• 6900000
  • info@iis-international.org
  • Athens, Greece

ITS2021 - ATHENS (Online Conference)

ITS

ITS2021 is the 17th Conference of the series of Intelligent Tutoring Systems Conferences on Computer and Cognitive Sciences, Artificial Intelligence and Deep Learning in Tutoring and Education.

The theme of the conference is “INTELLIGENT TUTORING SYSTEMS IN AN ONLINE WORLD”.

The conference will be held in Athens, Greece, in June 2021.

PROGRAM

To check the Conference Program  click on a respective day on the table below:

 

 

Testing Teams Platform
Networking Session
Sunday, June 6, 2021
Special PHD Student Session
Workshop
Tutorial 1
Monday, June 7, 2021
Tutorial 2
Main Conference – Day 1
Panel Discussion
Tuesday, June 8, 2021
Main Conference – Day 2Wednesday, June 9, 2021
Main Conference – Day 3Thursday, June 10, 2021
Main Conference – Day 4Friday, June 11, 2021

The timetable of ITS2021 Conference corresponds to Eastern European Summer Time (EEST); UTC+3 hours

Sunday, June 6

14:00-
15:30

TESTING DAY: Testing Microsoft Teams platform for everyone who feels uncertain about sharing their presentation and wants to try it beforehand

16:00-
19:00
NETWORKING SESSION
16:00-
17:30
B2B meetings
17:30-
17:40
Break
17:40-
19:00
Thematic groups

Monday, June 7

 

Special Session

10:00-
13:00
Title:  SPECIAL SESSION FOR PHD STUDENTS

 

Coordinators: Mizue Kayama, Shinshu University , Japan

Mike Joy, University of Warwick , UK

Workshop

13:30-
15:30
Title: Intelligent Tutor Demonstrations

 

Coordinators: Mihai Dascalu,  University Politehnica of Bucharest, Romania

Amruth Kumar, Ramapo College of New Jersey, USA

Daniela Romano, University College London, UK

13:30-
15:10
Part I: ITS showcases and demos
13:30-
13:50
Presentation of Alast
Discussion and Q&A
13:50-
14:10
Presentation of ReadMe
Discussion and Q&A
14:10-
14:30
Presentation of Solvelets
Discussion and Q&A
14:30-
14:50
Presentation of Cram
Discussion and Q&A
14:50-
15:10
Presentation of Selflt
Discussion and Q&A
15:10-
15:30
Part II: Open discussions

Tutorial  1

16:00-
19:00
Title:  Learning Analytics Hands-On Tutorial (LA)

 

Coordinator: Professor Alexandra I. Cristea, Durham University

16:00-
16:10
Introduction of Topic and Team
16:10-
16:25
Introduction of Participants
16:25-
16:30
Break
16:30-
16:50
Theory of LA
16:50-
17:00
Break
17:00-
17:20
Hands-on LA
17:20-
17:50
Theory of LA
17:50-
18:00
Break
18:00-
18:30
Hands-on LA
18:30-
19:00
Panel Discussion
19:00End of Session

Tuesday, June 8 

Tutorial  2

10:00-
13:30
Title:  Data Science for Learning Process management

 

Coordinator: Filippo Sciarrone, ROMA TRE University, Rome (IT)

10:00-
10:10
Introduction: Summary and main goals
10:10-
10:25
Introduction of Participants
10:25-
10:35
Break
10:35-
11:35
Introduction to the Knime Platform: workflow environment, ML algorithms, workflow building, Data management
11:35-
11:45
Break
11:45-
13:15
Learning Process management: case studies
13:15-
13:30
Panel Discussion
13:30End of Session

 Main Conference DAY 1

15:00-

 

15:30

Opening / Greetings
Prof. Cleo Sgouropoulou – General Conference Chair
Prof. Claude Frasson – President of the ITS Steering Committee
Prof. Alexandra I.Cristea  & Dr. Christos Troussas – Program Committee Chairs
Dr. Kitty Panourgia – Organization Chair
15:30-

 

17:20

SESSION 1: ASSESSMENT

 

Session Chair: Christos Troussas

Arthur Rump, Ansgar Fehnker, Angelika Mader
#49: Automated Assessment of Learning Objectives in Programming Assignments (FP)

Moritz Marutschke, Yugo Hayashi
#31: Ex-Ante and Ex-Post Feature Evaluation of Online Courses Using the Kano Model (FP)

Robert-Mihai Botarleanu, Mihai Dascalu, Laura Allen, Scott Crossley, Danielle McNamara
#53: Automated Summary Scoring with ReaderBench (FP)

Bogdan Nicula, Mihai Dascalu, Natalie Newton, Ellen Orcutt, Danielle McNamara
#54: Automated Paraphrase Quality Assessment using Recurrent Neural Networks and Language Models (SP)

17:20End of Session

Panel Discussion 

17:30-
18:50
Title:  From Models to Deployments – The Industry Perspective on The Future of ITS Research and Implementations

 

Coordinators: Richard Tong, IEEE Learning Technology Standards Committee, Squirrel AI Learning

Eric Cosyn, ALEKS/MHE

Jerry Liu, IEEE Learning Technology Standards Committee, TAL

Janice Gobert, Rutgers University,  Apprendis

17:30-
17:35
Opening Remarks and Introduction: Mark Lee and Richard Tong
17:35-
18:05
Short Presentations
Moderator: Janice Gobert
Panelists: Richard Tong, Eric Cosyn, Jerry Liu
18:05-
18:35
Panel Discussion
18:35-
18.50
Open Q&A
18:50End of Session

Welcome Event: Virtual Tour Of Athens

19:00-
20:00
Title: Virtual live-guided tour around Athens 

 

