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Stable Roommate Framework for Deploying chess Measurably in Schools. Presented by Malola Prasath T S. Foundation for Learning Research in Chess. Introduction.

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Stable Roommate Framework for Deploying chess Measurably in Schools


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    1. Stable Roommate Framework for Deploying chess Measurably in Schools Presented by Malola Prasath T S Foundation for Learning Research in Chess

    2. Introduction • We support the notion of Chess in Schools and focus on developing a structured environment to potentially deploy chess within classroom. • We address the process for deploying chess in schools based on simulated tournament conditions to expedite learning across the classroom. • We potentially exploit the individuality of student pairs who controllably dissipate emotions over interactions. • We focus to make the learning mutual, to help the teachers to simultaneously evolve within classroom. • We measure the indicator of overall progress of the individual under controlled emotional considerations.

    3. Background • The skill availability is minimizing with increasing sophistication of technology. • Faster and more robust learning has been the current focus area for education • Education is rapidly catching up with the pace of the market. • However, with the openness of information the present classroom is not a closed world. • So the transformation in the learning process have come out of the way to structure the learning environment to improve the focus. • Emotional Stability and Visibility have been the key towards employable feature in today’s service oriented industries.

    4. Approach • Identify the Emotional stability of classroom • Identify the process of understanding Emotional visibility of chess based learning • Identify a marriage for chess and classroom processes to evolve a framework for learning. • Interface ‘the people’ to framework • Maximize artifact level visibility to teacher • Optimize learning on Emotional visibility of students • Quantify the progress accounting the artifacts from controlled interaction.

    5. Traditional classroom: Imbalance vs Method • Imbalances in a classroom • Gradient in knowledge between the student and teachers • Individual Ability • Ephemeral / Sub-optimal Learning pattern in students • Focus of Teacher • Objectively deliver the Instructions • Bring to a common platform of understanding • Neutralize the impact over the imbalances over • Socializing behavior of students • learning and assimilating capabilities of students • Reproduce and Usage of Learning • Method for Students • Chaotic Learners (Unreliable) • Subjectively Optimized • Sub-optimal learning methods

    6. Emotional Visibility in Chess • Historic: Prophesies and world champion prophets • Philidor’s Era – the notion of philosophical approach to chess • Paul Morphy,W. Stenitz - reflected the freshness and the aggression of Industrial revolution in America. • Hyper Modern Era of Nimzowitch is the sensation of Innovation • The Endgame Persistence of Capablanca • Botwinnik’s Emphasis on methods/processes reflect then scientific community • Blitz attack by Tal and Fischer reflect the notion of World dominance • Notion of Strategic defense and incremental positional manoeuvre reflect cold-war mentality is observed in Anatoly Karpov. • Computer Assisted Reactive chess in Styles of Garry Kasparov, Anand reflect the current practice of Re-use and design patterns. • Method: History is not mere co-incidence • Project the thought processes against the imbalance in chess • Sense and Observe our depth of perception • Incrementally progress by improvisation. • Observe ourselves back and forth to realize ourselves • Realization • Cultural state of Man greatly influences the individuality • Chess is a framework built over simulated imbalances of Life. • Thoughts in Chess reflect the sensation of the cultural state of Mind.

    7. Notion of Chess in classroom: A Stable Marriage • We attempt to marry chess and classroom activity at a process level to obtain emotional visibility over our progress • Imbibe the responsibility of professionalism • Conscious on the state of mind (Individuality) • Ability to observe ourselves emotionally • Interacting with our own individuality over likes and dislikes • Interacting across individualities and imbalances • Develop a highly visible framework for students and teachers to observe and intervene timely. • Develop a Culture for simultaneous learning and practicing learning • Increase the responsibility • Adopt continuous process improvement • Predictability • Measurability

    8. Grand Challenge in the Framework • Deploy students in chess based process Framework • Interface the students to the Framework • Controllable Interaction for emotional visibility • Interface the teachers, so as to improve the vision over activity level of students. • Visibility of Chess through Optimal Learning practices Qualitatively measure the student’s progress • Achieve: • Meet the objective of learning through individualistic sub-optimal processes • Improved visibility over learning • Accomplish: • Uniform and continuous progress within the classroom

