Setsuya Kurahashi: Teaching Simulation on Collaborative Learning, Ability Groups and Mixed-ability Groups
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This document presents a teaching simulation focused on the impact of teaching strategies, seating arrangements, and student grouping (ability vs mixed-ability) on collaborative learning effectiveness. Various experiments were conducted to analyze the influences of these factors on students' understanding and the overall learning process, utilizing models like item response theory and complex doubly structured networks. The results suggest that collaborative learning and strategic seating arrangements can significantly enhance learning outcomes.
Setsuya Kurahashi: Teaching Simulation on Collaborative Learning, Ability Groups and Mixed-ability Groups
- 1. 1 Teaching Simulation on Collaborative Learning, Ability Groups and Mixed-ability Groups Setsuya KURAHASHI* and Keisuke KUNIYOSHI Graduate School of Systems Management (GSSM) University of Tsukuba, Tokyo
- 2. 2 Agenda • Motivation and Aims • Related Work of Learning theory • Item Response Theory • Graphical Test Theory • Complex Doubly Structured Network • Learning Model with Complex Doubly Structured Network • Experiment 1 : Effect of teaching strategies • Experiment 2 : Effect of collaborative learning • Experiment 3 : Effect of seating arrangement • Experiment 4 : Effect of ability classes • Discussion and Summary • Future work
- 3. 3 Development of Human Resources Cultural Capital Education Development of Human Resources Gene MOOC
- 4. Motivation and Aims • What kind of influence could teaching strategies have on learning effects? • Modeling of a learning process of each student and teaching strategies. • What kind of influence could the seating arrangement of learners have on collaborative learning effects? • Modeling of learner’s interaction in a classroom. • What kind of influence could ability groups and mixed-ability groups have on collaborative learning effects? • Scenario analysis of learning environments. • The aims of the model is to analyse the actual conditions of understanding of learners regarding instructions given in classrooms. 4
- 5. Related Work of Learning Theory Test theory This study Item Response Theory (IRT) 5 Graphical Test Theory Bayesian Network Learning structuration study • Learning Material Structure Analysis • Course Outline Determination • Item Relational Structure (IRS) Complex Doubly Structural Network Social network study Doubly Structural Learning Model Probabilistic reasoning method
- 6. The approach of this study 6 Test theory for exam questions (IRT) Learning material structure model (Bayesian net) Collaborative learning approach In-class learning process regarding a teaching strategy is one of unexplored fields. Quantitative method of collaborative learning has not been developed yet. ■This study The understanding status, knowledge structure, and collaborative effect of each learner are simulated on an agent-based model integrated by using a complex doubly structural network. Experiment 1: Effect of teaching strategies in a classroom Experiment 2: Effect of collaborative learning Experiment 3: Effect of seating arrangements Experiment 4: Effect of ability classes
- 7. Probability of Understanding Item Response Theory : IRT 7 Item Response Theory (IRT) has been proposed to evaluate examina9on ques9ons. • IRT • Standard Test Theory • n Parameters Logistic Model • Xn : exam question n Estimation of Item Parameters(2PL) 2PL Model θ = + −θ −
- 8. 8 Graphical Test Theory: Bayesian Network Learning item Ｘ１ Ｘ2 Ｘ３ Ｘ4 Ｘ５ ■Estimation of a learning material structure fx3 = P(X1)× P(X1, X3) P(X3) = 0.82 fx1 = P(X1) fx2 = P(X1)× P(X3)× P(X4)× P(X2, X1, X3, X4) P(X1, X3, X4) = 0.74 fx 4 = P(X1)× P(X3) × P(X4, X1, X3) P(X1, X3) fx5 = P(X2)× P(X3)× P(X4) × = 0.83 P(X5, X2, X3, X4) P(X2, X3, X4) = 0.61 Dependency relationship Conditionally probability of dependency
- 9. 9 Complex Doubly Structural Network Internal Network (knowledge) Social Network (society) Internal Network This model can express networks in microscopic and macroscopic ways as an integrated model.
