N Zibani

L, Bellatreche H El Kechai

S Iksal

H El

Kechai El

Requirement-driven Architecture for Learning Analytics: The Case of AT41 Project

Keywords: Dashboard, Learning Analytics, Trace Exploitation, Requirements

Digital technologies are becoming more present and essential in all sectors of our life. In education, the intensive usage of digital learning devices contributes to generating a large amount of trace data from digital learning activities.

Intelligent exploitation of these traces represents a valuable asset for both device producers (to improve the design of the devices) and consumers (learners and teachers). In this paper, we first share our vision for better exploitation by teachers, of traces from middle schoolers' digital activities generated by their use of tools and digital learning services during different classes. This vision is a part of the AT41 project funded by the French Ministry of Education. This exploitation has to meet the requirements of the different teachers. Conducting such a project is not an easy task, because it has to consider the following issues: (i) the lack of comprehensive and clear methodology to design and exploit these traces, (ii) heterogeneity of teacher requirements that complicates their elicitation and analysis, and (iii) the diversity of trace sources. Secondly, we propose a requirement-driven architecture for Learning Analytics composed of a well-identified life cycle. This architecture is augmented by learner traces. It offers a repository storing both teacher requirements and traces to facilitate the Learning Analytics in generating relevant and valuable indicators.

Introduction

In information and communication, the technological environment is continuously changing and consequently impacting our lifestyles. Education with its Eco-system is one of the most important pillars in our life. The school is a noble institution that trains and educates future citizens. Thus in a digital era, schools spend a lot of money to move from traditional practices to digital practices. A digital practice is a set of frequent and usual instrumented thematic actions, constructed in the interaction with an object or the same environment aiming at a certain efficiency. In this context, the French Ministry of Education deployed a Digital Plan for Education from 2015 till the end of 2017, where 1668 middle schools were equipped with various digital equipment [14]. Following this plan, the Directorate for Digital in Education in its Numéri'Lab incubation mission, financed various projects, in priority the ones dealing with Learning Analytics' topics.

Learning Analytics is the measurement, the collection, the analysis, and the reporting of data about learners and their contexts, in order to better understand and optimize learning and the environments in which it occurs [START_REF] Siemens | Penetrating the Fog: Analytics in Learning and Education[END_REF]. Our work is part of an incubator project of the Orleans-Tours academy entitled AT41 1 . This project aims mainly at analyzing the digital practices of Loir-et-Cher's public middle school pupils that are equipped in class with Sqool tablets issuing digital traces. A Sqool2 tablet is a French solution with an eeducational system dedicated, adapted to each cycle, and offering three spaces associated to the learner, the teacher, and the school headmaster. The explosion of traces issued from these devices represents an asset for teachers and school managers for building smart educational decision support systems to enhance the teaching activities.

The exploitation of traces has to meet the requirements of the different teachers. These participating teachers are associated to different persona profiles created based on teachers' requirements. Crucial issues have to be addressed when conducting our project: (i) the absence of comprehensive methodology to design and exploit these traces adapted to the context of French middle schools; (ii) the elicitation and analysis of teacher requirements are not an easy task since requirements are heterogeneous. More precisely, they are given by various teachers using different formalisms, multimodal formats (text, audio, video, drawing) and syntax; and (iii) the diversity of the profile of learners. This situation motivates us in proposing a requirementdriven architecture augmented by traces for Learning Analytics. This joint consideration of requirements and data is a common approach in constructing valuable Decision Support Systems [START_REF] Boukhari | Therole of user requirements in data repository design[END_REF]. It is a common approach composed of a well-identified life cycle that includes the following phases: (1) a middle school composed of teachers and pupils, respectively issuing requirements and traces, (2) the requirement elicitation and analysis that requires the carrying out of workshops in order to collect relevant needs of teachers involved in diverse teachings. The process of analyzing teacher requirements will allow us to understand different activities, their performance indicators, and their evaluation. (3) The trace pre-processing, (4) the storage repository, in charge of storing both teacher requirements and learner traces, (5) exploitation by different tools such as visualization, querying, data mining, recommendation, and so on and (6) the capitalization of indicators for the reuse purpose. It should be noticed that the first five steps of our architecture are quite similar to existing Big Data Analytics solutions proposed in various domains such as Smart Cities [START_REF] Bellatreche | SONDER: A Data-Driven Methodology for Designing Net-Zero Energy Public Buildings[END_REF]. The majority of these solutions ignore the capitalization phase. These different generic phases of our architecture will be deeply detailed in this paper, by instantiating them use the school of Pierre de Ronsard, located at Mer, France 3 . The remainder of this paper is organized as follows: Section 2 presents different research issues related to our project. Section 3 gives a state of the art on Learning Analytics, dashboards, and indicators as well as our positioning within existing works. In Section 4, we describe our architecture by detailing its different components illustrating by examples. Section 5 concludes our paper. .

Problem and Challenges

Several works are interested in the analysis of digital traces of the learning activity. As far as we are concerned, we are interested in digital activity that supports the learning activity when it is realized with different digital technologies and devices. The analysis of digital practices is a good indicator of the progress of that activity. Therefore, our objective is to identify and develop one or more learning dashboard structures restoring pupils' digital activities meeting the teacher's requirements. These structures shall at the same time ensure reuse, sharing, and evolution from one middle school context to another, in particular, the capitalized indicators. To solve such problem, we attempt to answer the following research questions:

• What are the teacher requirements in terms of restoring juvenile digital practices via dashboards? Answering this question allows us to categorize different digital practices.

• What are the indicators that emerge from these teacher requirements? What are the appropriate metrics for evaluating the quality of indicators? In [START_REF] Luengo | What indicators to personalize learning in a digital school?[END_REF], an indicator is defined in general as "an evaluation or information tool (device, instrument, quantity) which should serve as an aid to decisionmaking". Answering this second question leads us to define and structure the indicators per category of digital practices. The evaluation metrics of these indicators is performed using traces. This data has to be cleaned, transformed, and stored in a given repository in order to generate relevant indicator and their visualization in dashboards.