A virtual journey through the most significant archaeological sites of Athens – the birthplace of democracy and philosophy – live from Greece to the ITS2021 participants.
This virtual, real-time, live-guided tour through the most fascinating places (i.e. Acropolis, Parthenon, Erechtheion, Pnyx Hill, the Ancient Agora, and Plaka area) will give  participants the opportunity to explore and feel the spirit of the beautiful and hospitable city of Athens by Athens Walking Tours

Wednesday, June 9

11:00-
12:30
SESSION 2:  THEORY AND REVIEWS

 

Session Chair: Lei Shi

Ryan Hodgson, Alexandra I. Cristea, Lei Shi, John Graham
#64: Wide-scale Automatic Analysis of 20 Years of ITS Research (FP)

Zhongtian Sun, Anoushka Harit, Jialin Yu, Alexandra I. Cristea, Lei Shi
#70: A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs (SP)

MARINA AIVAZIDI, Christos Michalakelis
#60: Exploring the Barriers of Educational Innovation (SP)

Konstantinos Karampidis, Athina Trigoni, Giorgos Papadourakis, Maria Christofaki, Nuno Escudeiro
#48:  Difficulties and disparities to distance learning during Covid-19 period for deaf students – A proposed method to eradicate inequalities  (P)

12:30-
13.00
Break
13:00-
15:40
SESSION 3: GAMES AND GAMIFICATION

 

Session Chair: Mohammad Alshehri

Elad Yacobson, Armando Toda, Alexandra I. Cristea, Giora Alexandron
#68: Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design (FP)

Mohamed Sahbi Benlamine, Claude Frasson
#73: Confusion detection within a 3D adventure game (FP)

 Kamilla Tenório, Bruno Lemos, Pedro Nascimento, Rodrigo Santos Silva, Alexandre Machado, Diego Dermeval, Ranilson Paiva, Seiji Isotani
#28: Learning and Gamification Dashboards: a Mixed-Method Study with Teachers (FP)

Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill
#32: An Automatic Adaptive Sequencing in a Webgame (SP)

Amruth Kumar
#9: Do Students Use Semantics When Solving Parsons Puzzles? – A Log-Based Investigation (SP)

Christos Troussas, Akrivi Krouska, Filippos Giannakas, Cleo Sgouropoulou, Ioannis Voyiatzis
#33: Representation of generalized human cognitive abilities in a sophisticated student leaderboard (P) 

Grigoreta Cojocar, Adriana Guran, Laura Diosan
#55: Towards Smart Edutainment Applications for Young Children. A Proposal (P)

15:40-
16:00
SPECIAL SESSION: PRESENTATION OF THE JOURNAL OF EDUCATION SCIENCES

 

Title: Education Sciences – An Open Access Journal by MDPI

Speakers: Milica Milosev & Mladen Rajic

16:00-
17:00
Break
17:00-
19:00
SESSION 4GROUPS, TEAMS, SOCIAL, CROWD AND COMMUNITIES

 

Session Chair: Maria Tzelepi

Filippos Giannakas, Christos Troussas, Akrivi Krouska, Cleo Sgouropoulou, Ioannis Voyiatzis
#21:XGBoost & Deep Neural Network comparison: The case of teams’ performance (SP)

Tao wu, Maiga Chang
#13: The Influence of Five Personality Traits on the Interactive Model of Online Group Formation (SP)

Stefano A. Cerri, Philippe Lemoisson
#10: Sovereignty by personalization of information search: collective wisdom influences my knowledge (SP)

 Fidelia Orji, Julita Vassileva
#39: A Comparative Evaluation of the Effect of Social Comparison, Competition, and Social Learning in Persuasive Technology on Learning (SP)

Fabio Gasparetti, Filippo Sciarrone, Marco Temperini
#86: Using Graph Embedding to Monitor Communities of Learners (SP)

Karima Boussaha, Samia Drissi
#5: New Horizons on Online Tutoring System Inspired by Teaching Strategies and Learning Styles (P)

19:00-
20:00
Keynote Speaker: Prof.  Peter Brusilovsky

 

Title: The return of Intelligent Textbooks

20:00End of Session

 Thursday, June 10

10:00-
11:00
Keynote Speaker: Adina Magda Florea,University POLITEHNICA of Bucharest, Romania

 

TitleInterpretability and Explanations in Intelligent Tutoring Systems

 

 

 

 

11:00-

13:45

SESSION 5: STUDENT PREDICTION 

 

Session Chair: Valia Triperina

Ahmed Alamri, Zhongtian Sun, Alexandra I. Cristea, Craig Stewart, Filipe Dwan Pereira
#69: Next week dropout prediction in MOOCs: weekly assessment of time and learning patterns (FP)

Tahani Aljohani, Alexandra I. Cristea
#52: Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification (FP)

Laila Alrajhi, Ahmed Alamri, Filipe Dwan Pereira, Alexandra I. Cristea
#51: Urgency Analysis of Learners’ Comments: an Automated Intervention Priority Model for MOOC (FP)

Efthyvoulos Drousiotis, Lei Shi, Simon Maskell
#24: Early Predictor for Student Success Based on Behavioural and Demographical Indicators (FP)

Mohammad Alshehri, Ahmed Alamri, Alexandra I. Cristea
#66: Predicting Certification in MOOCs based on Students’ Weekly Activities (FP)

Mona Alotaibi, Mike Joy
#46: Internet of Things (IoT) Based Support System for Diabetic Learners in Saudi Arabian High Schools (P)

13:45-
14:45
Break
 

 

14:45-
16:00

 

SESSION 6 : EXTENDED REALITY 

 

Session Chair: Jingyun Wang

Alessia Genovese, Federica Marino, Francesco Orciuoli, Gennaro Zanfardino
#57: ARDNA: a Mobile App based on Augmented Reality for supporting knowledge exploration in learning scenarios Predicting Certification in MOOCs based on Students’ Weekly Activities (SP)

