trial (and second occurrence overall), children in the Verb condition increased their looks toward the action video more than children in the Noun condition.

Aligning with these observations, the cluster-based analysis found a significant time-window where the proportion of looks toward the action video was significantly different in the Verb condition compared to the Noun condition, from 1720ms after the beginning of the trial until 3080ms (p =.043).

Figure 4 shows adults' average proportion of looks toward the action video in the Verb condition (purple curve) and in the Noun condition (orange curve), time-locked to the beginning of trial onset. Visual inspection of the data reveals that from the beginning of the test trials participants in the Verb condition increased their looks toward the action video more than those in the Noun condition. Note that a first occurrence of "ko" with a novel word was presented during the blank interval before the onset of each test trial, enabling adults to anticipate the side of the target video. Aligning with these observations, the cluster-based permutation analysis found a significant time-window where the proportion of looks toward the action video was significantly different between the Verb and the Noun conditions, from 840ms after the beginning of the trial until 8640ms (p < .001). This shows that adults, just like 3-to-4-year-olds, were able to exploit the novel function word in real-time to infer the probable meaning of the novel co-occurring content words.

We also compared looking times averaged over the entire duration of the test trials (see children's data in Figure 5, and adults' data in Figure 6). This analysis aimed to ensure that an effect would not be missed simply because there is no single moment at which all participants direct their gaze to one of the videos. To do so, a two sample t-test was conducted on the These results confirm that both children and adults from the Verb condition were more likely to interpret the novel words as referring to novel actions than those in the Noun condition.

Results of the pointing responses

The proportion of pointing towards the action video for each child is shown in Figure 7, and for each adult in Figure 8. To analyze this data, we ran for each group a mixed model analysis in which we modeled the occurrence of a pointing response toward the action video as predicted by the condition (Noun Condition coded as 0, Verb Condition coded as 1). With our model, which included a by-subject intercept, we found a significant main effect of Condition (β = .92; SE=.34; z = 2.71; p =.007), predicting an increase of 0.22 in the probability of children pointing to the action video if they were in the Verb Condition. As can be seen in the figure 7, children in the Verb Condition pointed more toward the action video (M=.55; SEM=.05) than those in the Noun Condition (M=.35; SEM: .04). This trend was found for all of the four novel target words. With the adult data, we also found a significant main effect of The lower and upper hinges correspond to the first and third quartiles, the dotted white lines represent the means, and the black lines within the squares represent the median. The top whiskers denote the maximum value, and the bottom whiskers the minimum value. Note that outliers (one child in the Verb condition and another one in the Noun condition; four adults in the Verb condition) were not removed from any of the reported analyses. For each group, participants from the Verb condition are looking at the action video significantly more than those from the Noun condition Condition (β = 2.39; SE= .62; z = 3.84; p < 0.001), predicting an increase of 0.53 in the probability of adult participants pointing to the action video if they were in the Verb Condition.

As can be seen in figure 8, adults in the Verb Condition pointed more toward the action video (M=.74; SEM=.05) than those in the Noun Condition (M=.30; SEM = .05). were similar to those obtained with preschoolers. Overall, these results indicate that children in the Noun and Verb condition learned something different about the novel function word "ko". One possible interpretation is that children in the Verb condition learned that 'ko' appears in verb contexts, and therefore interpreted a novel word following 'ko' as more likely to refer to a novel action, while children in the Noun condition learned that "ko" appears in noun contexts, and thus at test they interpreted a novel word following 'ko' as more likely to refer to a novel object. However, our results are also compatible with an alternative interpretation in which only one group of children learned something about the novel word 'ko' (either the Noun or the Verb group), and the other group was just baffled and did not learn anything. We cannot test this by comparing children's looking behavior to 'chance', since there is no guarantee that chance looking is at 50% --indeed, our results show a bias with more looks towards the action video, in which there is distracting movement, compared to the object video 1 . At any rate, the demonstration that the two groups of children learned something different about the novel function word "ko" shows that children of this age have the ability to track the use of a novel function word with familiar content words during a brief training phase and to use their knowledge later on to narrow down the probable meaning of co-occurring novel words, although it remains unclear whether children learned which semantic category was cooccurring with "ko" in both the Noun and the Verb conditions (or in only one of them).

