Recherche

Ingram Sandy

Professeure HES ordinaire

Compétences principales

Centre de Compétences Numériques

Professeure HES ordinaire

Téléphone: +41 26 429 65 97

Bureau: HEIA_C10.17

Haute école d'ingénierie et d'architecture de Fribourg
Boulevard de Pérolles 80, 1700 Fribourg, CH

Institut
iSIS - Institut des systèmes intelligents et sécurisés

BA HES-SO en Architecture - Haute école d'ingénierie et d'architecture de Fribourg

human computer interaction
technologies web
Recommender Systems

MA BFH/HES-SO en Architecture - HES-SO Master

software engineering
devOps
Software development
Automated tests

En cours

"Deep Reinforcement Learning" for News Recommendations

Rôle: Requérant(e) principal(e)

Financement: HES-SO

Description du projet :

This project aims at developing a unified user-centered recommendation framework and proof-of-concept based on deep reinforcement learning, specifically tailored to aggregated social streams and news recommendation, and able to simultaneously: (1) target long-term user satisfaction, (2) automatically update recommendations based on online user feedback (3) improve the target user’s well-being and time spent passively « scrolling » online, by injecting into the social news feed, the « right » type and « amount » of micro-learning information bits at the « right » intervals, based on learned user interests and feedback.

Equipe de recherche au sein de la HES-SO: Islambouli Rania , Ingram Sandy

Durée du projet: 01.02.2022 - 01.03.2022

Statut: En cours

G-Gama: Guide pratique de la GAMification des Apprentissages (2019-2020)

Rôle: Co-requérant(s)

Requérant(e)s: Masset Philippe, VD- EHL

Financement: HES-SO - Projet Innovation Pédagogique

Description du projet :

La «Gamification des apprentissages» (GA) repre'sente une approche théoriquement idéale pour enrichir les expériences d'apprentissages des étudiants. Mais, en pratique, elle reste peu employée du fait de la nature souvent technologique, peu flexible et dispendieuse de ses applications. Ce projet a pour objectif d'élaborer un guide des bonnes pratiques complémenté par un ensemble d'exemples commentés. Ainsi les enseignants pourront aisément s'approprier la démarche GA, ce qui permettra de renforcer l'acquisition des compétences pour les étudiants.

Philippe Masset, VD- EHL; Ingram Sandy, FR - EIA - Institut iSIS; Truchot-Cardot Dominique, Institut et Haute Ecole de Santé La Source; Andrianantenaina Miharisoa, FR - EIA - Institut iSIS

Equipe de recherche au sein de la HES-SO: Ingram Sandy , Andrianantenaina Miharisoa Hanitrarivony

Partenaires académiques: Masset Philippe, VD- EHL; Truchot-Cardot Dominique, Institut et Haute Ecole de Santé La Source; WeissKopf Jean-Philippe, VD- EHL

Statut: En cours

Terminés

Aspire: Graasp for Open Evidence-Based Research in Digital Education (2019-2020)

Rôle: Requérant(e) principal(e)

Financement: Swiss Universities

Description du projet :

This project broadens the scope of the current strategic Swiss and European initiatives on open digital education, to the emerging and also strategic Swiss and European initiatives on open science and especially open data, strengthening as such the international leadership of Switzerland in these areas. Targeted research communities include not only education, digital education, and human computer interaction, but also information systems and knowledge management.

Equipe de recherche au sein de la HES-SO: Ingram Sandy , Nwachukwu Uchendu

Partenaires académiques: Gillet Denis, VD - EPFL - REACT Group; Arnaud Legourriérec, HEP Bejune; Boechat-Heer Stéphanie, HEP Bejune

Durée du projet: 01.02.2021 - 30.06.2022

Statut: Terminé

Multi-Confort (2018-2020)

Rôle: Co-requérant(s)

Financement: Smart Living Labs

Description du projet :

L'apparition de nouveaux types d'environnement de travail cherchant à la fois la satisfaction des usagers et l'accord avec des types de travail spécifiques à l'organisation des entreprises demande une compréhension systémique du confort de l'usager dans les bureaux. Le projet Multi-Confort répond à cet enjeu en prenant en compte les trois composantes du confort (physiologique, psychologique et fonctionnel) et en cherchant les corrélations entre les facteurs ambiants, les types (routines) de travail, l'occupation effective et l'usage des équipements.

