This talk presents how learning analytics can be applied to improve serious games and serious games research. It describe what is needed for implementing a sucessful game learning analytics approach. It presents 3 examplos of how GLA are being actually used with games in schools, one in the medical domain, one for improving independent life of people with cognitive impairement and one dealing with cyberbullying.
keynote talk given at the Internationa Joint Conference on Serious Games
Full Lyifecycle Architecture for Serious Games - JCSG 2017Cristina Alonso
Presentation of the full paper "Full Lifecycle Architecture for Serious Games: Integrating Game Learning Analytics and a Game Authoring Tool" at the Joint Conference on Serious Games (JCSG) 2017 in Valencia (Spain),
Using Game Learning Analytics to Improve the Design, Evaluation and Deploymen...Baltasar Fernández-Manjón
Game Learning Analytics (GLA) is the process of applying Learning Analytics techniques to Serious Games in order to get insight about how the game is being used and improve the educational experience. In this talk we will present the general ideas about the GLA and provide details about the GLA supporting framework and some of the experiences done on H2020 EU projects RAGE and BEACONING and in cooperation with the Telefonica-Complutense Chair on Digital Education and Serious Games.
This talk presents how learning analytics can be applied to improve serious games and serious games research. It describe what is needed for implementing a sucessful game learning analytics approach. It presents 3 examplos of how GLA are being actually used with games in schools, one in the medical domain, one for improving independent life of people with cognitive impairement and one dealing with cyberbullying.
keynote talk given at the Internationa Joint Conference on Serious Games
Full Lyifecycle Architecture for Serious Games - JCSG 2017Cristina Alonso
Presentation of the full paper "Full Lifecycle Architecture for Serious Games: Integrating Game Learning Analytics and a Game Authoring Tool" at the Joint Conference on Serious Games (JCSG) 2017 in Valencia (Spain),
Using Game Learning Analytics to Improve the Design, Evaluation and Deploymen...Baltasar Fernández-Manjón
Game Learning Analytics (GLA) is the process of applying Learning Analytics techniques to Serious Games in order to get insight about how the game is being used and improve the educational experience. In this talk we will present the general ideas about the GLA and provide details about the GLA supporting framework and some of the experiences done on H2020 EU projects RAGE and BEACONING and in cooperation with the Telefonica-Complutense Chair on Digital Education and Serious Games.
How can game learning analytics contribute to improve the serious games industry with the new apportunities offered
Results from H2020 RAGE and BEACONING are described.
The xAPI application profile for serious games is introduced
Multi-level game learning analytics for serious games - VSGames 2018Iván Pérez Colado
Serious games are usually used or deployed in an educational setting as an isolated or individual activity, disconnected from other curricular activities. However, to really increase the adoption of serious games in different educational scenarios, the combination and integration of games into the educational flow should be simplified. We envision Serious Games as new type of educational activity that can be combined as parts of other games (e.g. minigames integrated in larger games), integrated into other online activities, or even mixed with both game and non-game activities. In addition, if we want to make the most from serious games, a learning analytics system must be in place to harvest and analyze interactions, providing metrics and insights to instructors regarding the gameplay sessions. Moreover, if a course-level learning analytics strategy is designed, it must be aligned with the game learning analytics. This approach requires communication between games and educational activities used during the educational experience. From a game learning analytics standpoint, gaining insights from these integrated experiences introduces new requirements within potentially complex multi-level or hierarchical activities. Moreover, the analysis required to generate these metrics should be both efficient and provide insight in an understandable way and for different stakeholders. This paper describes an approach to multilevel game learning analytics from the perspectives of data model, implementation architecture, and result visualization in teacher-oriented dashboards.
GLAID: Designing a Game Learning Analytics Model to Analyze the Learning Process in Users with Cognitive Disabilities
Downtown: Serious Game designed and develop to teach young people with Down Syndrome to move around the city using the subway
We are using learnig analytics for evaluating the game and for knowing how the user is doing in the game
This work is part of the H2020 BEACONING project
Downtown is a game
Gaming learning analytics and how this learning analytics applied to games can help to improve the use in different learning scenarios
We also present how H2020 european projects RAGE and BEACONING are creating infrastructure and technology to improving and simplify how gaming analytics is applied to serious games
Using Simva to evaluate serious games and collect game learning analytics dat...Cristina Alonso
Presentation of full paper "Using Simva to evaluate serious games and collect game learning analytics data" at LASI-Spain 2019, held in Vigo 27-28 June 2019.
