Ontological Design to Support Cognitive Plasticity for Creative Immersive Experience in Computer Aided Learning

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9192)


This paper discusses Ontological Design (OD) to support creative and insightful thinking in the increasingly customised modern world, specialised for augmented reality interfaces. The motivation was built upon IBM’s suggestion that capitalising complexity enables creativity, and the latter is the single most important leadership competency to deal with the increasing world complexity. Thus, OD simplifies the customisation processes and reduces anxiety when comes to challenging digital literacy for computer aided learning (CAL) skills. In a mixed reality modern world learners need to constantly adapt to changes into information, knowledge, signification and meaning, skills and competencies. This requires or enables cognitive plasticity bringing back the initial educational target, learning to learn. OI is based on the mediated ways the tools are used to enhance our senses and mind and the interaction as well as the influence our world view.


HCI Ontological design Immersive experience Creativity Computer aided learning Cognitive plasticity 

1 Introduction

Our world has been changed dramatically in the ways we think, work, learn, read, communicate, play, have fun or collaborate. The Internet of Things is creating a new global network and the human perception finds hard to grasp and adjust. Education is behind the current transformations the humans and the environment is going through. As Nicolas Carr illustrates in his book [1], possibly Google makes us stupid and perhaps there is much more to say about the ways the Internet is changing us. As we enjoy the Net’s bounties, we are sacrificing our ability to read and think deeply. He started a discussion about Internet’s intellectual and cultural consequences as for many centuries human thought has been shaped by ‘tools of the mind’; the alphabet, maps, printing press, clock, and the computer. Our brains change in response to our experiences. Neuroplasticity or brain plasticity refers to synaptic plasticity and non-synaptic plasticity, this means to changes in neural pathways and synapses which are due to changes in behaviour, environment, neural processes, thinking, emotions, as well as changes resulting from bodily injury [2]. Therefore, the technologies we use to find, store, and share information can literally reroute our neural pathways. For example, the printed book served to focus our attention, promoting deep and creative thought; however, the Internet encourages scanning and scattered small bits of information from many sources. Scanning and skimming evaporate our capacity for concentration, contemplation, and reflection. Such chronic distraction, and taking into account our brain’s plasticity, aid in losing our abilities to employ a slower, more contemplative mode of thought; thus, the better we are in multitasking the less prolonged, focused concentration and in result, we are less creative in our thinking.

Currently, there are no propositions towards the continuously new capabilities needed and acquired to deal with changing complexity. Furthermore, existing working and educational models are collapsing and a need to fill the gap is urgent. ICT, the Web and open source software extend our senses and capabilities. These targets are incorporated into interface design fitting systems into the ways we function. From face-to-face conversations with more than 1,500 CEOs worldwide aiming at capitalising complexity, an IBM report [3] suggests that creativity is the single most important leadership competency to deal with the increasing world complexity. As the tools enable us to expand our perception and learning we exchange knowledge, skills and competencies by being inter-dependent and inter-collective organising ourselves into small groups, communities and social networks. A Computer Aided Learning Community is a social aggregation that emerges in online courses when enough people carry on progressive dialogues for the purpose of learning via new idea generation for the individuals and the groups. Learning occurs by containing different levels en route for members’ engagement and practice whereas the group or the community evolves including the artefacts used within a cultural practice. Eventually these artefacts carry a substantial portion of our specific practices and professions heritage. Thus, users’ early participation in a kind of design that enhances the immersive experience with the environment, and the learning environment in particular can be also associated with the overall cultural life.