Equipe de recherche au sein de la HES-SO: Radu Florinel , Bacher Jean-Philippe , Ingram Sandy , Iseli Yael , Nwachukwu Uchendu , Spoto Martin

Durée du projet: 01.09.2011 - 31.12.2020

Statut: Terminé

Reinforcement Learning for Multi-criteria Dynamic Price Modeling (2018)

Rôle: Requérant(e) principal(e)

Financement: InnoSuisse (Innovation Check)

Description du projet :

By 2018, 40% of B2B digital commerce sites will dynamically configure product pricing using price optimization algorithms. Adapting product prices dynamically as demand, transportation pathway costs, and predicted product success fluctuates over time, contributes to increasing revenue margin. Considering the increasing demand for dynamic price optimization algorithms, OrchardAi aims at developing a global, business-agnostic yet customisable framework for dynamic price optimization. Preliminary research initiated by OrchardAi shed light on the use of reinforcement learning for dynamic price optimization.

Results: A proof of concept of the reinforcement learning approach proposed, was implemented and packaged as a library. The proof of concept used dynamic programming to find the optimal the commission at each time period based on expected cumulative reward. A web-based parametrisable simulation tool was also provided to allow OrchardAi to experiment with the proof of concept and data provided.

Equipe de recherche au sein de la HES-SO: Ingram Sandy , Goetschi Damien

Partenaires professionnels: Hamilton-Smith Robert, OrchardAI

Durée du projet: - 31.12.2018

Statut: Terminé

2021

Well-being at Work: Applying a Novel Approach to Comfort Elicitation

Scientifique

Sandy Ingram, Uchendu Nwachukwu, Nicole Jan, Jean-Philippe Bacher, Florinel Radu

Lecture Notes in Computer Science Proceedings of HCI-2021: International Conference on Human-Computer Interaction Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Body, Motion and Behavior, 19-24 July 2020, Copenhagen, Denmark, 2021

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Résumé:

This paper presents a novel approach for assessing comfort at the workplace, resulting from an interdisciplinary work between researchers in hman-computer interaction, architecture, social sciences, smart buildings and energy management. A systemic comfort elicitation model including but not limited to thermal comfort, is suggested. A proof-of-concept prototype application developed based on the proposed model is also presented. The results of a first evaluation of the application's acceptability in a real working environment are discussed.

2015

Klewel webcast: From research to growing company

Scientifique

Mael Guillemot, Jean-Marc Odobez, Alessandro Vinciarelli, Sandy Ingram

IEEE MultiMedia, 2015 , vol. 22, no 4, pp. 94-99

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Résumé:

The main motivations behind the webcasting company, Klewel, were to go beyond text-based conference proceedings to offer a user-friendly way to browse and replay presentations, access slides, and search for specific information within a recording. As the project got under way, the team came together, and eventually an innovative webcasting solution saw the light of day. Learn how the company moved from research to technology by focusing on multidisciplinary research, early real-world prototyping and testing, collaboration, and client needs.

2013

Multi-factor segmentation for topic visualization and recommendation: the MUST-VIS system

Scientifique

Chidansh Amitkumar Bhatt, Andrei Popescu-Belis, Maryam Habibi, Sandy Ingram, Stefano Masneri, Fergus McInnes, Nikolaos Pappas, Oliver Schreer

Proceedings of the 21st ACM international conference on Multimedia, 2013 , pp. 365-368

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Résumé:

This paper presents the MUST-VIS system for the MediaMixer/VideoLectures .NET Temporal Segmentation and Annotation Grand Challenge. The system allows users to visualize a lecture as a series of segments represented by keyword clouds, with relations to other similar lectures and segments. Segmentation is performed using a multi-factor algorithm which takes advantage of the audio (through automatic speech recognition and word-based segmentation) and video (through the detection of actions such as writing on the blackboard). The similarity across segments and lectures is computed using a content-based recommendation algorithm. Overall, the graph-based representation of segment similarity appears to be a promising and cost-effective approach to navigating lecture databases.

