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Human-Human Interaction

Human-Human Interaction. Human-Computer Interaction. replicated in. Topics covered during the presentation. Communication Preference. Personality Types. Neuro-linguistic Programming Language Patterns. Learning Styles. Human-Computer Interaction. Subliminal Text Messaging.

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Human-Human Interaction

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  1. Human-HumanInteraction Human-Computer Interaction replicated in

  2. Topics covered during the presentation Communication Preference Personality Types Neuro-linguistic Programming Language Patterns Learning Styles Human-Computer Interaction Subliminal Text Messaging. Start with a story!!

  3. The Story The manager - Eddy The salesman - John The clients – Bill & Cathy - Restaurateurs

  4. Communication Preference

  5. The Story - continued The manager - Eddy The salesman - John Auditory Visual The clients – Bill & Cathy - Restaurateurs

  6. Personality Types - Where are you? Extrovert Reacts slowly Extrovert Reacts fast Introvert Reacts Fast Introvert Reacts slowly

  7. The Story - continued The manager - Eddy The salesman - John Extrovert Reacts fast Introvert Reacts slowly Auditory Visual Cathy defers to Bill The clients – Cathy & Bill - Restaurateurs

  8. Neuro-Linguistic ProgrammingWhen did it start? ---- What is it? Neuro-Linguistic Programming comes from the disciplines that influenced the early development of its field, beginning as an exploration of the relationship betweenneurology, linguistics, and observable patterns (programs) of behaviour. John Grinder, a Professor at UC Santa Cruz and Richard Bandler, a graduate student, developed NLP in the mid-1970s. Definition 1: The reception, via our nervous system, of instances received and processed by the five senses (sight - iconic, hearing – echoic, touch – haptic, taste – gustatory, and smell – olfactory), the resultant use of language and nonverbal communication system through which neural representation are coded, ordered, and given meaning using our ability to organise our communication and neurological systems to achieve specific desired goals and results. Definition 2: The Study of the Structure of Subjective Experience and what can be calculated from it. (Pasztor, 1998; Sadowski & Stanney, 1999; Slater, Usoh, & Steed, 1994).

  9. Learner Profile - Communication Preference Sensual Memory NLP LP 60% Iconic Visual SEE 30% Echoic Auditory HEAR 10% Haptic Kinaesthetic(tactile-haptic instances) FEEL(emotional) NLP = Neuro-Linguistic Programming LP = Language Patterns

  10. Learner Profile –VARK(Neil Fleming – 1987) Learning Style Preferences Visual oriented students Learn via their eyes, in charts, graphs, flow charts, and symbolic representation Auditory oriented students Learn via their ears Read/Write oriented students Learn via the written/printed word Kinaesthetic oriented students Learn by doing – simulated or real Multi-modality Learn by multi-sensory input Learner’s Learning Style Preference is firmly established before joiningHigher –Education and may be not be interpreted correctly by tutors.

  11. Learner Profile – MBTI®(Myers-Briggs 1948) Type Indicator Preference Types ESTJ - ESTP - ESFJ - ESFP - ENTJ - ENTP - ENFJ - ENFP ISTJ - ISTP - ISFJ - ISFP - INTJ - INTP - INFJ - INFP 16 Styles:

  12. WISDeM – Intelligent Tutoring System Algorithms map types to factors

  13. Learner Profile Research indicates that • Creating a Learner’s Profile from his/her • Communication Preference & • Learning Styles • Mapping Learning Styles & Teaching Styles • Providing timely relative motivational input is beneficial in inter-personal communication.

  14. The Way We Learn

  15. Subliminal Text Messaging Subliminal images and text: Definition: Instance input that the conscious mind does not observe but the subconscious does. See: Gustavsson, 1994 “Unconscious words are pouring into awareness where conscious thought is experienced, which could from then on be spoken [the lips] and/or written down”.

  16. Output – Topic Testing – Visual Q&A’s

  17. Output - Topic Testing - Visual Feedback

  18. Output - Topic Testing – Buttons and Links

  19. Evaluation (119 respondents) Some results

  20. Evaluation Communication Preference

  21. Evaluation Personality Types

  22. Evaluation Personality Types

  23. Evaluation Question Average Marks

  24. Evaluation Improvement Analysis

  25. Future • Further develop authoring tool • Transfer to SQL database for scalability • Research & create auditory input facility • Develop a talking avatar (face only)??? • Student facility to choose avatar’s: • Features – hair, image, shape, etc • Voice tone, eye gaze and pupil size • Sex.

