Nonverbal Communication as a Means to Support Collaborative Interaction Assessment in 3D Virtual Environments for Learning

In the classrooms at school, when a group of students is working in a predetermined task, the teacher or the tutor identifies some problems related to collaboration by observing the students’ behavior. While interacting, people interchange messages composed of speech, actions and gestures, as the wordless messages emphasize, support or even substitute speech. In 3D collaborative virtual environments (CVE), the user’s graphical representation, an avatar, is the means to express this nonverbal communication (NVC). The authors’ proposal is that, like in a real learning scenario, by the observation of specific NVC cues, indicators of collaborative interaction can be inferred to an extent that they can be used to foster collaboration, if necessary, in a learning task situation. The various NVC cues that have been selected for that purpose and their corresponding collaborative learning interaction indicators will be presented. An exploratory study that consisted in the analysis of a real life situation during a collaborative task accomplishment, directed to the development of an experimental 3D CVE desktop application that allows avatars’ display of NVC cues, will be discussed.

Web-Based Multimedia Tools for Monitoring and E-Learning

This chapter is devoted to the application of Web-based multimedia tools as a complement to traditional e-learning resources to improve the quality of teaching in two senses: adapting lesson contents to improving the understanding and increasing the motivation of the students. The authors present a set of practical tools that have achieved successful results in their courses and that, together, provide a more proactive teaching methodology based on interactive and mobile learning materials. These tools can be divided into two main groups: simulations and interactive videos, directly related to the process of studying, and quizzes and questionnaires, useful to adapt the teaching to the objective comprehension level. In addition, the authors point out the advantages of providing the students with more familiar multimedia materials suitable for being transported and consulted in mobile devices. A basic point of this methodology is that all these resources are available through a Web-based interface, so that the interaction does not depend on the physical presence of the students. Finally, the authors must point out that with their methodology they are focused on monitoring learning, which is achieved directly with online questionnaires, but they have also performed resource monitoring, in terms of degree of satisfaction and practical use. This is achieved, in this case, through the use of surveys and from the analysis of the statistics provided by the Web-based application.

Monitoring Students' Activity and Performance in Online Higher Education

In this chapter the authors first explain the recently created European Higher Education Area and its implications over instructors’ and students’ roles. They also analyze how e-learning management systems are contributing to modify higher education around the world, and which are the benefits and the challenges associated to their use. In this new educational scenario, the authors discuss the importance of monitoring students’ and groups’ activity and performance, and some of the monitoring tools already available in the most popular learning management systems are reviewed. Then, after identifying the informational necessities of online instructors and students, the authors propose a data-analysis model to assist instructors by providing them with easy-to-understand and updated visual reports. Instructors can use these reports to classify students and groups according to their activity and learning outcomes, track their evolution, and identify those who might need immediate guidance or assistance.

Improvement of Self-Assessment Effectiveness by Activity Monitoring and Analysis

Self-assessment is one of the crucial activities within e-learning environments that provide learners with feedback regarding their level of accumulated knowledge. From this point of view, the authors think that guidance of learners in self-assessment activity must be an important goal of e-learning environment developers. The scope of the chapter is to present a recommender software system that runs along the e-learning platform. The recommender software system improves the effectiveness of self-assessment activities. The activities performed by learners represent the input data and the machine learning algorithms are used within the business logic of the recommender software system that runs along the e-learning platform. The output of the recommender software system is represented by advice given to learners in order to improve the effectiveness of self-assessment process. The methodology for obtaining improvement of self-assessment is based on embedding knowledge management into the business logic of the e-learning platform. Naive Bayes Classifier is used as machine learning algorithm for obtaining the resources (e.g., questions, chapters, and concepts) that need to be further accessed by learners. The analysis is accomplished for disciplines that are well structured according to a concept map. The input data set for the recommender software system is represented by student activities that are monitored within Tesys e-learning platform. This platform has been designed and implemented within Multimedia Applications Development Research Center at Software Engineering Department, University of Craiova. Monitoring student activities is accomplished through various techniques like creating log files or adding records into a table from a database. The logging facilities are embedded in the business logic of the e-learning platform. The e-learning platform is based on a software development framework that uses only open source software. The software architecture of the e-learning platform is based on MVC (model-view-controller) model that ensures the independence between the model (represented by MySQL database), the controller (represented by the business logic of the platform implemented in Java) and the view (represented by WebMacro which is a 100% Java open-source template language).