2 On Creativity and Cognitive Plasticity for CAL

Detailed research or review of our act of perception is currently missing. One reason is that the technology is not advanced enough so that researchers can study the brain in depth. Also, instead of considering perception intact and accurate based on the ways the brain receives sensory stimuli as concrete and solid matter, we may enhance the right brain hemisphere functionality in order to receive data processed and envisaged in and delivered to our awareness differently. As the brain is our main tool for examining physical reality, in order to determine the validity of our perceptions, we need to study of our brain’s physiology, and in particular the ways both parts of the brain receive and perceive sensory stimuli. The retinex (combination of retina and cortex) theory of vision posits that the brain’s cortex compares the data it receives and creates an appropriate visual perception. Our visual perception requires a kind of reasoning process, not just retinal stimulation [4]. Our brain is working hard to create a classical perception that is useful mostly for practical purposes. The left-brain/right-brain dichotomy or, more accurately, processed versus unprocessed data, and the mechanism by which we form perception may provide a solution. The dichotomy suggests that classical-level perception is partly constructed by our judgmental left hemisphere. The perception of the suppressed but unbiased right hemisphere is more in line with quantum-mechanical principles. Our classical perception may be just an approximation of the actual realty out there. The left hemisphere is objective, analytical, logical or classical whereas the right one is informational, holistic, continuous, subjective or quantum mechanical. Our world has been built based mostly upon the left brain functionalities which makes our abilities and competences inadequate for the new century. Perhaps more attention, study and research to the right brain functionalities and abilities are needed, moving from the individual self-perception to a more unified perception of our world. Based on the theory of entanglement borrowed from quantum physics, both parts of our brains can function as a unity much faster providing more accurately perception of reality. This approach requires reconsidering the whole educational and corporate system as they function at the moment [5].

Insight is any sudden comprehension, realization, or problem solution that involves a reorganization of the elements of a person’s mental representation of a stimulus, situation, or event to yield a nonobvious or non-dominant interpretation [6]. Insight occurs (a) when a simple solution breaks an impasse or mental block initially fixated on an incorrect solution strategy or strong but ultimately unhelpful association; (b) when the solution suddenly intrudes on a person’s awareness when he or she is not focusing on any solution strategy, (c) when an insight pointing to a solution occurs while a person is actively engaged in analytic processing but has not yet reached an impasse, and (d) when a person has a spontaneous realization that does not relate to any explicitly posed problem. The neural basis of insight is anchored in the hemispheric differences. The right hemisphere contributes relatively more to insight solving than to analytic solving, whereas the left hemisphere contributes more to analytic solving than to insight solving.

A new kind of consciousness arise, a quantum total one [7]. Creativity is divided into inner creativity, the evolution and transformation of the Self, and outer creativity, the design and development of a product. Also, quantum theory can provide approaches to explain the human brain infinite trajectories to manifest perceptions of reality and suggests that creativity is an evolutionary process that requires unconscious processing. There are two realms of reality, potentiality and actuality. Collapses produce dependence co-arising of experience and creativity is a phenomenon of consciousness manifesting new possibilities anchored in brain plasticity as it chooses from quantum possibilities. It is therefore based on discontinuity, non-locality of ideas already existing in the human brain and the entanglement phenomenon; this is the holistic view that is all is part of one system. Such gestalts refer to the collections of separate fragments, the breakthrough pattern of a single significant whole. In fact, the entanglement phenomenon explains the potential for non-locality and discontinuity as non-local correlations of synapses rearrange the neuron pathways. This is idea generation, the Eureka! experience, creative insights or the quantum leap arise. As such, perception requires memory and memory requires perception, however, creativity requires changes in the brain’s sub-structures responsible for memories and representations of experience. Therefore, humans’ experiences intuitive insights turn into new meanings in older or newer contexts.

Learning results in the change of thinking, understanding and behaviour that can be measurable compared to specific indicators before the learning intervention. If the learning experience is enhanced, then learning is deeply experienced and thus, accelerated. To create such an immediate and rapid learning intervention, pedagogical and learning design is necessary so the coordination of both the learning activities (including associated educational content) and the group learning experience as such can occur and converge.

Based on the assumption that creativity is related to the idea generation caused by nonlocal quantum consciousness, the creativity techniques in this section are related to the broader perception of the world and the insights production in a larger community, compared to the individual and the group as in the previous sections.

