This paper describes the development of different training scenarios for engineering students on experimental laboratory platforms in the field of robotics. The system in its current configuration is designed to enable distance training of students in real scenarios of robot manipulator programming. From a technological perspective, our research efforts are directed towards the adaptation of concepts and techniques developed in thefield of telerobotics and virtual reality, and their integration in such e-laboratory settings.
The paper focuses particularly on the educational impact of such systems. Our goal is to assess the performance of elaboratory scenarios in terms of the efficacy of training provided to students. The results of two experimental studiesalready been conducted- are of main interest. The experiments on different student users are still in process.
Training, as a dynamic process, is approached according to a classical three dimensional model, and performance scores are accordingly assessed in these dimensions (namely: low-level vs. mid- and high-level skills and understanding). The obtained results reveal some differences between the three groups, particularly as related to the low-level skill training score, giving some insight about the training 'dimensions' that are expected to be mostly affected by the absence of physical (or realistic virtual) presence on a real hands-on experimentation site. Statistical analysis indicate however that, despite these apparent differences, such elaboratory modules can indeed be integrated quite effectively in practical scenarios, creating virtual training environments that can provide adequate learning elements, as related particularly to mid and high-level skill transfer. Further work and large-scale studies are still needed, though, in order to explore the extent to which such a general conclusion is valid in different training settings, and to form the basis of a more theoretical evaluation towards a comprehensive understanding of the pedagogical differences between real, virtual and remote learning/training experiences.
During the last decade we have observed a rapid development of many distance learning platforms and applications, constituting a characteristic example of the potential that is offered by new information and communication technologies (ICT), and particularly by the continuous evolution of those technologies related to the Internet.
Nowadays, teaching from a distance in a synchronous or asynchronous e-learning mode, or attending and participating in classroom lectures and seminars remotely, constitute a common practice, as those technologies are mature enough and many application platforms have already been established as a standard. The development of such applications is often based on some type of tele-conferencing (video/audio streaming) platform, with an MCU (multipoint conferencing unit) at the core of the system, enhanced by many software features such as application sharing, or other functionalities forming "virtual classroom" web-spaces.
However, in many cases, exchanging audio/video streams, sharing educational material (such as presentation slides) in a synchronous or asynchronous way, or interacting in a "virtual classroom" space, is often not adequate to complete an efficient educational program. A typical example is teaching in engineering disciplines, where hands-on laboratory experimentation is essential for enhancing and completing classroom lectures. Although the development of systems that can offer such kind of practical laboratory training courses from a distance has been in progress for almost a decade now, these efforts have been mostly sporadic or isolated and the related technological components are just now beginning to assemble into integrated platforms, with however no standardized or common solution available yet. The difficulty here is of course related to the fact that such remote and/or virtual "e-laboratory" applications involve interfacing through the network of many different physical devices and diverse experimental equipment needed to complete a real physical experiment. These devices must be remotely operated through the network, and this may call for a variety of different technological solutions depending on the type of the equipment and the real physical experiment involved.
During the last 4-5 years, a number of "remote laboratory" projects have been initiated, on a national or international basis, aiming to teach fundamental concepts in different engineering fields, through the remote operation and control of specific experimental facilities. A typical example is the project ReLAX (remote laboratory experimentation trial), funded by the European Commission within the IST framework. The goal of this project was to study the feasibility of making remote experimentation available as a component in distance learning, both from a technological point of view as well as from an economic perspective
This project proceeded with the evaluation of a new business model, the so-called experiment service provider model, proposing the establishment of a global remote laboratory network (the Cyberlab network [7]). A continuation of this effort was the eMersion project aiming to study the deployment of innovative pedagogical scenarios and flexible learning resources for carrying out virtual or remote experiments via Internet [8].
A case study of the implementation of such remote experimentation scenarios in an automatic control course is presented in[11], where useful hints concerning best practices in deploying sustainable flexible education scenarios, from academic and pedagogical perspectives, are also presented. This work is based on the development of a user-interface for remote experimentation, called the "Cockpit interface" [12], which enables the remote observation and manipulation of real mechatronic systems, such as an electric drive and an inverted pendulum.