• How these indicators are capitalized, enriched, and reused in the analysis processes of juvenile digital practices? This question is fundamental since it implies the definition of capitalization approach augmenting the reuse of the identified indicators in other middle schools than those that have contributed to our project. Usually, data-driven decision support systems ignore the capitalization phase.

Related work

This section reviews major studies related to different components involved in Learning Analytics: Requirements, Activity, Data, and Indicators (see Fig. 1).

Fig. 1 Requirement-driven Architecture for LA concepts 3 http://clg-ronsard-mer.tice.ac-orleans-tours.fr/php5/ Requirement gathering is a crucial step in Learning Analytics. In Hubble project, [START_REF] Luengo | What indicators to personalize learning in a digital school?[END_REF] identified the teacher requirements by interviewing them analyzing to personalize the learning of their 3rd cycle students in a digital environment at school and propose a model defining learning indicators. [START_REF] Wilms | Digital Transformation in Higher Education -New Cohorts, New Requirements?[END_REF] aimed at examining how digital transformation affects universities and students. Semi-structured interviews were conducted and the analysis of the transcribed interviews was based on Mayring's qualitative content analysis [START_REF] Mayring | Qualitative In halts analyse[END_REF]. In [START_REF] Vondra | Learning Analytics: Meeting the Needs of Students and Teachers in Pre-tertiary Education[END_REF] researchers developed Learning Analytics and Educational Data Mining meeting the needs of students and teachers in pre-tertiary education. Requirements were gathered using specific groups, workshops, interviews, literature review, and research experience. They also proposed a new methodology for needs analysis for the learning analytics system in pre-tertiary education and claim that it becomes imperative to develop feasible needs analysis methodology to ensure that main groups of users get what they need and require.

The analysis of the digital activity by exploiting learning's digital traces has been widely studied in the literature in order to enhance teaching activities. The Living Cloud project 4 is an example of these studies. Also the work of [START_REF] Pierrot | Using a Mixed Analysis Process to Identify the Students' Digital Practices[END_REF] made it possible to conduct an analysis of the circulation of juvenile digital practices using their traces and proved the existence of a correlation between commitment, behavior, and academic performance based on the activity system model proposed by Engeström [START_REF] Engeström | Learning by Expanding An Activity-Theoretical Approach to Developmental Research[END_REF].

The Hubble project5 aimed at creating a national observatory for the construction, development, and sharing of massive data analyzing's processes issued from digital traces generated in e-learning environments for several actors (such as teachers, designers, administrators or even politicians). The MULCE project [START_REF] Reffay | Multimodal learning and teaching corpora exchange: lessons learned in five years by the Mulce project[END_REF] aimed at collecting and sharing traces and propose the diffusion of a learning data corpus called LETEC. Many are the tools and methods from French research concerning collection, storage, and trace analysis as DDART, Lab4ce, Tactiléo, Kidlogger, TraceMe, TRAVIS 6 .

Several research efforts conducted to design dashboards. The authors of [START_REF] Schwendimann | Per-ceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research[END_REF] present a systematic review of the literature on learning dashboards in Learning Analytics and Educational Data Mining fields.

They claim that learning dashboards are gaining popularity due to the increased use of educational technologies, such as Learning Management Systems (LMS) or Open and Massive Online Courses (MOOC) [START_REF] Schwendimann | Per-ceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research[END_REF]. The work of [START_REF] Dabbebi | Towards Adaptive Dashboards for Learning Analytic -An Approach for Conceptual Design and Implementation[END_REF] which is a part of Hubble focused on the identification of learning dashboard structures, where different models were proposed to describe users, and the context. An automatic process of generating learning dashboards based on the engineering knowledge approach [START_REF] Charlet | Knowledge Engineering: developments, results and perspectives for Knowledge Management in medical field[END_REF] design using xAPI 7 and meeting the needs of primary and secondary school teachers in terms of learning activity's indicators. Recent studies were focused on the capitalization of indicators [START_REF] Lebis | Capitalisation of analysis processes: enabling reproducibility, openness and adaptability thanks to narration[END_REF] to increase their reuse.

Our architecture

The architecture we implement is organized over four phases. First, two phases realized in parallel: A step of workshops to collect teachers' needs then elicit and analyze them to also identify digital practice categories required by teachers in order to produce instruments to be used to design and implement both the dashboards desired by teachers but also the approach to capitalize on indicators. The other one consists of pre-processing of the pupils' digital tracesdata collected using tracing tools. Cleaning, transformation, and structuration of these traces is necessary in order to be appropriately stored. In the third phase, we store all the data already collected and structured in both previous phases. Finally, we pass in the last phase to the data processing stage where the data stored are exploited and used in different Learning Analytics formats such as dashboards or recommendation systems based on teachers' needs we developed the tools for. Our Requirement-driven Architecture for Learning Analytics is presented in the Fig. 2 Fig. 2 Requirement-driven Architecture for LA 7 http://experienceapi.com/overview 5

The approach phases illustrated by our implementation in AT41 project (Pierre De Ronsard middle school of Mer) case are detailed below:

Requirement Elicitation and analysis

This phase requires significant implementation efforts.

On the one hand, teachers are not always aware of their needs, on the other hand, analysts do not necessarily have the same knowledge in education as teachers.

Workshops

As part of the first phase, participatory design workshops are organized in collaboration with pilot middle school teachers participating in the AT41 project. The objective of these workshops is to collect their relevant needs for reporting on their pupils' digital activity allowing teachers to express their needs and identify the information they wish to view on the dashboards. Eight teachers were contacted by the school principal and accepted to participate in this workshop, which represents 30% of the college's teaching staff (5 teachers and 3 teachers). Several teaching subjects are represented: documentation, mathematics, English, technology, geography, history, and sport.

To realize this work, we organized 2 workshops for each middle school with an average duration of 3 hours. The two workshops take place in two different dates (see Fig. 3). These methodology phases are presented below:

Fig. 3 Workshops general outlines First phase of workshop 1 (Inspiration):

Individual work is initiated so that each teacher produces their own needs, then in groups teachers work together in order to identify common needs and then prioritize them according to their importance for them.

