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1 Can Chess Improve Math Scores? An Italian Experiment Goes International. Roberto Trinchero Department of Philosophy and Education.

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Presentation on theme: "1 Can Chess Improve Math Scores? An Italian Experiment Goes International. Roberto Trinchero Department of Philosophy and Education."— Presentation transcript:

1 1 Can Chess Improve Math Scores? An Italian Experiment Goes International. Roberto Trinchero Department of Philosophy and Education University of Turin Giuliano D'Eredità – University of Palermo Workgroup: Alessandro Dominici, Giovanni Sala Dario Mione, Malola Prasath, Gianluca Argentin

2 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Can Chess Improve Math Scores in primary school children? The implicit in the chess activities in school is the belief that skills acquired playing chess can transfer to other domains; Is this belief based on well-substantiated evidence?; Italian research  A basic in- presence Chess course of 30 hours can improve specific Math ability. 2 Gobet F., Campitelli G. (2006), Educational benefits of chess instruction. A critical review, Trinchero R. (2012), Gli scacchi, un gioco per crescere. Sei anni di sperimentazione nella scuola primaria, Milano, FrancoAngeli.

3 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Our Research: Chess and Oecd-Pisa Math Scores Hypotesis: A blended (in-presence+online) basic Chess course can improve Oecd-Pisa Math Scores in children of 8-11 age; Sample: 568 pupils of Italian primary school (non- random sample from Piedmont and Lombardy); Method: Solomon 4-group test-retest experimental design; Subsamples: The Experimental Group was differentiated by:  Class attended (grade 3, 4, 5);  Number of hours of the course (10, 11, 14, 16);  Year of chess course (1, 2, 3). 3

4 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy The Math test Seven Oecd-Pisa released item (selected to be faceable by 8-11 years-old pupils): 4 Oecd-Pisa item code Math abilities involvedOecd-Pisa Estimated difficulty Analogy with chess ability M145Q01Calculate the number of points on the opposite face of showed dice 478 (Level 2) Calculate material advantage R040Q02Establish the profundity of a lake integrating the information derived from the text and from the graphics 478 (Level 2) Find relevant information on a chessboard M520Q1ACalculate the minimum price of the self- assembled skateboard 496 (Level 3) Calculate material advantage M806Q01Extrapolate a rule from given patterns and complete the sequence 484 (Level 4) Extrapolate checkmate rule from chess situation M510Q01TCalculate the number of possible combination for pizza ingredients 559 (Level 4) Explore the possible combination of moves to checkmate M159Q05Recognize the shape of the track on the basis of the speed graph of a racing car 655 (Level 5) Infer fact from a rule (e.g. possible moves to checkmate) M266Q01Estimate the perimeter of fence shapes, finding analogies in geometric figures 687 (Level 6) Find analogies in chessboard situations

5 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy An Example of item 5

6 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy The Experimental Design: Solomon 4-group test-retest 6 GroupN.Activities G1 (Experimental)380Pre-testBlended chess training (in presence + CAT) Post-test G2 (Experimental without pretest) 32-Blended chess training (in presence + CAT) Post-test G3 (Control)115Pre-testOrdinary school activitiesPost-test G4 (Control without pretest) 41-Ordinary school activitiesPost-test CAT = Computer Assisted Training (www.europechesspromotion.org) October- November 2012 January- February 2013 Shadish W. R., Cook T. D., Campbell D. T. (2002), Experimental and Quasi-Experimental Designs for Generalized Causal Inference, Boston-New York, Houghton Mifflin Company,

7 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Score gain in mathematic ability: General results 7 Initial scoreGain Sign. SubgroupMean St. dev. Mean St. dev. G1 (Experimental)1,37 1,17 0,67 1,51 0,000 G3 (Control)1,53 1,30 0,08 1,42 - Math final scores Group Mean St. dev.Sign. Experimental (G1) 2,03 1,310,006 Experimental without pretest (G2) 2,72 1,61- Math final scores Group Mean St. dev.Sign. Control (G3) 1,61 1,190,56 Control without pretest (G4) 1,49 1,03- There is a little but significative increase of Math scores in Experimental Group (0,67 vs a maximum of 7, Anova) The pre-test has lead to a significative decrease of gain in Experimental Group (probably «boredom» effect)

8 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Score gain in mathematics ability: Subgroups analysis 8 Initial scoreGain Sign. SubgroupMean St. dev. Mean St. dev. G1b ,74 1,79 0,11 1,88 0,942 G1a ,64 1,20 0,16 1,74 0,763 G1p4-8-21,57 1,06 0,27 1,38 0,409 G1d ,14 0,86 0,51 1,37 0,103 G1g ,27 0,93 0,63 1,41 0,023 G1g ,05 0,84 0,66 1,26 0,022 Whole G11,37 1,17 0,67 1,51 0,000 G1p ,56 1,30 0,79 1,36 0,003 G1r ,16 0,94 1,04 1,43 0,003 G1c ,68 1,42 1,43 1,17 0,000 G1b ,94 1,43 1,44 2,12 0,001 G1c ,55 0,93 1,73 0,79 0,000 G3 (control)1,53 1,30 0,08 1,42 - Score gain Successful subgroups Significance relevant to Control Group (from Anova)