- 10. Doubly Structural Learning Model 10 Understanding probability Teacher Social Network Internal Network Social (Classroom) Network Students Teaching Level of achievement Knowledge structure Classroom Internal (Knowledge) NetworkTeaching strategy Knowledge Collaborative learning 2 ) 2 * 2 + 2 , 2 - ) * Teacher + , - . / 0 1 )( )) )* )+ ), )- ). )/ )0 )1 *( *) ** *+ *, *- *. */ *0 *1 +( '
- 11. ! # $ Item Response Theory %
- 12. Simulation Method 11 ■In-class learning model ・30 learners in a classroom ・5 teaching materials: X1, X2, X3, X4, X5 ■Internal network From arithmetic exam answer data of 300 learners, estimating (1) understanding probability(IRT), (2) material structured model(Bayesian Network) ■Social network From seating allocation and correct answer data in a class, modeling a social network in a classroom. ■Simulation This simulation is to estimate what material should be taught, in what order and how many times, until all learners in the classroom could give the correct answer. ■Criteria 1) Attainment degree : the proportion of correct answer 2) Average teaching time : the time until the attainment degree has reached 1
- 13. Estimated Ability and Understanding Probability 12 Item parameters: ability, difficulty, discrimination (IRT) Understanding probability (IRT, Bayesian network) Correct or Incorrect Ability Probability X1 X2 X3 X4 X5 X1 X2 X3 X4 X5 1 1 1 1 1 1 0.8457 1 0.93 0.96 0.95 0.68 2 1 1 1 1 0 0.1658 0.99 0.77 0.89 0.87 0.39 3 1 1 1 0 1 0.2427 0.99 0.8 0.9 0.88 0.43 4 1 1 1 0 0 -0.297 0.97 0.57 0.79 0.76 0.22 5 1 1 0 1 1 0.2 0.99 0.78 0.89 0.87 0.41 6 1 1 0 1 0 -0.332 0.97 0.56 0.78 0.75 0.21 7 1 1 0 0 1 -0.268 0.98 0.59 0.8 0.77 0.23 8 1 1 0 0 0 -0.731 0.91 0.37 0.64 0.63 0.12 9 1 0 1 1 1 0.0953 0.99 0.74 0.88 0.85 0.37 10 1 0 1 1 0 -0.419 0.96 0.52 0.75 0.73 0.19 … … … … … … … … … … … … 29 0 0 0 1 1 -1.102 0.78 0.22 0.49 0.49 0.07 30 0 0 0 1 0 -1.475 0.55 0.12 0.35 0.35 0.04 31 0 0 0 0 1 -1.427 0.58 0.13 0.36 0.37 0.04 32 0 0 0 0 0 -1.817 0.31 0.06 0.23 0.24 0.02
- 14. Simulation procedures 13 For each knowledge Xn { For each learner { If a learner's Xn == 0 { if a collaborative relationship == true on the social network and a student on the relationship already understand the knowledge { P(Xn) - 1 } else { Select subsequent knowledge connected Xn on the internal network. The probability is calculated as multiplication of the probability of all precedent knowledge connected and the conditional probability. } Based on the probability calculated, the value is conversed into two values 1 and 0. } } A=er evalua9ng understanding status of all students for every material, a teacher decides the most effec9ve material to teach next.
- 15. 14 Transition of the understanding status
- 16. ODD protocol 15 Overview 1.Purpose What kind of influence could teaching strategies have on learning effects? What kind of influence could ability groups and mixed-ability groups have on collaborative learning effects? 2.Entities, State valuables and Scales Teacher: teaching strategy, understanding status of students Students: understanding status, 3.Process overview and scheduling Applying teaching strategies for some class patterns in which students are seated, and then by comparing the average time of teaching sessions and the attainment degrees.