    9. Epitome: Defining the controlled process The 3 As Process Paradigm • Actors: • Controlling Interaction to optimally pace the student interaction for maximizing learning • Both within and across multiple framework of learning • Improved Observation without disturbing learning process • Internal: Implicit interaction with Students, Teachers • External: Interaction with External consultants • Activity: • Orientation • Defining the chess based activity • Artifacts: • Managing the artifacts accountable for continuous learning. • Analysis of Artifacts for continuous learning

    10. Actor: Interaction specific formulation • Increase the focus on Observation • Decouple Student –Teacher at direct interaction Level to improve observation on students • Cluster the students into groups that can be managed by a mentor/Teacher. • Controllably facilitate interaction both within group and across the groups simultaneous. • Intra – group – Learning measured • Inter – group – Experience is measured • Focus the measurement across Stable cliques, where the Imbalance is optimized • Interaction within and across stable cliques • Interactions of stable cliques within and across groups • Project the observation against mentors influence • Teacher/ Mentor proximity • Improve the observation

    11. Actor: Schematic Diagram Discussion Desk Observers Group 4 Group 1 Group 2 Group 3 Mentors / Teacher Student within Group Student moving across Groups Figure 1: Class Room Architecture Gaming Group

    12. Scheme for facilitating controlled interaction Group I {A,B,C,D,E,F} Group II {G,H,I,J,K,L} Group III {M,N,O,P,Q,R} Group IV {S,T,U,V,W,X} Figure 2: Clustered Group • Step 1: Generate an overall ranking, based on any acceptable scheme. • Step 2: Identify the pairing condition over the entire group using the Swiss system of pairing over different emotions over learning. • Step 3: Cluster the students into group of 6 to be mentored over a dedicated table as illustrated in figure 2. The clustered group is ensured that there exist a stable marriage among the students and the mentor. • Step 4: Identify the stable pair within each clustered groupusing a round-robin pairing scheme to exhaust possible interaction within a group, to computing the optimal gradient between rankings as metric potentially to identify stable pairs. • Step 5: Cluster the students into two groups, first to learn within the proximity from the mentor in an intra-group interaction setting and second, for the stable pairs to interact across the group at an inter-group interaction site. • Step 6: Identify further interactive pairs based on the visibility over the interactions of pair that is identified over increasing proximity with the mentor. • Step 7: Cluster the students of intra-group into two sub-groups based on the proximity of the student pairs to the mentor, in such a way that the closer proximity include larger gradient over the ranking of students. • Step 8: Circulate the student pair across the inter-group and intra groups; in such a way that student interacts over the identified optimal pairs over all three proximity distance from the mentor. • Step 9: Iterate the process over shuffling the student ranks. A-C, B-D, G-I, H-J, M-O, N-P S-U, T-V, E-F, K-L,Q-R,W-X Figure 3: Stable cliques Intra-Group interaction || A-D C-B || Inter-Group interaction || E –R Q-F|| Figure 4: Student Interactions Sequence 1: || A-D C-B || || E –R Q-F|| Sequence 2: || E-C F-D || || G–B A-H|| Sequence 3: || B-F E-A || || J –D C-I || Figure 5:Cycle of Interaction

    13. Activity: Developing chess based program • We base the activities based on the chess program • Chess Activity Centric: • Developing the scope of chess syllabus • Instruction Centric • Developing adaptive chess Lessons • Customizing chess Lessons based on individuality • Emotional Centric • Chess activity for Controlled Interaction Levels both within and across interactive groups • External Observer Centric • Teacher’s Birds eye view for Intervention and Measurement • External Observer’s Visibility for Intervention.