Similar activities towards the development of virtual and remote laboratory systems are also carried out by many other academic institutions, covering various engineering fields ranging from electronics [9] and control[6], to a larger variety of mechanical and chemical engineering experimental set-ups [13]. Experience acquired from this work and from other similar initiatives (e.g. [2], [22]) reveals the difficulties and the challenges associated with the introduction and deployment of distance laboratory modules. From a technical point of view, such a goal requires adaptation of existing equipment, which must often be performed on a task specific way. Each laboratory setup -and often each associated learning scenario- may call for a different type of operation and control, which raises considerable challenges when performed remotely.
From a didactical perspective, substantial effort is still needed for assessing the effectiveness of these learning modalities compared to traditional means of "hands-on" (onsite) laboratory training. Some initial attempts to evaluate in pedagogical terms remote and virtual laboratory platforms are reported in [14], [15]. In [14], [15], a methodological evaluation approach is presented, for a distributed internet-assisted laboratory experiment. More results, however, are to be reported in the near future, in the frames of on-going international collaboration projects (such as ILabs project, between KTH - Royal Institute of Technology at Stockholm, Hannover University, and Stanford University).
Robotics is a multidisciplinary field which is taught at Departments of Electrical and Computer Engineering. It encompasses the areas of computer science, mathematics, physics, mechanical engineering, industrial engineering, electrical engineering, computer engineering, materials science, and manufacturing engineering among others. Robotics provides an opportunity to break the barriers between all the above disciplines by integrating them in a single course for engineering students; for this reason, this course is an ideal example of curriculum integration. During the robotics course students have the possibility to combine the knowledge acquired in a variety of different disciplines beforehand[25].
Classical robotics courses include elements such as kinematics, dynamics and control of robot manipulators and robot building concepts. The overall goal of the robotics theoretical course is to offer the students an introduction to the state of the art and technology of robotics and its applications for productivity gain in the industrial field. Robotics offers an opportunity to apply many engineering concepts to practical situations; as a result, they could be considered as an invaluable teaching tool for all aspects of the Engineering field [25].
The main challenge and difficulty in the development of an undergraduate course in Robotics has been to organise the laboratory course in terms of methodology and training scenarios in order to meet the educational needs of different target teaching groups (laboratory, remote, real). Moreover, another aim is to take advantage of the devices and platforms used during a robotics laboratory course, which are considered to be very expensive equipment [23].
Taking into consideration the trends in the direction of teaching robotics during the last years, our effort is to develop different learning scenarios and assess them in order to combine the beginning classical robotics course with the ongoing laboratory hands-on experimental training for an effective students' training. Such a training aims to teach students classical robotics concepts, such as robot manipulator kinematics, dynamics and control, and, furthermore, to help them acquire relevant skills[23]. Through the robotics laboratory course our efforts are to experiment with different pedagogical approaches and training scenarios and assess the degree to which they can be incorporated in the traditional engineering curriculum. Collaborative learning and peer-tutoring methods are used to fulfil the above purpose.
Remote laboratories offer remote access to real laboratory equipment and instruments. The common principle of remote laboratory experimentations is that learners can change system parameters through Internet and then a special interface converts those parameters to comprehensible and acceptable data for the local computer attached to the physical set-up. Remote laboratories are essential to e-learning platforms in scientific and technical disciplines. However, there exists a delay in their development in comparison with other (less complex) e-learning contexts, such as virtual classrooms, e-projects etc. Furthermore, remote laboratories should be interactive and support collaborative learning. The contribution of a virtual assistant to help instructor in tutoring could be valuable [27]
In classical laboratory training, one can distinguish three system categories, according to their degree of correspondence with real life situations. These are the following ones (adopted from Leleve[27]) :
1. Educational specific (simplified and/or adapted) systems for "zooming" on specific phenomena (typically physics or chemical experiences).
2. Realistic (sometimes at small scale) systems (for example, a replica of an industrial system such as a conveyor) which can be interpreted as physical simulators of real systems.
