This paper presents a model of Questions & Answers (Q&A) learning where students are the ones that ask and also answer questions, as a method to increase and reinforce knowledge.
Classsourcing: Crowd-Based Validation of Question-Answer Learning Objects @ I...Jakub Šimko
A simple approach for assessing answer validity information from a student crowd in an online learning scenario context. Raises the questions about using of the student crowds for enhancing learning content and online student collaboration.
Course-Adaptive Content Recommender for Course AuthoringPeter Brusilovsky
Developing online courses is a complex and time-consuming
process that involves organizing a course into a sequence of topics and
allocating the appropriate learning content within each topic. This task
is especially difficult in complex domains like programming, due to the
incremental nature of programming knowledge, where new topics extensively
build upon domain concepts that were introduced in earlier lessons.
In this paper, we propose a course-adaptive content-based recommender
system that assists course authors and instructors in selecting the most
relevant learning material for each course topic. The recommender system
adapts to the deep prerequisite structure of the course as envisioned
by a specific instructor, while unobtrusively deducing that structure from
problem-solving examples that the instructor uses to present course concepts.
We assessed the quality of recommendations and examined several
aspects of the recommendation process by using three datasets collected
from two different courses.While the presented recommender system was
built for the domain of introductory programming, our course-adaptive
recommendation approach could be used in a variety of other domains.
The Virtuous Loop of Learning Analytics & Academic Technology Innovation John Whitmer, Ed.D.
Faculty and academic departments creating innovative educational practices are often starved for useful data and analysis to determine whether their innovations made a difference. Research has found that this data is a systematically significant predictor of success much more powerful than traditional demographic or academic preparedness variables. This leads to a “virtuous loop” in which digital technology adoption enables assessment which then improves educational practices using those technologies.
This presentation was delivered at the Online Learning Consortium Collaborate Event, November 19, 2015.
Classsourcing: Crowd-Based Validation of Question-Answer Learning Objects @ I...Jakub Šimko
A simple approach for assessing answer validity information from a student crowd in an online learning scenario context. Raises the questions about using of the student crowds for enhancing learning content and online student collaboration.
Course-Adaptive Content Recommender for Course AuthoringPeter Brusilovsky
Developing online courses is a complex and time-consuming
process that involves organizing a course into a sequence of topics and
allocating the appropriate learning content within each topic. This task
is especially difficult in complex domains like programming, due to the
incremental nature of programming knowledge, where new topics extensively
build upon domain concepts that were introduced in earlier lessons.
In this paper, we propose a course-adaptive content-based recommender
system that assists course authors and instructors in selecting the most
relevant learning material for each course topic. The recommender system
adapts to the deep prerequisite structure of the course as envisioned
by a specific instructor, while unobtrusively deducing that structure from
problem-solving examples that the instructor uses to present course concepts.
We assessed the quality of recommendations and examined several
aspects of the recommendation process by using three datasets collected
from two different courses.While the presented recommender system was
built for the domain of introductory programming, our course-adaptive
recommendation approach could be used in a variety of other domains.
The Virtuous Loop of Learning Analytics & Academic Technology Innovation John Whitmer, Ed.D.
Faculty and academic departments creating innovative educational practices are often starved for useful data and analysis to determine whether their innovations made a difference. Research has found that this data is a systematically significant predictor of success much more powerful than traditional demographic or academic preparedness variables. This leads to a “virtuous loop” in which digital technology adoption enables assessment which then improves educational practices using those technologies.
This presentation was delivered at the Online Learning Consortium Collaborate Event, November 19, 2015.
An accurate ability evaluation method for every student with small problem it...Hideo Hirose
To enhance the chance of use of the item response theory (IRT) in universities, we developed a test evaluation system via the Web for university teachers, and we have been evaluating students' abilities by using the IRT system in midterm and final examinations for two years.