A recommender system for job seeking and recruiting website

Scientifique

Yao Lu, Sandy Ingram, Denis Gillet

Proceedings of the 22nd International Conference on World Wide Web, 2013 , pp. 963-966

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Résumé:

In this paper, a hybrid recommender system for job seeking and recruiting websites is presented. The various interaction features designed on the website help the users organize the resources they need as well as express their interest. The hybrid recommender system exploits the job and user profiles and the actions undertaken by users in order to generate personalized recommendations of candidates and jobs. The data collected from the website is modeled using a directed, weighted, and multi-relational graph, and the 3A ranking algorithm is exploited to rank items according to their relevance to the target user. A preliminary evaluation is conducted based on simulated data and production data from a job hunting website in Switzerland.

Processing and linking audio events in large multimedia archives: The EU inevent project

Scientifique

Sandy Ingram, Hervé Bourlard, Marc Ferras, Nikolaos Pappas, Andrei Popescu-Belis, Steve Renals, Fergus McInnes, Peter J Bell, Maël Guillemot

First Workshop on Speech, Language and Audio in Multimedia, 2013

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Résumé:

In the inEvent EU project, we aim at structuring, retrieving, and sharing large archives of networked, and dynamically changing, multimedia recordings, mainly consisting of meetings, videoconferences, and lectures. More specifically, we are developing an integrated system that performs audiovisual processing of multimedia recordings, and labels them in terms of interconnected “hyper-events”(a notion inspired from hyper-texts). Each hyper-event is composed of simpler facets, including audio-video recordings and metadata, which are then easier to search, retrieve and share. In the present paper, we mainly cover the audio processing aspects of the system, including speech recognition, speaker diarization and linking (across recordings), the use of these features for hyper-event indexing and recommendation, and the search portal.

2012

Analyzing User Patterns to Derive Design Guidelines for Job Seeking and Recruiting Website

Scientifique

Yao Lu, Sandy Ingram, Denis Gillet

Proceeding of The Fourth International Conferences on Pervasive Patterns and Applications, 2012 , pp. 11-16

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A federated recommender system for online learning environments

Scientifique

Zhou Lei, Sandy Ingram, Laurent Moccozet, Laurent Opprecht, Omar Benkacem, Christophe Salzmann, Denis Gillet

International Conference on Web-Based Learning, 2012 , vol. Springer, Berlin, Heidelberg

Résumé:

From e-commerce to social networking sites, recommender systems are gaining more and more interest. They provide connections, news, resources, or products of interest. This paper presents a federated recommender system, which exploits data from different online learning platforms and delivers personalized recommendation. The underlying educational objective is to enable academic institutions to provide a Web 2.0 dashboard bringing together open resources from the Cloud and proprietary content from in-house learning management systems. The paper describes the main aspects of the federated recommender system, including its adopted architecture, the common data model used to harvest the different learning platforms, the recommendation algorithm, as well as the recommendation display widget.

A social media platform in higher education

Scientifique

Evgeny Bogdanov, Sandy Ingram, Freddy Limpens, Na Li, Christophe Salzmann, Denis Gillet

Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON), 2012 , pp. 1-8

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Résumé:

This paper reports on the successful use of Graasp, a social media platform, by university students for their collaborative work. Graasp features a number of innovations, such as administrator-free creation of collaborative spaces, a context-aware recommendation and privacy management. In the context of a EU-funded project involving large test beds, we have been able to extend this platform with lightweight tools (widgets) aimed for learning and competence development and to validate its usefulness in a collaborative learning context.

2011

A federated search and social recommendation widget

Scientifique

Sten Govaerts, Sandy Ingram, Eric Duval, Denis Gillet

Proceedings of the 2nd International Workshop on Social Recommender Systems (SRS 2011) in conjunction with the 2011 ACM Conference on Computer Supported Cooperative Work (CSCW 2011), 2011 , pp. 1-8

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Résumé:

This paper presents a federated search and social recommen-dation widget. It describes the widget’s interface and the un-derlying social recommendation engine. A preliminary eval-uation of the widget’s usability and usefulness involving 15 subjects is also discussed. The evaluation helped identify us-ability problems that will be addressed prior to the widget’s usage in a real learning context.

May I suggest? Comparing three PLE recommender strategies.

Scientifique

Felix Modritscher, Barbara Krumay, Sandy Ingram, Denis Gillet, Alexander Nussbaumer, Albert Dietrich, Ingo Dahn, Carsten Ullrich

Digital Education Review, 2011 , vol. 20, pp. 1-13

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Résumé:

Personal learning environment (PLE) solutions aim at empowering learners to design (ICT and web-based) environments for their learning activities, mashingup content and people and apps for different learning contexts. Widely used in other application areas, recommender systems can be very useful for supporting learners in their PLE-based activities, to help discover relevant content, peers sharing similar learning interests or experts on a specific topic. In this paper we examine the utilization of recommender technology for PLEs. However, being confronted by a variety of educational contexts we present three strategies for providing PLE recommendations to learners. Consequently, we compare these recommender strategies by discussing their strengths and weaknesses in general.