3. Real systems (e.g. tool machines, industrial robots).
The planning of a didactic and educational activity requires a theoretical background, cultural approach and practical effort. According to IMS "a learning design is a description of a method enabling learners to attain certain learning oblectives by performing certain learning activities in a certain order in the context of a certain learning environment. A learning design is based on the pedagogical principles of the designer and on specific domain and context variables" [26].
The didactic design requires the determination of the background (kind of student and training location), of the objectives (in terms of knowledge and competencies), of the contents and methods to approach learning, of the pre-requisites, of the necessary tools (material and activities) and of the tools for the proper evaluation of the final results and the validation of a learning project [26].
"Simulation" is used when manipulated system is virtual, based on a model run by a computer. Simulation is linked to virtual laboratories (where no physical system is used, only computer simulations) and in this aspect is complementary with remote laboratories.
In this dimension, there are two different categories of users: the active ones (when they can interact with the remote system) and the passive (when they are only observers of an experiment made by another person). The latter state is interesting for trainers to make a demo to every learner or to show to other observers how it works[27].
During the robotics laboratory course, teaching scenarios are developed by tutors and run by learners. In the end, the evaluation process takes place- as an important methodological step of the experiment- through adequate interviews and questionnaires addressed to learners.
Laboratory experiment could be implemented through educational scenarios in the following ways: a) one can imagine learners acting in a remote lab as in a role playing game in order to give them the maximum of realism, to enforce cognitive appropriation, and b) proposing on-line contextual documentation according to steps in a scenario and studied concepts [27].
As in any distance training system, the feasibility of communication between learners and instructor is essential. One has to take into account several parameters in order to implement remote lab sessions considering the location of every participant (such as: Where is the instructor? besides the platform, besides his learners or away from both? Where are learners?, together (with or without their instructor) or alone in front of their own desktop?).
This aspect is essential for synchronization with other linked training activities. It enables the automated proposing of different scenarios suited to learner's profile, needs and preferences.
Our experience reveals that during learning on our robotic laboratory platform, students are stimulated by facing unprecedented real situations, they collaborate and work cooperatively. Their low, medium and high skills are developed; their critical thinking skills are enhanced, and they can apply what they have learned in new settings.
In line with all the aforementioned, our goal in the casestudy presented in this paper was to assess performance in these dimensions comparatively for two different elaboratory systems: (a) a remote laboratory version, providing direct visual, tele-operation and teleprogramming link with a real, remotely located, robot manipulator (but with a simplistic 2D graphical user interface), and (b) a virtual laboratory interface, incorporating realistic, virtual (3D graphical) animations of the robot and programming tasks (but with no visual and tele-operation link with a real remote robot). These laboratory modalities are tested in comparison with respect to the classical "hands-on" training and experimentation on the real robot (on-site laboratory training), forming a total of three student groups participating in the controlled experiments (namely, group-I: real, group-II: remote, and group-III: virtual). In the experiment presented in this paper, these groups were formed by a total of 18 teams of 3-4 graduate-level students, who were participating in a laboratory training course on robotics (that completes a theoretical course on robot kinematics, path-planning and control).
At this point, it should be noted, particularly, that the primary focus is on realistic emulation of target-learning tasks, in order to enable students to practice realistic robot manipulator programming tasks by making the most of the functionalities and programming modalities provided by the real robotic system. In other words, students must be offered the possibility to learn how to program a real robotic system without having one at proximity, but in a way that realistically emulates how actual robot programming operations and procedures are performed in real practice.
One can then really refer to the system as providing actual "distance training", instead of a simple "familiarization" with robot motion principles. This is more clearly explained in the sequel.