Learning Analytics and how to use in educational or serious games for improving the use of the games
game traces
evidence based education
Talk at the Ecole Normal Superior, Lyon, France
VII Jornadas eMadrid "Education in exponential times". Mesa redonda eMadrid L...eMadrid network
VII Jornadas eMadrid "Education in exponential times". Mesa redonda eMadrid Learning Analytics. "Using Learning Analytics to support a more scientific approach to Serious Games: Three Examples". Baltasar Fernández Majón. 04/07/2017.
Using Learning Analytics to support a more scientific approach to Serious Gam...Baltasar Fernández-Manjón
Using Learning Analytics to support a more scientific approach to Serious Games: Three Examples
Do games actually works?
Usually, no full formal evaluation has been carried out
Limited number of users
Formal evaluation could be as expensive as creating the game (or even more expensive)
Difficult to deploy games in the classroom
Teachers have very little info about what is happening when a game is being used
Game Learning analytics can help us to: create better games and to (formally) validate games
Moving from pre-post to Learning Analytics based evaluation
To use games as assessments
Gaming Learning Analytics: using data for improving serious games applicability”
This talk will present how to use a data-driven approach to improve how serios games are applied in different domains and how H2020 RAGE project is trying to simplify this analytics processes by creating an open software infrastructure.
Downtown, A Subway Adventure: Using Learning Analytics to Improve the Develop...Ana Rus Cano Moreno
In this paper we analyze the process of designing and developing a Serious Game intended to train people with intellectual disabilities in moving around a city using the public transportation system. The first step in our investigation is to understand the cognitive, psychological and motor abilities of our users and their specific needs. Secondly, we translated the characteristics of the players into user requirements, with adapted mechanics to improve the understanding and to increase the probability for the user to be able to carry out the tasks to perform in the video game. Finally, due to the specific characteristics of our final users a Learning Analytics module has been included in the game to collect relevant information about how users are actually playing and to infer how the learning process of every user is occurring. We also discuss the next steps in our research and the future work related with it: design a range of experimental tests to verify the adequacy of the video game as a learning tool for this type of users
In this talk we will introduce serious games as games which purpose is not only amusement and can be effectively used for educational or training purposes. This kind of games are also frequently named as educational games or even as game-like simulations. We will describe the general characteristics of serious games and how they are used in several domains (e.g. military, medicine), describing their main advantages (e.g. engagement, student motivation) and some of the shortcomings that prevent a wider generalization in educational settings (e.g. cost, deployment). We will also describe new emerging trends in the field of serious games such as gaming for solving scientific problems or how the application of learning analytics techniques can improve and simplify serious games application in different domains.
11_04_2019 EDUCON eMadrid special session on "Game learning analytics for edu...eMadrid network
Authors: Antonio Calvo Morata, Cristina Alonso Fernández, Manuel Freire Morán, Iván Martínez Ortiz y Baltasar Fernández Manjón / Universidad Complutense de Madrid (UCM)
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How can game learning analytics contribute to improve the serious games industry with the new apportunities offered
Results from H2020 RAGE and BEACONING are described.
The xAPI application profile for serious games is introduced
Multi-level game learning analytics for serious games - VSGames 2018Iván Pérez Colado
Serious games are usually used or deployed in an educational setting as an isolated or individual activity, disconnected from other curricular activities. However, to really increase the adoption of serious games in different educational scenarios, the combination and integration of games into the educational flow should be simplified. We envision Serious Games as new type of educational activity that can be combined as parts of other games (e.g. minigames integrated in larger games), integrated into other online activities, or even mixed with both game and non-game activities. In addition, if we want to make the most from serious games, a learning analytics system must be in place to harvest and analyze interactions, providing metrics and insights to instructors regarding the gameplay sessions. Moreover, if a course-level learning analytics strategy is designed, it must be aligned with the game learning analytics. This approach requires communication between games and educational activities used during the educational experience. From a game learning analytics standpoint, gaining insights from these integrated experiences introduces new requirements within potentially complex multi-level or hierarchical activities. Moreover, the analysis required to generate these metrics should be both efficient and provide insight in an understandable way and for different stakeholders. This paper describes an approach to multilevel game learning analytics from the perspectives of data model, implementation architecture, and result visualization in teacher-oriented dashboards.