Kodjine Dare, Hamdi Ben Abdessalem, Claude Frasson
#62: Extraction of 3D Pose in Video for Building Virtual Learning Avatars (SP)

Muhamad Irfan Rosli, Zarina Che Embi, Dr. Junaidi Abdullah
#58: A Non-immersive Virtual Reality Application for Children with Autism Spectrum Disorder (SP)

Sarah Alshamrani
#74: Using Augmented Reality in Computing Higher Education (P)

16:00-
17:05
SESSION 7: CONCEPT MAPS   

 

Session Chair: Jingyun Wang

Junya Morita, Yoshimasa Ohmoto, Yugo Hayashi
#18: Integrating Knowledge in Collaborative Concept Mapping: Cases in an Online Class Setting (SP)

Victor Uglev, Oleg Sychev
#11: Creating and Visualising Cognitive Maps of Knowledge Diagnosis During the Processing of Learning Digital Footprint (P)

Carla Limongelli, Carmine Margiotta, Davide Taibi
#19: Towards Semantic Comparison of Concept Maps for Structuring Learning Activities (P)

Jingyun Wang, Hiroaki Ogata
#35: An evaluation of a meaningful discovery learning support system for supporting E-book user in pair learning. (P)

17:05-
17:30
Break
17.30-
19:40
SESSION 8: FEEDBACK AND PERSONALISATION

 

Session Chair: Christos Papakostas

Seounghun Kim, Woojin Kim, Hyeoncheol Kim
#8: Learning Path Construction Using Reinforcement Learning and Bloom’s Taxonomy. (FP)

Victor J. Marin, Maheen Riaz Contractor, Carlos Rivero
#42: Flexible Program Alignment to Deliver Data-Driven Feedback to Novice Programmers (FP)

Ilya Posov, Sergei Pozdniakov, Anton Chukhnov
#61: Interaction of human cognitive mechanisms and “computational intelligence” in systems that support teaching mathematics. (SP)

Victor J. Marin, Hadi Hosseini, Carlos Rivero
#72: Customizing Feedback using Semantic Clusters. (SP)

Mohammad Niknazar, Aditya Vempaty, Ravi Kokku
#56: Voice Privacy with Smart Digital Assistants in Educational Settings. (P)

Laurentiu Neagu, Eric Rigaud, Vincent Guarnieri, Sebastien Travadel, Mihai Dascalu
#59: Selfit – An Intelligent Tutoring System for Psychomotor Development. (P)

19:40End of Session

     

Friday, June 11

10:00-
11:00
Keynote Speaker: Spyros Vosinakis

 

Title: Extended Reality Technologies in Education: Moving beyond the “Wow” factor

 

 

11:00-
13:05

SESSION 9:  EMOTIONS AND AFFECT  

 

Session Chair: Ahmed Alamri

Soelaine Rodrigues Ascari, Andrey Pimentel, Ernani Gottardo
#25: Tutorial Intervention’s Affective Model Based on Learner’s Error Identification in Intelligent Tutoring Systems (FP)

Doru Anastasiu Popescu, Gabriel Ciprian Stanciu, Daniel Nijloveanu
#15: Evaluation test generator using a list of keywords (FP)

Filipe Dwan Pereira, Hermino Junior, Luiz Rodriguez, Armando Toda, Elaine Harada Teixeira de Oliveira, Alexandra I. Cristea, David Oliveira, Leandro Carvalho, Samuel Fonseca, Ahmed Alamri, Seiji Isotani
#27: A recommender system based on effort: towards minimising negative affects and maximising achievement in CS1 learning (FP)

Mahsa Aghajani, Hamdi Ben Abdessalem, Claude Frasson
#34: Voice Emotion Recognition in Real Time Applications (SP)

Moh’d A. M. Abuazizeh, Kristina Yordanova, Thomas Kirste
#40: Affect-aware Conversational Agent for Intelligent Tutoring of Students in Nursing Subjects (P)

13:05-
14:00
Break
14:00-
16:25
SESSION 10: LEARNER BEHAVIOUR    

 

Session Chair: Tahani Aljohani

Khulood Alharbi, Alexandra I. Cristea, Lei Shi, Peter Tymms, Chris Brown
#41: Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students (FP)

Alejandra Ruiz Segura, Susanne Lajoie
#47: Expert, Novice, and Intermediate Performance: Exploring the Relationship Between Clinical Reasoning Behaviors and Diagnostic Performance (FP)

Sungeun An, William Broniec, Spencer Rugaber, Emily Weigel, Jennifer Hammock, Ashok Goel
#30: Recognizing Novice Learners’ Modeling Behaviors (FP)

Rita Kuo, Ted Krahn, Maiga Chang
#26: Behaviour Analytics – A Moodle Plug-in to Visualize Students’ Learning Patterns (SP)

Yoshimasa Ohmoto, Shigen Shimojo, Junya Morita, Yugo Hayashi
#29: Investigating Clues for Estimating ICAP States based on Learners’ Behavioural Data during Collaborative Learning (SP)

Komi Sodoke, Roger Nkambou, Issam Tanoubi, Aude Dufresne
#87: Toward an ITS to enhance novice clinician situational awareness based on expert perception behaviors in clinical reasoning (P)

16:25-
17:00
Break
17:00-
19:10
SESSION 11: MODELS

 

Session Chair: Katerina Makri

Seounghun Kim, Woojin Kim, Heeseok Jung, Hyeoncheol Kim
#7: DiKT: Dichotomous Knowledge Tracing (FP)

Jialin Yu, Laila Alrajhi, Anoushka Harit, Zhongtian Sun, Alexandra I. Cristea, Lei Shi
#45: Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums (FP)

Roger Nkambou, Janie Brisson, Ange Tato, Serge Robert, Maxime Sainte-Marie
#67: Learning Logical Reasoning Using an Intelligent Tutoring System: Improving the Student Model with a data driven approach (SP)