Second phase of the workshop 1 (Structuring):

In a group, teachers use a design cards kit [START_REF] Gilliot | Participatory design of learning analytics dashboards[END_REF] in order to categorize and structure their expressed needs in the first phase. In this second workshop, the groups are formed based on the teachers' interest to the same needs and the same thematic categories of digital practices that they expressed in workshop 1. The second workshop also takes place in two phases:

First phase of workshop 2 (Reminders of needs expressed):

The needs expressed during the first workshop are structured according to two large thematic categories, one of the digital pupils' practices and another concerning teaching pedagogical practices. They are presented again to teachers in the new structured format.

Second phase of workshop 2 (Explanation of use cases):

This phase consists of each teacher individually to choose from the list of needs expressed and categorized previously the most relevant ones in order to describe use cases that make sense for their teaching practice. Teachers who share the same interest for the same needs gather to sketch their first projections in terms of content (indicators and objectives) and visualizations of dashboards. During these workshop stages, we collected in addition to the needs expressed various other data like videos, audios, photos and also notes taken by teachers and researchers, a questionnaire has also been distributed to the participating teachers in order to understand their profiles, their digital practices, their uses of the Sqool tablets as well as their (potential) previous uses of dashboards.

Requirement Analysis

During the workshops, we collected a large amount of data in different formats. Most of this data can not be directly stored and exploited. Therefore, in this phase, we analyze and structure the data to bring them to such a state that they can be easily stored and interpreted.

Analysis methodology

Users' needs analysis is one of the main issues in the Learning Analytics context [START_REF] Vondra | Learning Analytics: Meeting the Needs of Students and Teachers in Pre-tertiary Education[END_REF]. Within the AT41 project, after realizing the workshops, we developed the methodology for needs analysis for Learning Analytics-based on pupils' digital practices, we analyzed everything produced or collected from the workshops over 5 phases (see Fig. 4) Fig. 4 Analysis process (1) During the first phase, we collected information to create our target users personas [START_REF] Reimann | About Face: The Essentials of Interaction Design[END_REF]. We collected a set of information, in particular from questionnaires that we distributed to teachers before the beginning of the workshops. This allowed us to create user groups, structure them, and thus develop the persona for whom we will design the dashboards (see Fig. 5a) (2) For each persona, we have modeled usage scenarios. Next, we identified situations-problem for which the dashboards could provide an answer. This usage scenario also describes the opportunities that dashboards could offer to respond to the problems posed (see Fig. 5b) Fig. 5a Persona Fig. 5b Scenario

(3) The third phase involves concretely modeling how teachers project themselves in using the future dashboards in terms of human-machine interaction in use scenarios format. We proceeded to analyze the Intermediate Objects [START_REF] Vinck | Taking intermediary objects and equipping work into account when studying engineering practices[END_REF] produced for each need during the workshops. Thanks to these use scenarios, teachers describe anticipated actions interacting with the future tool, which we then modeled with use case diagrams.

(4) In a 4th step, we associated the needs expressed to thematic categories of digital practices.

(5) Finally, from the different productions and our analysis, we started transcribing projections in terms of visualizations produced by the teachers and develop the indicators. The first indicators that emerged from the workshops are classified into four categories. We give here a nonexhaustive list:  View indicators: to view statistics about the sites and files visited, the time spent on a site, the percentage of each site visited over the all or pupils state in front of the tablet (active, not active)  Information retrieval indicators: analysis of all pupils searches: for example number of a successful search, search status, search keywords, or search duration  Monitoring indicators: monitoring of search progress over time with the history recording  Comprehension indicators: relate to autonomy, profiles of information searcher and digital behavior, the relevance of the keywords typed during a search, the methodology, and the strategy used for the information retrieval In terms of visualization modes, the first projections suggest the need for simple visualizations considered effective by teachers: tables, monitoring trees, flow diagrams, word clouds, hourglass sand timer … a notification system left to the appreciation of the pupils in case of difficulty for more targeted remediation is also expressed. The teachers insist to have two interfaces, one dedicated to the teachers and the other one to their pupils with some common parts shared between them, which will serve as awareness tools [START_REF] Bellotti | Awareness and Coordination in Shared Workspaces[END_REF] to bring pupils to operate a reflexive approach on their own digital practices in interaction with the teacher.

Data pre-processing

In order to track pupils' tablets, with the collaboration of the DSI (Department of Information Systems) of the Loir-Et-Cher department, a "Kidlogger" tracking solution that collects basic traces relating to the pupils' digital activity on Sqool tablets is installed. This tool was insufficient in terms of needed traces, so we complete the missing needed-data using "DPA" solution locally developed for a similar project. We claim that an easy data-exploitation process and good results depend, among others, on the quality of the data used. Therefore, before integrating traces in our repository, we clean, transform, and structure them.

Requirements/Trace Repository

In this phase, we aim at storing the data already treated in the previous phases (workshops and tracking). One of the most important data that we store is the indicators expressed by teachers and constructed during the previous phases. This model can be completed by realizing other workshops if other information was required and is not mentioned in the current model. Indicator model: In order to develop the indicators in a complete and rigorous way, we decided to describe and model an indicator inspiring by the OVAR method 8 and the Unesco9 which describes many indicators for education. We have created an indicator model as presented below (see Fig. 6) We instantiate the model using the AT41 project indicator example. For the persona Anna who represents teachers needing to restore the information retrieval strategies of her students, the Activity consists in perceiving the student's information retrieval strategy. Performance inducer: restoring the temporality of search. Indicators to identify sources of information and their relevance: domain names of the sites visited, extensions. Indicators: duration of site consultation, the total duration of information retrieval. Thematic category of digital practices: information retrieval. Type of indicators: monitoring. Educational objectives: Teaching pupils to select information sources taking into account domain extensions, diversify information sources, and make a search in a limited time. Type of disaggregation of these indicators: per student.

Exploitation

An important amount of data is stored in our repository. For our AT41 project, this mine of data allows us to developed relevant Learning Analytics in generating and capitalizing the required digital practices. The indicators displayed on the dashboard adapt to each persona requirements.

