Post on 07-Jan-2017
1July, 2016
Evaluating the impact of Mars and Venus Effect on the use of an Adaptive Learning Technology for Portuguese and Mathematics
Center of Excellence for Social TechnologiesComputing Institute (IC) - Federal University of Alagoas (UFAL)
ig.ibert@ic.ufal.brSivaldo Joaquim, Ig Ibert Bittencourt, et al
The 16th IEEE International Conference on Advanced Learning Technologies - ICALT2016 – Austin, Texas
Brasil
Maceió
Maceió
Maceió, Alagoas, Brazil
6July, 2016
Evaluating the impact of Mars and Venus Effect on the use of an Adaptive Learning Technology for Portuguese and Mathematics
Center of Excellence for Social TechnologiesComputing Institute (IC) - Federal University of Alagoas (UFAL)
ig.ibert@ic.ufal.brSivaldo Joaquim, Ig Ibert Bittencourt, et al
The 16th IEEE International Conference on Advanced Learning Technologies - ICALT2016 – Austin, Texas
14th Century
http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg
http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg
14th Century
http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg
14th Century
http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg
14th Century
Few evolution in this area
1870 Paoli Classroom
http://sjvnoticias.com/sala-de-aula-ontem-e-hoje/ 2015
http://www.grmwebsite.com/blog/bid/67340/Welcome-to-the-21st-Century-Why-YOU-Should-Be-Marketing-on-the-Web 21st Century
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
https://onlineacademiccommunity.uvic.ca/jjohal93/category/blogs/
http://www.theaerodrome.com/forum/showthread.php?t=61895
http://www.theaerodrome.com/forum/showthread.php?t=61895http://andthatswhyyouresingle.com/2013/04/14/why-testing-a-man-will-almost-always-backfire/frustrated-woman-at-computer-3/
Gamification
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Adaptive Techniques for Individualized Learning
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Skills
Topics
Disciplines
[Vail et al., 2015]
Of all the learner characteristics that are known to influence the effectiveness of adaptive support, gender is one of the most widely recognized.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
In several domains: Mathematics; Introduction to Computer Programming.
[Arroyo et al., 2011, 2013]; [Vail et al., 2015]
Gender difference in the use of intelligent educational technologies:
http://passofundo.notredame.org.br/estudantes-conquistam-a-2a-colocacao-em-olimpiada-de-programacao-de-computadores/
http://pt.123rf.com/photo_31784263_menina-da-escola-doce-latin-pouco-com-rabo-de-cavalo-cansado-e-entediado-com-o-computador-de-casa-ma.html
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
According to these studiesThere is a difference in:
Behavior; Attitude; Learning and; Emotion based on the gender.
[Arroyo et al., 2011, 2013]; [Vail et al., 2015]
http://blog.tricae.com.br/educacao/psicomotricidade-na-educacao-infantil/ http://colegiomarista.org.br/santamaria/diferenciais/para-mais-de-um-nivel
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Cognitive levels: Conceptual and problem-based approaches; Affective assistance (motivation and engagement)
[Arroyo et al., 2011, 2013]; [Vail et al., 2015]
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Gender Difference Studies: Usually performed as lab studies; Few studies investigated the gamification support; Only some studies about language course (but no Portuguese); No experimental study with ecological settings in Brazil; No model to estimate Math and Portuguese performance based on
gender.
http://blog.tricae.com.br/educacao/psicomotricidade-na-educacao-infantil/ http://colegiomarista.org.br/santamaria/diferenciais/para-mais-de-um-nivel
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Our Study
Mars and Venus Effect
Different variables: Learning performance (Portuguese and
Mathematics); Age; Location area; Adaptive learning technology.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Investigate learning performance (Math and Portuguese); The gamification support; Experimental study with ecological settings; Propose a model to estimate Math and Portuguese
performance.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Instrument: A Gamified Intelligent Tutoring System
100 5000
+30.000
NUMBER OF USERS
STUDENTS
48%FASTER More learning
27%
Game elements of MeuTutor
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Student solving a recommended problem for him in MeuTutor
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
5th Grade
School D
School C
School B
School A
5th Grade
5th Grade
5th Grade
9th Grade
9th Grade
9th Grade
9th Grade
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
School C
School D
School A
School B
Experimental group Control group
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School A
5th Grade 9th Grade
School B
5th Grade 9th Grade
Experimental group (with the use of ITS gamified)
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
School C
5th Grade 9th Grade
School D
5th Grade 9th Grade
Control group (without the use of ITS gamified)
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Timeline
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Intervention models
Teacher
Intervention models
Integrated class instruction Homework
After-class instruction
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| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Results
Participants
191students
87 (45.55%) Male
104 (54.45%)Female
Between 9 and 21 years old (mean = 13.8, sd = 2.01)
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
the use of an adaptive learning technology improves student’s performance in Mathematics and Portuguese for both male and female students (p-Value < .05).
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
The improvement of male student’s performance is more significant (p-Value < .05)
Math Portuguese
39.1%43.4%
19.7%24.6%
Male Female
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
When we focus on technology, male students had better performance in mathematics (21%), but no significant difference in Portuguese.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Beta regression model
The response variables of the models are:
Ymath (Math performance);
Yport (Port performance).
