The age old learning systems can have limitations for students who could be distant or having certain limitations. Moreover, the old systems have more of theoretical knowledge that is disbursed to students. Application of the knowledge in actual physical world is rarely tested in the traditional methods of learning Use of computer devices for learning provided additional learning opportunities for students as it would expose them to large amount of the recent data that could keep them update with the latest through the use of computer interfaced technologies. This would allow them to get ahead of the traditional course and take up vocational learning.
Besides the remote learning, virtual environment is also being used in the learning systems that could actually give certain sense of reality to the learners making them experience the reality through the virtual world which makes learning an immersive experience. There are a variety of tools available for designing and implementation of virtual environments in the education systems. Moreover, they can be used at different levels of complexities starting from simple text based virtual systems to systems providing a total immersive experience.
Besides learning which is a part of the process, assessment of students learning outcomes is another major area of the education system that can be benefited with the use of the virtual systems as they could to an extent automate the process of assessment for students. Formative feedbacks can be provided against the student responses to provide assessments. The virtual environment can be used to come up with unique problems and solutions providing a student enough flexibility to experiment with Reponses in order to enhance the learning capability.
This paper proposes development of a virtual system for student assessment which can be used for any university. The idea is based on the concept of constructivist approaches that take learning not just as passive activity but an active construct which requires more of the application based learning than the theoretical learning. Based on this phenomenon, an assessment system may be designed to combine both instructional systems and the application based systems for a complete learning experience.
An Action-based Learning Assessment program can be developed providing a complete assessment system for students. This system is based on the concept of gaming in which leaning can be received in the form of action sequences that are to be practiced by a user to learn and practice learning in applications. The system would record all the actions of the learner and would compare the as with the actions of the experts of the field that would be recorded earlier so as to pride a normative feedback.
The report first presents the literature review which explores various learning theories that justify the emergence of the virtual systems of learning and how they could actually be useful from the logical perspective. Further, the paper would identify the assessment needs of the students in a virtual learning environment by exploring Action-based Learning Assessment program which would be proposed in this research paper. The paper explores the working of this system in depth providing the methods used for development and implementation. Further, the paper assesses the potential of the implementation of the virtual assessment system.
The virtual assessment system would be useful for universalities, falsities and students as it would make things faster by automating several aspects of assessment. Assessment is actually a passive process and not directly productive for faculties. The actual learning is carried out when the teacher is explaining things to students but the assessment is an important step as it would tell the level at which student is learning. However, the process of assessment may not add any direct value to the learning system except telling if the student has learnt enough. However, the outcome of assessment would add value to the learner’s life as he or she would knew where he or she stands in terms of learning. If an automated procedure could be used for such assessments, it would definitely improve the overall system allowing faculties the flexibility to come up with new ideas of assessment and instead of carrying out assessments themselves, make use of the computer programs to judge the performance of the students which would be much faster and accurate.
The traditional approach to teaching involved a programmed instructional model where information is transferred form the teacher to a student who would accumulate the knowledge to learn. The model is still primarily followed in almost all educational institutions further supported by the test systems. The objective of such a system is design a system of education with clear and well structured content in an efficient manner and it is driven by certain materials and procedures. Cognitive scientist sees it as a mental model where acquisition of knowledge is the way of understanding concepts.
Objectivist view is a student must contract his or her own knowledge with support from teachers but constructivists believe in creation of a new meaning and creating link between new ideas and existing knowledge. Focus of an approach from constructivists would be on facilitation rather than on priding clear instructions allowing a teacher take the role of a mentor. Discovery, play and imagination are considered to be the fundamental learning activities in the constructivists view. A mentor in such a situation would stimulate in students the use of initiative, playing, experimentation, reasoning and collaboration.
Vygotsky's theory combines the two perspectives including instructional design and constructivist approach to learning. This model works on the idea of the collaborative construction of knowledge. While many curriculums follow this model and have learning programs using both methods, extreme implementations of two methods are also not uncommon.
