=Paper=
{{Paper
|id=Vol-1914/TUTORIAL2
|storemode=property
|title=Immersion in e-Learning
|pdfUrl=https://ceur-ws.org/Vol-1914/TUTORIAL2.pdf
|volume=Vol-1914
|authors=Alexandra Cristea
|dblpUrl=https://dblp.org/rec/conf/ht/Cristea17
}}
==Immersion in e-Learning==
Immersion in e-Learning Alexandra I. Cristea University of Warwick Coventry CV4 7AL, UK a.i.cristea@warwick.ac.uk ABSTRACT Csikszentmihalyi recommends as flow antecedents clear goals & immediate feedback, and a good challenge & skills balance. Flow is a state of intense concentration and engagement, when a user is so immersed in her activity, that all other external influences cease. It is a well-known fact that flow is experienced 3 IMMERSION FEATURES in games, where we all had the 'just one more minute' request An appropriate source for extracting immersion and flow-related from our children. This paper analyses the notion of flow from features are games. It is easy, at first glance, to attribute the two perspectives: the theoretical concepts and the practical reality. typically high level of immersion in game environments to For the latter, game environments are compared to current e- advanced computer graphics (such as Halo 51), or 3D interactivity learning environments. Finally, the extracted features are mapped (such as in EVE Online2); however, this is only part of the answer. back to the theoretical underpinning. It also represents the part that is more difficult to implement, requiring large teams of dedicated programmers. In the following CCS CONCEPTS I identify some tangible features of current game environments that are much more straightforward to implement, but that are • Human-centred computing → Interaction paradigms → currently missing in current e-learning environments (even in Hypertext / hypermedia; Web-based interaction; Applied more advanced adaptive or personalised ones [4,5]), which may computing → Education → e-learning; Information systems → trigger immersion [6]. The focus here is mainly on feedback, Decision support systems → Data analytics; which is considered an essential aspect to be supported in e- learning [7]. KEYWORDS 1) Game environments, unlike TEL environments, often have flow, e-learning, adaptation, social web, semantic web, multi-dimensional levels of interactivity and feedback. Thus, gamification, learner analytics unlike in a learning system, where feedback often relates to scores, marks, or percentage of progress, which all reflect, in principle, the single dimension of knowledge-increase, in game Reference format: environments various parameters can be tracked, and the user can Cristea, A. I. 2017. Immersion in e-Learning. In Workshop and Tutorial progress in various ways, as defined by these parameters. Proceedings of the 28th ACM Conference on Hypertext and Social Media, Prague, Czech Republic, July 4-7 2017 (Hypertext’17), 2 pages, 2) Next, in game environments, the feedback is frequent. At each CEUR-WS.org. ‘kill’ or ‘success’, for instance, the popular first-player-shooter games immediately display on-screen the experience feedback. Opposed to that, most learning environments, adaptive or not, 1 INTRODUCTION give delayed feedback, often significantly so, only, e.g., when a In e-learning, immersion is a concept based on the psychological whole chapter is read, or an important concept is mastered. concept of flow: learners 'are so engaged in learning, that time and 3) Moreover, the feedback is highly visible. Games often place fatigue disappear' [1,2]. We mostly know this experience from their feedback in the middle of the screen, as in the previous online and offline games. The challenge is to create e-learning example, with perhaps strong colours, or even graphics. In offers that can lead to a similar intense involvement. This seems learning environments, especially in adaptive settings, a lot of to be an impossible challenge for educational software, and thus discussions have centred on the benefits of high level of feedback. represents almost a 'holy grail' for online education. This is 4) Furthermore, in game environments, the feedback is fine- especially relevant now, with the rising of MOOCs, such as grained. At each event, popular games immediately display Corsera in the US and FutureLearn in Europe, backed up strongly, experience feedback. A player feels at all times that she is making in a top-down fashion, by current politicians, but which suffer some progress. Opposed to that, most learning environments, greatly from extremely high dropout rates. adaptive or not, display quite a coarse-grained feedback. 