From Research to Innovation in Computers and Education: Bridging the Gap between Science and Social Contribution

1April 20, 2016

From Research to Innovation in Computers and Education: Bridging the Gap between Science and Social Contribution

University of Saskatchewan, Saskatoon, Canada

Center of Excellence for Social TechnologiesComputing Institute (IC) - Federal University of Alagoas (UFAL)

[email protected] Ibert Bittencourt

Brasil

April 20, 2016 2July, 2007

Brasil

April 20, 2016 3

April 20, 2016 4

Maceió

April 20, 2016 5

Maceió

Maceió, Alagoas, BrazilApril 20, 2016 6

8April 20, 2016





The beginning...

Research and Innovation...

Bridging the gap...

MeuTutor

How it was created?

Many researchers working with Computers in Education have a dream ....

...that is:research achievements should also have a strong impact on real classrooms and teaching-learning processes

Unfortunately, this dream does not come true to most of us !

Usually it happens because we often choose to follow two distinct path ways

óri

Technology-oriented Research

Cutting-edge technological advancement, tested in controlled environments. Yet, not mature enough to be used in classrooms

óri

Pedagogy-oriented research

Understanding on how to instructional processes and

Technologies affect students and teachers. It has strong local impact,

yet, it is very difficult to be generalized and used in large scale

Ig Ibert Bittencourt | [email protected]

19http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg

April 20, 2016


20http://media.linkjab.com/i/images/university-of-bologna-the-worlds-oldest-university.jpg

April 20, 2016 July, 2007

2007

IG IBERTPHD UFCG

SEIJI ISOTANIPHD OSAKA/Japão

We decided to create a platform that allow us to research on advanced technology and scale results from pedagogical research

We also believed that such a platform should live even after we left academia

IG IBERTPHD UFCG

SEIJI ISOTANIPHD OSAKA/Japão

2007

But, how we do that?

We generate innovation from research findings

And create products that will have a real impact on society

MeuTutor

Startup company that developed a platform to create Intelligent tutoring systems

http://meututor.com.brPersonalized Learning for All

Research Spin-off Company

MeuTutor: First Generation

Negative feedback - First Version








MeuTutor: Second Generation First Version

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MeuTutor: Second Generation Second Version

Student Module

Student Module

Student Module

Student Module

Teacher Module

Coordinator Mod.

Coordinator Mod.

Secretary of Education Module

Secretary of Education Module

• BANDEIRA, J. M. ; AVILA, T. ; I. BITTENCOURT, IG ; Isotani, Seiji.; et al. Dados Abertor Conectados para a Educação. JAIE, Sociedade Brasileira de Computação, 2015, v. 1, p. 47-69.

Mobile Version

Mobile Version


How does it work?

Learn Essay

Personalized Learning

Semantically Structured

Motivational Perspective

Intelligent Approach

Learn Essay





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Skills

Topics

Disciplines

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Learn Essay





Learn Essay





Know

ledg

e

Resources Semanticallyconnected

Lightweight Ontologies

User Model

ExpertModel

Domain Model

Interface


• Bittencourt, I. I.; et al. (2009). A Computational Model for Developing Semantic Web-based Educational Systems. Knowledge-Based Systems.• Bittencourt, Ig Ibert; Olavo Holanda ; Isotani, Seiji . JOINT: Java Ontology Integrated Toolkit. Expert Systems with Applications, v. 40, p. 6469-6477, 2013.

Lightweight OntologiesDomain Model



User Model



Pedagogical Model


Lightweight OntologiesGamification Model

Learn Essay





Learn Essay





GAMIFICAÇÃO

Results Expected

Student Model

Specialist Model

Domain Model

Interface Model

ITS Core

Player Types

Gamification

Model

Gamification

ElementsGamificatio

n Layer

ITS Gamification Platform

Acquire knowledge to built a framework to help designing Personalized Gamified ITSs.