Conclusion

In this paper, we present a clear and comprehensive architecture for Learning Analytics. In addition to the fundamental phases dedicated to data-driven analytics solutions, our architecture includes an important phase in the education representing the capitalization of indicators generated by the process of Learning Analytics. This capitalization of indicators augments the reuse, share, and evolution potential to satisfy a large number of schools. All steps of our architecture have been implemented by considering the middle school of Pierre de Ronsard, located at Mer, France. The particularity of our architecture is that it is based on teacher requirements and pupils' traces generated during their digital learning activities. Before proposing this architecture, we identified different issues that have to be handled in middle schools in terms of eliciting and analyzing requirements, cleaning traces, and understanding different activities offered by each teacher profile. The fieldwork allowed us to identify different requirements and activities and contributed to generating indicators. Currently, we are reproducing our experience in the other two new middle schools to validate/extend our elaborated models.

Fig. 6

 6 Fig.6Indicator model We describe each concept of this model in Table1below: Table1Model's concepts.Concept Description ActivityThe name of the activity to be treated or analyzed using a set of indicators Activity objective

Table 1 below : Table 1 Model's concepts.

 1:1

	Source	Sources where we can recover
		data
	Calculation	The steps or approach to follow
	method	to calculate the indicator
	Formula	Mathematical	formula	to
		calculate the indicator
	Disaggregation	The	different	levels	of
	's type	calculation of the indicator
					Concept	Description
					Activity	The name of the activity to be
						treated or analyzed using a set of
						indicators
					Activity	The goal we want to achieve by
					objective	this activity
					Performance	Actions that induce to have a
					inducer	good performance and reach the
						objective
					Indicator	The element to calculate, track
						and display
					Abbreviation	Abbreviation of the indicator
						name
					Graphics	The mode of the indicator on the
					Visualization	dashboard adapted to the type of
						indicator
					Description	A	description	and
						documentation of the indicator
					Objective	The target of the present
						indicator
					Educational	The objective motivated by
					objective	the educational situation
					Stake	Explanation of the impact of this
						indicator on the user
					Data	The necessary data for the
						construction or calculation of the
						indicator

From the Appropriation of digital tools to the Transformation of teaching practices in the Loir-et-Cher department (41)

http://www.sqool.fr

https://techne.labo.univ-poitiers.fr/living-cloud/

http://hubblelearn.imag.fr

GTnum2: http://techne.labo.univ-poitiers.fr/gtnum2/

Objectives Action Variables Responsibility; consistent French approach to designing a dashboard system.

l'Institut de statistique de l'UNESCO. 2009. Indicateurs De L'éducation: Directives Techniques. (2009).


Aurélien Flura

Jérôme Laurencin

Sébastien Fourcade

Fabrice Mauvy

Vaibhav Vibhu

Jean-Paul Salvetat

Julie Mougin

Jean-Marc Bassat

J-P Salvetat

J-M Bassat

Development of an isotopic oxygen exchange setup operating under high pressure: preliminary measurements performed on

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.

Introduction

There is nowadays a growing need of clean and sustainable energy sources. Due to the intermittency of renewable energies, new solutions for energy storage are required, in particular to match the fluctuations between the demand and the production. In this frame, hydrogen is considered as one of the most relevant energy vectors [1]. For its production at low cost and high efficiency, the High Temperature Steam Electrolysis (HTSE), based on the Solid Oxide Electrolysis Cells (SOEC) technology, appears as a promising and attractive technical solution [2]. Nevertheless, hydrogen has to be stored or distributed at high pressure. Since the compression of liquid water consumes much less energy than gaseous hydrogen, it can be advantageous to perform the steam electrolysis directly under pressure [3]. Moreover, the high-temperature co-electrolysis of steam and carbon dioxide enables to convert electricity into a syngas of carbon monoxide and hydrogen [2,4]. This syngas can be further transformed in liquid or gaseous hydrocarbons with conventional catalytic processes working at high pressure between 10 and 100 bars [START_REF]Catalysis in C1 Chemistry[END_REF]. In this case, it has been shown that an integrated system working directly under pressure could also be energetically favored [START_REF] Giglio | [END_REF]7]. In this context, it is essential to investigate the impact of high pressure on the electro-catalytic properties of the electrode materials that control the cell electrochemical response, especially the oxygen electrode.

Mixed Ionic Electronic Conductors (MIEC) are commonly used as oxygen electrodes in SOEC cells. In addition to a high electronic conductivity, the electrodes require both high oxygen diffusivity (D) and surface exchange coefficient (k) at the considered operating temperatures. Among different candidates substitutes to oxygen deficient perovskites such as La 0.4 Sr 0.6 Co 0.8 Fe 0.2 O 3-δ (LSCF), a second type of MIEC concerns overstoichiometric oxides, such as nickelates Ln 2 NiO 4+δ (Ln = La, Pr, Nd) [8,9], belonging to the so-called Ruddlesden series Ln n+1 Ni n O 3n+1 (here with n=1). These compounds with the K 2 NiF 4 -type layered structure have shown promising oxygen electrode performance because of their large anionic bulk diffusion and surface exchange coefficients, combined with a good electrical conductivity and a thermal expansion coefficient matching with those of other cell components [10,11].

To date, the reported measurements of D and k in the literature have been performed at ambient pressure and even below, whatever the considered material. Therefore, the objectives of the current work consist in: 1) performing isotopic oxygen exchanges on dense pellets with Ln 2 NiO 4+δ (Ln = La, Pr, Nd) compositions under high oxygen pressure, 2) checking that the resulting oxygen over-stoichiometry  was significantly changed after such an exchange and 3) evaluating the consequence of  variation on D and k coefficients.

Experimental

Samples preparation

Oxygen exchange experiments require dense samples in pure materials with a compacity of at least 95%. In this study, we prepared pellets of lanthanide nickelates reaching these requisites, with a diameter of roughly 20 mm after sintering.

Pure powders of the three lanthanide nickelates were produced using the modified Pechini method [12] from Pr 6 O 11 (Aldrich chem, 99.9%), La 2 O 3 and Nd 2 O 3 (Strem Chemical, 99.99%) and Ni(NO 3 ) 2 ,6H 2 O (Acros Organics, 99%) precursors. The final annealing was performed at 1200 °C for 12 h in air, leading to well crystallized phases.

The obtained powders were ground with zirconia balls and ethanol for 4 h with the aim to obtain a mean particle size of about 0.6 µm (as determined by laser diffraction analysis).