Post-experiment questions to adult participants

After completing the experiment, a majority of the adult participants (46 out of 52; the total includes the three participants who were excluded based on their poor eye-tracking data) were able to explicitly describe the regularity (e.g. when they were in the Verb condition, they explained that "ko" was used as a pronoun or referred to the stuffed animal, and when they were in the Noun condition, that it was acting as a determiner or preceded things and animals), but they did not systematically report that their choices during the test phase (i.e. pointing/looking more towards the novel actions or towards the novel objects) was driven by this explicit knowledge. Many of them reported that they still had a doubt on how to use "ko" as a cue to novel word meaning. For instance, some participants in the Noun condition reported being aware that nouns can also denote events (e.g. a dance), not just objects.

1 One reviewer suggested testing a control group of children who would not be exposed to a training video (and who would encounter 'ko' for the first time at test) could be an adequate measure of chance behavior. Such a control group is quite unpractical to run for two reasons: First, the difference in looking time between the two experimental groups is already rather small: if the control group fell in-between these two experimental groups, there is a good chance that its looking time would not be different from either experimental condition, making interpretation of the results difficult.

Discussion

Our study provides the first evidence that young children can rapidly track the distribution of a novel function word and learn what type of semantic properties it can predict.

After watching a 5-min training video in which a novel function word "ko" either replaced pronouns (Verb condition) or articles (Noun condition), 3-4-year-olds were able to infer the probable meaning of novel content words that co-occurred with this newly-learned function word "ko"(e.g. Oh look, ko dase!), interpreting them as either referring to novel actions or novel objects. Children's behavior during the test trials was most likely conditioned by their experience with "ko" during the training video. Children in the Verb condition heard "ko" preceding verbs that were referring to actions that were being performed by the agents, whereas children in the Noun condition heard "ko" preceding nouns that referred to the agents themselves (i.e. the stuffed animals) or to inanimate objects (e.g. the car). Since the training videos presented "ko" embedded in full sentences, and participants' focus was on the storyline, children had to use their distributional analysis skills in order to keep track of the kind of words which co-occurred with the new function word. Hence, our results demonstrate that children at this age can proficiently use a newly-learned syntactic context as a "zoom lens" to guide their real-time interpretations of the meaning of novel words, mapping novel nouns to objects and novel verbs to actions.

The present findings have important implications for our understanding of the synergies between semantics and syntax during language development. While numerous studies over the past decades have focused on the use of syntactic contexts to guide young children's acquisition of novel content word meanings (i.e., "they dax", dax is a verb and likely refers to an action), a process called syntactic bootstrapping, the current study focusses on the process through which children might come to learn about the properties of specific syntactic contexts in their native language: it provides the first evidence that young children can exploit known content words to learn the properties of a novel function word (i.e., "ko eats", "ko plays", "ko is reading" => "ko" is followed by action-denoting words). These results bring empirical evidence to the hypothesis that children expect words from similar conceptual categories to occur in similar syntactic contexts (e.g., [START_REF] Gleitman | The Structural Sources of Verb Meanings[END_REF]Pinker, 1984), while also supporting the modeling-based learning mechanism of the semantic seed (e.g., [START_REF] Brusini | Simulation de l ' apprentissage des contextes nominaux / verbaux par n-grammes[END_REF][START_REF] Christophe | Bootstrapping the syntactic bootstrapper[END_REF][START_REF] Gutman | Bootstrapping the Syntactic Bootstrapper: Probabilistic Labeling of Prosodic Phrases[END_REF]. Our study shows that around 3-to-4 years of age, children rapidly and efficiently undertake a distributional analysis to build predictions about the type of concept that can co-occur with a newly-learned function word.