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MINERAÇÃO DE DADOS

PERFIL DO ESTUDANTE

PERFIL GERAL

CRIA O PERFIL DO ESTUDANTE BASEADO NA

MÉDIA

MISSÕES PERSONALIZADASALUNOIdentifica Missões para

um determinado Aspecto

Pers

onal

ized

Miss

ions

Pers

onal

ized

Miss

ions

Colaborative

Social Gamified

Individualized

Colaborative

Social Gamified

Individualized• PAIVA, R. ; BITTENCOURT, I. I. ; et al . Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment. In: the 30th ACM SAC 2015.

Pers

onal

ized

Miss

ions

• PAIVA, R. ; BITTENCOURT, I. I. ; et al . Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment. In: the 30th ACM SAC 2015.• PAIVA, R. ; BITTENCOURT, I. I. ; et al . What do students do online? Modeling students' interactions to improve their learning experience. EAAI. (under review)

Peer Assessment

640

Peer Assessment approach to Learn Essay

• Tenório, T.; Bittencourt, I. I.; Isotani, S. A gamified peer assessment model for on-line learning environments in a competitive context. Computers and Human Behavior (under review)• Tenório, T.; Bittencourt, I. I.; Isotani, S. Does Peer Assessment in On-line Learning Environments work? A systematic review of the literature. Internet and Higher Education (under review)

Learn Essay





Learn Essay





GENETIC ALGORITHMS

Adaptive Strategy (1st Generation)

• Questions

• User Profile

Classification

• Recommendation

IRT• Micro concepts

• Learning Outcomes

BKT

Adaptive Strategy (2nd Generation)

• Ryan S. J. d. Baker, Albert T. Corbett, Vincent Aleven (2008). More Accurate Student Modeling through Contextual Estimation of Slip and Guess Probabilities in Bayesian Knowledge Tracing. In. ITS Conference.

User model updating

User model updating

99April 20, 2016Recommentation: Video

Recommentation: Mission

Peer Assessment

Define the sample

MINE (CLUSTERING)

Recommendation Profiles

Pedagogical Recommendation

Learning Essay to ENEM ExamImprove learning

Best Performance

Worst Performance

Define the Sample

Mine (Clustering)

RECOMMENDATION PROFILES

Pedagogical Recommendation

Group of recommendation Profiles Activities

1 1, 2 e 4 Read a new essay with grade 1000

2 3, 5, 8, 10 e 11 Resource to Competency 5

3 6, 7, 9, 12, 16, 17 e 18 Resource to Competencies 2, 3 and 5

4 14 Resource to Competencies 1 and 4

5 15 Resource to Competencies 2, 3 and 5

6 13 e 19 Resource to Competencies 1 and 4


640

Não houve ganho Ganho Parcial Ganho total0

2

4

6

8

10

12

14

10

13

6

Writing Two Essays

Não houve ganho Ganho Parcial Ganho total0

1

2

3

4

5

6

1

4

5

Writing Three Essays

65,5% of the students Improved 90% of the students ImprovedNo Imp. Partial Imp. Total Imp. No Imp. Partial Imp. Total Imp.


Santos, D. ; Bittencourt, I. I.; Paiva, R. Learning Essay through Educational Data Mining and Pedagogical Recomendation. Computers and Human Behavior (to be submitted)

Learning Essay to ENEM ExamMobile Learning

Learn Essay





100 5000

+30.000

NUMBER OF USERS

STUDENTS

48%FASTER More learning

27%

April 20, 2016 108Ig Ibert Bittencourt | [email protected]

≈ 30.000 in 2016

TWO NEW CLIENTS

109

1. Telco Company (B2C)

2. Big School Player (B2B)≈ 100.000 in 2017

≈ 20.000 in 2017≈ 50.000 in 2018

2000 10000


What are the next steps?

MeuTutor (Third Generation)

Learn Essay

Second Generation

Improvements

Collaboration

Optimal Experience

Authoring

Second Generation

Improvements

SANTANA, S. J. ; I. BITTENCOURT, I. ; ISOTANI, S. (2016). A Quantitative Analysis of the Most Relevant Gamification Elements in an Online Learning Environment. In: WWW@WebED. Canadá: ACM, 2016. v. 1.