- 17. ODD protocol 16 Design concepts 4.Design concepts ・Basic Principles: Item Response Theory for understanding probability model Bayesian Network for the course material structure model Social Network and the complex doubly structured network model ・Emergence: Collaborative learning ・Adaptation: A teacher decides order of a teaching material depending on understanding status of students. ・Objectives: Understanding status of students, teaching time ・Learning: No ・Prediction: A teacher predicts the most effective order of a teaching material. ・Sensing: Understanding status ・Interaction: Collaborative learning between students ・Stochasticity: Seating arrangements, ・Collectives: In-class social network between students and a teacher ・Observation: Understanding status, teaching times
- 18. ODD protocol 17 Details 5.Initialization Teacher: 1, Student: 30, Material: 5 Teaching strategy: 4 types Learning style: lecture, left-and-right, group Seating arrangement: random, concentrated, dispersed Ability class: mixed-ability, high ability, medium ability, low ability 6.Input Data Arithmetic examination results of 300 students from an online learning system 7.Submodels Item response theory Graphical Test theory Course material structure model Complex doubly network theory
- 19. EXPERIMENT 1: EFFECT OF TEACHING STRATEGIES 18
- 20. Comparison between teaching strategies TS No. Method TS 1 Teaching along with estimation by the complex doubly structured network method TS 2 Teaching by selecting items to teach in a random manner TS 3 Teaching an item where many learners gave wrong answers TS 4 Teaching by moving to next item when all learners understood an item by order of the highest correct answer rate 19 What kind of influence teaching strategies could have on learning effects. ■Teaching strategy Teacher
- 21. 20 The transition of attainment degree TS 1 TS 2 TS 3 TS 4
- 22. 21 Results of Experiment 1: Teaching Strategies ■Simulation result （The average teaching time） No. Method Lecture style (Non-collaborative) TS 1 Teaching along with estimation by the complex doubly structured network method 22.5 TS 2 Teaching by selecting items to teach in a random manner 41.4 TS 3 Teaching an item where many learners gave wrong answers 32.3 TS 4 Teaching by moving to next item when all learners understood an item by order of the highest correct answer rate 23.4 TS 1 has the highest attainment degree, TS 4 is the second best which adopts the teaching order of the highest correct answer rate.
- 23. EXPERIMENT 2: EFFECT OF COLLABORATIVE LEARNING 22
- 24. Collaborative Learning Model 23 What kind of influence collaborative learning could have on learning effects. Left-and-right collaborative learning Group collaborative learning Teacher Lecture style learning (non-collaboration) Teacher Teacher High academic capability
- 25. 24 Results of Experiment 2: Collaborative learning ■Simulation result （The average teaching time） No. Method Collaboration type 1) Collaborative learning effect is higher than non-collaborative one. 2) Group collaborative learning is higher than left-and-right collaborative learning. Lecture Left-and-right Group TS 1 Teaching along with estimation by the complex doubly structured network method 22.5 8.2 6.0 TS 2 Teaching by selecting items to teach in a random manner 41.4 17.7 13.6 TS 3 Teaching an item where many learners gave wrong answers 32.3 11.8 8.3 TS 4 Teaching by moving to next item when all learners understood an item by order of the highest correct answer rate 23.4 9.3 6.0
- 26. 25 EXPERIMENT 3: EFFECT OF SEATING ARRANGEMENTS IN COLLABORATIVE LEARNING
- 27. 26 Comparison between seating arrangements What kind of influence the seating arrangement could have on learning effects. Concentrated arrangement Dispersed arrangement Teacher High academic capability
- 28. 27 Effect of seating arrangements in “left-and-right” collaborative learning Random arrangement Concentrated arrangement Dispersed arrangement Teacher Teacher Teacher
- 29. High academic capability Average teaching time: Left-and-right collaboration Concentrated Random Dispersed 9.5 8.2 7.7
- 30. Effect of seating arrangements in “group” collaborative learning 28 Random arrangement Concentrated arrangement Dispersed arrangement Teacher Teacher Teacher Average teaching time Group collaboration Concentrated Random Dispersed 8.4 6.0 5.6
- 31. Results of Experiment 3: Seating arrangement 29 Average teaching time Seating arrangement Collaborative learning type Random Concentrated Dispersed Left-and-right 8.2 9.5 7.7 Group 6.0 8.4 5.6 1) While the teaching time increases in the concentrated arrangement. it decreases in the dispersed arrangement. 2) Learning effects vary by making changes in the seating arrangement and the dispersed arrangement could enhance teaching effects.