We would expect even younger children to rely on this learning strategy as well, since it would be most useful during the second year of life, when infants already have enough knowledge of the lexicon (e.g. [START_REF] Bergelson | At 6 -9 months, human infants know the meanings of many common nouns[END_REF], and the necessary computational skills (e.g. Gomez & Gerken, 1999). Although it would be fascinating to test it directly, our experimental task is too difficult for toddlers: even when they are tested with real determiners and pronouns (rather than newly-learnt ones) 20-month-olds have failed the online task of allocating their visual attention towards the appropriate meaning (action vs object) for novel content words [START_REF] De Carvalho | Studying the Real-Time Interpretation of Novel Noun and Verb Meanings in Young Children[END_REF].

Nevertheless, previous work has demonstrated infants' ability to use frequent function words to build syntactic and semantic expectations shortly after their first birthday. For instance, at only 14 months of age, infants expect novel words to follow a determiner (and not a pronoun) if they were first encountered following other determiners (Babineau, Shi & Christophe, under review;[START_REF] Shi | Syntactic Categorization in French-Learning Infants[END_REF][START_REF] Höhle | Functional elements in infants' speech processing: The role of determiners in the syntactic categorization of lexical elements[END_REF][START_REF] Höhle | Functional elements in infants' speech processing: The role of determiners in the syntactic categorization of lexical elements[END_REF]. At 18 months of age, after an infant-controlled habituation phase, infants can map a novel word to either the action performed by an agent or the agent itself (the name of the animal) depending on the syntactic context in which this novel word appeared (e.g. "It is a bamoule" vs "She is bamouling"; de Carvalho, [START_REF] De Carvalho | Prosody and Function Words Cue the Acquisition of Word Meanings in 18-Month-Old Infants[END_REF][START_REF] He | Verb Learning in 14-and 18-Month-Old English-Learning Infants[END_REF]. These latter findings demonstrate that infants have acquired the two fundamental prerequisites for learning the semantic predictiveness of function words. In the present experiment, we simply took advantage of the 3-to-4-year olds' fast inferential processing skills in order to obtain direct evidence of the learning mechanism that bootstraps the syntactic bootstrapper.

It is worth mentioning that children's ease to integrate a novel function word in our study might have been facilitated by the chosen semantic categories (i.e. objects vs actions) cooccurring with it, which are already marked in their native language's morphosyntax. That is, French-speaking preschoolers already master a language in which verbs are preceded by personal pronouns and nouns by articles, so learning the predictiveness of the novel function word "ko" might have been facilitated by its familiar position and use during the training video.

Moreover, it remains unclear whether children interpreted the novel function word "ko" as a synonym of the real function words in their language or as a new member for an already existing group of function words (i.e., a new kind of personal pronoun or article). In the control group with adults, a majority of participants reported that they were aware of such equivalents, although their generalization to novel words during the test phase was not at ceiling. Interestingly, a minority of adults reported to have no clue on the use or function of the novel function word. Therefore, implicitly learning the predictiveness of "ko" was a challenging task, even if this novel function word mimicked an already existing group of function words in the participants' native language. As a final point, we acknowledge that the mapping between nouns and objects, and between verbs and actions, is far from perfect. Obviously, many nouns also refer to actions (e.g. the dance, the construction), not only to concrete objects. This blurred line between the chosen distinctions might have added some noise, perhaps especially for adult participants who know many more action words belonging to the noun category.

In light of these limitations, future work should explore whether children can readily learn to predict other types of semantic categories that are not marked in their native language.

We suspect that learning a new type of syntactic marker would require a lengthier exposure (more than a 5-min video). It is still unclear whether there are limits on the types of lexical semantics that can be inferred through this semantic seed learning mechanism. Inspection of cross-linguistic universals reveals that across the world's languages, certain conceptual categories are often marked in morphosyntax (e.g. object/action, animate/inanimate distinctions), while others are typically not (e.g. electric appliance). As [START_REF] Strickland | Language Reflects "Core" Cognition: A New Theory About the Origin of Cross-Linguistic Regularities[END_REF] proposed, the cause of the cross-linguistic regularities might be that since morphosyntax helps infants to learn word meanings, only morphosyntactic regularities that mark conceptual distinctions that are noticeable by infants (e.g. core knowledge) would be selected by human languages. Overall, children's ability to pay attention to function words and their distribution, which starts in infancy and develops during early childhood, represents a powerful aid to learn a large lexicon without explicit teaching, which is one of the hallmarks of human languages.