In the era of the internet of Things, where all devices are going to be connected on platforms to enable communication and interaction with not only other people but also with the environment surrounding us, learners and educators are called to enable capabilities in an increasingly complex world. Humans are now participants in smaller or bigger groups, communities and networks connected with the associated and evolving tools and need to deal with complex mazes of information, communication patterns, strategic and critical thinking for information utilization and meaning making. Creativity inspires and empowers the mind with innovative ideas. For such a state to exist, a moment-by-moment awareness of our thoughts, feelings, bodily sensations, and surrounding environment is needed. Mindfulness, awareness, concentration or sentiment suspension aids in being continuously present and immerse with experience which in turn enables our brain plasticity. Such openness facilitates creativity by drawing the self away from its personality encasement and absorption, detaching from the physical, emotional and mental aspects of the personality. The development of the abstract mind and thinking makes it possible to see the broader structures underlying outer events. Life and circumstances are seen anew and not realized before developing intuitional insight to input in everyday life and production.

3 Mixed Reality in CAL

There are many different ways for people to be educated, which include classroom lectures with textbooks, computers, handheld devices, and other electronic appliances. The choice of learning innovation is dependent on an individual’s access to various technologies. Virtual Reality (VR) and Augmented Reality (AR) are technologies that can dramatically shift the location and timing of education. The use of VR and AR in education can be considered as one of the natural evolutions of computer-assisted instruction (CAI) or computer-based training (CBT) [8]. Augmented Reality (AR) is a technology that allows computer-generated virtual imagery information to be overlaid onto a live direct or indirect real-world environment in real time. AR is different from Virtual Reality (VR) in that in VR people are expected to experience a computer-generated virtual environment. In AR, the environment is real, but extended with information and imagery from the system. In other words, AR bridges the gap between the real and the virtual in a seamless way [9].

The last decade showed how production activities have been split and segments localized in some specialized countries while customers have been involved into the design processes. New technologies suggest that learners have to be creative, active innovators developing new services and products, new production and social processes. Technological waves as rapid change of technologies are becoming more frequent and shorter, so that IT expert must evaluate quickly how each wave gives opportunity for new individual, social or business applications. As an example beside may others, the Internet of things is a giant coming wave opening the web to astonishing possibilities in situation awareness as added social reality.

During the last two decades VR and AR have been experimentally applied to school environments, although not as much as classic methods of education and training [10]. Augmented Reality (AR) builds upon virtual layers that overlay superimposed on physical reality (such as for use in simulated retail and training environments), where customized messaging and applications requires positioning and orientation of visors and displays and other objects.

Moreover, the existence of mixed reality (MR) technology which is powerful and compact enough to deliver MR experiences to not only corporate settings but also academic venues through personal computers and mobile devices can make several educational approaches are more feasible [9]. Devices such as wireless mobiles, smart phones, tablet PCs, and other innovations in electronics are increasingly ushering MR into applications which offer a great deal of promise, especially in education.

Professionals and researchers have striven to apply MR to classroom-based learning within subjects like chemistry, mathematics, biology, physics, astronomy, and other K-12 education or higher, and to adopt it into augmented books and student guides [9]. However, AR has not been much adopted into academic settings due to little financial support from the government and lack of the awareness of needs for AR in academic settings [11]. It is estimated that simple AR applications in education will be realized within a few years.

Mixed reality can make education more productive, pleasurable, and interactive. MR can engage a learner in several interactive ways, which before where not possible, as well as can also provide each individual with one’s unique discovery path with rich content from computer-generated 3D environments. It has been shown in previous research works that mixed reality can be focused on simplicity and ease of providing education, so that learners can accept knowledge and skills with 3D simulations generated by computers or other devices. MR can support the efficiency of education in academia by providing information at the right time and right place and offering rich content with computer-generated 3D imagery. MR may be helpful where students take control of their own learning and thus could provide opportunities for more authentic education and training styles. MR-based systems offer motivating, entertaining, and engaging environments conducive for learning. Except this, MR in education is attractive, stimulating, and exciting for students and provides effective and efficient support to the learners.