However, constructivism has only gained popularity in recent years where some educational programs supporting spontaneous and uncontrolled learning over organized and systematic delivery of knowledge. The change to constructivist instructional model would need creation of a balance between the two extreme methods. A combination of two can bring in flexibility with multidimensional instructional techniques used. Acceptance of this view by many educators has lead to development of open and informal learning systems like virtual learning environment.
Virtual reality in Education
Range o different types of virtual worlds can be created for a learning environment from simple virtual environment involving textual lessons, to no audio, to a mix of sophisticated graphics, audio, and other interactive objects. These varieties are primarily caused by the differences of presence, immersion and interactivity between different methods. Presence is just the feeling of having a virtual space experience such as virtual walkthroughs and MOOs. Immersion involves a complete submersion of visual and auditory deliveries into the virtual world using Virtual reality systems like CAVE and HMD. Interactivity refers to the capability of the system to respond to the user actions and modify the environment accordingly.
Text Based Virtual Worlds: Text based virtual worlds are the real time environment that involve multiple people that deliver lectures through the use of textual descriptions that are delivered virtually. Such environments are commonly known as Multi-User Dungeons. There could be two reasons behind encouraging the use of text based content in a virtual learning environment. One is allowing creation of community based text and second encouraging students to learn the skills of reading and writing. The involvement of community factor makes space for inclusion of social codes and group dynamics. Text-based VR can make way for virtual fiction and participants can form identities and interact with objects and characters in the story. However it has been argued that lack of physical senses like tactile, visual and auditory would make MUD an incomplete environment for learning. Moreover, student and faculties are required to learn various conventions of design and construction to create the objects taught about through the text. Mastering such art could be difficult at times.
Desktop Virtual reality: Virtual reality applications running on desktop can help students take a walk through a stimulated environment that could have been developed using commercial applications like Virtues Walkthrough. Some advanced systems may also make use of peripheral devices like tracker, plugs, headcounts, joysticks, data gloves, and so on that can increase the degree of interactivity between application and the student. However, such technologies have limitations of size and complexities they can handle. They do not provide much of immersive experience or interactive qualities. Typical desktop VR projects would be 3D multimedia simulations based on simple models. Such systems are mostly used for students with learning disabilities or special needs as they may to be able to able to experience some aspects of the physical world otherwise. Integration between such VRML systems and internet has expanded the applications of virtual reality by allowing access to the students through the network. VR software is used in classrooms for teaching kids. However, such implementations come with some major challenges like funding issues, safety problems, training requirements, curriculum restructuring, technological confusion and anxiety. These systems require beavers to convince parents and colleagues about value and relevance of virtual reality in classrooms (Bodomo, Luke, & Anttila., Evaluating Interactivity in Web-Based Learning, 2003).
Immersive Virtual Environment: These types of virtual environments can be developed with the use of high-end equipments which would be expensive and thus, require significant funding. Most immersive virtual environment projects re developed using head-mounted display systems (HMD). University of Washington was the first to adapt to this technology through its The Human Interface Technology Laboratory (HITL) where Virtual Reality Roving Vehicle (VRRV) was developed. VRRCV was used in the summer camp projects for helping students in word building activities allowing them to use 3D simulation software to create their own objects. It helps students understand process of creating virtual settings but it did not provide much of the educational benefit and thus, could be justified for the use in education setting. The actual immersive experienced gained by students from the system was only limited to 4 to 10minutes. Some of these immersive virtual systems that made use of HMDs were not even flexible to allow more than one participants. However, there are some technologies that are not limited by the use HMDs such as CAVE and ImmersaDesk but they do have limitations in terms of size and cost. There have been limited applications where CAVE was actually used to build a learning environment. CitySpace was one such project that demonstrated the use of CAVE. Immersive virtual systems have been used more in non-academic settings like Computer Museum of Boston (Roussos, 1997).
Learning Assessment with VR
Virtual reality can be used for learning assessment with computer aided grading systems. Mostly, theses grading systems deal with only textual objects but virtual systems could be re-designed to suit to the needs of discussions and assessments happening in virtual classrooms (Lazarus, 2003).