SANTANA, S. J. ; BITTENCOURT, I.; et al . (2016). Evaluating the impact of Mars and Venus Effect on the use of an Adaptive Learning Technology for Portuguese and Mathematics. In: IEEE ICALT.

Malta, C. ; Bittencourt, I.; et al . (2016). A Computational Model to Automatically Classify the Goal-Orientation Motivation of Students. Plos One (to be submitted)

Collaboration

• Isotani, S. ; MIZOGUCHI, R. ; Bittencourt, I.; et al. A Semantic Web-based authoring tool to facilitate the planning of collaborative learning scenarios compliant with learning theories. Computers and Education, 2013.

• REIS, R. RODRIGUEZ, C; LYRA, Bittencourt, I. I.; Isotani, S.; et al. Affective States in CSCL: Studying the Past to Drive the Future. Computers and Education (under review).

Collaboration

Optimal Experience

• CHALCO, G.; ANDRADE, F. R. H. ; BORGES, S. S. ; BITTENCOURT, IG, I. ; Isotani, Seiji . Toward A Unified Modeling of Learner?s Growth Process and Flow Theory. Educational Technology & Society, 2016.• SANTOS, W. O. ; BITTENCOURT, IG, I. ; Isotani, Seiji ; MARQUES, L. ; Frango, I . Challenges of Flow Theory Applied to Computers in Education. In: DesafIE, 2015, Recife. 2015. v. 1. p. 1-10.• SANTOS, W. O. ; BITTENCOURT, IG, I. ; Isotani, Seiji ; MARQUES, L. ; Frango, I . Flow Theory applied to Computers in Education: Systematic Literature Review . Computers and Human Behavior (to be submitted).

Authoring

Diego Dermeval

• Dermeval, Diego ; TENÓRIO, THYAGO ; BITTENCOURT, IG IBERT ; et al.. Ontology-based Feature Modeling: An Empirical Study in Changing Scenarios. Expert Systems with Applications, v. 1, p. 1-26, 2015.• Dermeval, Diego ; VILELA, JÉSSYKA ; BITTENCOURT, IG IBERT ; CASTRO, JAELSON ; Isotani, Seiji ; Brito, Patrick ; Silva, Alan . Applications of ontologies in requirements engineering: a systematic review of the

literature. Requirements Engineering (London. Print), v. 1, p. 1-35, 2015.• Dermeval, Diego ; BITTENCOURT, IG IBERT ; et al. An Ontology-driven Software Product Line Architecture for Developing Gamified Intelligent Tutoring Systems. Educational Technology & Society (under review)

Authoring

Ranilson Paiva

• PAIVA, R. ; Bittencourt, I. I.; et al. (2014). A Systematic Approach for Providing Personalized Pedagogical Recommendations Based on Educational Data Mining. 12th ITS Conference.• Paiva. R; Bittencourt, I. I. et al. A Data-Informed Intelligent Process for the Authoring of Pedagogical Decisions. IJAIED (Under Review)

How to bridge the gap?


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MissionFormation of Social Leaders through RDI in ICT.

VisionIn 10 years, be an International Reference in the formation of Social Leaders

Goals

1. Generation of Scientific Knowledge2. Promotion of Social Spin-offs3. Formation of Social Leaders

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NEES

Artificial Intelligence in

Education

Social Entrepreneurship

Computational Ontology

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Research ProjectPrototype Paper PublicationProduct

4P Cycle to generate research spinoffs

Transfer Technology Process


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People Money

SocialValue

Opportunity


“My grade in ENEM (National Exam) was 675, I was accepted in 1° Place in Law School at Federal University of Tocantins and I was accepted at Federal University of Rondônia. I used MeuTutor and it helped me a lot, mainly in Math, because I have lots of difficult”

“I did ENEM (National Exam) and had 127 correct questions from 180. I was approved in Medicine at UMC. I studied alone and the MeuTutor-Platform was very important because of the videos and explicative questions. Congratulations for the Platform”

Social Spinoffs

Social Inequality

Research

Innovation



Maceió

Maceió, Alagoas, Brazil

Thank you!Muito Obrigado!

Merci Beaucoup!April 20, 2016 131

132April 20, 2016