5) Additionally, feedback is volatile. This means, feedback 1.1 Flow Components doesn’t linger on the screen for very long. The noted psychologist Csikszentmihalyi identified 4 key components of flow: control (learner's control over the 1 https://www.halopedia.org/Halo_5:_Guardians experience); attention (learner's dedication to the task at hand); 2 https://www.eveonline.com/ intrinsic interest (motivated by the desired outcome) and curiosity (leading them forward) [3]. Specifically, Tutorial at Hypertext'17, Prague, Czech Republic, July 2017 Copyright held by the author(s). Hypertext'17, July 2017, Prague, Czech Republic A. I. Cristea 6) Moreover, feedback is traceable. Whilst the information can are well equipped to deal with a multitude of inputs online, flash quickly in front of the user, a user in a game environment without losing focus [9, 10]. can usually find, for instance, information about a certain 5) volatile feedback: this feature supports 'immediate feedback' by achievement, when desired. Adaptive learning environments are still allowing for learner's 'attention' to the task at hand (instead of more concerned with keeping track of the current state (e.g., the interrupting with interaction demands). percentage of current knowledge) instead of storing minor 6) traceable feedback: this features supports 'immediate feedback' achievements. by helping, when 'interest' and 'attention' are caught, to easily be 7) Adaptive educational environments may often track the in 'control' and find the required information. distance to achievement, instead of challenges conquered. I.e., as 7) challenges conquered, not distance to achievement: this deals in the above example, the percentage of knowledge as compared with the 'challenge & skills balance', in that, even harder to the desired state of knowledge may be displayed. Instead, game problems, are presented in a manner in which they can be environments display achievements, experience levels, ranking in perceived as simpler and approachable, where skills and challenge a leader board etc. are matched. 8) Furthermore, interactivity with other players is often used in 8) social aspects: interestingly, instead of detracting from a multi-player games as an extra dimension for exploration. learner's attention', social interaction can actually help to improve Competition and collaboration are encouraged via reward the 'challenge & skills' balance, and lower achievement systems. Whilst interactivity and collaboration have been explored thresholds, by involving help from peers, tutors, etc. Such aspects, in previous work on TEL environments (e.g., the ALS EU project 3 if well-implemented, can increase the level of perceived learner led by Warwick), its effect on the learning immersion is not yet 'control', and thus increase the motivation and 'interest'. fully explored and exploited. 9) redundant access to information: a less intuitive outcome, the 9)VAccess to information (such as feedback) can be obtained in availability of multiple paths to the same piece of information (be multiple, redundant ways in game environments. In such cases, it feedback, or learning content, or social interaction) helps redundancy is no undesirable feature, but the contrary: users can towards learner 'control', adjusting to the learner's mental model get to the information in whichever way they are more of the information organisation, and lowers the challenge from a comfortable with. Contrary to this, educational environments system perspective, thus achieving a better 'challenge & skills rarely introduce redundancy in their paths. balance'. 4 DISCUSSION 5 IMMERSION FRAMEWORK Analysing how the features above map onto the theory provides Figure 1 represents these features in the form of an initial the reassurance that these are indeed features which could be immersion features framework, including also the flow scaffolding flow and ultimately immersion in a learning dimensions, directly mapped from the theory [1,2,3] (under environment, as follows. features, on the right hand side of the image), 1a) multi-dimensional levels of interactivity: in terms of flow As can be seen in section 4, the majority of the features discussed antecedents, it maps onto 'challenge & skills balance'. In terms of there are centred around feedback. These involve points 1b- 7 the key components, it maps best onto 'control', although it allows from section 4. Others are concerned with delivery (Features- also the learner to follow their 'intrinsic interest' and nurture >Delivery on right hand side of image), corresponding to 9 in 'curiosity', which could enhance 'attention'. section 4, and interactivity (Features-> multi-dimensional levels 1b) multi-dimensional feedback: in terms of flow antecedents, it of interactivity), corresponding to feature 1a in section 4. maps well onto the 'immediate feedback'. In terms of the key Additionally, the framework describes the user activities components, it maps onto 'attention' (as it keeps a learner's (Features->Activities, right hand side of Figure 1) - the type of attention by the various type of feedback), gives a feeling of actions users are likely to perform when learning via a hypertext 'control', which could increase 'intrinsic interest' and 'curiosity'. environment. Finally, the framework provides well as additional 2) frequent feedback: directly maps to 'immediate feedback', and metrics and measurement methods (left hand side of the image), is generally related to 1b) above. which can be involved in tracing and estimating the 3) highly visible feedback: spurs 'attention', potentially increasing appropriateness of the specific implementation for this set of 'curiosity' and 'intrinsic interest', as well as giving a greater feeling features. of 'control'. This framework represents, to the best of the author's knowledge, 4) fine-grained feedback: allows clearly for 'control' - the learner the first attempt of systematically analysing and differentiating is in charge and aware of most aspects of her learning. between flow parameters in games, and their counterpart in e- Importantly, in opposition to previous research, which was learning environments. Whilst some of these features have been concerned about learning overhead [8], in fact, modern learners studied separately, they have not been analysed in a systematic way, based on evidence from their source, as well as per their potential to inducing the flow state in the learners. 