Oleg Sychev, Anton Anikin, Nikita Penskoy, Mikhail Denisov, Artem Prokudin
#22: CompPrehension – Model-Based Intelligent Tutoring System on Comprehension Level (SP)

Téo Orthlieb, Hamdi Ben Abdessalem, Claude Frasson
#71: Checking Method for Fake News to Avoid the Twitter Effect (P)

Vanesa Getseva, Amruth Kumar
#63: Comparing Bayesian Knowledge Tracing Model Against Naïve Mastery Model (P)

19:10-
19:30
Closing Session

 

Announcements for future events:

University of Bucharest, ITS2022

Dr. C.Trousas NiDS 2021

Other matters

19:30End of ITS2021 Conference

Greek Party

19:30-
20:00
Farewell party with traditional Greek folklore dance and music. 

 

 

Tuesday, June 8 

 

15:00-

 

15:30

Opening / Greetings
Prof. Cleo Sgouropoulou – General Conference Chair
Prof. Claude Frasson – President of the ITS Steering Committee
Prof. Alexandra I.Cristea  & Dr. Christos Troussas – Program Committee Chairs
Dr. Kitty Panourgia – Organization Chair
15:30-

 

17:20

SESSION 1: ASSESSMENT Session Chair: TBA

 

Arthur Rump, Ansgar Fehnker, Angelika Mader
#49: Automated Assessment of Learning Objectives in Programming Assignments (FP)

Moritz Marutschke, Yugo Hayashi
#31: Ex-Ante and Ex-Post Feature Evaluation of Online Courses Using the Kano Model (FP)

Robert-Mihai Botarleanu, Mihai Dascalu, Laura Allen, Scott Crossley, Danielle McNamara
#53: Automated Summary Scoring with ReaderBench (FP)

Bogdan Nicula, Mihai Dascalu, Natalie Newton, Ellen Orcutt, Danielle McNamara
#54: Automated Paraphrase Quality Assessment using Recurrent Neural Networks and Language Models (SP)

17:20End of Session

Wednesday, June 9

11:00-
12:30
SESSION 2:  THEORY AND REVIEWS

 

Session Chair: Lei Shi

Ryan Hodgson, Alexandra I. Cristea, Lei Shi, John Graham
#64: Wide-scale Automatic Analysis of 20 Years of ITS Research (FP)

Zhongtian Sun, Anoushka Harit, Jialin Yu, Alexandra I. Cristea, Lei Shi
#70: A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs (SP)

MARINA AIVAZIDI, Christos Michalakelis
#60: Exploring the Barriers of Educational Innovation (SP)

Konstantinos Karampidis, Athina Trigoni, Giorgos Papadourakis, Maria Christofaki, Nuno Escudeiro
#48:  Difficulties and disparities to distance learning during Covid-19 period for deaf students – A proposed method to eradicate inequalities  (P)

12:30-
13.00
Break
13:00-
15:40
SESSION 3: GAMES AND GAMIFICATION

 

Session Chair: Mohammad Alshehri

Elad Yacobson, Armando Toda, Alexandra I. Cristea, Giora Alexandron
#68: Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design (FP)

Mohamed Sahbi Benlamine, Claude Frasson
#73: Confusion detection within a 3D adventure game (FP)

 Kamilla Tenório, Bruno Lemos, Pedro Nascimento, Rodrigo Santos Silva, Alexandre Machado, Diego Dermeval, Ranilson Paiva, Seiji Isotani
#28: Learning and Gamification Dashboards: a Mixed-Method Study with Teachers (FP)

Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill
#32: An Automatic Adaptive Sequencing in a Webgame (SP)

Amruth Kumar
#9: Do Students Use Semantics When Solving Parsons Puzzles? – A Log-Based Investigation (SP)

Christos Troussas, Akrivi Krouska, Filippos Giannakas, Cleo Sgouropoulou, Ioannis Voyiatzis
#33: Representation of generalized human cognitive abilities in a sophisticated student leaderboard (P) 

Grigoreta Cojocar, Adriana Guran, Laura Diosan
#55: Towards Smart Edutainment Applications for Young Children. A Proposal (P)

15:40-
16:00
SPECIAL SESSION: PRESENTATION OF THE JOURNAL OF EDUCATION SCIENCES

 

Title: Education Sciences – An Open Access Journal by MDPI

Speakers: Milica Milosev & Mladen Rajic

16:00-
17:00
Break
17:00-
19:00
SESSION 4GROUPS, TEAMS, SOCIAL, CROWD AND COMMUNITIES

 

Session Chair: Maria Tzelepi

Filippos Giannakas, Christos Troussas, Akrivi Krouska, Cleo Sgouropoulou, Ioannis Voyiatzis
#21:XGBoost & Deep Neural Network comparison: The case of teams’ performance (SP)

Tao wu, Maiga Chang
#13: The Influence of Five Personality Traits on the Interactive Model of Online Group Formation (SP)

Stefano A. Cerri, Philippe Lemoisson
#10: Sovereignty by personalization of information search: collective wisdom influences my knowledge (SP)

 Fidelia Orji, Julita Vassileva
#39: A Comparative Evaluation of the Effect of Social Comparison, Competition, and Social Learning in Persuasive Technology on Learning (SP)

Fabio Gasparetti, Filippo Sciarrone, Marco Temperini
#86: Using Graph Embedding to Monitor Communities of Learners (SP)

Karima Boussaha, Samia Drissi
#5: New Horizons on Online Tutoring System Inspired by Teaching Strategies and Learning Styles (P)

19:00-
20:00
Keynote Speaker: Prof.  Peter Brusilovsky

 

Title: The return of Intelligent Textbooks

20:00End of Session

 Thursday, June 10

10:00-
11:00
Keynote Speaker: Adina Magda Florea,University POLITEHNICA of Bucharest, Romania