We show a surprising aspect regarding the adoption of the IRT system in university tests. That is, the IRT can not only give us the problem difficulty information but also can provide the accurate student ability evaluation, even if the number of problems is small. Therefore, we can include high and low level test items together so that we can assess a variety of students' abilities accurately and fairly; we do not worry about providing easier problems that will make the lecture level decline; in other words, we do not care about finding the most appropriate problem levels to each student. We can provide all level problems uniformly distributed to all students, and we can still assess the students' abilities accurately. Consequently, students do not raise claims about their scores; they seem to be satisfied with it.
We show these results, in this paper, by a theoretical background, a simulation study, and our empirical results.
Improving Student Achievement with New Approaches to DataJohn Whitmer, Ed.D.
Presentation delivered at WASC ARC conference on April 11, 2013 on the CSU Data Dashboard and Chico State Learning Analytics case study.
Chico State Case Study: Academic technologies collect highly detailed student usage data. How can this data be used to understand and predict student performance, especially of at-risk students? This presentation will discuss research on a high-enrollment undergraduate course exploring the relationship between LMS activity, student background characteristics, current enrollment information, and student achievement.
CSU Data Dashboard: By monitoring on-track indicators institutional leaders can better understand not only which milestones students are failing to reach, but why they are not reaching them. It can also help campuses to design interventions or policy changes to increase student success and to gauge the impact of interventions.
The study examines the efficacy of the free software Socrative in:
- Enhancing attendance taking routines
- Improving engagement and participation
- Improving learning outcomes
- Enhancing process of course preparation
- Underscore the importance of the 7 Principles of Undergraduate Teaching and Learning
When Student Confidence Clicks - Using Student Response SystemsFabio R. Arico'
In this presentation I illustrate the methodology used to measure the relationship between student attainment, engagement, and self-efficacy beliefs through Student Response Systems.
https://sites.google.com/site/fabioarico
Using Learning Analytics to Assess Innovation & Improve Student Achievement John Whitmer, Ed.D.
Presentation about Learning Analytics for JISC network event; discussion of research findings and implications for individual and institutions considering a Learning Analytics project. Also discuss implications for my work with Blackboard on "Platform Analytics."
The Achievement Gap in Online Courses through a Learning Analytics LensJohn Whitmer, Ed.D.
Presentation at San Diego State University on April 12, 2013.
Educational researchers have found that students from under-represented minority families and other disadvantaged demographic backgrounds have lower achievement in online (or hybrid) courses compared to face-to-face course sections (Slate, Manuel, & Brinson Jr, 2002; Xu & Jaggars, 2013). However, these studies assume that "online course" is a homogeneous entity, and that student participation is uniform. The content and activity of the course is an opaque "black box", which leads to conclusions that are speculative at best and quite possibly further marginalize the very populations they intend to advocate for.
The emerging field of Learning Analytics promises to break open this black box understand how students use online course materials and the relationship between this use and student achievement. In this presentation, we will explore the countours of Learning Analytics, look at current applications of analytics, and discuss research applying a Learning Analytics research method to students from at-risk backgrounds. The findings of this research challenge stereotypes of these students as technologically unsophisticated and identify concrete learning activities that can support their success.
Toward an automated student feedback system for text based assignments - Pete...Blackboard APAC
As the use of blended learning environments and digital technologies become integrated into the higher education sector, rich technologies such as analytics have the ability to assist teaching staff identify students at risk, learning material that is not proving effective and learning site designs that aid and facilitate improved learning. More recently consideration has been given to automated essay scoring. Such systems can be used in a formative way, such as providing feedback on initial assignment drafts or summatively through the analysis of final assignment submissions. Further, providing students with quick feedback on written assignments opens the opportunity through formative feedback to improved learning outcomes.
This presentation details a current project developing a system to analyse text-based assignments. The project is being developed for broad application, but the findings focus on an undergraduate pilot subject: ‘Ideas that Shook the World’ (a compulsory first year Bachelor of Arts subject taught on 5 campuses to more than 1000 students by 15 staff). Preliminary results of a fist scan of assignments are presented and the issues raised in developing the system presented together with an outline of additional work planned for the project. It is believed the work will have wide application where text-based assignments are utilised for assessment.
An app idea to facilitate feedback and improve student learningEldon Prince
This is an app idea I came up with to improve student learning.