GLAID: Designing a Game Learning Analytics Model to Analyze the Learning Process in Users with Cognitive Disabilities
Downtown: Serious Game designed and develop to teach young people with Down Syndrome to move around the city using the subway
We are using learnig analytics for evaluating the game and for knowing how the user is doing in the game
This work is part of the H2020 BEACONING project
Downtown is a game
Gaming learning analytics and how this learning analytics applied to games can help to improve the use in different learning scenarios
We also present how H2020 european projects RAGE and BEACONING are creating infrastructure and technology to improving and simplify how gaming analytics is applied to serious games
Using Simva to evaluate serious games and collect game learning analytics dat...Cristina Alonso
Presentation of full paper "Using Simva to evaluate serious games and collect game learning analytics data" at LASI-Spain 2019, held in Vigo 27-28 June 2019.
Learning Analytics and how to use in educational or serious games for improving the use of the games
game traces
evidence based education
Talk at the Ecole Normal Superior, Lyon, France
VII Jornadas eMadrid "Education in exponential times". Mesa redonda eMadrid L...eMadrid network
VII Jornadas eMadrid "Education in exponential times". Mesa redonda eMadrid Learning Analytics. "Using Learning Analytics to support a more scientific approach to Serious Games: Three Examples". Baltasar Fernández Majón. 04/07/2017.
Using Learning Analytics to support a more scientific approach to Serious Gam...Baltasar Fernández-Manjón
Using Learning Analytics to support a more scientific approach to Serious Games: Three Examples
Do games actually works?
Usually, no full formal evaluation has been carried out
Limited number of users
Formal evaluation could be as expensive as creating the game (or even more expensive)
Difficult to deploy games in the classroom
Teachers have very little info about what is happening when a game is being used
Game Learning analytics can help us to: create better games and to (formally) validate games
Moving from pre-post to Learning Analytics based evaluation
To use games as assessments
Gaming Learning Analytics: using data for improving serious games applicability”
This talk will present how to use a data-driven approach to improve how serios games are applied in different domains and how H2020 RAGE project is trying to simplify this analytics processes by creating an open software infrastructure.
Downtown, A Subway Adventure: Using Learning Analytics to Improve the Develop...Ana Rus Cano Moreno
In this paper we analyze the process of designing and developing a Serious Game intended to train people with intellectual disabilities in moving around a city using the public transportation system. The first step in our investigation is to understand the cognitive, psychological and motor abilities of our users and their specific needs. Secondly, we translated the characteristics of the players into user requirements, with adapted mechanics to improve the understanding and to increase the probability for the user to be able to carry out the tasks to perform in the video game. Finally, due to the specific characteristics of our final users a Learning Analytics module has been included in the game to collect relevant information about how users are actually playing and to infer how the learning process of every user is occurring. We also discuss the next steps in our research and the future work related with it: design a range of experimental tests to verify the adequacy of the video game as a learning tool for this type of users
In this talk we will introduce serious games as games which purpose is not only amusement and can be effectively used for educational or training purposes. This kind of games are also frequently named as educational games or even as game-like simulations. We will describe the general characteristics of serious games and how they are used in several domains (e.g. military, medicine), describing their main advantages (e.g. engagement, student motivation) and some of the shortcomings that prevent a wider generalization in educational settings (e.g. cost, deployment). We will also describe new emerging trends in the field of serious games such as gaming for solving scientific problems or how the application of learning analytics techniques can improve and simplify serious games application in different domains.
11_04_2019 EDUCON eMadrid special session on "Game learning analytics for edu...eMadrid network
Authors: Antonio Calvo Morata, Cristina Alonso Fernández, Manuel Freire Morán, Iván Martínez Ortiz y Baltasar Fernández Manjón / Universidad Complutense de Madrid (UCM)
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
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Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
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Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
3. Introduction
Serious Games
● applied successfully in multiple fields
● however, poor uptake in formal education
Why?