The purity of the powder was controlled by X-ray Diffraction (XRD) analysis. The materials were then sintered at 1350 °C for 4 h in order to get dense pellets.

The dense pellets were first mirror polished, using abrasives of decreasing grain diameter, then diamond paste to complete the work. Finally, cubes of roughly 4 mm side length werecut from the pellet, using a diamond cutting-disc (Isomet Buehler), in order to ensure that our samples are comparable.

Development of the specific (high pressure) oxygen exchange setup

The isotopic oxygen exchange setup (Fig. 1) was developed with the aim to resist to an operating pressure under oxygen up to 40 bars. This specification requires the use of degreased stainless steel for the tubing. One line of the setup is dedicated to pumping: a vacuum of roughly 10 -6 mbar is obtained using a turbomolecular pump. The marked 18 O gas is routed through another line, from a gas (air) cylinder provided by Euriso-top company with the following specifications: 1L, P = 20 bar, being the 16 O of air changed by of 18 O with purity close to 98%. Another line is dedicated to 16 O from the laboratory.

A fourth line is dedicated to cryo-pumping of the marked 18 O at the end of the exchange, which is achieved by immersing an one meter stainless steel rod into liquid helium. The gas may then be used for another experiment, provided that the ratio 18 O/ 16 O is still high.

Two manometers read respectively the low and high pressures. The sample holder (Fig. 2) is a closed cylinder built in magnesium doped zirconia: it was designed to withstand both stationary high pressure and high temperature steady state and also quick thermal quenching. It resisted through all our experiments, up to a starting quenching temperature of 800°C down to room temperature. A sliding oven mounted on rails produces the thermal quenching. In order to assure that the setup is gastight, a polished copper ring is pressed between the zirconia cylinder and the stainless-steel head, using six screws carefully tightened with a torque wrench.

A platinum grid introduced inside the zirconia cylinder allows precisely placing the sample in the oven hot zone. A fine gold grid was added between platinum and lanthanide nickelates to avoid the chemical reaction we observed during the first experiment at high temperature.

Oxygen exchange experiments

After placing the samples in the zirconia cylinder, the gas tightness of the setup was verified by pumping all the gas in the setup and checking that a vacuum of roughly 10 -6 mbar was reached.

As a first step, the samples were equilibrated at the target temperature (600 °C for instance) in 16 O 2 for a period at least ten times longer than the one chosen for the oxygen exchange experiment, then quenched down to room temperature. This treatment creates the baseline in 18 O/ 16 O inside the sample that will be used as reference later during the TOF-SIMS analyses. Besides, it fixes the chemistry of the materials in the bulk: for instance, the oxygen over-stoichiometry of the lanthanide nickelate. Another interest of this preliminary experiment is to determine with accuracy the pressure of gas needed at room temperature to reach 30 bars at the studied temperature.

Next, the gas was pumped and replaced with the desired pressure of 18 O 2 at room temperature. The samples were quickly heated to reach the target temperature, and the oxygen exchange experiments carried out for a determined time. Samples were then quenched down to room temperature, and 18 O 2 recovered using liquid helium. Finally, the samples were taken out of the zirconia cylinder to be prepared for the TOF-SIMS analyses.

A correction on the exchange time, related to the duration needed to reach the target temperature and then to quench the samples, was applied using the Killoran correction [13].

Thermogravimetric analyses

Our first goal was to determine the delta (δ) value characterizing the oxygen overstoichiometric nickelates (with general formulation Ln 2 NiO 4+ ), after each thermal treatment performed under pressure followed by a thermal quenching. For this purpose, TGA experiments were carried out using a TA Instrument ® TGA-5500 device. First, the dense bar samples of nickelates (after exchange experiments) were crushed into powder using mortar-pestle. Then the powders were heated under air up to 150 °C/1h, then cooled down to room temperature with a slow rate (2 °C.min -1 ), with the aim to remove any traces of water. Then, a second cycle was performed under Ar -5% H 2 flux with a very slow heating rate of (0.5 °C.min

ToF-SIMS analyses

Samples preparation

The cubes were cut in half with the utmost care using the diamond cutting-disc. This cut is necessary to reveal the gradient in 18 O. The new face created was then mirror polished.

The resulting two samples were pressed altogether in a way detailed thereafter and fixed inside a stainless-steel ring with Wood alloy (cf. Fig 4). The particularity of this preparation is that one of the samples exposes the surface of the cube that was in direct contact with 18 O 2 , while the other sample exposes the bulk of the cube that contains the gradient of 18 O. The benefit of this setup is to measure with precision the ratio 18 O/ 16 O at the surface of the sample, averaged over a large area. This value is used as the origin of the gradient measured on the other sample.

TOF-SIMS analyses

SIMS experiments were performed using a TOF SIMS 5 (IONTOF, Münster, Germany).

Samples were analysed in spectroscopy mode by scanning a primary 30 keV Bi + beam over 500x500 µm 2 area, interlaced with a 1 keV Cs + sputter beam scanned over 600x600 µm 2 to eliminate surface impurities and enhance production of negative secondary ions. Area of interest was adjusted using the integrated optical camera and sample stage controls so that a sample edge was located vertically on the right or left of the raster field of view. Data acquisition was started in the 3D mode, and the following procedure was used to determine the stopping condition: once the secondary ions of interest (e.g. 18 O and 16 O) peaks were selected on the spectra subpanel, images of ion intensity with definition 256 x 256 pixels were automatically generated by the instrument software (SurfaceLab 7) in the image stockpile subpanel. The images of 18 O and 16 O intensities are then combined to generate an image of the isotopic ratio of interest I( 18 O)/(I( 18 O)+I( 16 O)), and performed an average linescan thereof using the X-area feature of SurfaceLab linescan editor. Using this procedure we could follow the gradient line-scan progress in real-time so that data acquisition could be stopped, typically after 5 to 10 min, when the gradient was stabilized at a good S/N ratio. Doing so an isotopic ratio profile averaged over a volume of approx. 500X500X0.1 µm 3 is generated, which minimizes artifacts from impurities and inhomogeneities. The data were finally exported as ASCII file for further analysis. In some cases, 18 O gradient spanned over 500 µm so that a second adjacent area was analysed similarly and stitched to the previous one.