Automated text processing systems can be used for predicting class performance using a novel assessment model. Class performance evaluation in distant learning programs can also be evaluated using this model. The evaluation can be done on the basis of factors like quality of work, quantity of work, and activeness of students in class discussions or participation in other activities. An Automated text processing system would require to extract information through three types of measures including keyword contribution (KC), Message count (MC), and Message Length (ML). These measures could be combined into a linear model each of them counting to some portion of the score called performance indicator. A computer based grader may not fully replace the human instructor in evaluation but it can serve as a supplementary tool helping instructors take better decisions on performance assessment for class (Wu & Chen, ASSESSING STUDENT LEARNING WITH AUTOMATED TEXT PROCESSING TECHNIQUES , 2003).
In the virtual learning environment, a design consisting of three phases including INPUT, SYNTHESIS, and OUTPUT can be proposed. The model makes use of Action-based Learning Assessment program which focuses on assessment on certain actions taken by students that reflect upon the knowledge they gained from a class structure. These actions would be goal oriented and can include speeches, verbal actions, non-verbal actions, and gestures. Choice of action would be noted as it would also be the part of assessment. As per the Bloom’s taxonomy, actions reflect upon the learnt knowledge of a student displayed at the application level. By contributing to the assessment at the highest level of learning, Action based leaning assessment would contribute to both theory and utility allowing automation of assessment process (Naidu S, 2012).
Stealth assessment is another concept that has emerged from the field of gaming environments where user actions can be recorded continuously and assessed at the same time. Based on the same concept, Action Based Learning environment would involve recognition of certain goal oriented actions that would involve a problem solving such that student can be assessed on his or her capability to solve specific problems (Verhulsdonck G, 2012).
Choice of ALAM over other learning systems is due to the fact that it provides much more flexibility for customization of assessment as it does not restrict a student to choose some predefined actions just as done in educational games but learners are allowed to perform full actions that are possible within the system and see what consequences are faced by their choice of actions. The formative feedback is generated from assessment of the combination of actions performed by learners and their sequence. The feedback would include description of the correctness of thee performance of learner, the mistakes done by player, and best possible solution (I, S, & S, 2011).
Action-based Learning Assessment Method (ALAM) when used in a virtual environment, it can be used for providing formative assessment of action sequences of students for assessing their learning capabilities. The system would be designed to carry out both formative and summative assessment of the knowledge that is memorized by students and the knowledge that is learnt and applied to actions. It is not just what actions are taken by students that are analyzed but also how they do them is also used for assessment.
Input consists of an interface and knowledge model. The knowledge model consists of includes machine learning, natural learning, speech, and vision. The interface model consists of gaming model instances, gaming design, and gaming logic model. Action-based Learning Assessment would be used as the base for the model development.
Action-based Learning Assessment is based on the Taxonomy of Actions which divides actions into Goal, Constitutive, and Functional acts. These acts would be the inputs to the evaluation system.
Goal Act: It is the action carried out in a Virtual Training Environment (VTE) at the highest level. This action can be complex and composite and is considered completed only when a goal is achieved by the learner. One goal act can be formed out of two or more Constitutive Acts.
Constitutive Acts: Constitutive acts are at a lower level than goal acts and are performed in order to achieve the learning goal. Several constitutive acts would be required to be finished in order to reach the goal act level.
Functional Acts: Constitutive Acts are further completed using lower level actions called Functional Acts. They are at the lowest level in the VTE and enables avatar for action. The sole objective of any number of functional acts is to form Constitutive Acts. Functional Acts can belong to any of the six classes of actions including Gestural, Responsive, Decisional, Operative, Constructional, and Locomotive.
Gestural: Movements of the body of the avatar and the facial expressions form the gestures and they carry different meaning and thus, communicate different messages as well as feelings or thoughts that could be anything from approval to affection, hostility or contempt.
Responsive: Some actions are triggered when there is a change in the learning environment or in objects. For instance, a game may ask a learner to push a button when a specific colour light flicks (Dunwell, De Freitas, & Jarvis, 2011).