Figure 1 :

 1 Figure 1: Example of the script used in the two versions of the training video

Figure 2 :

 2 Figure2: Example of the time-course of a test trial. The practice trials were presented in the same way with the exception that during the inspection period the prompt sentences were informative: they contained the familiar words (e.g., 'Oh look! Ko ball! Do you see that?'). Children were asked to point after the test trial has ended, while the 'frozen' version of the videos were displayed on the screen. Once their response was entered, the end-of-trial video with the baby laughing was presented

Figure 3 :

 3 Figure 3: Proportion of looks toward the action video for preschoolers (a) and adults (b), time-locked to the onset of the trial for participants in the Verb condition (purple curve) and those in the Noun condition (orange curve).Error bars represent the standard error of the mean. A cluster-based permutation test revealed significant difference between the Verb and the Noun conditions for both age groups (grey time-windows). For preschoolers, the significant time-window started 307 ms after the first occurrence of the novel function word 'ko'. For adults, the significant time-window started slightly after the onset of the trial. Note that a first sentence containing the novel word preceded by 'ko' was played during the blank interval.

  average overall looking time per participants. Children from the Verb Condition looked significantly more toward the action video (M=.691, SD=.095) than children from the Noun Condition (M=.626, SD=.0858; t (46) =-2.48, p=.017; Cohen's d = .716). Similarly, adults from the Verb Condition looked significantly more toward the action video (M=.559, SD=.216) than those from the Noun Condition (M=.297, SD=.22; t (46) =-4.21, p=.001; Cohen's d = -1.202).

Figure 4 :

 4 Figure 4: Preschoolers' (a) and adults' (b) mean overall proportion of looks toward the action video in the test phase for the two conditions (Verb Condition in purple and Noun Condition in orange). Yellow dots represent individual participants. The lower and upper hinges correspond to the first and third quartiles, the dotted white lines represent the means, and the black lines within the squares represent the median. The top whiskers denote the maximum value, and the bottom whiskers the minimum value. Note that outliers (one child in the Verb condition and another one in the Noun condition; four adults in the Verb condition) were not removed from any of the reported analyses. For each group, participants from the Verb condition are looking at the action video significantly more than those from the Noun condition

Figure 5 :

 5 Figure 5: Boxplots of preschoolers' (a) and adults' (b) proportion of pointing towards the action. Each yellow dot represents one participant (with each score based on up to four novel target words). White dashed lines represent the means of the distributions

Acknowledgements

This research was supported by a postdoctoral fellowship from the Fyssen Foundation to Mireille Babineau and to Alex de Carvalho and by a postdoctoral fellowship from the H2020 European Research Council [Marie Skłodowska-Curie grant No 799380) to Mireille Babineau. It was also supported by grants from the National Institute of Child Health and Human Development (Grant R01HD37507 to John Trueswell), Fondation de France, and the French ANR (ANR-13-APPR-0012 LangLearn, ANR-17-CE28-0007-01 LangAge, and ANR-17-EURE-0017 FrontCog).

The authors thank all the bright "actors" who participated in the videos, as well as Anne-Caroline Fiévet for her help in recruiting the children and organizing the partnerships with preschools, and Lara Narbona Sabaté who assisted us in the recording of the training videos. We also thank all the parents, and preschoolers who participated in this study and the directors and teachers of the preschools that so warmly welcomed us and allowed us to conduct our research.

Author Contributions

All authors made a significant contribution to the study. A. de Carvalho, J. Trueswell, and A. Christophe

Declaration of Conflicting Interests

The authors declare that they had no conflicts of interest.