Virtual and augmented reality is not appropriate for every instructional objective. There are some teaching scenarios when VR can be used and some when it should not be used. For example the use of VR is suggested when a simulation could be used, teaching using the real thing is dangerous/impossible/inconvenient/difficult, interacting with a model is as motivating as or more motivating than interacting with the real thing, travel, cost, and/or logistics of gathering a class for training make an alternative attractive, etc. On the other hand, VR is not suggested to be used when no substitution is possible for teaching/training with the real thing, interaction with real humans, either teachers or students, is necessary, using a virtual environment could be physically or emotionally damaging.

Research on educational applications of mixed reality show the potential value of MR in the educational process. The use of MR can help the educator to enhance their courses and provide multiple perspectives for engaging learners into active learning.

4 Ontological Design for Cognitive Plasticity in Mixed Reality

Ontological Design refers to the cycle of designing and developing systems based upon the interaction between us and the tools and vice versa. Such design is not fixated but rather agile, responsive and evolving acquiring information from the surrounding environment to adjust the software to the individual user’s needs. Ontological Design implementation improves the Human Computer Interaction for the human to human interaction based on existing databases as well as gathering, interpreting and integrating information via users’ interaction on both individual and collective level. In this way, the design aims at serving individuals’ capabilities and visions to deal with the increasing complexity of the world. OD is directed towards Computer Aided Learning (CAL) systems based upon solid educational and technical design principles for associated platforms to be designed and developed aiming at creating active participants and producers of the educational content and knowledge.

The Perception-Action Model (PAM) is a process-based suggestion on empathy made by [12]. According to PAM, attended perception activates subject’s representations of the state, situation and object, and that activation of this representation automatically primes or generates the associated autonomic and somatic responses, unless inhibited. PAM suggests that levels of empathy can be associated to levels of awareness, reconciliation, vicarious learning or effortful information processing. On balance, both the neuropsychological and psychophysical data support this distinction. They claim that critical results were either statistically inconclusive (because they consisted of negative evidence) or based on a suspect “calibration” procedure. Correction (‘calibration’) of illusion effects is critical for comparisons across stimuli, studies, and tasks [13]. PAM proposes that vision-for-perception and vision-for-action are based on anatomically distinct and functionally independent streams within the visual cortex. It comprises a set of core contrasts between the functional properties of the two visual streams, capturing broad patterns of functional localisation suggesting that should reject the idea that, according to the two streams hypothesis, the ventral (visually guided behaviour) and dorsal (guidance of actions and recognizing where objects are in space) streams are functionally independent processing pathways. Using tools to enhance empathy and awareness of the Self and Other may lead to the next skill level of shared intentions, feelings and thoughts for common goals, desires and beliefs in CAL.

Ontological Design for CAL is applied for solutions related to complex, ill-structured, and agile, scope creep problems and situations, according to the following principles: (a) facilitating situated human cognition in an attempt to address complexity; (b) provide tools which expand the capacity of cognitive plasticity; (c) make a careful analysis of the implicit assumptions of the system and limit competing values; (d) understand social structure and context, (e) view breakdowns as creative design opportunity; (f) use digital medium to narrate a transmedia story; (g) engage features from game mechanics such as play, competition, challenge, quests, choices, surprise, curiosity, association, flow and expression; and (h) make visible the effects of interaction between the human and the world mediated by the particular tool for computer enabled mechanics, such as VR, AR and MR.

5 Creative Immersive Experience for Computer Aided Learning

Creative learning experiences are a way to think about what a learning intervention might be (i.e. – its design) in the context of desired end goals and outcomes. This can then inform our technological choices within multiples real and mixed reality contexts. Creative Immersive Experience aids in:
  1. 1.

    Promoting cognitive plasticity in action by activating multiple reality perceptions

  2. 2.

    Reducing transactive cost by enabling multiple associations in real-time to occur

  3. 3.

    Orchestrating learning teaching and learning pathways convergence including learning activities coordination and knowledge building for signification

  4. 4.