The general goal of our work, as stated above, is the development of efficient virtual and remote laboratory platforms to enable student training, particularly in robot manipulation and control technologies, from remote locations via Internet. Robot manipulator arms and related mechatronic devices are not always readily available for experimentation by students in their training program. Access to such equipment for education and practical training purposes is often either limited by very specific time restrictions, or even not provided at all. Moreover, cost of such equipment makes it infeasible for many academic institutes to obtain, and related laboratory training courses are completely missing from many educational curricula. Therefore,
the benefits from providing a means for virtual and/or remote experimentation (for instance, in a "lab facilities sharing" context), are evident both from a socioeconomic point of view, as well as from an educational perspective directly related to the completeness and quality of practical training possibilities offered to all students. There are very few attempts reported in the literature aiming to develop virtual and remote (webbased) laboratory systems in the particular field of robotics education.
One of these is described in [17], presenting a platform that includes, among other virtual (simulated) experiments, the control of a simple 2-dof robotic arm. This was based on a java applet performing kinematic simulation of the robot arm motion (with 2D only graphical animation).
Simple motion commands can be issued at the joint trajectory level and can be used to convey basic principles of robot motion characteristics. The system illustrates basic web-based virtual laboratory concepts, but only in simulation (i.e. with no remote real robot in the loop).
On the contrary, [5] presents a Java-based interface providing the functionality both to simulate and teleoperate a robot manipulator. This system can be thus used to practice movement commands of a simulated and/or remote robot manipulator, and can supposedly convey in a more efficient way the same basic concepts of robot motion control.
From a literature survey in this field, we can thus state in general that existing virtual or remote robotic laboratory systems are very few and provide some limited spectrum of functionalities in the sense of: (a) simulating and animating (in 2D or 3D) the motion of simple robot arms, (b) practicing movement commands, which are usually issued either as desired end-effector's position in -xy coordinates, or even directly as desired angles in the robot's joint-space, and eventually (c) submitting these commands for execution by a remotely located real robot. Such functionalities can indeed demonstrate and teach students the basic principles of robot manipulation and control. However, programming a real robot arm to perform a specific manipulation task (e.g. a pick-andplace task in an assembly sequence) is usually more complicated than that. The human operator should often resort in programming the task directly using the robot's own programming language usually some script-like interpreter language, such as VAL, V+ etc.); more often, however, an on-line robot programming scheme is employed, for instance using the robot's Teach Pendant tool, in order to teach (record) the intermediate configurations that will constitute the complete robot motion sequence.
Taking into account all these considerations, we directed our work towards the development of an e-laboratory platform that will train students how to program a robot manipulator arm, using the functionality and programming modalities provided by the real robotic system. For the case study that is treated in this paper, we consider the task of programming a robot manipulation task using the functionality of the Manual Teach Pendant. The robot used is a SCARA-type AdeptOne-MV manipulator, which is particularly suitable for assembly operations such as typical pick-and-place tasks, which is the case considered in our experiment.
Thus, the key issue to be emphasised is the support of real robot programming modalities within a virtual/remote laboratory platform, with the main objective being to provide students with real practical training on how to actually create and issue a complete robot manipulation program in a real-world task scenario.
The following goals are set among others: (a) to explore the potential and applicability of tele-operation technologies in such distance training scenarios, and (b) to evaluate, principally from a pedagogical point of view, to which extent different remote and/or virtual laboratory scenarios can be efficiently implemented in practice and used by students to obtain practical training additionally to their theoretical modules. In the rest of this Section we describe the main technological (design and implementation) features of the two prototype platforms used in the experimental evaluation study presented in this paper: the first one (remote lab) supporting real robot tele-programming using an emulation of the manual teach pendant of the robot, while the second one (virtual lab) supporting in addition interactive, virtual (simulated) robot animations.
In Figure 2 above, the overall architecture of the Virtual Remote Robot Laboratory platform is presented.
Keeping in mind the various initiatives towards the development of remote laboratory modules worldwide, some of which are cited above, we pursue our research focusing mainly on the following two goal directions:
a. From a technological point of view, we aim to develop platforms that will enable both virtual and remote laboratory training scenarios, related to the operation, programming and control of complex mechatronic devices such as
"robot manipulators". At this point, the use of the terms virtual and remote, in describing differrent dimensions of what can be more generally termed "e-laboratory" platforms, should be clarified.