The experimental oxygen profiles (evolution of I( 18 O)/I( 18 O)+I( 16 O) vs. depth) were then fitted using the Crank solution to the equation of the second Fick's law of gas diffusion in solids [START_REF] Crank | The Mathematics of Diffusion[END_REF][START_REF] Bassat | [END_REF], which leads determining the D* and k* coefficients (* being relative to the diffusion of the 18 O tracer).

Results and discussion

Summary of the oxygen isotopic exchange conditions

Table 1 gathers the temperatures and time durations used for the isotopic exchanges. For a given temperature, three pellets (one for each studied composition) were used together. 2 gathers the results obtained for each exchanged sample, the given value is an average between the two calculations detailed above.

 = 0,31  = 0,29 550 -  = 0,33  = 0,27 600  = 0,21  = 0,43  = 0,27 650 -  = 0,36  = 0,28 700  = 0,23  = 0,5  = 0,28
As a preliminary result and as expected, whatever the temperature used for the oxygen exchange all the samples exhibit a significant increase of oxygen over-stoichiometry after the thermal treatment performed under oxygen pressure, compared to the value obtained after the chemical synthesis. Indeed, let us recall the compositions determined at room temperature after the synthesis performed in air: La 2 NiO 4.16 , Pr 2 NiO 4.22 and Nd 2 NiO 4.21 .

There is a large agreement in the literature regarding these values (see, for instance, [16] and the joined references). Note that under air and atmospheric pressure, such overstoichiometry slightly decreases upon heating (for instance, for Ln=Nd, the measured composition is Nd 2 NiO 4.13 at 700°C [16]). Such evolution was also expected on the current results (the higher the exchange temperature, the lower the  value should be).

However, this conclusion is difficult to draw when considering the results gathered in table 2. However, the exchange duration times were different depending on the temperature (to ensure a partial diffusion of the 18 O gas in the ceramic the exchange time is lower for higher temperatures), which could partly explain this result. Another questionable point is the observed scattering of the  values regarding Pr 2 NiO 4+ , being this material the most oxidized one.

Finally, at this stage our conclusion is that the three studied compositions are significantly over-oxidized after the thermal treatments performed under 18 O pressure, and that we will be able to evaluate the changes in  on the D* and k* coefficients. The k* plot of La 2 NiO 4+ was quite peculiar, and we suspected that the high temperature values were erroneous. Indeed, the exchange rate largely increases with the temperature, and it is easy to saturate the surface of our sample with 18 O if the exchange time is too long. In this case, the measured value of k* will be false. Then, we reduced the exchange time at 700 °C from 80 min down to 42 min : we measured a k* value that is close to the linear regression plot of the k* values obtained at 500 °C, 550 °C and 600 °C. we observed a limited increase of the diffusion coefficient, while a larger one could be expected. The largest increase is observed when the initial oxygen overstoichiometry is the lowest one, for La 2 NiO 4+ ( = 0.16 at room temperature after annealing under air at normal pressure).

Oxygen diffusion profiles and determination of the D* and k* coefficients on samples treated under high 18O

On the opposite, within this work, we also evidenced that the kinetic constant of oxygen exchange k* increases significantly with the pressure. Indeed, considering the reaction of oxygen insertion into the material it can be easily shown that the chemical kinetic constant k chem (which is directly related to k*) must evolve with the square root of the oxygen partial pressure. This theoretical dependence with P(O 2 ) is thus consistent with the reported experimental results. Moreover, this increase is also in good agreement with other experiments carried at low oxygen partial pressure [19].

Conclusions

For a higher efficiency of the Solid Oxide Electrolyser devices, it is envisaged to operate them under high oxygen pressure. On another hand, oxygen over-stoichiometric nickelates with the K 2 NiF 4 -type structure have been developed for several years as oxygen electrodes because being a valuable alternative to the more conventional oxygen deficient perovskites. Then the goal of this work was to determine the oxygen diffusion and surface exchange coefficients (which characterize the O 2-ionic conductivity) of three well known nickelates (La 2 NiO 4+ , Pr 2 NiO 4+ and Nd 2 NiO 4+ , respectively) by the IEDP method after a preliminary isotopic exchange step performed under high oxygen pressure.

For this purpose, an original set-up has been developed, which is now available for future experiments performed on another kinds of materials.

As expected, the measured oxygen over-stoichiometry of the three materials is significantly increased after the oxygen isotopic exchanges performed in the temperature range 500 < T°C < 700 under p(O 2 )  6.

Fig. 1 -

 1 Fig.1 -Overview of the original isotopic exchange device for operating up to P = 50 bar and T=1100°C

Fig. 2 -

 2 Fig.2-Mg-doped zirconia ceramic glove designed for the isotopic oxygen exchange setup operating at high pressure and temperature (approximate length and internal diameter: 20 cm and 1.5 cm, respectively)

  -1 ) up to 1000 °C. The full decomposition of the material under reducing atmosphere leads to the determination of the oxygen stoichiometry after cycling the sample down to room temperature. The decomposition products (Ln 2 O 3 and metallic Ni) were verified by XRD after the thermal cycle. An example of a thermal cycle recorded under Ar/5% H 2 , on Nd 2 NiO 4+ after isotopic exchange performed under oxygen pressure is given in Fig.3.