What is the motivation for this app?
Students, who are the customers of education, have little input. Teachers, who heavily influence student learning, lack the data to improve teaching. Administrators, who can promote change, have little information.
The auris app is designed to facilitate feedback and serve as a powerful tool to empower students, enable teachers, and inform administrators.
What do you think?
NVivo in educational research two examples from new mexicoQSR International
The use of NVivo in the evaluation of higher education initiatives. Understand the various challenges faced and successes realized in the analyses of these various data sets. First is a two-year study of an innovative teacher education program where NVivo was used in a comparative analysis. Second was the use of NVivo in the analysis of qualitative responses from surveys.
An accurate ability evaluation method for every student with small problem it...Hideo Hirose
To enhance the chance of use of the item response theory (IRT) in universities, we developed a test evaluation system via the Web for university teachers, and we have been evaluating students' abilities by using the IRT system in midterm and final examinations for two years.
We show a surprising aspect regarding the adoption of the IRT system in university tests. That is, the IRT can not only give us the problem difficulty information but also can provide the accurate student ability evaluation, even if the number of problems is small. Therefore, we can include high and low level test items together so that we can assess a variety of students' abilities accurately and fairly; we do not worry about providing easier problems that will make the lecture level decline; in other words, we do not care about finding the most appropriate problem levels to each student. We can provide all level problems uniformly distributed to all students, and we can still assess the students' abilities accurately. Consequently, students do not raise claims about their scores; they seem to be satisfied with it.
We show these results, in this paper, by a theoretical background, a simulation study, and our empirical results.
Improving Student Achievement with New Approaches to DataJohn Whitmer, Ed.D.
Presentation delivered at WASC ARC conference on April 11, 2013 on the CSU Data Dashboard and Chico State Learning Analytics case study.
Chico State Case Study: Academic technologies collect highly detailed student usage data. How can this data be used to understand and predict student performance, especially of at-risk students? This presentation will discuss research on a high-enrollment undergraduate course exploring the relationship between LMS activity, student background characteristics, current enrollment information, and student achievement.
CSU Data Dashboard: By monitoring on-track indicators institutional leaders can better understand not only which milestones students are failing to reach, but why they are not reaching them. It can also help campuses to design interventions or policy changes to increase student success and to gauge the impact of interventions.
The study examines the efficacy of the free software Socrative in:
- Enhancing attendance taking routines
- Improving engagement and participation
- Improving learning outcomes
- Enhancing process of course preparation
- Underscore the importance of the 7 Principles of Undergraduate Teaching and Learning
When Student Confidence Clicks - Using Student Response SystemsFabio R. Arico'
In this presentation I illustrate the methodology used to measure the relationship between student attainment, engagement, and self-efficacy beliefs through Student Response Systems.
https://sites.google.com/site/fabioarico
Using Learning Analytics to Assess Innovation & Improve Student Achievement John Whitmer, Ed.D.
Presentation about Learning Analytics for JISC network event; discussion of research findings and implications for individual and institutions considering a Learning Analytics project. Also discuss implications for my work with Blackboard on "Platform Analytics."
The Achievement Gap in Online Courses through a Learning Analytics LensJohn Whitmer, Ed.D.
Presentation at San Diego State University on April 12, 2013.
Educational researchers have found that students from under-represented minority families and other disadvantaged demographic backgrounds have lower achievement in online (or hybrid) courses compared to face-to-face course sections (Slate, Manuel, & Brinson Jr, 2002; Xu & Jaggars, 2013). However, these studies assume that "online course" is a homogeneous entity, and that student participation is uniform. The content and activity of the course is an opaque "black box", which leads to conclusions that are speculative at best and quite possibly further marginalize the very populations they intend to advocate for.
The emerging field of Learning Analytics promises to break open this black box understand how students use online course materials and the relationship between this use and student achievement. In this presentation, we will explore the countours of Learning Analytics, look at current applications of analytics, and discuss research applying a Learning Analytics research method to students from at-risk backgrounds. The findings of this research challenge stereotypes of these students as technologically unsophisticated and identify concrete learning activities that can support their success.