2010

Graaasp: a web 2.0 research platform for contextual recommendation with aggregated data

Scientifique

Evgeny Bogdanov, Sandy Ingram, Stéphane Sire, Christophe Salzmann, Denis Gillet

CHI'10 Extended Abstracts on Human Factors in Computing Systems, 2010 , pp. 3523-3528

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Résumé:

In this paper we describe Graaasp, a social software currently under development to support the creation of a real usage database of social artifacts. Our goals are twofold: First to offer a generic aggregation service and user interface to people and communities. Second, to experiment with recommendation and reputation models and algorithms in e-learning.

The 3A interaction model: towards bridging the gap between formal and informal learning

Scientifique

Sandy Ingram, Na Li, Denis Gillet

IEEE Third International Conference on Advances in Computer-Human Interactions, 2010 , pp. 179-184

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Résumé:

This paper discusses the adoption of bottom- up social software tools in formal learning environments. This is believed to enhance the learning experience of today's young generation characterized by being technology savvy and keen on social networking. As a first step towards this objective, the 3A interaction model that aims at aiding the design of personal and collaborative learning platforms is presented. It accounts for interaction paradigms widely used in Web 2.0 applications and builds on Distributed Cognition and Activity Theory while remaining at the right level of abstraction to be easily ¿translatable¿ into tangible applications supporting both formal and informal learning.

The 3A Personalized, Contextual and Relation-based Recommender System.

Scientifique

Sandy Ingram, Christophe Salzmann, Denis Gillet

Journal of Universal Computer Science, 2010 , vol. 18, no 18, pp. 2179-2195

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Résumé:

This paper discusses the 3A recommender system that targets CSCL (computersupported collaborative learning) and CSCW (computer-supported collaborative work) environments. The proposed system models user interactions in a heterogeneous graph. Then, it applies a personalized, contextual, and multi-relational ranking algorithm to simultaneously rank actors, activity spaces, and assets. The results of an empirical evaluation carried out on an Epinions dataset indicate that the proposed recommendation approach exploiting the trust and authorship networks performs better than user-based collaborative filtering in terms of recall.

Using social software for teamwork and collaborative project management in higher education

Scientifique

Ullrich Carsten, Sandy Ingram, Denis Gillet

(Springer) International Conference on Web-Based Learning, 2010 , pp. 161-170

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Résumé:

This paper discusses the potential role of social software in supporting teamwork and collaborative project management in higher education. Based on the fact that social software has been widely spread among young students nowadays, using it for collaborative learning is believed to increase students’ involvement and create learning incentives. Two social software platforms, Graaasp and Google Wave are examined in terms of sustaining collaborative learning activities. Relevant existing features and possible extensions that enhance the learning experience are addressed. Benefits and challenges resulting from the bottom-up learning paradigm are also presented.

2009

A study of the acceptability of a Web 2.0 application by higher-education students undertaking collaborative laboratory activities

Scientifique

Sandy Ingram, Denis Gillet, Christophe Salzmann, Chiu Man Yu

Second IEEE International Conferences on Advances in Computer-Human Interactions, 2009 , pp. 117-125

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Résumé:

This paper presents the findings of a study on the acceptability in higher education of a Web 2.0 collaborative application, namely eLogbook. The latter offers several features for sustaining collaboration and supporting personal and group learning. It was introduced to students taking a laboratory course that spans over one semester and mainly consists of in-class group experiments. In this paper, we present eLogbook. We then describe our hypotheses as well as the qualitative and quantitative methods used to evaluate the usefulness and usability of eLogbook in a formal learning context. Finally, we discuss our findings and its implications.