  26. WISDeM • Web • Intelligent • Student • Distance • education • Model

  27. Published Janvier, W. A., & Ghaoui, C. (2001, September). Searching for WISDeM, the Holy Grail of Intelligent Distance Education. Paper presented at the HCT2001 Workshop - Information Technologies and Knowledge Construction: bringing together the best of two worlds, University of Sussex, Brighton. Janvier, W. A., & Ghaoui, C. (2002, 1-4 November). WISDeM - Student Profiling using Communication Preference and Learning Styles mapping to Teaching Styles. Paper presented at the APCHI 2002 - 5th Asia Pacific Conference on Computer Human Interaction, Beijing, China. Janvier, W. A., & Ghaoui, C. (2002, 26-27th Sept). WISDeM: Communication Preference and Learning Styles in HCI. Paper presented at the HCT2002 Workshop - Tools for thought: Communication and Learning Through Digital Technology, Brighton, UK. Janvier, W. A., & Ghaoui, C. (2003, September 3-5). Using Communication Preference and Mapping Learning Styles to Teaching Styles in the Distance Learning Intelligent Tutoring System - WISDeM. Paper presented at the Knowledge-Based Intelligent Information and Engineering Systems - 7th International Conference - KES 2003, Oxford, UK. Janvier, W. A., & Ghaoui, C. (2003, 18-21 May). WISDeM and E-Learning System Interaction Issues. Paper presented at the 2003 IRMA International Conference, Philadelphia Pennsylvania, USA. Janvier, W. A., & Ghaoui, C. (2004, May 23-26). Interactive E-Learning.Paper to be presented at the 2004 IRMA INTERNATIONAL CONFERENCE - Innovations Through Information Technology, New Orleans Marriot Hotel, New Orleans, LA, USA. Ghaoui, C., & Janvier, W. A. (2004). Smart ProFlexLearn: An Intuitive Approach to Virtual Learning Environment. To be published by Idea Group Inc. Janvier, W. A., & Ghaoui, C. (2004). Human-Human Interaction replication in Human-Computer Interaction. Interactive Technology and Smart Education (ITSE): To be published by (Troubador Publishing Ltd).

  28. Bibliography Bandler, R., & Grinder, J. (1981). Frogs into Princes: Neuro Linguistic Programming: Real People Pr. Borchert, R., Jensen, D., & Yates, D. (1999). Hands-on and Visualization Modules for Enhancement of Learning in Mechanics: Development and Assessment in the Context of Myers Briggs Types and VARK Learning Styles. Paper presented at the ASEE Annual Conference, Charlotte, NC, USA. Catania, A. C. (1992). Learning - Remembering (3rd ed.): Prentice-Hall International Editions. Cotton, J. (1995). The Theory of Learning - An Introduction. London: Kogan Page. Fleming, N. (2001). Teaching and Learning Styles: VARK Strategies: Neil Fleming. Fuller, D., Norby, R. F., Pearce, K., & Strand, S. (2000). Internet Teaching By Style: Profiling the On-line Professor. Educational Technology & Society, 3(2), 71-85. Gustavsson, B. (1994, March 21 - 22). Technologizing of Consciousness - Problems in textualizing organizations. Paper presented at the Workshop on Writing, Rationality and Organization, Brussels. Handley, K. (2002, 26-27 Sept). Comparison of novice and expert learner's perception of instructional feedback in computer-based training to develop managerial problem-solving skils. Paper presented at HCT2002 Workshop - Tools for thought: Communication & Learning Through Digital Technology, Brighton, UK. Janvier, W. A., & Ghaoui, C. (2003b, September 3-5). Using Communication Preference and Mapping Learning Styles to Teaching Styles in the Distance Learning Intelligent Tutoring System - WISDeM. Paper presented at the Knowledge-Based Intelligent Information and Engineering Systems - 7th International Conference - KES 2003, Oxford, UK. Myers, I. B., & Myers, P. B. (1995). Gifts Differing : Understanding Personality Type. Palo Alto, CA, USA: Financial Times Prentice Hall. Pasztor, A. (1997, 7-10, August). Intelligent Agents with Subjective Experience. Paper presented at the 19th Annual Conference of the Cognitive Science Society, Stanford University, Stanford, CA, USA. Rutz, E., Elkins, V., Rafter, C., Houshmand, A., & Echart, R. (2000). Evaluation of Learning Styles and Instructional Technologies Sadowski, W., & Stanney, K. (1999). Measuring and Managing Presence in Virtual Environments. Retrieved January, 2002, from http://vehand.engr.ucf.edu/handbook/Chapters/Chapter45.html Slater, M., Usoh, M., & Steed, A. (1994). Depth of Presence in Virtual Environments - Body Centred Interaction in Immersive Virtual Environments. Presence: Teleoperators and Virtual Environments, 3.2, 130-144. Wilson, K., Dugan, S., & Buckle, P. (2002). Understanding Personality Functioning Without Forced Choice: Expanding the Possibities for Management Education Based on Empirical Evidence.

  29. Thank you for listeningAny questions?

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