Toward an automated student feedback system for text based assignments - Pete...Blackboard APAC
As the use of blended learning environments and digital technologies become integrated into the higher education sector, rich technologies such as analytics have the ability to assist teaching staff identify students at risk, learning material that is not proving effective and learning site designs that aid and facilitate improved learning. More recently consideration has been given to automated essay scoring. Such systems can be used in a formative way, such as providing feedback on initial assignment drafts or summatively through the analysis of final assignment submissions. Further, providing students with quick feedback on written assignments opens the opportunity through formative feedback to improved learning outcomes.
This presentation details a current project developing a system to analyse text-based assignments. The project is being developed for broad application, but the findings focus on an undergraduate pilot subject: ‘Ideas that Shook the World’ (a compulsory first year Bachelor of Arts subject taught on 5 campuses to more than 1000 students by 15 staff). Preliminary results of a fist scan of assignments are presented and the issues raised in developing the system presented together with an outline of additional work planned for the project. It is believed the work will have wide application where text-based assignments are utilised for assessment.
An app idea to facilitate feedback and improve student learningEldon Prince
This is an app idea I came up with to improve student learning.
What is the motivation for this app?
Students, who are the customers of education, have little input. Teachers, who heavily influence student learning, lack the data to improve teaching. Administrators, who can promote change, have little information.
The auris app is designed to facilitate feedback and serve as a powerful tool to empower students, enable teachers, and inform administrators.
What do you think?
NVivo in educational research two examples from new mexicoQSR International
The use of NVivo in the evaluation of higher education initiatives. Understand the various challenges faced and successes realized in the analyses of these various data sets. First is a two-year study of an innovative teacher education program where NVivo was used in a comparative analysis. Second was the use of NVivo in the analysis of qualitative responses from surveys.
Geographical indications international & national perspective with specia...Vidya Menon
What is G.I?- a conceptual analysis and its evolution, laws prevailing-national and international, problems and challenges in India along with case studies and findings from the empirical study conducted by the researcher within the State of Kerala.
Apresentação de motores e servomecanismos slideshareWatson Oliveira
Apresentação de motores monofásicos e trifásicos, partida compensada, estrela/triângulo e com softstart, princípios de mecânica para esteiras transportadoras e aterramento elétrico.
Computers are a familiar sight in classrooms in the 21st century, and technology has been used to streamline many educational tasks. CAL started in the 1950s and 1960s mainly in USA. Term often used interchangeably with Computer-Based Instruction (CBI), Web Based Instruction (WBI), Computer-Assisted Learning (CAL), Computer-Enriched Instruction (CEI), and Web Based Training (WBT). Logo project was the first CAL system that was based on a specific learning approach.
1
Last Name
Student Name
Professor Dybala
Engl 1302: CRN #####
13 September 2021
Formal Outline for Essay One: Classical Scheme of Argumentation
Follow this outline sentence by sentence when you write Essay One. Be sure to lead up to your argumentative thesis in the introduction and begin each body paragraph (Section III-VI) with a topic sentence that refers back to a subtopic stated or suggested in the thesis.
Essay One must include all parts of this outline. Note that each Roman numeral (I.-VIII.) represents one paragraph, and each capital letter (A.-G.) represents one sentence in each paragraph. So the structure includes a minimum of 46 sentences: I. 3 sentences, II. 5 sentences, III. 7 sentences, IV. 7 sentences, V. 7 sentences, VI. 7 sentences, VII. 7 sentences, VIII. 3 sentences.
The outline form is required for the first draft; in the final essay, the Roman numerals and capital letters will be removed and each sentence will follow paragraph form, with each paragraph indented one tab or five spaces. The outline is single-spaced and the final essay is double-spaced.
I. Introduction (3-4 sentences)
A. Introduce topic: State the author and title of the short story (in quotation marks)
and topic to capture the readers’ attention.
Kate Chopin’s short story “Desiree’s Baby” set in antebellum times in Louisiana,
exhibits race and racism throughout the entire text.