Decisional: Avatars make choices all the time from different types of actions such as choosing between going up or down, choosing between left or right, saying yes or no, choosing quantities or numbers and so on. Their decisions are reflected based on these choices that form decisional actions.
Operative: There could be some simple non-construction actions such as pushing, collecting, and grabbing that are called operative actions. These are simple and basic actions that help a learn function inside a virtual environment.
Constructional: These are some fundamental actions that allow avatars to do manipulations in the environment or on the objects such as cutting which can manipulate the shape of an object, screwing which can change the environment.
Locomotive: Locomotive actions allow learners to move around in the virtual landscape and it an include actions like walking, running, flying, teleporting, and so on (Wu & Chen, ASSESSING STUDENT LEARNING WITH AUTOMATED TEXT PROCESSING TECHNIQUES , 2004).
These actions would be performed in a sequence by the learner while going through the learning environment and this sequence would be recorded using some syntax for representation. These syntaxes can define position of sequence, instantiation of actions, list of attributes like location, quality, and quantity, and relationships between different actions. ALAM can also identify irrelevant actions so that the assessment remains fault free and a comprehensive feedback can be provided (Hiltz, Coppola, Rotter, Turoff, & Benbunan-Fich, 2000).
When VTE is used for training, different peripheral devices may be used by the learners to achieve different goals by means of Goal Acts. These actions would be recognized and recorded and verified for relevance to understand if they belonged to a specific action sequence. The experts or trainers would already have their action sequences recorded earlier such that the action sequences of the learner and trainer can later be compared for evaluation and providing formative feedback such that an appropriate assessment score can be given to the learner (Bodomo, Luke, & Anttila, Evaluating Interactivity in Web-Based Learning, 2003).
The synthesis process consists of personal judgement, feedback from the system, and action from the user. The process occurs in chain reaction (one event is followed by the other) and loop (personal judgementàfeedback from the systemàaction from the userà personal judgementàfeedback from the systemàaction from the user...). For synthesis of the data obtained from users in the Action-based Learning Assessment program, first an Action Recognition Agent would recognize the user actions recorded and then the assessment engine would evaluation the action sequences.
ALAM system involves a subsystem that contains an Action Recognition Agent which is used for recognition of actions and further it checks the relevancy of the action as well as maps the sequence of actions. The system then comes up with a list of codes of the sequence of actions fed to the Assessment engine for interpretations.
The action sequences are encoded using a lot of actions following a syntax of  where is the position of the sequence, represents that functional act, represents instantiation of these actions, would present a list of attributes like location, quality and quantity, presents a list of relationships between actions. The Evaluation engine is given a list of these codes for evaluation such that it can compare the sequence of actions with the sequence of actions of experts previously recorded.
The output process consists of the learning outcomes from the system process such as speech recognition, objectives recognition, language translation, and self monitoring.
The ALAM system would make use of a 5-stage classification of the feedback used for assessment of the learning outcomes of the students. Formative feedback would be provided at stages 4 or 5 of the learning process and would require a deeper understanding through experts who would help in understanding if the student is valid when considering the scope of learning and the body of knowledge. The evaluation would also make use of short answer or multiple choice questions that would be added as a part of assessment. These are usually used at stages 1 or 2 and are easy to act on. Other stages would be more complex as they would require an understand of the context, specific problem and even the language. Intelligent assessment algorithms would be developed for carrying out these assessments automatically. The complexities in the problem and solution space are reduced when specific constraints are put on the system.
In ALAM, a series of action sequence starting from initial stage to the final state of the environment would take a learner from problem to solution. For every change of stage, action sequences used by learners would be recorded such that a complete protocol of how student learned from the system could be revealed. The action sequences of these learners are compared with the action sequences of instructional designers so that milestones can be verified. The order of sequence would carry importance although the learner would have the freedom to move from one milestone to other without facing any of the constraints during the transition.
