2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

Cognitive engineering

In recent years, two communities have grown around a joint interest on how big data can be exploited to benefit education and the science of learning: Educational Data Mining and Learning Analytics. This article discusses the relationship between these two communities, and the key methods and approaches of educational data mining. The article discusses how these methods emerged in the early days of research in this area, which methods have seen particular interest in the EDM and learning analytics communities, and how this has changed as the field matures and has moved to making significant contributions to both educational research and practice.

/pdf/educational-data-mining-and-learning-analytics-2kepggrl5r.pdf

Educational Data Mining and Learning Analytics

Introduction Learning Management Systems (LMS) or Virtual Learning Environments (VLE) are widely used and have become part of the common toolkits of educators (Schroeder, 2009). One of the main goals of the integration of traditional teaching methods with technology enhancements is the improvement of teaching and learning quality in large university courses with many students. But does utilizing a VLE automatically improve teaching and learning? In our experience, many teachers just upload existing files, like lecture slides, handouts and exercises, when starting to use a VLE. Thereby availability of learning resources is improved. For improving teaching and learning it could be helpful to create more motivating, challenging, and engaging learning materials and e.g., collaborative scenarios to improve learning among large groups of students. Teachers could e.g., use audio and video recordings of their lectures or provide interactive, demonstrative multimedia examples and quizzes. If they put effort in the design of such online learning activities, they need tools that help them observe the consequences of their actions and evaluate their teaching interventions. They need to have appropriate access to data to assess changing behaviors and performances of their students to estimate the level of improvement that has been achieved in the learning environment. With the establishment of TEL, a new research field, called Learning Analytics, is emerging (Elias, 2011). This research field borrows and synthesizes techniques from different related fields, such as Educational Data Mining (EDM), Academic Analytics, Social Network Analysis or Business Intelligence (BI), to harness them for converting educational data into useful information and thereon to motivate actions, like self-reflecting ones previous teaching or learning activities, to foster improved teaching and learning. The main goal of BI is to turn enterprise data into useful information for management decision support. However, Learning Analytics, Academic Analytics, as well as EDM more specifically focus on tools and methods for exploring data coming from educational contexts. While Academic Analytics take a university-wide perspective, including also e.g., organizational and financial issues (Campbell & Oblinger, 2007), Learning Analytics as well as EDM focus specifically on data about teaching and learning. Siemens (2010) defines Learning Analytics as "the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning." It can support teachers and students to take action based on the evaluation of educational data. However, the technology to deliver this potential is still very young and research on understanding the pedagogical usefulness of Learning Analytics is still in its infancy (Johnson et al., 2011b; Johnson et al., 2012). It is a current goal at RWTH Aachen University to enhance its VLE--the learning and teaching portal L2P (Gebhardt et al., 2007)--with user-friendly tools for Learning Analytics, in order to equip their teachers and tutors with means to evaluate the effectiveness of TEL within their instructional design and courses offered. These teachers still face difficulties, deterring them from integrating cyclical reflective research activities, comparable to Action Research, into everyday practice. Action Research is characterized by a continuing effort to closely interlink, relate and confront action and reflection, to reflect upon one's conscious and unconscious doings in order to develop one's actions, and to act reflectively in order to develop one's knowledge." (Altrichter et al., 2005, p. 6). A pre-eminent barrier is the additional workload, originating from tasks of collecting, integrating, and analyzing raw data from log files of their VLE (Altenbernd-Giani et al., 2009). To tackle these issues, we have developed the "exploratory Learning Analytics Toolkit" (eLAT). …

Design and Implementation of a Learning Analytics Toolkit for Teachers

This article introduces this special issue by exploring the nature and
diversity of the Grounded Theory Method (GTM) and the opportunities associated with its use in Information Systems (IS) research. As guest editors for this special issue and as practicing grounded theorists, we feel that the nature of GTM is often misunderstood and its label abused in different ways. Therefore, in this editorial article, we attempt to clarify what we see as the
essential characteristics of GTM. We also present some issues that are commonly discussed among grounded theorists, but which are less well known publicly. We argue that GTM can be a powerful tool for IS scholars interested in theory development, allowing researchers to conduct pioneering research with both flexibility and rigour. This argument is illustrated by the seven papers that we have selected for this special issue. These papers represent the wide variety of ways in which GTM can be used in our field.
Further, they show how, through innovative uses of GTM, IS researchers can address some long-standing research challenges.