The 3A contextual ranking system: simultaneously recommending actors, assets, and group activities

Scientifique

Sandy Ingram, Christophe Salzmann, Stéphane Sire, Denis Gillet

Proceedings of the third ACM conference on Recommender systems, 2009 , pp. 373-376

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Résumé:

In this paper, we propose a personalized and contextual ranking algorithm implemented on top of the 3A interaction model. The latter is a generic model intended for designing and describing social and collaborative learning platforms integrating Actors, Assets and group Activities (the 3" A"). The target user's interactions with his/her environment are modeled in a heterogeneous graph. Then, the algorithm is applied to simultaneously rank actors, assets and group activities taking into account the target user and his/her context. As an illustrative application and a preliminary evaluation, we apply the algorithm on data related to the activities carried out in a European Research Project, especially the collaboration between its members through the joint production of deliverables in workpackages.

2008

Turning Web 2.0 social software into versatile collaborative learning solutions

Scientifique

Denis Gillet, Sandy Ingram, Christophe Salzmann, Chiu Man Yu

First international conference on advances in computer-human interaction, 2008 , pp. 170-176

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Résumé:

In the framework of the European Integrated Project PALETTE, the Ecole Polytechnique Federale de Lausanne (EPFL) is developing the eLogbook Web 2.0 social software. The purpose of eLogbook is to support tacit and explicit knowledge management in communities of practice. It can be customized by the users to serve as an asset management system, as a task management system or as a discussion platform. In this paper, the innovative Computer-Human Interaction features of eLogbook are introduced and its deployment scenario to support collaborative laboratory activities in engineering education is described. The main idea is to sustain interaction for learning purpose within self-organized teams that integrate -on a seamless level- both human actors (students, teaching assistants) and non-human actors such as laboratory equipments or software agents.

Social software modeling and mashup based on actors, activities and assets

Scientifique

Evgeny Bogdanov, Sandy Ingram, Christophe Salzmann, Denis Gillet

EC-TEL08-Workshop on Mash-Up Personal Learning Environments (MUPPLE’08), 2008

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Résumé:

Despite the extreme diversity of Web applications, one can find similarities among them. This paper proposes an answer to the question of knowing whether it is possible to conceptually represent different Web applications in a common manner such that they can generically be integrated in other Web applications. The 3A model developed at EPFL in the framework of the European PALETTE project is used to generalize the visual and functional properties of Web applications. A Web 2.0 personal learning environment based on the 3A model called eLogbook is used as a mashup container to integrate existing Web applications. The mapping procedure is described and illustrated with the example of an instant messaging application, showing that mashup is possible with 3A model.

2007

Context-sensitive awareness services for communities of practice

Scientifique

Denis Gillet, Sandy Ingram, Christophe Salzmann, Yassin Aziz Rekik

12th International Conference, HCI International 2007, 2007 , pp. 1079-1083

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Résumé:

Denis Gillet, Sandy El Helou, Yassin Rekik, Chr Salzmann

The eLogBook Framework: Sustaining Interaction, Collaboration, and Learning in Laboratory-Oriented CoPs

Scientifique

Yassin Aziz Rekik, Sandy Ingram, Denis Gillet, Christophe Salzmann

International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 2007 , vol. 2, no 3, pp. 61-76

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Résumé:

Convinced by the important role of CoPs (communities of practice) and the innovative learning modality they offer, the École Polytechnique Fédérale de Lausanne is currently developing a framework to sustain interaction, collaboration, and learning in laboratory-oriented CoPs, namely the eLogBook. This paper describes the services provided by this framework, the 3A model on which it is based, and the main features it presents. The eLogBook presents several innovative features that make it different from other classical collaboration workspaces. The eLogBook offers a high level of flexibility and adaptability so that it can fit the requirements of various CoPs. It allows CoPs’ members to define their own rules, protocols, and vocabularies. The eLogBook also focus on usability and user acceptance thanks to its personalization and contextualization mechanisms.

Designing services for CoPs: first results of the PALETTE project

Scientifique

Sandy Ingram, Bernadette Charlier, Aida Boukottaya, Amaury Daele, Yannick Naudet, Nathalie Deschryver

TEL-CoPs’ 07: 2nd International Workshop on Building Technology Enhanced Learning Solutions for Communities of Practice, 2007

Résumé:

In this contribution, we specify and categorize CoPs’ needs (this includes the analysis of CoPs practices, resources and environments) in order to identify specific functions that meet these needs. This enables the efficient identification of possible interactions between PALETTE services’ categories that will be used as the basis to refine functional specifications of PALETTE services and enhance the development guidelines.