Fig. 3 -

 3 Fig.3 -TGA experiment performed under Ar/5%H 2 flow (heating rate 2°C.min -1 ), on a Nd 2 NiO 4+ sample (powder crushed from a dense pellet), after the oxygen isotopic exchange step performed at 600°C during 18.600s under pO 2 = 6,5 bar. The graph shows the mass evolution vs. T°, the calculations of delta are explained below in the text

Fig. 4 -

 4 Fig.4 -Preparation of the samples prior to the TOF-SIMS measurements

Table 1 . 3 ,

 13 Temperatures and duration times used for the oxygen exchange steps Oxygen exchange temperature (°C) Oxygen exchange time (Determination of the oxygen over-stoichiometry's of the studied samples after the oxygen exchange steps After the oxygen exchange steps, the samples were quenched to stop the oxygen diffusion phenomenon and to keep the oxygen composition that the oxide reached in the used experimental conditions. Our first goal was to determine the corresponding oxygen overstoichiometry values and, for this purpose, we used TGAs experiments performed under reducing atmosphere (Ar/5%H 2 flow) on powders (crushed pellets). As evidenced on Fig. the decomposition of the oxide is occurring in two steps: 1) At intermediate temperature a first plateau is evidenced, which corresponds to the stabilization of the oxide only containing Ni +II , i.e. a composition Ln 2 NiO 4.0 (Ln=La, Pr, Nd). The measured weight loss between room temperature and this temperature corresponds exactly to the disappearancee of the oxygen over-stoichiometry ; 2) in a second step, at higher temperature the full decomposition of the oxide is observed, leading as checked by XRD to the formation of Ln 2 O 3 plus metallic Ni. Measuring the weight loss recorded between room temperature and the full reduction is then a second way to determine . Table

Fig. 5 -

 5 Fig.5-Gradient in18 O/16 O measured on Pr 2 NiO 4+ (PNO) cross-section after oxygen exchange experiment performed in air at 700 °C, P total = 30 bar (PO 2  6,5 bar) for 4920s.

Fig. 5

 5 Fig.5is an example of oxygen profile recorded on Pr 2 NiO 4+ at 700°C after an exchange performed under total pressure of air P tot = 30 bar (PO 2  6.5 bar).

Fig. 6 ,

 6 Fig. 6, 7 and 8 plot the evolutions of the D* and k* coefficients vs. T, on the overoxidized materials, i.e. La 2 NiO 4+ , Pr 2 NiO 4+ and Nd 2 NiO 4+ , respectively.

Fig. 6 -

 6 Fig.6 -Evolutions as a function of temperature of the k* (red dots) and D* (black dots) coefficients for over-oxidized La 2 NiO 4+ samples (table 2). The red and black dashed lines give respectively the corresponding k* and D* data for isotopic exchanges performed under pO 2 = 0.2 bar (from [10])

Fig. 7 -Fig. 8 -

 78 Fig.7 -Evolutions as a function of temperature of the k* (red dots) and D* (black dots) coefficients for over-oxidized La 2 NiO 4+ samples (table 2). The red and black dashed lines give respectively the corresponding k* and D* data for isotopic exchanges performed under pO 2 = 0.2 bar (from [10])

  5 bars. The measured evolutions of D* and k* coefficients are thus representative of materials in a very different oxidation state. Both D* and k* coefficients are improved after oxygen exchanges performed under pressure compared to that performed under pO 2 = 0.2 atm (atmospheric condition). However, D* is less improved compared to k*, whatever the composition. This statement would thus indicate that the electrochemical properties of such MIEC materials are improved for a SOEC operation under pressure.

Table 2 .

 2 Oxygen over-stoechiometries values determined by TGAs experiments performed under reducing atmosphere, on the different samples previously exchanged under18 O atmosphere, at a given temperature, under pO 2 = 6,5 bar

	Exchange T°C	La 2 NiO 4+	Pr 2 NiO 4+	Nd 2 NiO 4+
	500	= 0,25

Acknowledgments

A.F. thanks the CNRS French grouping GDR HysPàc for supporting this research work via an internal project. CEA is acknowledged for its valuable technical aid, including the supply of the pressurized air bottle enriched in 18 O.


Paolo Mairano

Leonardo Contreras

Marc Capliez

Caroline Bouzon

The acquisition of the English /s-z/ voice contrast by learners of three L1s

The acquisition of the English /s-z/ voice contrast by learners of three L1s Mairano, P., Contreras Roa, L., Capliez, M., Bouzon, C.

Results Introduction

We investigate the acquisition of the /s/ -/z/ contrast in L2 English by FrenchL1 (FR), Northern ItalianL1 (NI) and American SpanishL1 (AS) learners. Given the status of [s] and [z] in their L1s, and based on predictions of current L2 phonology acquisition models 1,2 , we expect that the three groups will show different voicing patterns for these sounds. where the primary feature is length.

• In AS only /s/ exists, but partial [s̬ ] or total voicing [z] can happen in various contexts due to non-obligatory voice assimilation with the following consonant [START_REF] Hualde | The sounds of Spanish with audio CD[END_REF] .

Conclusions

Non-inflectional medial and final /s-z/ are produced differently in terms of duration and periodicity by learners of all three different L1s.

The spelling associated to /s-z/ might have an effect on voicing, regardless of learners' L1.

For more on this topic: Mairano, P

Methodology

We analysed productions by 40 instructed learners from the Interphonology of Contemporary English corpus (IPCE) of L2 English.

Read-aloud task (506 words) Extraction of periodic signal (voicing) and duration of all occurrences of /s-z/. → Except for cases of inflectional /s-z/ (see our other poster!):

• Plural • 3rd person singular • Genitive 's
• Clitic forms of is or has We expect that:

i. FR and NI learners will exhibit no difficulties in producing distinct realizations for /s/ and /z/.

ii. AS learners will exhibit difficulties in producing distinct realisations for this contrast.

Additionally, based on the Markedness Differential Hypothesis 2 , we also expect that:

iii. AS learners will have difficulties producing /z/ rather than /s/. → /z/ is universally and cross-linguistically more marked iv.

AS and NI learners will show difficulties with /z/ word-finally (more marked than word-initially, and non-existent in NI). Linear mixed effect model analyses showed significant interactions between variables PHONEME and L1 GROUP in terms of periodicity (Figure 1) and duration (Figure 2):

L1

FR and NI speakers produce differences in periodicity between /s/ and /z/, whereas AS learners do not.

Furthermore, by-item analyses showed differences in periodicity associated to the spelling of words (Figure 3):

There might be an effect of orthography on voicing: sounds graphically represented with <c> and <ss> tend to be voiceless whereas sounds represented with <s> or <z> tend to be more voiced, regardless of their target L1 voicing patterns.

Figure 1 .

 1 Figure 1. Average periodic proportion for realisations of /s/ and /z/.

Figure 2 .

 2 Figure 2. Average duration for realisations of /s/ and /z/.

Figure 3 .