    Providing direct fit between educational tasks, methods and tools

VR, AR and MR enhance the experiential learning to develop new creativity competencies based upon the agile cognitive plasticity and rapid knowledge acquisition in such rich learning environments. HCI Education (HCI-Ed) is the design, evaluation and implementation of systems and tools from a user/learner-centred perspective and the study of major phenomena surrounding them. In HCI-Ed both inclusive and participatory User-Centred Design (UCD) and Learner-Centred Design (LCD) are utilised. UCD is that the system should have the capability in human functional terms to be used easily and effectively by the specified range of users, given specified training and user support, to fulfil the specified range of tasks, with the specified range of environmental scenarios. Whereas UCD focuses on making users more effective, LCD focuses on making learners more effective by utilising pedagogical frameworks. Pedagogical Utility is the degree to which the functionality of the system allows the learner to reach his/her learning goal. Pedagogical Usability should question whether the tools, contents, interfaces, and tasks provided within the e-learning environments can support e-learners. Pedagogical Usability utilises guidelines and principles to bring together the pedagogical and technical CAL targets. Lastly, Pedagogical Acceptability refers to the previous compatibility as well as the degree to which the system is compatible with learners’ motivation, affects, culture and values. HCI-Ed works through a framework with seven iterative and non-linear stages, as follows:
  1. 1.

    Context & Learning Values - Hypotheses

  2. 2.

    (Iterative) Design – Requirements – User Modelling

  3. 3.

    Evaluation with user groups/experts

  4. 4.


  5. 5.

    Evaluation with user groups

  6. 6.

    Re-Design & Development

  7. 7.

    CAL Study & Research based on Final Tool Release


The process follows the suggested instructional design model ADDIE (Analysis, Design, Development, Implementation and Evaluation); however, it incorporates the initial context and learning values as initially defined before actual design.

Although user modelling has been implemented for adaptive systems, it can provide initial profiling for other systems, as it describes the process of building up and modifying a user model towards user’s/earner’s specific needs. The specific data needed are gathered by initial profiling questions and identifying users’ preferences via observing and interpreting their interactions with the system. User modelling supports the constant evolution of technologies and services as it evolves on user abstract models that are easy to understand by systems making appropriate for multi-disciplinary educational design. The Model-Based Education System Design Environment notations (eLearniXML & eLearniCNL), which contains several and different models (Task, Domain, Platform, Environment, Context, and Presentation) and these models can be divided and classified into different ways based on multiple criteria. The Model-Driven Development specifies three models on a system, a computation independent model; a platform independent model and a platform specific model. Existing user modelling standards (e.g. IMS-LIP for eLearning) provide the learning quality assurance checklists. Model-based Distributed User Interfaces are usually anchored in the international standard ISO 9126 (ISO 9126-1, 2001) for quality assurance. The ISO 9126-1 software quality model identifies six main quality characteristics, namely: Functionality, Reliability, Usability, Efficiency, Maintainability and Portability. User modelling is taken one step further by also profiling the user based on human-human and human-computer interactions. User/Learner eXperience (U/LX) is considered to be a vital part in HCI for evaluating the Graphical User Interface as well as the Distributed User Interfaces.

Unambiguously, Adaptive VR, AR and MR have to be evaluated empirically to guarantee that the collective intelligence really works. In HCI-Ed flexibility demands are explicit for human computer interaction, including the adaptivity system capabilities for Ontological Design:
  1. 1.

    Evaluation of reliability and external validity of input data acquisition

  2. 2.

    Evaluation of the inference mechanism and accuracy of user properties

  3. 3.

    Appropriateness of suggestions

  4. 4.

    Change of system behaviour when the system adapts based on characteristics

  5. 5.

    Change of user behaviour when system adapts based on characteristics

  6. 6.

    Change and quality of total interaction to conform with characteristics

  7. 7.

    Triangulation for rich, valid and timely recommendations


The last evaluation step can only be interpreted correctly if all the previous steps have been completed. Especially in the case of finding no difference between an adaptive and a non-adaptive system the previous steps provide hints at shortcomings. The results of such a layered evaluation are much better to interpret and give more exact hints for failures and false inferences than a simple usability evaluation.