B. Add more information about the topic to suggest the significance of the work.
The plot centers revolves around race and racism where Desiree’s husband Armand displays cruelty to her and other slaves basing on entrenched ideas of race and ironically Armand himself turned out to have a black descent.
C. State thesis: Narrow topic more specifically and state your claim and suggest four
subtopics (Organizing principle of your essay—most important sentence)
The text exposes racial segregation as experienced by slaves and the protagonist Desiree and his son through various scenes as depicted by the author. It is evident on how the slaves were mistreated, how Armand reacted after the birth of his son, How Armand ended the relationship with his wife due to her heritage and also how Madame reacted when he first saw the baby.
II. Expository paragraph: This paragraph demonstrates your expertise on
this author and short story and identifies terms or explains pertinent background information. (Ethicalappeal) (5-7 Sentences) Refer to the links to websites on the authors posted in Module Two on the Readings and Resources page. Use MLA style to cite any information from a source that you include.
A. State the topic: What kind of background information will you describe
It is true to ascertain that the background of Kate Chopin informed her writing of the text and she intended to showcase the slaves were treated in the plantation including the percept ...
The ‘assessment for learning’ pedagogical approach in an Academic Integrity o...Neda Zdravkovic
6APCEI: The 6th Asia Pacific Conference on Educational Integrity
TITLE: The ‘assessment for learning’ pedagogical approach in The University of Auckland Academic Integrity online course
Author: Neda Zdravkovic, BA, DipLIS5, MLIS, RLIANZA
Learning Support Services Librarian, The University of Auckland Libraries & Learning Services, Auckland, New Zealand, email: n.zdravkovic@auckland.ac.nz
Conference theme: Academic Integrity and Assessment Design – Policy, practice & pedagogy
Learner Analytics and the “Big Data” Promise for Course & Program AssessmentJohn Whitmer, Ed.D.
Presentation delivered at the San Diego State University "One Day in May" conference on May 22, 201 by John Whitmer, Hillary Kaplowitz, and Thomas J. Norman
Universities archive massive amounts of data about students and their activities. Students also generate significant amounts of “digital exhaust” as they use academic technologies. How can faculty and administrators use automated analysis of this data to save time and conduct targeted interventions to improve student learning?
The emerging discipline of Learner Analytics conducts analysis of this data to learn about student behaviors, predict students at-risk of failure, and identify potential interventions to help those students. In this presentation, we will discuss the contours of this discipline and review the state of research conducted to date. We will then look at several examples of Learner Analytics services and hear from California State University educators who are using these tools to help their students. Finally, we will suggest some immediate ways that Analytics can be conducted at San Diego State.
Presenters:
John Whitmer, California State University, Chico
Hillary Kaplowitz, California State University, Northridge
Thomas J. Norman, CSU Dominguez Hills
Complete the following discussion questionFor this Discussion, yo.docxsheenaat5wa
Complete the following discussion question:
For this Discussion, you will narrow the scope of each
education-related issue
you identified in order to formulate problems that merit further investigation. What are some of the problems associated with each of the issues and whose resolution might be informed by applying knowledge from existing research or conducting a new research study? Why is it important to investigate one or more of these problems? Identifying issues and problems early in your advanced graduate degree program allows you to build on your knowledge base related to them. Further, you will be prepared to analyze and evaluate scholarly inquiry with a critical eye.
When evaluating an issue and reflecting on ways to positively address the issue, the task, at first, might seem overwhelming. For this reason it is important to critically examine the issue to determine the most important related problems. As you consider problems associated with an issue, you should be able to begin identifying potential research
topics
. Before you can begin
planning a research study
for a topic, the topic must be quite narrow. When attempting to narrow a topic to a specific problem to study, you need to consider the following:
What has already been studied in the literature?
How much time will it take me to complete a study related to this problem?
What stakeholder buy-in will I need to obtain to perform this study?
What are the benefits of doing this study?
What are the ethical considerations related to this study?
Will I be able to recruit participants for this study?
These questions are not inclusive of all that need to be considered when contemplating a research study, but they give you an idea of what needs to be considered when you take an educational issue and extract problems for possible investigation in the form of a research study.