 

TitleInterpretability and Explanations in Intelligent Tutoring Systems

 

 

 

 

11:00-

13:45

SESSION 5: STUDENT PREDICTION 

 

Session Chair: Valia Triperina

Ahmed Alamri, Zhongtian Sun, Alexandra I. Cristea, Craig Stewart, Filipe Dwan Pereira
#69: Next week dropout prediction in MOOCs: weekly assessment of time and learning patterns (FP)

Tahani Aljohani, Alexandra I. Cristea
#52: Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification (FP)

Laila Alrajhi, Ahmed Alamri, Filipe Dwan Pereira, Alexandra I. Cristea
#51: Urgency Analysis of Learners’ Comments: an Automated Intervention Priority Model for MOOC (FP)

Efthyvoulos Drousiotis, Lei Shi, Simon Maskell
#24: Early Predictor for Student Success Based on Behavioural and Demographical Indicators (FP)

Mohammad Alshehri, Ahmed Alamri, Alexandra I. Cristea
#66: Predicting Certification in MOOCs based on Students’ Weekly Activities (FP)

Mona Alotaibi, Mike Joy
#46: Internet of Things (IoT) Based Support System for Diabetic Learners in Saudi Arabian High Schools (P)

13:45-
14:45
Break
 

 

14:45-
16:00

 

SESSION 6 : EXTENDED REALITY 

 

Session Chair: Jingyun Wang

Alessia Genovese, Federica Marino, Francesco Orciuoli, Gennaro Zanfardino
#57: ARDNA: a Mobile App based on Augmented Reality for supporting knowledge exploration in learning scenarios Predicting Certification in MOOCs based on Students’ Weekly Activities (SP)

Kodjine Dare, Hamdi Ben Abdessalem, Claude Frasson
#62: Extraction of 3D Pose in Video for Building Virtual Learning Avatars (SP)

Muhamad Irfan Rosli, Zarina Che Embi, Dr. Junaidi Abdullah
#58: A Non-immersive Virtual Reality Application for Children with Autism Spectrum Disorder (SP)

Sarah Alshamrani
#74: Using Augmented Reality in Computing Higher Education (P)

16:00-
17:05
SESSION 7: CONCEPT MAPS   

 

Session Chair: Jingyun Wang

Junya Morita, Yoshimasa Ohmoto, Yugo Hayashi
#18: Integrating Knowledge in Collaborative Concept Mapping: Cases in an Online Class Setting (SP)

Victor Uglev, Oleg Sychev
#11: Creating and Visualising Cognitive Maps of Knowledge Diagnosis During the Processing of Learning Digital Footprint (P)

Carla Limongelli, Carmine Margiotta, Davide Taibi
#19: Towards Semantic Comparison of Concept Maps for Structuring Learning Activities (P)

Jingyun Wang, Hiroaki Ogata
#35: An evaluation of a meaningful discovery learning support system for supporting E-book user in pair learning. (P)

17:05-
17:30
Break
17.30-
19:40
SESSION 8: FEEDBACK AND PERSONALISATION

 

Session Chair: Christos Papakostas

Seounghun Kim, Woojin Kim, Hyeoncheol Kim
#8: Learning Path Construction Using Reinforcement Learning and Bloom’s Taxonomy. (FP)

Victor J. Marin, Maheen Riaz Contractor, Carlos Rivero
#42: Flexible Program Alignment to Deliver Data-Driven Feedback to Novice Programmers (FP)

Ilya Posov, Sergei Pozdniakov, Anton Chukhnov
#61: Interaction of human cognitive mechanisms and “computational intelligence” in systems that support teaching mathematics. (SP)

Victor J. Marin, Hadi Hosseini, Carlos Rivero
#72: Customizing Feedback using Semantic Clusters. (SP)

Mohammad Niknazar, Aditya Vempaty, Ravi Kokku
#56: Voice Privacy with Smart Digital Assistants in Educational Settings. (P)

Laurentiu Neagu, Eric Rigaud, Vincent Guarnieri, Sebastien Travadel, Mihai Dascalu
#59: Selfit – An Intelligent Tutoring System for Psychomotor Development. (P)

19:40End of Session

     

Friday, June 11

10:00-
11:00
Keynote Speaker: Spyros Vosinakis

 

Title: Extended Reality Technologies in Education: Moving beyond the “Wow” factor

 

 

11:00-
13:05

SESSION 9:  EMOTIONS AND AFFECT  

 

Session Chair: Ahmed Alamri

Soelaine Rodrigues Ascari, Andrey Pimentel, Ernani Gottardo
#25: Tutorial Intervention’s Affective Model Based on Learner’s Error Identification in Intelligent Tutoring Systems (FP)

Doru Anastasiu Popescu, Gabriel Ciprian Stanciu, Daniel Nijloveanu
#15: Evaluation test generator using a list of keywords (FP)

Filipe Dwan Pereira, Hermino Junior, Luiz Rodriguez, Armando Toda, Elaine Harada Teixeira de Oliveira, Alexandra I. Cristea, David Oliveira, Leandro Carvalho, Samuel Fonseca, Ahmed Alamri, Seiji Isotani
#27: A recommender system based on effort: towards minimising negative affects and maximising achievement in CS1 learning (FP)

Mahsa Aghajani, Hamdi Ben Abdessalem, Claude Frasson
#34: Voice Emotion Recognition in Real Time Applications (SP)

Moh’d A. M. Abuazizeh, Kristina Yordanova, Thomas Kirste
#40: Affect-aware Conversational Agent for Intelligent Tutoring of Students in Nursing Subjects (P)

13:05-
14:00
Break
14:00-
16:25
SESSION 10: LEARNER BEHAVIOUR    

 