Virtual laboratory as the term refers to the use of graphical user interfaces that incorporate interactive simulation techniques (particularly realistic 3D graphics animations), but providing no visual or tele-operation link to a real (remote) physical system (only simulation of the physical system is on the loop). On the contrary, a remote/distance laboratory platform involves tele-operation of a real, remotely located, physical system (e.g. a tele-robot), including visual and data feedback from the remote site (that is, involving some type of "tele-presence" to the remote site). Our research in the direction of designing and developing such systems focuses principally on the adaptation of concepts and technologies developed in the field of tele-robotics, and on exploring their implementation in remote laboratory settings. Robot teleoperation technologies have been constantly advancing and evolving for more than two decades now [25]. Initial tele-operation systems were deployed in dangerous and hostile environments (e.g. in the nuclear industry for the tele-manipulation of radioactive material). With the advent of communication and networking technologies, as well as with the development of new human-machine interactive simulation media, particularly virtual reality systems [3], research in the field of tele-robotics has shown considerable progress, with new concepts proposed and demonstrated with success, such as "predictive displays"[1], "shared autonomy" tele-operation control[4], or the "hiddenrobot" concept [18].
b. From an educational point of view, teaching robot manipulation principles involves the familiarization with a variety of mechanical and control engineering concepts and skills, such as for instance task- vs. joint-space control of serial kinematic chains, programming and executing motion sequences to perform a desired manipulation task etc.
We aim to evaluate, principally from a pedagogical perspective, to which extent a combination of remote and/or virtual laboratory scenarios can be effectively implemented in practice and used by students to obtain practical training as a supplement to theoretical courses. A literature review shows that the majority of the research results in this direction are restricted either in a qualitative type evaluation or in a "usability-oriented" approach. On the contrary, we prefer to give emphasis on the didactical perspective in our evaluation approach, based on specific experimental protocols, combining qualitative and quantitative metrics.
A principal focus of the research is, thus, to assess the performance of such e-laboratory systems, in terms of the 'quality'/'efficacy' of training provided to students, comparatively for various training modalities. This can achieved by conducting experimental evaluation studies with different versions of the platform, supporting various combinations of "learning elements" integrated in the graphical user interface (virtual and/or remote control, information feedback, interactive visualization modes, etc.).
In our evaluation methodology, emphasis is given on the didactical/educational perspective of the learning process, to measure efficiency and efficacy of the elaboratory system, from the viewpoint of training. Quantitative performance measures are obtained through the use of a scoring chart especially designed for the considered target training task.
The keyword here is training, which is often approached and modelled as a three-dimension dynamic process, namely that of building awareness, knowledge, and skills [21], [16].
As mentioned in previous sections, our goal at a first stage was to validate the usability and, in particular, to assess the performance of the e-laboratory concepts presented in the paper, in terms of providing adequate "distance training" to the students. In accordance with this goal, the key issue on which our research focused was the evaluation (principally from a didactical perspective) of the relative efficacy of the different virtual and remote laboratory training scenarios proposed in this paper. Our objectives are: (i) to explore to which extent such distance e-laboratory modalities can be efficiently implemented in practice and used by students to obtain practical training as a supplement to a theoretical course module (in our case, an introductory course on robotic manipulation), and (ii) to explore the relative importance of various e-learning elements, particularly virtual vs. remote training modules in comparison with traditional hands-on experimentation. Of course, the context of this work is a continuous effort to contribute towards efficient engineering educational paradigms, which in this casestudy would suggest a more efficient exploitation of existing laboratory equipment by means of remote laboratory modules within a "lab-facilities sharing" network.
For all these reasons, we conducted a pilot study that comprised three student groups, each one trained using a different learning modality, but all of them assessed in exactly the same way to obtain comparative quantitative evaluation scores.
For the pilot study presented in this section, a strict methodological process was followed, since experimental and assessment programs require specific activities in order to be effective and meet the goals that have been set. Furthermore, an effective experimental program should measure what it was designed for, and accomplish this through consistent and understandable tasks. A review of the related literature highlights that any evaluation process in engineering education should follow a structured procedure providing all the participants a clear direction and understanding of the appropriate steps required to develop and implement an effective assessment program [20], [19].