Respond to the following discussion questions:
Discussion reponses should be at leat 3-4 paragraphs with citations
Discussion #1
When a research begins their work, they must start by assessing an issue. Next, the researcher must think of ways to positively address the issue. The task, at first, might be overwhelming. Therefore, it is important that the researcher critically examines the issue and determines what the most important related problems are. As the researcher considers problems associated with an issue, they should be able to begin identifying potential research topics. Before the researcher can start planning a research study for a topic, the topic must be quite narrow.
Identifying a problem for each issue that can be researched
Common Core State Standards
– The common core state standards is one of the most critical issues facing education in the 21
st
century. A problem with the common core state standards is that it does not adequately address the needs of students with disabilities.
Technology
– After all these years technology is an issue in the field of education. Technology can be u.
The Development Problem Based Learning Collaborative Model in Sociology Learn...iosrjce
This reseach in based on the real condition Senior High School Sociology learning activity in
Madiun regency which is still far from what we wish, still focus on cognitive aspect. Affective aspect and skill
need a little touch, if it is impossible to say they are still untouched. Even, we are obliged to implement the
attitude or character values in the activity of learning.
The purpose of the research is: (1) to recognize the recent condition of sociology learning activity, (2) to
create a sociology learning model, Problem Based Learning Collaborative, (3) to identify the effectiveness of
the model in improving student achivement.
The method of the research and the model development is carried out through these stages : Preliminary
research, development design, model testing or product evaluation. Collecting the data is using observation,
interviews, questionnaries, and documentation technique. Data analysis in the preliminary research is using
qualitative approach while model testing or product evaluation is using quantitative approach experiment. Ttest
isused to determine the differences between Problem Based Leraning Collaborative model and varied
lecturing model.
The result of the study is concluded as follows: (1) Sociology learning activity in Madiun Regancy is still
varied in delivering the knowledge, not yet focus on delivering of the value. Also the process of learning
evaluation is still focus on cognitive aspect ( knowledge ). Where as according to curriculum, sociology must be
conducted as an integral subject. The aim must also touch all aspect, include : cognitive, affective, skill, and
attitude. That is why, it is needed to conduct Problem Based Learning Collaborative model. (2) After being
validated by a team of experts and practitioners, the draft of Problem Based Learning Collaborative Model is
experimented in, among others, SMAN 1 Parang. The result of the model can be understood and implemented
by both teachers and students. After the trial, the model is applied as a restricted quasi–experimental test in
SMAN Bungkal Ponorogo and SMAN Badegan Ponorogo. The results show that the experimental groups have a
better average than the control group both in the cognitive aspect and the affective one. When the model is
applied extensively in SMAN 1 Parang, SMAN 2 MAGETAN, SMAN Sukomoro, SMAN Sampung, the results
remains the same. It shows that the experimental groups heve a better average than the contol ones, both in the
coginitive aspect and the affective one. Applying the model, it shows that the model effects the students
significantly in increasing the achivement ( cognitive aspect ) and strengthen the character and attitude
( affective aspect and skill ) compared with the varied lecturing model. Thus, it can be concluded that the groups
using Problem Bsed Learning Collaboraive Model has a better achivement and effort in implementing the
characters values more than that of using varied lecturing model.
Online Grading System
Traditional Grading System Essay
Essay on Grading System Reform
Grading System
Standard Grading Scale
Grading System Rationale
K-12 Grading System
Grading System
DPFManager workshop in Barcelona with members of the Official Association of at the Librarians (Col·legi Oficial de Bibliotecaris i Documentalistes de Catalunya – COBDC), to show the functionalities offered by the DPF Manager to check TIFF files.
IMPROVING LONG-TERM DIGITAL PRESERVATION EXPERIENCE WORKSHOP
23 NOVEMBER 2016
Kulturforum
Matthäikirchplatz, 10785 Berlin
The aim of the workshop is to demonstrate the conformance checkers for file-formats developed in the project, involve memory institutions outside the PREFORMA consortium in testing, using and further developing the software, and share the experience gained by PREFORMA memory institutions working with developers under R&D service agreements.