Session Chair: Tahani Aljohani

Khulood Alharbi, Alexandra I. Cristea, Lei Shi, Peter Tymms, Chris Brown
#41: Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students (FP)

Alejandra Ruiz Segura, Susanne Lajoie
#47: Expert, Novice, and Intermediate Performance: Exploring the Relationship Between Clinical Reasoning Behaviors and Diagnostic Performance (FP)

Sungeun An, William Broniec, Spencer Rugaber, Emily Weigel, Jennifer Hammock, Ashok Goel
#30: Recognizing Novice Learners’ Modeling Behaviors (FP)

Rita Kuo, Ted Krahn, Maiga Chang
#26: Behaviour Analytics – A Moodle Plug-in to Visualize Students’ Learning Patterns (SP)

Yoshimasa Ohmoto, Shigen Shimojo, Junya Morita, Yugo Hayashi
#29: Investigating Clues for Estimating ICAP States based on Learners’ Behavioural Data during Collaborative Learning (SP)

Komi Sodoke, Roger Nkambou, Issam Tanoubi, Aude Dufresne
#87: Toward an ITS to enhance novice clinician situational awareness based on expert perception behaviors in clinical reasoning (P)

16:25-
17:00
Break
17:00-
19:10
SESSION 11: MODELS

 

Session Chair: Katerina Makri

Seounghun Kim, Woojin Kim, Heeseok Jung, Hyeoncheol Kim
#7: DiKT: Dichotomous Knowledge Tracing (FP)

Jialin Yu, Laila Alrajhi, Anoushka Harit, Zhongtian Sun, Alexandra I. Cristea, Lei Shi
#45: Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums (FP)

Roger Nkambou, Janie Brisson, Ange Tato, Serge Robert, Maxime Sainte-Marie
#67: Learning Logical Reasoning Using an Intelligent Tutoring System: Improving the Student Model with a data driven approach (SP)

Oleg Sychev, Anton Anikin, Nikita Penskoy, Mikhail Denisov, Artem Prokudin
#22: CompPrehension – Model-Based Intelligent Tutoring System on Comprehension Level (SP)

Téo Orthlieb, Hamdi Ben Abdessalem, Claude Frasson
#71: Checking Method for Fake News to Avoid the Twitter Effect (P)

Vanesa Getseva, Amruth Kumar
#63: Comparing Bayesian Knowledge Tracing Model Against Naïve Mastery Model (P)

19:10-
19:30
Closing Session

 

Announcements for future events:

University of Bucharest, ITS2022

Dr. C.Trousas NiDS 2021

Other matters

19:30End of ITS2021 Conference

TUTORIAL 1

 

Title:  Learning Analytics Hands-On Tutorial (Half-a-day )

Coordinator:

  • Professor Alexandra I. Cristea, Durham University (Bio on webpage: Professor AI Cristea – Durham University)
  • Experience: currently running a 4th year Learning Analytics Module; have given LA keynotes and tutorials in the past.

Team: a team of PhD students and guest researchers in Learning Analytics, demonstrating

Target Audience:

  • Young Researchers
  • Researchers wanting to move from more traditional ITS approaches towards big data analytics for learning
  • Teachers, practitioners, education decision-makers
  • Min numbers to run: 5 participants;
  • Max numbers able to run: 50 participants;

Abstract:

  • Motivation:
    • Data is becoming ubiquitous, and data analytics has almost swallowed up the term ‘AI’ in the understanding of the press and mass-media. Its applications are everywhere – in industry, governance, and, more recently, in education – the latter called Learning Analytics. ‘Old fashioned’ ‘top-down’ approaches, such as Intelligent Tutoring Systems (ITS) and Artificial Intelligence in Education (AIED), based on solid pedagogical foundations, have almost been replaced in many ways by the new ‘bottom-up’ approach of letting data guide us. Whilst I believe that the truth is somewhere in the middle, in this tutorial I wish to address what this new hype is about, some of its main methods, as well as allow participants some hands-on experimentation.

  • Aims (Expected Outcomes):
    • The aims of this tutorial is to give participants a fundamental understanding of some of the core approaches and problem-solving principles for Learning Analytics (LA) and the role of LA in current and future learning settings and environments.

  • Content:
    • Statistical Learning Analytics and visualisation: data pre-processing; methods for tackling learning analytics based on statistical approaches; the types of LA that can be done with such approaches – e.g. descriptive and beyond. Visualisation of LA data for different stakeholders – e.g. learner, teacher, administrator, etc.

    • Ethics of Learner Data Usage: discussions on ethical considerations of using learner data, starting from societal view, laws involved, (common) practice, future practice. Algorithmic perspectives, such as (expanded) sensitivity analysis.

    • Machine Learning-based Learning Analytics: shallow and deep Machine Learning methods for LA; numerical versus textual data analytical methods for LA; combined methods; sentiment analysis for LA; the types of LA that can be done with such approaches – e.g. descriptive, diagnostic, predictive, prescriptive.

 

Format:

  • Talks interspersed with hands-on sessions (Note: for the hands-on sessions, Google Colab will be used, so participants will be asked to ensure to have a Google account in advance to be able to participate hands-on; otherwise, they can see the demonstrations projected by the teaching team)

Tutorial  1

16:00-
19:00
Title:  Learning Analytics Hands-On Tutorial (LA)

 

Coordinator: Professor Alexandra I. Cristea, Durham University

16:00-
16:10
Introduction of Topic and Team
16:10-
16:25
Introduction of Participants
16:25-
16:30
Break
16:30-
16:50
Theory of LA
16:50-
17:00
Break
17:00-
17:20
Hands-on LA
17:20-
17:50
Theory of LA
17:50-
18:00
Break
18:00-
18:30
Hands-on LA
18:30-
19:00
Panel Discussion
19:00End of Session

TUTORIAL  2

 