In order to assess the objectives and goals that were set in this experiment, a combination of quantitative and qualitative methods were used. For this purpose, we have designed a special experimental evaluation protocol, which was used consistently throughout the experiments. According to this protocol, the students participating in the laboratory training course (that completes a theoretical introductory course on robot kinematics, path-planning and control) were divided into three main groups: group-I (real) was trained the "traditional way" on the real robot, while experimental group-II (remote) was trained on the first version of the remote laboratory platform (using the interface described in section II-B), and experimental group-III (virtual) was trained on the virtual robot laboratory, as described in section II-C. Each group was subdivided in six teams of three to five students. Each team of students was trained separately in different laboratory time slots (approximately 1h 30min per each). The total number of the sample of this pilot study was 60 (N) students. Both groups of students had undergone the same training phases and were exposed to exactly the same educational material by the trainer during each experimental session, with the only difference between groups being the modality used to practice the robot programming procedures learned, that is: (i) directly on the real robotic system (group-I real, i.e. physical presence on the real-robot site), (ii) using the remote laboratory platform (group-II remote, i.e. tele-presence), or (iii) using the virtual robot interface (group-III, virtual presence).
Each training session lasted approximately one hour and a half, with the tutor (always physically present) explaining all key issues to the students. Tutorial and educational support material was provided to the students describing: (i) the robot used in the experiment (its mechanical and kinematic characteristics, as well as its control and programming features) and (ii) the exact procedure and steps to follow to program a robot manipulation task using the pendant.
During each training session, two simple tests were performed by the students to assess their learning progress and the needs for further tutoring, as well as to motivate students' initiative in specific problem solving situations.
Such intermediate tests can also be used to track differences in the learning curve between different experimental groups, but such an evaluation study, regarding laboratory training as a dynamic process in time, is not included in this paper and is left as a future work option. By the end of each training session, students belonging to all three groups completed their training by performing a specific experimental evaluation test on the real robot (test- 3, final assessment test). During this final test, a robot programming task was assigned to the students (a pick and- place operation using the real robot teach-pendant). It must be emphasized here that this final assessment test was performed on the real robot for all three student groups (meaning that group-II and group-III students had to move from a remote location - separate building- to the real robot laboratory site to perform the final assessment tests). The test was subdivided into distinct time phases, to facilitate tracking the performance of the students and identifying errors committed and/or difficulties encountered. In order to help the trainer (examiner) assess students' performance during the final test, a specially designed scoring chart was used. This was organized in a sequence of rows, tracking the distinct time-phases, sub-tasks and manual operations involved in the final assessment task assigned to the students, and columns, corresponding to the different categories of skills (respectively errors) monitored by the trainer during the test. In line with our research objectives, the errors committed by the trainees were classified according to three main categories: low-level technical skills, mid-level skills, and higher-level understanding (with different weights assigned to them). The method used to consistently grade students' performance consisted of assigning a pre-specified "penalty grade" for each specific error committed. Moreover, team work between students (performing the experimental session in teams of 3-5 individuals) was qualitatively monitored, while total time needed to complete each phase of the test was also recorded. All these scoring items (indicating the frequency of the different types of mistakes) were coded in real-time on the scoring chart by the tutor monitoring the experiment, and were subsequently decoded to compute the final values for the different scores. For each final assessment test, a total score was computed giving a global measure of performance for the respective team of students, while individual categories scores give an idea of the type of difficulties encountered by the students, with respect to the three main dimensions used to model the dynamic process of training (often referred to as the triad of training).
As it was already mentioned above, during the students' assessment process the tutor noted down in the scoring chart the mistakes committed by them, according to the three categories described above. This categorization constitutes a first qualitative approach to this experiment. Based on the scoring chart and the associated penalty grades, a quantitative analysis followed by means of specific statistical techniques; for this reason we used S.P.S.S., version 12, to obtain statistical analysis results.