- 32. EXPERIMENT 4: EVALUATION OF EFFECTS ON ABILITY CLASSES 30
- 33. 31 Evaluation of the effects on ability classes What kind of influence ability classes could have on learning effects. Lecture style High ability class Medium ability class Low ability class Average teaching time of ability classes High Medium Low 17.0 20.0 23.7 Teacher Teacher Teacher
- 34. 32 Evaluation of the effects on ability classes Left-and-right collaborative learning High ability class Medium ability class Low ability class Average teaching time of ability classes High Medium Low 7.8 8.4 9.3 Teacher Teacher Teacher
- 35. 33 Evaluation of the effects on ability classes High ability class Medium ability class Low ability class Average teaching time Group collaboration Teacher Teacher Group collaborative learning High Medium Low 6.0 6.9 7.0
- 36. 34 Results of Experiment 4: Ability class Total number of average teaching time for mixed-ability and ability classes Learning type Mixed-ability classes Ability classes Lecture (non-collaborative) 67.5 60.7 Left-and-right collaborative learning 23.1 25.5 Group collaborative learning 16.8 19.9 In the lecture model, teaching time for the ability classes is less than the mixed ability classes. In the left-and- right, group collaborative learning model, teaching time for the ability classes is more than the mixed ability classes. The results indicate that ability classes have adverse effects on learners in collaborative learning.
- 37. 35 Results of Experiment 4: Ability class Average teaching time for mixed-ability and ability groups Mixed-ability class Ability class Learning style High Medium Low Lecture 22.5 17.0 20.0 23.7 Left-and-right 8.2 7.8 8.4 9.3 Group 6.0 6.0 6.9 7.0 The ability classes for students of high academic capability are effective more than or equal to mixed-ability classes, while not effective for students of medium and low academic capability in collaborative learning.
- 38. 36 Discussion and Summary • We designed the integrated simulation model for in-class learning processes considering academic capability, leaning material structure and collaborative relationship by interfacing internal and social network. • 1st experiment: Effect of a teaching strategy • Different teaching strategies cause different effects of learning. • The proposed teaching strategy has the highest attainment degree, • 2nd experiment: Effect of a collaborative learning • Collaborative learning has a positive effect more than the lecture style. • 3rd experiment: Effect of a seating arrangement • A dispersed seating arrangement is more effectively than a concentrated seating arrangement. • 4th experiment: Effect of ability classes • Mixed-ability classes are more effective than ability classes in the collaborative learning, while ability classes are effective in the lecture style.
- 39. Discussion and Summary 37 How influence could teaching strategies have on learning effects? (1) When different teaching strategies, seating arrangements, and collaborative learning are used, learning effects vary, (2) group style collaborative learning on dispersed seating arrangements using the doubly structural learning model has high learning effects, and the second best is the method in order of the highest answer rate, and (3)an ability group has negative effect on collaborative learning because they reduce diversity in a class, so homogeneity between learners has the risk to make collaborative effect fall into decline, (4) whereas, if teaching is done one time for one knowledge item, some learners could fall behind in the learning progress. Reviews should be conducted repeatedly to facilitate the anchoring of the knowledge in a class.
- 40. 38 Future work • We were not concerned about negative effects from unskilful students or misunderstanding, so we’ll add the negative effects in the model. • Some classes adopt more dynamic collaborative learning where high ability students are allowed to walk around and teach or discuss with others in a class. This dynamic situation should be designed in our model.