The mean Yport or Ymath,
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Beta regression model
Where:
is the linear predictor;
is the sample size;
is the individual;
is an unknown vector parameter;
are fixed covariates .
Can be written as:
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Almost all covariates are significant at the 5% nominal level (p-Value < .05), except Gender for
the performance model in Portuguese.
Beta regression model
Parameter Estimates and P-value for *General* Models. Full dataset.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Beta regression model
The systematic components of the models were defined by the following mathematical expressions:
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Beta regression model
Other six models, only considering the significant covariates
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
In this case:
If a model is correctly specified we expect that the residuals are randomly scattered around zero in the plots of residuals against observations index.
The residuals graphical analysis
It is essential to validate the aforementioned conclusions
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
The normal probability plot with generated envelope:
Can be used even when the empirical distributions of the residuals are not normal;
If the model fits well, we expect that most of the residuals fall within the band;
Are based on the differences between the observed responses (y) and its fitted value ().
Another residuals graphical
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
In figures
See: a, e, I, m - c, g, l, o
It is possible to notice that the residuals are randomly scattered around zero (no systematic features) in all plots of the combined residual against the observations index, for both Math and Portuguese models.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
However,...
For the normal probability plots there is a slight evidence of misspecification of two models for the Mathematics performance, the “Only Using MeuTutor” and the “Female” models, suggesting the need for other explicative variables, possibly elements of the MeuTutor; see Figures (f, n).
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Beta regression model
Six models, only considering the significant covariates
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Such as:
Receptiveness to technology
Preference of pedagogical approach
The meaning of optimal experience
Gamified Approach
Stereotype Threat
Possible Explanations to Technology and Female Models:
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
62
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Psychological Mediator
Affective Mechanisms
Cognitive Mechanisms
Motivational Mechanisms
Stereotype Threat
Less Performance
Anxiety
Individual Tendencies
Apprehension
Self-efficacy
Dejection
Self-handicapping
Effort/Motivation
Vigilance
Cognitive Load
Thought suppression Negative ThinkingMind-wandering
63
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64
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Different Gamification
Elements
Less Improvement
Implicit Stereotype
Threat
New Hyphotesis
Confirmed the hypothesis of gender’s influence on adaptive learning environments, by presenting its reliability with other research settings and instruments.
Proposition of models to estimate performance:
To sum up
New hypothesis raised to explain the Mars and Venus Effects related to the design of gamified educational systems.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
ReferencesIvon Arroyo, Beverly P. Woolf, David G. Cooper, Winslow Burleson, Kasia Muldner. "The Impact of Animated Pedagogical Agents on Girls’ and Boys’ Emotions, Attitudes, Behaviors and Learning". Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on. Doi: 10.1109/ICALT.2011.157.
Ivon Arroyo, Winslow Burleson, Minghui Tai, Kasia Muldner, Beverly Park Woolf. “Gender differences in the use and benefit of advanced learning technologies for mathematics”. Journal of Educational Psychology, Vol 105(4), Nov 2013, 957-969. http://dx.doi.org/10.1037/a0032748.
Alexandria Katarina Vail, Kristy Elizabeth Boyer, Eric N. Wiebe, and James C. Lester."The Mars and Venus Effect: The Influence of User Gender on the Effectiveness of Adaptive Task Support". 23rd International Conference, UMAP 2015, Dublin, Ireland, June 29 -- July 3, 2015. Proceedings. Doi: 10.1007/978-3-319-20267-9_22.
Ferrari, S.L.P.; Cribari-Neto, F. (2004) “Beta regression for modelling rates and proportions”, Journal of Applied Statistics.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
ReferencesEspinheira, P.L., Silva, C.M. Silva, A.O. (2015). “Prediction Measures in Beta Regression Models”. arXiv:1501.04830.
Gneezy, Uri, and Aldo Rustichini. "Gender and competition at a young age." The American Economic Review 94.2 (2004): 377-381.
Niederle, Muriel, and Lise Vesterlund. "Gender and competition." Annu. Rev. Econ. 3.1 (2011): 601-630.
Kim, Jung Tae, and Won-Hyung Lee. "Dynamical Model and Simulations for Gamification of Learning." International Journal of Multimedia and Ubiquitous Engineering 8.4 (2013): 179-190.
Koivisto, Jonna, and Juho Hamari. "Demographic differences in perceived benefits from gamification." Computers in Human Behavior 35 (2014): 179-188.
Paiva, Ranilson O. Araújo, et al. "Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment." Proceedings of the 30th Annual ACM Symposium on Applied Computing. ACM, 2015.
| www.nees.com.br/enIg Ibert Bittencourt | ig.ibert@ic.ufal.br
Maceió
Maceió, Alagoas, Brazil
Thank you!Muito Obrigado!
Questions???
72July, 2016
Evaluating the impact of Mars and Venus Effect on the use of an Adaptive Learning Technology for Portuguese and Mathematics
Center of Excellence for Social TechnologiesComputing Institute (IC) - Federal University of Alagoas (UFAL)
ig.ibert@ic.ufal.brSivaldo Joaquim, Ig Ibert Bittencourt, et al
The 16th IEEE International Conference on Advanced Learning Technologies - ICALT2016 – Austin, Texas