9 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Successful subgroups 9 SubgroupN.N. ClassesChess training G1p (grade 5) 16 hours in presence, 2 hours per week (first year of training) + CAT G1r (grade 4) 10 hours in presence (first year of training) + CAT G1c (grade 4) 14 hours in presence, 2 hours per week (year of training) + CAT G1b (grade 5) 14 hours in presence (second year of training) + CAT G1c (grade 5)14 hours in presence, 2 hours per week (third year of training) + CAT Successful subgroups have attended a chess course of almost 14 hour OR …

10 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Engagement in the online game (CAT) 10 Achieved level in online game SubgroupPlayers% on the subgroup Mean St. dev. G1p %5,38 4,17 G1g %5,75 4,36 G1d %5,86 4,71 G1g %6,08 4,48 Whole G131382%6,72 4,46 G1a %7,16 4,66 G1p %7,36 4,26 G1b %8,00 4,00 G1r %9,00 3,96 G1c %9,43 3,98 G1b %10,33 2,16 G1c %11,00 0,00 … have had a greater involvement in the CAT … with an exception …

11 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Unsuccessful subgroups 11 SubgroupN.N. ClassesChess training G1a (grade 4) 11 hours in presence (first year of training) + CAT G1g (grade 4) 10 hours in presence (first year of training) + CAT G1g (grade 3) 10 hours in presence (first year of training) + CAT G1d (grade 4) 10 hours in presence (first year of training) + CAT G1p (grade 4) 8 hours in presence, 2 hours per week (second year of training) + CAT G1b (grade 4)14 hours in presence (second year of training) + CAT Exception: a class with a very high initial score, and with several organizational problems in post-test

12 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Score gain in Chess ability 12 Initial scoreGain Sign. SubgroupMean St. dev. Mean St. dev. G1p4-8-25,45 3,39 3,52 3,37,000 G1d ,51 2,63 5,73 4,34,000 G1c ,71 4,16 5,86 4,54,000 G1b ,37 5,14 6,11 4,52,000 G1a ,23 4,48 6,25 4,11,000 G1c ,45 3,39 6,27 4,52,000 Whole G13,00 3,98 6,62 4,60,000 G1g ,57 3,40 7,04 4,92,000 G1g ,61 1,95 7,20 4,63,000 G1p ,54 3,85 8,46 4,22,000 G1r ,92 1,80 8,84 3,70,000 G1b ,17 4,49 10,17 5,11,000 G3 (control)1,17 2,46 0,47 2,10 - Maximum gain is 18.Significance is relevant to the control group and calculated with Anova

13 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Overall results The gain in math scores is proportional to time spent in the chess course; CAT can be an effective instrument for chess training; These results are compliant with results of Italian research Trinchero R. (2012), Gli scacchi, un gioco per crescere. Sei anni di sperimentazione nella scuola primaria, Milano, FrancoAngeli.

14 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy Weakness of the study and future challenges Weakness: Participants were not randomly selected:  Groups and subgroups are not statistically equivalent;  Results are not generalizable. Challenges:  To define the conditions of transferability  when the transferability can occur;  To explain the dynamics of chess transfer  what ability are transferable and why. 14

15 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy The experience in 2010:Using the digital technologies for chess scholastic learning A collaboration among Turin University, Palermo University and Italian National Research Council (CNR), with the support of Italian Chess Federation- Piedmont Committee, Banca San Paolo, MSP; The goal of the inquire was to compare different chess learning settings; We submitted to 3 rd grade students a short chess protocol (10h) using digital or traditional learning; For traditional learning we considered 3 modes: Chess Instr. only, Chess Instr.+Class Teacher, 2 Chess Instr.+Class Teacher We adopted the software Gatto Vittorio (it was its first appearance !) 15

16 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy The experience in 2010: Main results Surprisingly, kids who already knew chess obtained worst results! The best results were obtained using the 2 Ch.Instructors+Teacher mode, followed by Ch.Instr.+ Teacher, after Ch. Instr, at last the digital one, but the only significative difference was found for the 2Ch. Instr + teacher mode; We have to respect kids' learning time (digital activity requires more time with respect to the traditional one); 10 h is the minimum time to obtain any achievement ); Doing tests, and obtaining feedback from them improve the chess learning 16

17 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy In progress: Research «Chess World» Replication of research design, with: An international sample (Italy and India) (about 6000 participants); Sample with randomized pairs of equivalent classes (swap experimental-control groups): 17 Randomized selection Test G1 Experimental G2 Control G1 ControlG2 Experimental Change 1 Change 2 Hypotesis is corroborated if Ch1(G1)>Ch1(G2) And Ch2(G2)>Ch2(G1)

18 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy We are managing to realize an implicative statistical analysis with respect to the reasoning and arguing style of the students; Through an a-priori analysis of the items we will formulate other research hypotheses based on epistemological and social-linguistic considerations; These hypotheses are to be turned into implications and correlations among the occurrences of the tests outputs, using binary variables (Y or N); We'll adopt the implication and correlation indexes as in Gras (2000), using the software CHIC 18

19 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy 19 Syntesis of italian research R. Trinchero (2012), Gli scacchi, un gioco per crescere. Sei anni di sperimentazione nella scuola primaria, Milano, FrancoAngeli. R. Trinchero (2012), Chess, a game to grow up with: a synthesis of six years of research, Milano, FrancoAngeli (the book has a chapter in English that summarize the results).

20 Roberto Trinchero – Department of Philosophy and Education - University of Turin – Italy 20 Thanks… Presentation is available on Thanks to workgroup: Alessandro Dominici - Giovanni Sala Dario Mione - Malola Prasath - Gianluca Argentin


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