2022

Integrating code reviews into online lessons to support software engineering education

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Basile Spaenlehauer, Maria Jesus Rodriguez-Triana, Denis Gillet

Proceedings of 25th International Conference on Interactive Collaborative Learning (ICL 2022), 27-30 September 2022, Vienna, Austria

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Résumé:

The use of peer code review exercises is well established in software engineering education. Nevertheless, challenges involving students’ ability to perform code reviews have been identified as barriers to successfully integrating code reviews in educational settings. We have previously proposed code review notebooks as a way to address this is-sue. Code review notebooks resemble computational notebooks but focus on reviewing rather than executing code and can serve to introduce students to the code review process. In this study, we evaluated the effects of using a code review notebook via a case study whereby 25 university students were taught how to identify code style issues in JavaScript. Our mixed-method analysis suggests that the code review notebook format encourages students to reflect on their learning process and can result in short-term learning gains. These findings could serve instructors looking to incorporate code review exercises into their practice.

Toward code review notebooks

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Basile Spaenlehauer, Maria Jesus Rodriguez-Triana, Denis Gillet

Proceedings of ICALT 2022 – 22nd IEEE International Conference on Advanced Learning Technologies, 1-4 July 2022, Bucharest, Romania

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Résumé:

Peer code review has proven to be a valuable tool in software engineering. However, integrating code reviews into educational contexts is particularly challenging due to the complexity of both the process and popular code review tools. We propose to address this challenge by designing a code review application (CRA) aimed at teaching the code review process directly within existing online learning platforms. Using the CRA, instructors can scaffold online lessons that introduce the code review process to students through code snippets, following a format resembling computational notebooks. We refer to this online lesson format as the code review notebook format. Through a case study comprising an online lesson on code quality standards completed by 23 university students, we evaluated the usability of the CRA and the code review notebook format, obtaining positive results for both. These results are a first step toward integrating code review notebooks into software engineering education.

A blueprint for integrating task-oriented conversational agents in education

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Basile Spaenlehauer, Denis Gillet

Proceedings of Conversational User Interfaces (CUI) 2022, 26-28th July 2022, Glasgow, UK

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Résumé:

Over the past few years, there has been an increase in the use of chatbots for educational purposes. Nevertheless, the chatbot technologies and architectures that are often applied to educational contexts are not necessarily designed for such contexts. While general-purpose chatbot technologies can be used in educational contexts, there are some challenges specific to these contexts that need to be taken into consideration. Namely, chatbot technologies intended for education should, by design, integrate directly within online learning applications and focus on achieving learning goals by supporting learners with the task at hand. In this paper, we propose a blueprint for an architecture specifically aimed at integrating task-oriented chatbots to support learners in educational contexts. We then present a proof-of-concept implementation of our blueprint as a part of a code review application designed to teach programming best practices. Our blueprint could serve as a starting point for developers in education looking to build chatbot technologies targeting educational contexts and is a first step toward an open chatbot architecture explicitly tailored for learning applications.

Supporting developers in creating web apps for education via an app development framework

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Denis Gillet

Proceedings of 8th International Conference on Higher Education Advances (HEAd’22), 14-17 June 2022, Valencia, Spain

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Résumé:

As more educational activities are conducted online, the need for interactive applications (apps) that can effectively support educators in their practice is increasing. These apps are often created by web developers or by researchers, educators, and even students with programming experience. While a large body of work has focused on incorporating these apps into educational contexts, fewer studies have focused on their development. In this paper, we first present the design and implementation of an app development framework aimed at supporting developers in creating apps for education. We then report the results of a study comprising interviews with 12 developers who used the framework. Our findings highlight that while the creation of web apps for education can be facilitated by a purely software-based app development framework, effectively exploiting such a framework requires domain knowledge that could be acquired through in-depth documentation, tutorials, and collaboration between developers and educators.

A configurable serious game for inhibitory and interference control

Conference ArODES

Houda Chabbi, Sandy Ingram, Florian Hofmann, Vinh Nguyen, Yasser Khazaal

Proceedings of 24th International Conference on Human-Computer Interaction (HCII), 26 June - 1st July 2022, Gothenburg, Sweden (Virtual Event)

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Résumé:

Psychological disorders are often associated with a lack of inhibitory and interference control. In this paper, we present the software architecture design of a configurable serious game dedicated to inhibitory and interference control tests. The proposed architecture is based on generic components that are reusable across different game platforms and modes. Our design enables mental health practitioners to easily configure the serious game to adapt it to their test objectives and patients’ profile. The proposed game facilitates the tracking and analysis of inhibitory and interference control and their evolution over time, as data is logged over different gaming sessions. As a proof of concept, we implement a pilot application based on the proposed architecture, in both the 2D and VR modes. The developed application implements a gamified Stop Signal task (SST) augmented with interferences. We report the results of an empirical study assessing the perceived usability of the 2D and VR pilot games, using a standard usability test.