Monitoring Activity in E-Learning

In this chapter the authors will focus on the monitoring of students’ activities in e-learning contexts. They will start from a socio-cultural approach to the notion of activity, which is conceived of as a context composed by actions, which, in turn, are composed by operations. Subsequently, the authors will propose a model for monitoring activities in e-learning, which is based on two principal measures. Firstly, they will take into consideration specific data collected through Web tracking, which they will elaborate further in order to obtain indicators that do not simply express frequencies, but that measure individuals’ actions within a Web environment. Secondly, the authors will suggest a possible application of social network analysis (SNA) to Web interactions occurring in collective discussions within Web environments. In the model that the authors will present, Web tracking data are considered as indicators of individual actions, whereas SNA indices concern two levels: collective indices referring to the activity carried out by groups and individual indices referring to the role that members play in collective e-learning activities.

Time-Shifted Online Collaboration

This chapter examines online collaboration in a distributed e-learning environment. The authors describe the emerging technology of Web-based automated essay grading that provides extensive real-time data for monitoring and enhancing e-learning activities. They examine data from student use of this software service in a large introductory social science class. Using information routinely collected by the system, the authors find that students take advantage of this learning environment to revise and resubmit essays, dramatically improving their final grade by an average of 20% or two letter grades. They conclude the essential components of this learning environment that makes it so successful are its ability to provide detailed, personalized feedback to students immediately after they submit their work along with the opportunity to revise and resubmit. This transforms an automated assessment tool into a powerful collaborative learning environment. Instead of waiting days or weeks for instructor comments, that feedback is time-shifted to occur at the time it can be most effective for students. Changing the timing of feedback creates a powerful teachable moment when students have motivation, information, opportunity, and feedback. They are motivated to improve their grade, they are told what they did right or wrong while the relevant information is fresh in their minds, and they have the opportunity to revise and resubmit. The chapter ends with consideration of how those same elements can be, and sometimes already are, used in other instructional strategies such as podcasting to create effective learning environments that take advantage of the teachable moment.

Virtual Co Learner

Adaptation and personalization of the information and instruction offered to the users in on-line e-learning environments are considered to be the turning point of recent research efforts. Collaborative learning may contribute to adaptive and personalized asynchronous e-learning. In this chapter authors intend to introduce the Virtual co Learner (VcL) that is a system designed on a basis of distributed architecture able to imitate the behavior of a learning companion who has suitable to the user’s cognitive and learning style and behavior. To this purpose an asynchronous adaptive collaborating e-learning system is proposed in the sense of reusing digitized material which deployed before by the users of computer supported collaborating learning systems. Matching real and simulated learners who have cognitive characteristics of the same type, one can find that learning procedure becomes more efficient and productive. Aiming to establish such VcL, one faces a number of questions. An important question is related to the user’s cognitive or learning characteristics diagnosis. Other questions are examined too.

Proposal of a Set of Reports for Students' Tracking and Assessing in E-Learning Platforms

The teaching-learning process has undergone a deep change with the appearance of new technologies. E-learning environments and, in particular, learning content management systems have provided capacities and tools which have contributed notably to this change. Their use has spread rapidly in the educational environments due to the advantages that they offer: freedom of timetable, ubiquity, tools for the communication and collaboration, etc. However, they still lack a suitable tool for the monitoring and follow-up of the students that allows the instructors, in an easy and intuitive way, to know what is happening with their distance students. This lack of knowledge is, to a great extent, the cause of a higher number of dropouts and a lower students’ performance in comparison to traditional education. Consequently, in this chapter, the authors propose a set of reports, designed from an educational point of view, which help instructors to carry out this task and an architecture software for their implementation.

A Model for Monitoring and Evaluating CSCL

This chapter tackles the issue of monitoring and evaluating CSCL (Computer Supported Collaborative Learning) processes. It starts from the awareness that most of the tasks carried out in managing, tutoring, fine tuning and evaluating online courses heavily rely on information drawn through monitoring. Information of this kind is usually needed for both the assessment of individual learning and the evaluation of a learning initiative. The development of a sound, general purpose model to organize this information serves a variety of purposes, since it makes the monitoring, assessment and evaluation processes more systematic and effective. By describing the model and providing concrete examples of its use, the goal of this chapter is to demonstrate its potential, flexibility and suitability to meet evaluators’ aims in a wide range of cases. The model gathers consolidated practices in the field and is based on the most recent findings of theoretical CSCL research.

Expertiza

Educators and accrediting agencies demonstrate a growing awareness that students learn better when they work in groups, and on projects that are more similar to those encountered on the job, where their contributions are used by others to add value to the operations of the enterprise. However, it is very time consuming to assess project work; the only scalable way to accomplish this is to have students assist in the assessment. Expertiza is a system for managing all kinds of communication that is involved in assessment: double-blind communications between authors and reviewers, assessment of teammate contributions, evaluations by course staff, and surveys of students to assess the assignment and the peer-review process. This chapter places Expertiza in context among other electronic peer-review systems, algorithms, and methodologies. It relates the results of three experiments showing that through the peer-review process, students are capable of producing work that can be used as teaching materials in later classes.