3 http://www.academia.edu/12713425/Adaptive_Learning_Spaces 2 Figure 1: Immersion Features Framework. Industry, https://elearningindustry.com/applying-the-flow-theory-in-online- training [last accessed 09/06/2017] [4] O'Donnell, E., Lawless, S., Sharp, M. & V.Wade. (2015). A Review of 6 CONCLUSIONS Personalised E-Learning: Towards Supporting Learner Diversity. International Journal of Distance Education Technologies, pp.22-47. DOI: In summary, this paper has proposed a new method of adding 10.4018/ijdet.2015010102 [5] Ashman, H., Brailsford, T., Cristea,A. I., Sheng,Q. Z., Stewart,C., Toms E. and flow-related features to an e-learning environment, by extracting Wade,V. 2014. The Ethical and Social Implications of Personalisation relevant flow-inducing features from games environments, which Technologies for e-Learning International Journal of Information Management reflect the quintessence of user immersion, and creating an initial (IJIM), Special Issue on IS Ethics: Past, Present and Future at Information & Management, Elsevier, 51(6), September 2014, p. 819–832, DOI: framework for researchers. However, instead of being stuck at a 10.1016/j.im.2014.04.003 superficial level - such as assuming that e-learning has to be [6] Konradt, U., Filip, R., Hoffman, S. 2003. Flow experience and positive affect during hypermedia learning, British Journal of Educational Technology, DOI: delivered via games, in order to induce flow, or that it has to 10.1111/1467-8535.00329 include high resolution 2D or even 3D graphics, the focus was on [7] Aswek, S. (2000) Feedback for learning, Routledge Falmer, Taylor & Francis the more often overlooked aspects of games. Still, the results are Group. [8] Chen, F. et al. 2016. The State-of-the-Art. Chapter, Robust Multimodal not comprehensive. Results mainly centre on 'feedback', and, for Cognitive Load Measurement, Part of the Human-Computer Interaction Series, instance, 'goals' have not been studied at all. This study thus 13-32, Springer. [9] Zumbach, J., Mohraz, M. 2008. Cogitive load in hypermedia reading encourages researchers to further explore such features, to better comprehension: Influence of text type and linearity, Computers in Human reflect the intrinsic requirements of flow theory, and achieve the Behavior 24, 875-887, Elsevier. [10] Zunbach, J. 2006. Cognitive Overhead in Hypertext Learning Re-examined: immersive environments for the learners of the future. Recently, a Overcoming the Myths, J. of Educational Multimedia and Hypermedia, 15(4), new generation of e-learning tools are incorporating such 411-423. elements that are aimed at flow [11-20]. However, these [11] Liu S-H., Liao H-L., Pratt J.A. 2009. Impact of media richness and flow on e- learning technology acceptance, Computers & Education, Elsevier, 52, 599- researches are few and far between, and a broader effort of the 607. research community in general is needed, to get closer to this [12] Lee, M-C. 2010. Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation-confirmation model, Computers & 'holy grail' of online education. Education 54, 506-516. [13] Shi, L., Cristea, A. I., Awan, MSK., Hendrix, M., Stewart C. 2013. Towards REFERENCES understanding learning behavior patterns in social adaptive personalized e- learning systems, AMCIS, 1 - 10, Chicago, Illinois, USA, August 15 - 17. [1] Mihaly Csikszentmihalyi. 1991. Flow: The Psychology of Optimal Experience, [14] Shernoff, D. J. .et al. 2014. Measuring Flow in Educational Games and HarperCollins, ISBN 0-0609-2043-2. Gamified Learning Environments , EdMedia, Tampere, Finland, June 23-26. [2] Mihaly Csikszentmihalyi. 1997. Finding Flow: The Psychology Of [15] Shi, L., Cristea, A. I., Hadzidedic, S., Dervishalidovic, N. 2014. Contextual Engagement With Everyday Life, books.google.com [last accessed 09/06/2017] Gamification of Social Interaction –Towards Increasing Motivation in Social E- [3] Pappas, C. 2016. Applying the flow theory in online training, eLearning Learning, In: 13th International Conference on Web - based Learning Hypertext'17, July 2017, Prague, Czech Republic A. I. Cristea (ICWL2014), Tallinn, Estonia, 14-17. [16] Shi, L , Gkotsis, G., Stepanyan, K., Al Qudah, D., Cristea, AI. 2014. Social personalized adaptive e-learning environment: Topolor-implementation and evaluation. Int.Conference on Artificial Intelligence in Education, 708-711. [17] Cristea, A. I. and Shi, L. 2016. Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning. In: Intelligent Tutoring Systems (ITS) 2016, Zagreb, Croatia., 6-10 Jun 2016. [18] Shi, L. and Cristea, A. I. 2016. Simplifying is not always best : learners thrive when using multifaceted open social learner models. IEEE MultiMedia, 23 (1), 36-47. [19] Rodriguez-Ardura, I. and Meseguer-Artola, A. 2016. E-learning continuance: The impact of interactivity and the mediating role of imagery, presence and flow, Information & Management Journal, Elsevier 53, 504-516. [20] Rodriguez-Ardura, I., Meeguer-Artola, A. 2016. Flow in e-learning: What drives it and why it matters, British Journal of Educational Technology, doi: 10.111/bjet.12480. 2