Avatars in a virtual environment display different forms of reciprocations through various kinds of interactions including non-verbal, verbal and gestures. Major interactions happen between Avatar and Avatar, between Avatar and the environment, and between Avatar and Objects. At times, a collaborative assessment can also be done for a group which is a result of addition of multiple kinds of interactions.
Functional Acts for Interaction between Avatar and Avatar: Avatars can use both verbal and in verbal methods for interacting with each other. Expressions can happen through speaking, chats, or showing gestures. Responsive actions can also be followed by Avatars. In a responsive action, an Avatar may make use of facial expressions, head movements or hand movements.
The non-verbal acts are a result of the psychological state of an Avatar and it can be classified into oculesics which includes eye contact and gaze, deictics such as pointing, gesticulation through hand and arms, proxemics reflecting body distance, and chronemics reflecting upon the time lapses between interactions.
Functional Acts for Interaction between Avatar and Environment: When interacting with the environment, an Avatar can make use of multiple functional Acts including constructional, Locomotive, Responsive, Decisional, and so on. Moving, building, destroying, modifying, and more such types of interactions can happen between the Avatar and the environment. Some decisional actions like turning on of a switch can also be used. Responsive actions like flinching after touching something hot can also be a part of such interactions. Actions taken by Avatars can lead to modifications of an environment.
Functional Acts for Interaction Between Avatar and Objects: Objects in a virtual environment can be created or manipulated using constructional actions while they are used or moved from one location to another using operative acts. When Avatars have to show their reaction in response to the impacts they have on themselves of the objects, responsive actions are used. Objects can affect Avatar and thus, need correct response to be able to show the knowledge and understanding the user has of the system as reflected by the actions of the Avatar (Fardinpour & Reiners, The Taxonomy of Goal-oriented Actions in Virtual Training Environments, 2014).
All the interactions would be recorded by the system and the recorded data would include reflective data, machinima, and virtual environment data. Avatar Capabilities Model (ACM) classifies actions of Avatars into some pedagogical themes including movement, experience, and social interaction.
In the Virtual environment, the assessment system would involve expert feedback that can be actually very time consuming otherwise as number of experts can be limited and thus, recording of their best actions and comparing the same with learner action using the agent in the virtual environment can actually address many issues of the system thereby making things simple. This ways, learners will learn from their own mistakes. Self-assessment can be conducted by the learner which can be repeated again and again till the learner completely masters the skill to achieve a goal or solve a problem without needing any additional financial resources or human help. A more effective and efficient assessment can be done in much less time which would be useful for educators who would further be able to create new problems, add more solutions, extend the learning taxonomy, define actions, and so on (Cappella J, 2001).
A software testing framework would be used for grading students as per the policies and guidelines specified in the assessment program. This would include recording of the responses of students automatically. The grading criteria are based on the tasks created by experts. These experts provide task inputs and prompt to the system and also, tell the system method to be used for scoring the responses of students (Ahmed, Maqsood, Saif, & Salman, 2012).
The Assessment engine would also be able to assess the essays written by students during the virtual learning process. This kind of assessment would be based on content and the surface featured that would require human judges. However, to some extent the assessment can be useful with extracted linguistic features from the training essays such that a multiple regression model is used in order to develop an equation that can help making predictions about the grades of new essays written by students. The computer aided assessment tool would focus on semantic relationships between the words written by students and the content presented. Test essay would also be compared with the trainer essay to give evaluation (Fardinpour, Reiners, & Dreher, Action-based Learning Assessment Method (ALAM) in Virtual Training Environments, 2013).
Evaluation of implementation
In a normal learning environment, the courses are based on written materials or their electronic versions that contain questions, exercises and tests that are required to be completed by students so that the results could be assessed by the human trainers. In an online system, lectures are held remotely but the interaction between the trainer and the learner is similar as the face to face traditional learning system. However, virtual systems add telematics technologies that work in real time and allow for two ways video conferencing to stimulate teaching. In a self-assessment system implementation, students can actually examine their own action based on the goals of the learning system instead of needing the teacher intervention (Al-Smadi, Gütl, & Kannan, 2010).