 3 Figure 3. By-item proportions of periodicity for realisations of /s/ and /z/.

•

  In FR, /s/ and /z/ are both phonemes

	→ casse /kas/ -case /kaz/
	• In NI, [s] and [z] are obligatory allophones
	→ [z] before voiced sounds
	→ [s] in front of voiceless consonants 3
	yet voicing contributes to oppose minimal pairs such as
	casa /ˈkasa/ [ˈkaza] -cassa /ˈkasːa/ [ˈkasːa]


Leonardo Contreras Roa

Paolo Mairano

Marc Capliez

Caroline Bouzon

Contreras Roa

Voice assimilation of morphemic -s in the L2 English of L1 French,L1 Spanish and L1 Italian learners

Introduction

We investigate the /s/ -/z/ contrast in morphemic -s in L2 English by FrenchL1 (FR), Northern ItalianL1 (NI) and American SpanishL1 (AS) learners.

In English, morphemic -s can be a flexional suffix expressing: i) plurality, ii) 3 rd person singular, iii) genitive, and iv) clitic forms of is and has.

It is also subject to a progressive voice assimilation rule:

Conclusions and discussion

The progressive voice assimilation rule triggered by the Left context is realized by learners of all L1s, but to different degrees.

AS learners outperformed NI learners' voicing patterns in cases of

Methodology

We analyzed productions by 40 instructed learners from the Interphonology of Contemporary English corpus (IPCE) of L2 English.

Read-aloud task (506 words) Extraction of periodic signal (voicing) and duration of all occurrences of morphemic -s. → 1610 realizations in total.

Left context C[+voiced] C[-voiced] V

/z/ /s/ Given these facts, and given the higher relative markedness of /z/ in wordfinal position with respect to /s/, [START_REF] Eckman | Typological markedness and second language phonology[END_REF] we hypothesize that FR and NI learners will find it easier than AS learners to reproduce the outcome of the voice assimilation rule in English.

Results

• FR learners were the most successful in producing the expected patterns of periodicity, as expected.

• AS learners performed voicing patterns of morphemic -s better than NI learners (Figure 1).

• Opposite patterns were observed in non-morphemic -s (see our other poster!).

These results may be due to the L1 Spanish non-obligatory voice assimilation in syllable coda which may promote syllable-coda voice assimilation in L2 English, but with a change in directionality (regressive assimilation to progressive assimilation).

By-participant results (Figure 2) give a more detailed insights of the acquisition of this phonological process.

Figure 2 .

 2 Figure 2. By-participant analysis of the periodic proportion for word-final morphemic -s as pronounced by the three groups of learners.

  morphemic -s, although the opposite trend was observed previously in nonmorphemic -s. This different behavior may reflect recent findings on in L1 English 4 and may have potential repercussions on models of L2 phonology acquisition: The /s/ -/z/ opposition may be a partial exception to the markedness hierarchy of voiced obstruents. For more on this topic: Contreras Roa, L., Mairano, P., Capliez, M., & Bouzon, C. (2020) "Voice assimilation of morphemic -s in the L2 English of L1 French, L1 Italian and L1 Spanish learners." Anglophonia, 30. DOI: https://doi.org/10.4000/anglophonia.3711

  [s] and [z] present and behave differently in the learners' L1s: Morphologically: • The -s suffix exists in FR and AS to mark plurality, but it is subject to sandhi phenomena in French les_amis -/le#zami/ • NI does not present flexional final -s. Phonologically: • FR has a phonemic contrast opposing /s/ and /z/. • NI has [s] and [z] as contextual allophones, the latter being used before another voiced segment 1 sbuco -/ˈsbuko/ [ˈzbuːko] casa -/ˈkasa/ [ˈkaːza] • AS only has /s/, with non-obligatory regressive voice assimilation [ s̬ ] in casual speech 2 las mesas -[las̬ ˈmesas] Phonotactically: • FR allows word-final /s/ and /z/ • NI allows word-final /s/ (although infrequent) but not /z/ • AS allows /s/.

Figure 1 .

 1 Figure 1. Average periodic proportion for word-final inflectional /z/ by type of preceding phoneme (C[-voice], C[+voice], V) and following segment (voiced, unvoiced), by L1 of speakers.


Leonardo Contreas Roa

Paolo Mairano

Caroline Bouzon

Marc Capliez

The acquisition of /s/ -/z/ in a phonemic vs neutralised context: comparing FrenchL1, ItalianL1 and SpanishL1 learners of L2 English

) show that all learner groups tend to reproduce (at least globally) the output of the voice assimilation rule: the target segments are voiceless when following a C[-voice], and partially periodic if following a C[+voiced] or a vowel. While French learners clearly show the highest differentiation among conditions, it is surprising to observe that SpanishL1 learners seem to be able to reproduce the assimilation pattern, and even more neatly than ItalianL1 learners. This is confirmed by a linear mixedeffects model similar to the one above, revealing that differences across conditions are significant for

the FrenchL1 group (all p values < .001) and the SpanishL1 group (all p values < .03), but for the Italian group the condition C[-voice] does not significantly differ from the condition C[-voice] (p = .27). Conclusions. SLM predictions were confirmed in phonemic contexts. Instead, we find unexpected results for the voice assimilation rule, whereby SpanishL1 learners manage to produce more voiced realisations than ItalianL1 learners. The existence of a non-obligatory voice assimilation rule in Spanish (incl. morphemic -s, used for plural in Spanish) may promote voice assimilation in syllable-coda in L2 English, although with a change in directionality (regressive to progressive assimilation). Moreover, the behaviour shown by SpanishL1 and ItalianL1 learners in morphemic vs non-morphemic -s may reflect [START_REF] Plag | Homophony and morphology: The acoustics of word-final S in English[END_REF]'s findings for L1 English that morphemic and non-morphemic -s are not homophonous. If confirmed on more data, such results may have an impact on mainstream models of L2 phonology acquisition.

Figure 1 .

 1 Figure 1. Average periodic proportion for realizations of /s/ and /z/ in phonemic contexts.

Figure 2 .

 2 Figure 2. Average periodic proportion for realizations of morphemic -s.