An exploratory study of reactions to Bot comments on GitHub

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Basile Spaenlehauer, Xinyang Lu, Denis Gillet

Proceedings of 4th International Workshop on Bots in Software Engineering (BotSE 2022) in conjunction with the 44th International Conference on Software Engineering (ICSE 2022), 9 May 2022, Pittsburgh, PA, USA (Virtual Event)

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Résumé:

The widespread use of bots to support software development makes social coding platforms such as GitHub a particularly rich source of data for the study of human-bot interaction. Software development bots are used to automate repetitive tasks, interacting with their human counterparts via comments posted on the various discussion interfaces available on such platforms. One type of interaction supported by GitHub involves reacting to comments using predefined emoji. To investigate how users react to bot comments, we conducted an observational study comprising 54 million GitHub comments, with a particular focus on comments that elicited the laugh reaction. The results from our analysis suggest that some reaction types are not equally distributed across human and bot comments and that a bot’s design and purpose influence the types of reactions it receives. Furthermore, while the laugh reaction is not exclusively used to express laughter, it can be used to convey humor when a bot behaves unexpectedly. These insights could inform the way bots are designed and help developers equip them with the ability to recognize and recover from unanticipated situations. In turn, bots could better support the communication, collaboration, and productivity of teams using social coding platforms.

Impersonating chatbots in a code review exercise to teach software engineering best practices

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Basile Spaenlehauer, Vandit Sharma, Maria Jesus Rodriguez-Triana, Denis Gillet

Proceedings of the 2022 IEEE Global Engineering Education Conference (EDUCON), 28-31 March 2022, Tunis, Tunisia

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Résumé:

Over the past decade, the use of chatbots for educational purposes has gained considerable traction. A similar trend has been observed in social coding platforms, where automated agents support software developers with tasks such as performing code reviews. While incorporating code reviews and social coding platforms into software engineering education has been found to be beneficial, challenges such as steep learning curves and privacy considerations are barriers to their adoption. Furthermore, no study has addressed the role chatbots play in supporting code reviews as a pedagogical tool. To help address this gap, we developed an online learning application that simulates the code review features available on social coding platforms and allows instructors to interact with students using chatbot identities. We then embedded this application within a lesson on software engineering best practices and conducted a controlled in-class experiment. This experiment examined the effect that explaining content via chatbot identities had on three aspects: (i) students’ perceived usability of the lesson, (ii) their engagement with the code review process, and (iii) their learning gains. While our findings show that it is feasible to simulate the code review process within an online learning platform and achieve good usability, our quantitative analysis did not yield significant differences across treatment conditions for any of the aspects considered. Nevertheless, our qualitative results suggest that students expect explicit feedback when performing this type of exercise and could thus benefit from automated replies provided by an interactive chatbot. We propose to build on our current findings to further explore this line of research in future work.

2021

Learning finance with games :

Conference ArODES

an empirical study

Nicole Baudat, Sandy Ingram, Rania Islambouli, Philippe Masset, Jean-Philippe Weisskopf, Miharisoa Andrianantenaina

Proceedings of CSCI 2021 : The 2021 International Conference on Computational Science and Computational Intelligence, 15-17 December 2021, Las Vegas, USA

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Résumé:

This paper presents an empirical case study on applying game-based learning in an undergraduate finance course. The paper describes the experimental study context, protocol, and results. Using multivariate regression analysis, a significant game effect on student performance is observed for competitive strategy-based games.

Is your time well spent online ? :

Conference ArODES

focusing on quality experiences through a user-centered recommendation algorithm and simulation model

Sandy Ingram, Rania Islambouli, Denis Gillet

Proceedings of ICMLA 2021, International Conference on Machine Learning and Applications, 13-16 December 2021, virtual event

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Résumé:

Spending an uncontrolled quantity and quality of time on digital news and social media platforms can negatively influence mental health and decrease cognitive abilities. In this paper, we propose a sequential news recommendation system employing deep reinforcement learning to capture the user’s short and long-term interests while blending social news with microlearning informative news items that can help users derive useful outcomes out of their online presence. In the absence of a publicly available dataset, we developed a simulation model to synthesize data and evaluate the proposed news recommendation system. We train and evaluate our model on synthesized data and show an improvement in user satisfaction.