6 Concluding Remarks and Future Work

This paper described the need to consider both the brain cognitive plasticity and creativity when utilising Virtual or Augmented Reality in Computer Aided Learning. In order to capture users’ perceptual pathways, Creative Immersive eXperience (iX) is incorporated into the common Human Computer Interaction design and development cycle. Our computer tools are used to reduce our everyday complexity. Such world increasingly complex environment, rapid adaptability is necessary. Enhancing forward thinking is therefore essential for the learners to harness this complexity to their advantage [3]. Therefore the proposed Ontological Design for Creative Immersive Experience to utilise to empowered and enabled the processes needed to achieve such engagement with the world. Furthermore, such creative engagement can exploit and catalyse such complexity with inherent power to invent new perspective and assumptions and create new models geared to an ever-changing world. A fundamental objective of HCI research is to make systems more usable, more useful, more accessible and to provide users with experiences fitting their specific background knowledge and objectives. The challenge in an information-rich world is not only to make information available to people at any time, at any place, and in any form, but specifically to say the “right” thing at the “right” time in the “right” way. User models are defined as models that systems have of users that reside inside a computational environment.

New technologies such as Adaptive VR, AR and MR tools in particular can forward and accelerate thinking and also support problem solving processes as well as creative thinking and insight functioning in complex, ill-structured, plastic and ever changing and agile contexts. Ontological Design can optimise and sustain long term user and changing needs through emotional and physiological engagement in Immersive Experience for better user engagement in the creative flow.


  1. 1.
    Carr, N.: The Shallows. W.W. Norton & Company, London (2010)Google Scholar
  2. 2.
    Pascual-Leone, A., Freitas, C., Oberman, L., Horvath, J.C., Halko, M., Eldaief, M., et al.: Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI. Brain Topogr. 24, 302–315 (2011)CrossRefGoogle Scholar
  3. 3.
    IBM Report: Capitalizing on Complexity: Insights from the Global Chief Executive Officer Study.
  4. 4.
    Kalat, J.W.: Biological Psychology, 8th edn. Wadsworth, Australia (2003)Google Scholar
  5. 5.
    Lambropoulos, N., Romero, M.: 21st Century Lifelong Creative Learning: A Matrix of Innovative Methods and New Technologies for Individual, Team and Community Skills and Competencies. Nova Publishers, New York (2015)Google Scholar
  6. 6.
    Kounios, J., Beeman, M.: The Eureka Factor: Aha Moments, Creative Insight, and the Brain. Random House, New York (2015)Google Scholar
  7. 7.
    Goswami, A.: Quantum Creativity, Kindle edn. Amazon, New York (2014)Google Scholar
  8. 8.
    Pantelidis, V.S.: Reasons to Use Virtual Reality in Education and Training Courses and a Model to Determine When to Use Virtual Reality.In: Themes Science And Technology Education. Klidarithmos Computer Books, Athens (2014)Google Scholar
  9. 9.
    Kangdon, L.: Augmented reality in education and training. Tech Trends 56(2), 13–21 (2012)CrossRefGoogle Scholar
  10. 10.
    Johnson, L., Levine, A., Smith, R., Stone, S.: Simple augmented reality. The 2010 Horizon Report, pp. 21-24. The New Media Consortium, Austin (2010)Google Scholar
  11. 11.
    Shelton, B.E.: Augmented reality and education: Current projects and the potential for classroom learning. New Horizons for Learning (2002).
  12. 12.
    Preston, S.D., de Waal, B.M.: Empathy: its ultimate and proximate bases. Behav. Brain Sci. 25, 1–72 (2002)Google Scholar
  13. 13.
    Norman, J.: Two visual systems and two theories of perception: An attempt to reconcile the constructivist and ecological approaches. Behav Brain Sci 25, 73–144 (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of InformaticsLondon South Bank University, UK and OLON Organisation, Greece LSBULondonUK
  2. 2.Artificial Intelligence Group, Wire Communications Laboratory, Department of Electrical and Computer EngineeringUniversity of PatrasPatrasGreece
  3. 3.Computer and Informatics Engineering DepartmentTEI of Western GreecePatrasGreece
  4. 4.King Abdulaziz University of Saudi ArabiaJeddahKingdom of Saudi Arabia

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