https://link.springer.com/content/pdf/10.1057%2Fejis.2012.48.pdf

Grounded theory method in information systems research: its nature, diversity and opportunities

This paper presents TrAVis (Tracking Data Analysis and Visualization Tools), a Web-based system that assists the students in visualizing their communication activities in distance learning situations. While most of the existing systems in the same genre are exclusively dedicated to the teachers, TrAVis is objectively designed and implemented for both teachers and students. In particular, TrAVis is considered a “reflective tool” that helps students analyze and evaluate their own activities in relation to those of others. This paper focuses on how TrAVis provides the students with new ways to monitor in real-time their individual and group activities. It also discusses the experiment in an authentic learning situation along with students’ feedback on the usability and utility of TrAVis.

/pdf/travis-to-enhance-students-self-monitoring-in-online-33lrzcffm3.pdf

TrAVis to Enhance Students’ Self-Monitoring in Online Learning Supported by Computer-Mediated Communication Tools

Purpose – Keeping track of users' communication activities in web‐based environments has always been considered a complex task. It requires tracking systems that are capable of efficiently tracking users' activities and producing tracking data that can be useful to various users. The objectives of this paper are two‐fold: to present an approach for better observing the different levels of human and computer interactions (HCI) during a computer‐mediated communication (CMC) activity; and to present the technical aspects of a web‐based tracking system for communication tools such as discussion forums.Design/methodology/approach – The research applications are applied to educational settings. Three cases of experiments with result analysis will also be presented. The paper studied different CMC tools. With the participation of researchers from different disciplines, including HCI and e‐learning specialists, we adopted the 5W1H method (When, Where, Who, What, Why, and How) and a participative method to build t...

/pdf/a-closer-look-at-tracking-human-and-computer-interactions-in-toipkfqyj6.pdf

A closer look at tracking human and computer interactions in web‐based communications

Computer Mediated Communication (CMC) tools, such as forums, chats, etc., have become compulsory for distance learning situations, in facilitating the communications between learners, and between learners and instructors. Meanwhile, tracking the communications on CMC tools has also become one among other research interests and brought up a number of challenges and difficulties: exploitation of collected traces, providing synthetic information of communication activities via trace analysis, reusability of traces, etc. Our research works are biased toward methodological challenges involved in designing and developing a generic system for tracking user's activities while interacting with asynchronous communication tools like discussion forums. The main aim of the suggested approach that we present in this paper is for building a Web-based system architecture, which is composed of different trace collectors (client side and server side), trace manipulation procedures, trace repository, trace analysis, and trace visualization.

https://hal.archives-ouvertes.fr/hal-00195947/document

Tracking, analyzing, and visualizing learners' activities on discussion forums

The paper presents the development of a multimedia adaptive interface based on the cognitive profile of a user. It describes the cognitive profile and the document architecture that have been adopted. Indeed, the user profile is generated in a stage former to the adaptation, it is structured into a separate database. As for the document, it is presented in XML files. The paper describes in detail the way these components are combined ; it presents the adaptive process. During this process, the combination of medias that best fits the cognitive profile of each user is selected. This technique is applied on a hypermedia course called "Saga du Cerveau" (The Brain Story).

Adaptive presentation of multimedia interface case study: Brain Story course

Les jeux d'entreprises constituent une formation pertinente pour la formation initiale et continue d'ingenieurs. Ils ont l'avantage d'offrir une grande liberte d'action et d'intervention aux apprenants. Cependant, le nombre de chemins possibles etant important dans de tels jeux, il n'est pas evident de proposer du premier coup la bonne structure de jeu et de definir les parametres optimums pour atteindre les objectifs pedagogiques. Actuellement, cette mise au point se fait grâce aux retours d'usage, ce qui peut prendre des mois et nuire a l'utilisation du produit. Dans le cadre de ce projet, il s'agit de concevoir un banc de tests comprenant un « simulateur de comportements d'apprenants » visant a assurer la qualite pedagogique d'un jeu des la phase de conception. Dans cet article, nous definissons des profils type de comportements de joueurs-apprenants. Nous proposons alors un modele, nomme SIMCA, de fonctionnement d'un simulateur de comportements d'apprenants pouvant etre adapte a plusieurs jeux.

https://telearn.archives-ouvertes.fr/hal-00005714/document

Simulateur de comportements d'apprenants dans le cadre de jeux d'entreprise

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