Title: Data Science for learning process management (half-a-day)

Coordinator:

Filippo Sciarrone, Roma TRE University – Department of Engineering
Via della Vasca navale 79, 00146 Rome, Itay

Theme and goals:

Nowadays, all learning platforms are producing large amounts of data, i.e., big data. The scientific community that studies learning processes has the opportunity to have several available tools to extract useful information from data to improve the learning process itelf, in its broadest sense. Consequently, all the stakeholders involved have the opportunity to improve their contribution. The Internet provides business intelligence and data science platforms, aimed at processing and studying large amounts of data, regardless of the application domain which generated them, such as Weka, R, Knime, etc. etc. This tutorial aims to show the power of one of these tools, the Knime platform, free and available at www.knime.org, for applications to the learning domain of huge students’ communities such as Massive Online Open Courses. The proposal is aimed at the ITS community as a directly involved community in this field of research and especially in the field of educational data mining and learning and teaching analytics.

 

Fields of research strongly involved: Technology Enhanced Learning, Learning Analytics, Educational Data Mining

The tutorial will cover:

– Educational Data Mining: the most used techniques for studying learning processes

– The KNIME platform: workflows and functionalities at a basic level

– Simple case studies

Target audience:

Participants must have two important requirements: have the KNIME platform installed on their laptop or desktop and have a minimum of background in machine learning techniques, better if applied to learning processes.

Activities planned.  

    • 09:00-11:00
      • Introduction to the The Knime Platform
      • Machine Learning useful algorithms in Knime for education
      • Workflow Building
      • Data management
    • 11:00-13:00
      • Case study 1: MOOCS data
      • Case study 2: Moodle data

Expected outcomes.  

Through this tutorial, participants will acquire some basic skills and knowledge to be able to design a data management workflow applied to the educational field, by using the Knime business intelligence platform.

Video/audio facilities and other equipment needed

Participants need  some data sets for the case studies analysis, posted by myself before starting

Tutorial  2

10:00-
13:30
Title:  Data Science for Learning Process management

 

Coordinator: Filippo Sciarrone, ROMA TRE University, Rome (IT)

10:00-
10:10
Introduction: Summary and main goals
10:10-
10:25
Introduction of Participants
10:25-
10:35
Break
10:35-
11:35
Introduction to the Knime Platform: workflow environment, ML algorithms, workflow building, Data management
11:35-
11:45
Break
11:45-
13:15
Learning Process management: case studies
13:15-
13:30
Panel Discussion
13:30End of Session

WORKSHOP 1

 

Title: Intelligent Tutor Demonstrations

Chairs:  Mihai Dascalu, Amruth Kumar, and Daniela M. Romano

This is an interactive session in which participants are invited to demonstrate their intelligent tutoring system (whether completed or work in progress) for 10 minutes, followed by feedback and questions from the audience for 10 minutes.

This workshop is an invaluable opportunity for researchers to showcase their tutor and obtain formative feedback, whether their tutor is completed or in developmental stage. It is also meant to help researchers present their ideas, clarify their design, and get feedback on the design, implementation, and evaluation of their intelligent tutor.

Participation in this event is free of cost for both registrants and non-registrants of the conference.

For instructions to participate in the workshop, click HERE

Last day to submit a proposal for Tutor Demonstrations Session: Monday, May 24, 2021

Workshop

13:30-
15:30
Title: Intelligent Tutor Demonstrations

 

Coordinators: Mihai Dascalu,  University Politehnica of Bucharest, Romania

Amruth Kumar, Ramapo College of New Jersey, USA

Daniela Romano, University College London, UK

13:30-
14:15
First Part
14:15-
14:45
Break
14:45-
15:30
Second Part

SPECIAL SESSION FOR PHD STUDENTS

 

Title:  Special Tutoring Session for PHD Students (HD)

 

Coordinators:

Content:

A new initiative addressed to PhD students who are first authors of approved papers/posters. It constitutes an extra session where students can discuss their paper with experienced researchers and academics, before the official presentation of their papers during the main sessions of the conference.

This special session will take place during the workshop and tutorial dates and will be free of charge.

Target Audience:

  • PHD Students
  • Young Researchers
  • Teachers, practitioners, education decision-makers
  • Minimum number of participants:  Five (5)
  • Maximum number of participants: Fifty (50)

Special Session

10:00-
13:00
Title:  SPECIAL SESSION FOR PHD STUDENTS

 

Coordinators: Mizue Kayama, Shinshu University , Japan

Mike Joy, University of Warwick , UK

Key Note Speakers

Keynote Speech

Title: The return of Intelligent Textbooks

Abstract: Early research on hypermedia learning and Web-based education featured a strong stream of work on intelligent and adaptive textbooks, which combined the knowledge modeling ideas from the field of intelligent tutoring with rich linking offered by the hypermedia and the Web. However, over the next ten years from 2005 to 2015 this area was relatively quiet as the focus of research in e-learning has shifted to other topics and other creative ideas to leverage the power of Internet. A recent gradual shift of the whole publication industry from printed books to electronic books followed by a rapid growth or the volume of online books re-ignited interests to  “more intelligent” textbooks. The research on the new generation of intelligent textbooks engaged a larger set of technologies and engaged scholars from a broader range of areas including machine learning, natural language understanding, social computing, etc. In my talk I will review the past and present of research on intelligent textbooks from its origins to the diverse modern work providing examples of most interesting technologies and research results.