An end-to-end data pipeline for managing learning analytics

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Joana Soares Machado, Pedro Torres da Cunha, Denis Gillet

Proceedings of 19th International Conference on Information Technology Based Higher Education and Training (ITHET), 4-6 November 2021, Sydney, Australia

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Résumé:

Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tools that support researchers with these tasks and present a blueprint for how these tools can be integrated with existing platforms, enabling researchers to run studies within learning environments, adhere to legal and ethical privacy frameworks, and share their anonymous or anonymized data with a wider audience. We demonstrate the integration of these features into an existing online learning platform.

Conveying the perception of humor arising from ambiguous grammatical constructs in human-chatbot interaction

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Vandit Sharma, Denis Gillet

Proceedings of HAI '21: Proceedings of the 9th International Conference on Human-Agent Interaction, 9-11 November 2021, Virtual Event, Japan

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Résumé:

Chatbots have long been advocated for computer-assisted language learning systems to support learners with conversational practice. A particular challenge in such systems is explaining mistakes stemming from ambiguous grammatical constructs. Misplaced modifiers, for instance, do not make sentences ungrammatical, but introduce ambiguity through the misplacement of an adverb or prepositional phrase. In certain cases, the ambiguity gives rise to humor, which can serve to illustrate the mistake itself. We conducted an online experiment with 400 native English speakers to explore the use of a chatbot to harness such humor. In an interaction resembling an advanced grammar exercise, the chatbot presented participants with a phrase containing a misplaced modifier, explained the ambiguity in the phrase, acknowledged (or ignored) the humor that the ambiguity gave rise to, and suggested a correction. Participants then completed a questionnaire, rating the chatbot with respect to ten traits. A quantitative analysis showed a significant increase in how participants rated the chatbot’s personality, humor, and friendliness when it acknowledged the humor arising from the misplaced modifier. This effect was observed whether the acknowledgment was conveyed using verbal, nonverbal (emoji), or mixed cues.

A user centered news recommendation system

Conference ArODES

Sandy Ingram, Rania Islambouli, Denis Gillet

Proceedings of 4th Workshop on Human Factors in Hypertext, 30 July- 3 August, 2021, Virtual Event, Ireland

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Résumé:

Spending an uncontrolled quantity and quality of time on digital information sites is affecting our well-being and can lead to serious problems in the long term. In this paper, we present a sequential recommendation framework that uses deep reinforcement learning to capture the users' short and long-term interests, with a proposed use case of blending social news with recommended micro-learning informative news items that can help users derive useful outcomes out of their presence online.

Well-being at work :

Conference ArODES

applying a novel approach to comfort elicitation

Florinel Radu, Sandy Ingram, Jean-Philippe Bacher, Nicole Jan, Uchendu Nwachukwu

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An integrated approach to learning analytics

Conference ArODES

Sandy Ingram, Juan Carlos Farah, Uchendu Nwachukwu, Denis Gillet

Proceedings of FECS'21 - The 17th International Conference on Frontiers in Education: Computer Science and Computer Engineering, 26-29 July 2021, Las Vegas, USA

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Résumé:

Despite the rise in services generating learning analytics, there is a lack of standard models and guidelines for data integration and aggregation to inform the design choices of applications supporting learning analytics. We propose a bottom up, user-driven apporach enabling educators to select, match, and contextualize activity traces from several data sources to perform and visualize meaningful learning analytics. To facilitate the process, the proposed apporach recommends building customized auxiliary plugins that can be shared and re-purposed. We present the implementation of a use case following this approach. This use case focuses on supporting the import and side-by-side comparison of activity traces from multiple data surces that teachers might use in their practice. Implications of this approach on cross-platform learning analytics and future work are discussed.

Réalisations

Recherche

Ingram Sandy

Professeure HES ordinaire

Compétences principales

Human Computer Interaction

Recommender Systems

Centre de Compétences Numériques

deep reinforcement learning

Technology Enhanced Learning

User Experience Design (UX)

Professeure HES ordinaire