● high development cost of new games
● difficulty to assess acquired learning
● few serious games formally evaluated and with
limited number of users
Learning Analytics data can provide insight into students’ learning and
improve development and deployment of Serious Games.
4. Uses of Learning Analytics data
● Open data can be shared for research
purposes
● Real-time feedback for teachers to control
their classroom when applying games
● With enough data gathered, data mining to
improve design, evaluation and deployment
allow stakeholders to benefit from enhanced
feedback or stealth assessment
5. In-game user interaction data
● Anonymization: to ensure no personal details are attached to student data
● Collection: non-intrusive and transparent
● Storage: capability for large amounts of data and handle format
6. In-game user interaction data
● Anonymization: to ensure no personal details are attached to student data
Using randomly generated codes
● Collection: non-intrusive and transparent
Using standard tracking model (xAPI-SG) to simplify and standardize
● Storage: capability for large amounts of data and handle format
GLA System to handle data in standard format xAPI-SG
7. Experience API - Serious Games Profile
https://adlnet.gov/news/a-serious-games-profile-for-xapi
https://xapi.e-ucm.es/vocab/seriousgames
Ángel Serrano-Laguna, Iván Martínez-Ortiz, Jason Haag, Damon Regan, Andy Johnson, Baltasar Fernández-Manjón (2017):
Applying standards to systematize learning analytics in serious games. Computer Standards & Interfaces 50 (2017) 116–123,
http://dx.doi.org/10.1016/j.csi.2016.09.014
8. Learning Analytics Framework (LAF)
Ref: Chatti, M. A., Lukarov, V., Thüs, H., Muslim, A., Yousef, A. M. F., Wahid, U., … Schroeder, U. (2015). Learning Analytics: Challenges and
Future Research Directions. E-Learning and Education (Eleed), (10). Retrieved from http://eleed.campussource.de/archive/10/4035
10. Real-time applications: teachers
Games in a classroom environment
Visual analytics provide information of students’
interactions:
a) correct and incorrect alternatives selected
b) total session players
c) maximum progress of players per
completable
d) games started and completed
11. Real-time applications: teachers
Dashboards provide general
information
However, specific situations
may require immediate actions
for teachers (e.g. player inactive
for too long)
Alerts and warnings can be
triggered in those situations
12. Real-time applications: students
Students can receive information to easily
assess strengths and weakness
Common solutions: compare results of
students with their peers
Should promote knowledge mastery
instead of competition
Adaptive learning experiences in
response to players’ in-game performance
13. Offline data analysis
Data mining processes can provide richer information for all stakeholders.
● evidence-based
decisions: quantify to
what extent games
benefit learning
Game developer
or designer
Student
Educational institution
and administrator
● feedback to improve
game and learning
design
● categorize players creating
profiles for targeted feedback
● improve assessment without
pre-post experiments
● extract patterns of use to
improve the game for
future deploymentsTeacher
14. Offline data analysis
Evaluation of students with pre-post
Our alternative proposal, applying machine
learning on learning analytics data:
● Create prediction models at validation
stage
● Predict students post knowledge based on
interaction data
● Therefore, avoid carrying out post-test
Knowledge
before playing
Players’
interactions
Knowledge
after playing
15. Conclusions
Great variety of applications of Learning Analytics data to Serious Games:
● Improve all steps of full games lifecycle
● Benefits for all stakeholders involved
Both in real-time scenarios & after enough data has been collected (mining)
Increase and improve adoption of games in schools with a general game LA system
that standardizes data tracking, collection, analysis and visualizations.
Data-driven solutions that use game LA are key to guide the future of SGs.
16. Improving serious games analyzing
learning analytics data:
lessons learned
Cristina Alonso-Fernández, Iván Pérez-Colado, Manuel Freire Morán,
Iván Martínez-Ortiz and Baltasar Fernández-Manjón
Games and Alliance Conference (GALA Conf)
December 7th 2018, Palermo, Italy
calonsofernandez@ucm.es