    14. Scope of Adaptive Chess Lessons

    15. Emotional Centric: Measurements Two levels of emotional centric activities Stable Clique specific Interaction Observation specific Interaction Teachers / External observers / Stable Clique Measurement Focus Quality Participation Quality time Extent of Predictable and continuous development Table 2: Highlighting the quality attributes

    16. Workshop: Using In vivo Observation

    17. Gradient Bandwidth Gaming Farther Proximity Near Proximity Tolerance Co-ordination Contribution L.Dev Learning Collaboration Focus Usability Reach Diversion Analyzing the Artifacts • We have customized the EDA charts to qualitatively represent the progress • Continuous Improvement pattern in Students • Involvement bandwidth in Teachers Learning Learning Collaboration Collaboration Locus of Development Locus of Development Focus Focus Usability Usability Contribution Contribution Reach Reach Reach Co-ordination Co-ordination Diversion Tolerance Tolerance Diversion Over Gaming Over Learning Over Gaming Over Learning Figure 3: Results of Orientation Tests Figure 4: Results for Test Iteration Figure 3: Involvement Bandwidth for during interactions

    18. Artifacts: Impact of the Learning System • General Perspective • Highly Structured environment • Stable-pair based interaction facilitates rapid learning • Highly visibility over activities gives transparency • Students’ Perspective • Greater freedom to work on their individual needs. • Emotional visibility is quantifiable • Simulated tournament conditions facilitates both hands on experience under emotional constraints. • Meeting the objective through subjective methods. • Building an expectation from teachers • Teacher’s Perspective • Teaching to Mentoring • High Visibility over Activity specific. • Better understanding of the students expectation

    19. Conclusion • We have achieved the inception phase of a novel structured learning environment that facilitates active learning across student groups. • We have identified design of self evolving framework for deploying chess measurably in Schools with high visibility.

    20. Road ahead! • We wish to test the scalability of our system across cross culture, disabilities, educational status to evolve an ubiquitous design of learning systems.

    21. Reference • [1] R Beichner, J M Saul, D S Abbott, J. Morse, Duane Deardorff, Rhett J. Allain, S W Bonham, Melissa Dancy, and J. Risley, "Student-Centered Activities for Large Enrollment Undergraduate Programs (SCALE-UP) project," in PER_Based Reform in University Physics, edited by E F Redish and P. J. Cooney (American Association of Physics Teachers, College Park, MD, In Press). • [2] M Saul, R Beichner, D S Abbott, J. Morse, Duane Deardorff, Rhett J. Allain, S W Bonham, Melissa Dancy, and J. Risley, "Incorporating active learning in large introductory physics classes: The SCALE-UP Project," Phys. Rev. ST Phys. Educ. Res. • [3] Mourad Baiou and Michel Balinski. Erratum: The stable allocation (or ordinal transportation) problem. Mathematics of Operations Research, 27(4):662–680,2002. • [4] L. R. Ford and D. R. Fulkerson. Maximal flow through a network. Can. Journal of Math., 8:339–404, 1956. • [5] D.E. Knuth. Stable marriage and its relation to other combinatorial problems. In CRM Proceedings and Lecture Notes, vol. 10, American Mathematical Society, Providence, RI. (English translation of Marriages Stables, Les Presses de L’Universit´e de Montr´eal, 1976), 1997. • [6] Chung, K.-S. (2000). “On the existence of stable roommate matchings,” Games and Economic Behavior 33, 206–230. • [7] Tan, J. J. M. (1991). “A necessary and sufficient condition for the existence of a complete stable matching,” Journal of Algorithms 12, 154–178. • [8] Chung, K.-S. (2000). “On the existence of stable roommate matchings,” Games and Economic Behavior 33, 206–230. • [9] Blumenfeld, P. C., Soloway, E., Marx, R., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist,.26(3&4), 369-398. • [10] Ritter, F. E., & Bibby, P. (2001). Modeling how and when learning happens in a simple • fault-finding task. In Proceedings of ICCM–2001–Fourth International Conference on • Cognitive Modeling (pp. 187-192). Mahwah, NJ: Erlbaum. • [11] Richman, H. B., Gobet, F., Staszewski, J. J., & Simon, H. A. (1996). Perceptual and memory processes in the acquisition of expert performance: The EPAM model. In K. A. • Ericsson (Ed.), The road to excellence. Mahwah, NJ: Erlbaum. • [12] Ritter, F. E. (1993a). TBPA: A methodology and software environment for testing process models’ sequential predictions with protocols (Tech. Rep. No. CMU-CS-93-101).Pittsburgh, PA: Carnegie Mellon University, School of Computer Science.

    22. Thank you Your Questions ?