More specifically, t-test of independent groups was followed in order to find out whether there exists statistically significant difference between the Means of the various test scores (low, mid, high, time and total) for the two groups (group-I: local and group-II: remote); group is the independent variable and score values are the dependent variables; the criterion that was set for the statistical significance was p<0.05. In the following tables, we note that the scores correspond to penalty grades, meaning that higher score values indicate worse performance of the student; scores correspond to absolute penalty grades values, since it was not considered necessary to transform the penalty scores into relevant percentiles.
The mean values of the test-3 scores for both groups are also illustrated as a bar graph in Figure 3. A review of Means shows that there exist some apparent differences between the two groups for the three different score categories in test 3. Indeed, in the "low" category - representing errors committed related to low level technical skills, as described earlier- group I (local) students made very fewer mistakes compared to students of group II (remote). This could be explained by the fact that students forming the "local" group were trained the traditional way on-site, in physical contact with the real robot manipulator system, as opposed to group-II students who were trained remotely using the graphical user interface. Therefore, as it could be expected, group-I students exhibit a better "memorisation" of low-level technical dexterities, and thus better performance in the manipulation of the robot's teach pendant. Such skills require a visual memorisation of specific actions (e.g. button pressing etc.), which was facilitated when the student training (i.e. the skill acquisition process) was performed while in direct visual contact with the real system. On the contrary, group-II (remote) students had to rely, for their training, on the visual and "functional" quality of the virtual pendant (emulation) panel, which apparently influenced to some extent the skill acquisition process.
This is not the case for the mid- and high-level category skills, where the local group (group I) exhibited higher scores compared with the remote group (group II), though differences are much smaller (see table 1). This could be partially explained by the fact that students trained on a virtual environment appeared to have a better concentration and motivation level (as compared with students of the "local" group), which apparently aided them to assimilate higher-level concepts to a better extent. However, these differences are non statistically significant, which is due to the fact that midand higher-level skills are basically conveyed by the tutor (trainer), who was continuously physically present for both student groups (no tele-tutoring or e-tutoring took place, as already mentioned). Thus, one can conclude that the remote laboratory platform, with its graphical user interface, created a virtual training environment, which on its whole (integrating the various interactive control and visualisation panels) provided adequate learning elements, as related to mid and high level skills, compensating for the lack of direct physical presence on the real robot site.
Indeed, according to the results of T-test, no statistical significance was found (p<0.05) between the two groups in the final assessment's test scores (low: value t= -2.085, p=0.071; mid: value t= -0.606, p=0.561; high: value t= 0.175, p=0.865; total score: value t=-1.033). This means in fact that the performance of both student groups is similar in terms of the scores obtained in the final assessment test. In other words, all student teams from both groups (local/traditional and remote/experimental) performed equally well in statistical terms, with no significant deviations observed that can be attributed to the different type of training of each group (besides the minor differences discussed above). This result confirms the conclusion drawn above, that a remote laboratory platform, such as the one developed and implemented in this pilot
We have described the development and experimental evaluation of a "virtual and remote laboratory platform" in the field of robotics. The system in its current configuration is designed to enable distance training of students in real scenarios of robot manipulator programming. Our research efforts focus on the adaptation of concepts and technologies developed in the field of telerobotics and virtual reality, and on exploring their implementation in such remote laboratory settings. The experimental platform presented in this work was implemented based on Java technologies. The graphical user interface incorporates, among other features, a "Virtual Pendant" panel providing an exact emulation of the real robot's Teach Pendant functionality. The learning aim is to offer students the possibility to learn how to program a real robot without having one at proximity, in such a way that closely resembles the real robot programming operations and procedures. .
A pilot experimental study was conducted to evaluate system performance in remotely training students to program robot manipulation tasks. In our evaluation approach, emphasis is given on the didactical perspective of the system, based on specific experimental protocols combining qualitative and quantitative metrics. We aim to assess the effectiveness of these new media compared with traditional hands-on laboratory training scenarios. The experiments were conducted according to a specially designed evaluation protocol, using scoring charts to assess performance of the student groups participating in the laboratory-training course. Statistical analysis (t-test) of independent groups was performed to find out whether there exists statistically significant difference between the means of the various performance scores obtained for two student groups: group-I (local) trained the traditional way on the real robot, and group-II (experimental) trained using the remote laboratory platform. Results show that, despite some apparent differences mainly for the score category regarding low-level technical skill transfer, no statistically significant differences exist between the two student groups.