Keynote Speech

TitleInterpretability and Explanations in Intelligent Tutoring Systems

Abstract:

Since the first developments of ITSs, the capacity to understand and interpret student behavior while learning has been a key issue of the system. Interpreting the student model is important both for the teachers, making them able to evaluate the student progress, accumulated knowledge and week points, and for the students, in particular in the context of building open learner models, which allow the learner to view and understand information about himself/herself, thus better motivating and engaging the student. With the outburst of machine learning (ML) techniques, there is a strong interest in developing learner models based on different ML approaches. However, interpretability and explainability of such models are most of the time a challenge. The talk presents the recent advances in using machine learning methods to develop student models and analyses the extent to which these models can be interpreted and explained to both teachers and students. It compares these methods to the “traditional” knowledge-based approaches and explore the challenges of making ML an effective tool for delivering personalized learning experiences.

Keynote Speech

TitleExtended Reality Technologies in Education: Moving beyond the “Wow” factor

Abstract

: Virtual Reality (VR) has always been considered a medium with great potential for education, from the early days of expensive high-end immersive systems, through the era of massive multiuser virtual worlds, until the recent widespread releases of consumer headsets. Yet, despite the popularity and the strong research and commercial interest in these technologies, today their use as learning environments still not a commonplace. Mixed and Augmented reality are equally promising solutions that go beyond the ‘isolating’ nature of VR by effectively integrating digital content with the real world. As such, they bring new affordances for learning through the enhancement of real-world places and artifacts with learning content and activities. Again, their adoption in education is not as widespread as expected. So, although many researchers agree that extended reality technologies (XR – virtual, mixed or augmented reality) have the potential to deliver rich learning experiences, there seem to be several factors that hold them back. This talk introduces the main technological approaches and trends in XR and describes their affordances and limitations. It presents an overview of their usage in education and identifies good practices and paradigms. Additionally, it outlines our hands-on experience from the development and evaluation of a series of projects in the area of learning using XR technologies, focusing on critical observations, noteworthy results and usability issues. The talk concludes with a discussion on the prospects and pitfalls of XR as an educational tool and directions for future research that might further exploit their potential.

COMMITTEES

Senior Program Committee

  • Amruth Kumar, Ramapo College of New Jersey, USA
  • Bert Bredeweg, University of Amsterdam, The Netherlands
  • Christos Troussas, University of West Attica, Greece
  • Claude Frasson, University of Montreal, Canada
  • Filippo Sciarrone, University Roma Tre, Italy
  • Gordon McCalla, University of Saskatchewan, Canada
  • Julita Vassileva, University of Saskatchewan, Canada
  • Kinshuk Kinshuk, University of North Texas, USA
  • Lewis Johnson, Alelo Inc., USA
  • Maiga Chang, Athabasca University, Canada
  • Michel Desmarais, Ecole Polytechnique de Montreal, Canada
  • Nathalie Guin, Universite de Lyon 1, France
  • Noboru Matsuda, North Carolina State University, USA
  • Riichiro Mizoguchi, Japan Advanced Institute of Science and Technology, Japan
  • Roger Azevedo, University of Central Florida, USA
  • Roger Nkambou, Université du Québec à Montréal, Canada
  • Stefan Trausan-Matu, Politehnica University of Bucharest, Romania
  • Stefano A. Cerri, LIRMM: University of Montpellier and CNRS, France
  • Vivekanandan Kumar, Athabasca University, Canada
  • Yugo Hayashi, Ritsumeikan University, Japan

Program Committee

  • Akrivi Krouska, University of West Attica, Greece
  • Alvaro Ortigosa, Universidad Autónoma de Madrid, Spain
  • Benjamin Goldberg, University of South Florida, USA
  • Blair Lehman, Educational Testing Service, USA
  • Carla Limongelli, Roma Tre University, Italy
  • Chao-Lin Liu, National Chengchi University, Taiwan
  • Charalampos Karagiannidis, University of Thessaly, Greece
  • Chih-Yueh Chou, Yuan Ze University, Taiwan
  • Diego Dermeval, Federal University of Alagoas, Brazil
  • Dunwei Wen, Athabasca University, Canada
  • Elaine Harada Teixeira de Oliveira, Federal University of Amazonas, Brazil
  • Elise Lavoué, University of Lyon, France
  • Ella Haig, University of Portsmouth, UK
  • Elvira Popescu, University of Craiova, Romania
  • Emmanuel Blanchard, IDU Interactive Inc., Canada
  • Evandro Costa, Federal University of Alagoas, Brazil
  • Fuhua (Oscar) Lin, Athabasca University, Canada
  • Galia Angelova, Bulgarian Academy of Science, Bulgaria
  • Giora Alexandron, Weizman Institute, Israel
  • Gwo-Jen Hwang, National Taiwan University of Science and Technology, Taiwan
  • Jason Harley, Mc Gill University, Canada
  • Jesus Boticario, University UNED, Spain
  • Kaoru Sumi, Future University Hakodate, Japan
  • Kuo-Liang Ou, National Hsin-Chu University of Education, Taiwan
  • Lei Shi, Durham University, UK
  • Marco Temperini, Sapienza University of Rome, Italy
  • Maria Bielikova, Kempelen Institute of Intelligent Technologies, Slovakia
  • Mark Core, University of Southern California, USA
  • Mizue Kayama, Shinshu University, Japan
  • Olga C. Santos, National Distance Education University (UNED) , Spain
  • Patricia Jaques, Universidade do Vale do Rio dos Sinos, Brazil
  • Philippe Dessus, Université Grenoble Alpes, France
  • Radu Vasiu, Politechnica University of Timisoara, Romania
  • Reva Freedman, North Illinois University, USA
  • Seiji Isotani, University of Sao Paulo, Brazil
  • Sergey Sosnovsky, Utrecht University, Netherlands
  • Sunčica Hadžidedić, Durham University, UK
  • Thepchai Supnithi, National Electronics, and Computer Technology Center, Thailand
  • Tingwei Chen, Liaoning University, China
  • Valéry Psyché, Teluq University, Canada
  • Yang Long, Durham University, UK
  • Yusuke Hayashi, Hiroshima University, Japan

Chair

Members

VENUE