The expertise is distributed in the VLE and the learning is self-directed. There could be limitations on the course designed due to limited functionalities and tools available such as functions, bars, hierarchies and positions (again with some kind of pedagogical limitations) that limits the design of courses. However, VLE tools can actually provide ways to both tutor and mentor as they are adaptable to the purpose of the learning system (Bainbridge, 2007).
It may not always be possible for a university to have enough support systems for the implementation of the Virtual Learning environment for their regular classes but the system can be intruded for new initiatives having new curriculums and courses. Although the current activities proposed in the VLE system does not demand any change of policies or legislations, it would be affected by the internal politics of the institution largely. The current and future requirements o the university may affect the implementation of VLE programs. Moreover, a resistance may be seen from faculties who may not be willing to participate in the innovation as he or she may not be accustomed to working in virtual environments. Such human factors can raise concerns for successful implementation of the virtual system of assessment as it would majorly depend on the faculties or experts recording their responses to be able to make comparison between student Reponses and their responsive for effective assessment.
Implementation of virtual system needs a lot of new methods and approaches to be learnt and embedded into the system and thus, an exhaustive learning of such system would be required. In order to carry out such an implementation, the informant of the learning system experts would be necessary who would have to take help from teachers as experts of the learning system to achieve recordings from them and carry out coding and programming using the same for developing assessment system. However, as the system is designed and purposed for implementation, it can be easily said that it would more be of a onetime work and once everything is coded, the system would run automatically based on the recordings, syntaxes and data fed into the system of learning. However, as the system is used, new exercises and problems may be added by teachers and thus, certain level of training would be essential to explain them how things can be created in a virtual environment.
Although, the process of implementation is very straight forward but a high level of involvement of humans in the process cn actually makes it more complex. At every stage beginning with the defining the learning programs, the development of the content, forming of questions, recording of right responses, and coding of the same as per the assessment requirements so that automatic evaluation can be done would be required.
Another challenge in implementation could be the cost of development which would be significant as it would require a completely new system to be developed which would require specialized programmers who have expertise of developing learning systems. However, the implementation of the self-assessment system would still hold a great value for any university as it would simplify many things both for students and the faculties in the long run. While it would be easy to adopt for students who are more of technology savvy, the challenge of learning and acceptance would be more with the teachers who would be currently used to old traditional methods of assessment.
The open source systems may be used for implementation of the assessment system which would make the implementation less costly and easy. However, commercial systems may provide better options for flexibility and customization and thus, may be recommended for implementation.
This paper was developed to explore the area of virtual reality when used for creating systems of self-assessment for students. The paper covered the theoretical presumptions revealing that traditional systems of learning are not considered as very effective in today’s scenario and constructivist view seeks involvement of application based learning and assessment of students. The research report explores various forms of the virtual environment and deeply covers Action-based Learning Assessment program which is the proposed model chosen for the development of the self-evaluator system for a university.
It was found that the system largely depended on the inputs of the trainers or experts who would be closely involved in the development or implementation process. The solution is based on the concept of actions where the actions of the trainers are recorded in advance and then the tests are conducted on students by allowing them to carry out their own actions for learning. A comparison between expert action sequences and the learner action sequences formed the basis for normative assessment. It was found that such a system could be a great support to faculties as it would automate the major part of assessment and would allow teachers to come up with new assessments fast and make the system adapt to needs of students fast.
The Action-based Learning Assessment program would use up a significant resources including IT systems, financial funds, and the human resources for development of the system and the content. However, once the development is done, the system would provide the university an opportunity to extend their course to a wider number of students appearing from all over the world. Moreover, they can use innovation for showing theory course and can launch newer courses through the use of virtual environment.
Based on the proposal presented, it can be said that the Action-based Learning Assessment program has a great potential to make any university go to a next level of technological excellence and enhance their learning systems. However, dispute the activity being technology oriented, a human intervention and support would be very crucial especially at the stage of development and implementation of the system. The effectiveness of the system would largely depend on how the programming has been done and how the requirements and inputs of teachers on assessments are taken.
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