Thus, the main experimental result can be summarized by the following statement: the proposed remote laboratory platform created a virtual training environment, which provided adequate learning elements, as related particularly to mid and high level skill transfer, compensating for the lack of direct physical presence on the real robot site. We insist here on the fact that the results presented in this paper provide conclusions about performance comparison between the different student groups participating in the specific pilot study context analysed above. Despite the fact that we certainly do not assert that these initial results lead to a general conclusion about what one should definitely expect in a completely different didactical context (as this would require a largerscale sample and experimental procedure, which remains one of our key future work priorities), we do believe however that these results are helpful and insightful, indicating that such remote laboratory platforms can indeed be implemented quite efficiently and effectively. It should be noted at this point that there is also need for a more comprehensive evaluation between real, virtual and distant laborator y experimentation; this remains in our future plans to contribute towards a more profound understanding of the theoretical pedagogical basis of different laboratory experiences.
Having explored, to some extent, important factors related to the efficacy of such virtual and remote laboratory systems from a pedagogical point of view, another key issue that needs to be emphasized in the future concerns their long term deployment and the associated benefits that can result from such implementations. We refer more specifically to the concept of "lab facilities sharing" between academic and educational institutions (and not so much to other "flexible education" models). Our aim is to explore ways for a more efficient exploitation of existing laboratory experimental infrastructure to the practical training of students through the implementation of remote laboratory platforms. The benefits from providing the means to obtain remote access to experimental infrastructure, existing in various distant laboratory facilities, can become significant both from a socioeconomic point of view, as well as from an educational perspective. This is directly related to the quality and the equity of practical training possibilities offered to all students. In this context, we aim to conduct a more thorough experimental evaluation study in the near future, regarding the feasibility of these goals and the acceptability of such new technologies by students in their education and training practice.
Moreover, we are focusing on the laborator y experimental training aiming to give a motive to all instructors to experiment with different training methods and surpass the standardized classical- tutor-student student approaches.
Remote laboratory conception implies additional difficulties, compared to more traditional e-contents (virtual classrooms, e-projects). These difficulties are due to system tele-operation requirements, in synchronizing manipulations with e-learning applications, the whole within a standardized platform.
As important research work has proposed standards for traditional e-content in one hand and tele-operation techniques in the other one, the aggregation of the whole requires a certain interdisciplinarity.
This paper presented some aspects of the problem we are currently focusing on. Currently, we are exploring dynamic scenarios and current e-learning standards appropriateness.
Our ultimate goal is to provide to learners remote laboratory environments as effective as local ones (why not more?) considering cognitive criteria, and, to instructors, means and tools to improve and facilitate authoring and tutoring.
Amongst our future plans are to combine theoretical learning and laboratory training with service-learning which can offer a lot as a complement to classical classroom learning (tutor-students) Service learning could enhance the engineering curriculum by linking engineering directly to improving society, which makes the profession more appealing and more diverse. It is a teaching tool that focuses on critical thinking and problem solving, values clarification, social and personal development, and civic and community responsibility. These are all goals that are valued in engineering education and thus service learning is another pedagogical approach. Besides, industry shows a demand for engineers with a broader outlook, better team skills, a strong ethical sense and a global awareness. Working with the community partners ensures real issues and thus practical experiences. It helps the students realize the broader impact of engineering and the ethical responsibilities engineers have to the larger community [24].
In this direction, the robotics course could be enriched with further practical training where students could have the possibility to compete each other with robotic devices of their design. Such a competition will offer to students an opportunity to apply the knowledge gained and to contrast different design philosophies. In addition, the robotics laboratory course could be enriched with a students' competition in which teams of students can build robotic devices that compete against those of other teams.