(Gerard Gassol). This work will focus in how climate change will affect the city of Schiedam. We will study the main consequences of climate change in the Netherlands and we will focus in flood. How floods will affect the City at mid and long term. In order to do an accurate approach, we will consult various studies but specially the last KNMI’14 study, developed by the Royal Netherlands Meteorological Institute.
(Fernando Campos). Empowering local business parks through collaborative&complementary-IT based strategies : companies in Schiedam lack information about products and services delivered by other companies situated in the same business park. They could make better use of each other's services and products. We are looking for a social platform for local entrepreneurs to: improve industrial cooperation, improve exchange of personnel and other services, reduce traffic/transport, promote energy efficiency, facilitate communication with the local administration and improve safety.
(David Rodriguez). This project, on the collaboration agreement framework between the University of Girona and the Schiedam municipality, will try to analyze the current status of the waste collection in residential areas and propose some solutions in the smart city vision. The main goal is to improve recycling and reduce waste volume in a more sustainable city.
(Albert Tàpia). This work proposes some solutions for helping Schiedam to become a smart tourist destination and at the same time, boosting its economy and resolving some of its main problems such as the lack of occupancy in the main shopping street or the lack of real-time data that can help to improve the quality of life of Schiedam.
(Jaume Sala). The initial definition of this project consisted on three questions: How can the city administration connect/combine own data sets within the existing IT structure in order to make multidimensional analysis? How can we (the government of Schiedam) combine these datasets with datasets from several stakeholders? And finally, what kind of new information can become available? The objectives of the project were the following: Implement a tool to achieve the visual representation of georeferenced datasets, analyze the possibility to combine multiple datasets in the same graphical representation, and propose a new datasets organization related to smart city indicators and geospatial data.
Project 8. Project of Nearly Zero Energy District [nZED] for (Nil Juvanteny i Vanessa Gàlvez). The main objective of this project is to achieve a nearly zero energy district [nZED] for the city center of Schiedam. The most important idea of the project is to develop a model that can be exported to any neighborhood, district, area of the city, independently if it is rich or poor, big or small. The principle of “nearly zero energy” means a very high level of energy performance that is traduced in low energy consumption which should be covered using renewable sources. These renewable sources are used not just to cover the energy consumption but also to sell the surplus and make profit from that.
(Gerard Gassol). This work will focus in how climate change will affect the city of Schiedam. We will study the main consequences of climate change in the Netherlands and we will focus in flood. How floods will affect the City at mid and long term. In order to do an accurate approach, we will consult various studies but specially the last KNMI’14 study, developed by the Royal Netherlands Meteorological Institute.
Project 8. Project of Nearly Zero Energy District [nZED] for (Nil Juvanteny i Vanessa Gàlvez). The main objective of this project is to achieve a nearly zero energy district [nZED] for the city center of Schiedam. The most important idea of the project is to develop a model that can be exported to any neighborhood, district, area of the city, independently if it is rich or poor, big or small. The principle of “nearly zero energy” means a very high level of energy performance that is traduced in low energy consumption which should be covered using renewable sources. These renewable sources are used not just to cover the energy consumption but also to sell the surplus and make profit from that.
(Marc Fortuny). Parking management refers to strategies that result in a more efficient use of parking resources. Most parking management strategies have modest individual impacts, typically reducing parking requirements by 5 to 15 percent, but taken together cumulatively, their impacts are synergistic that often the amount of parking at a destination by 20 to 30 percent. Several steps must be taken to ensure parking management strategies will be supported by residents, business owners, and visitors to the affected area. The City is in the process of developing a comprehensive toolbox of parking management options that can be implemented in the study area.
DPF Manager is an open source modular TIFF conformance checker that is extremely easy to use, to integrate with existing and new projects, and to deploy in a multitude of different scenarios. It is designed to help archivists and digital content producers ensure that TIFF files are fit for long term preservation, and is able to automatically suggest improvements and correct preservation issues. The team developing it has decades of experience working with image formats and digital preservation, and has leveraged the support of 60+ memory institutions to draft a new ISO standard proposal (TIFF/A) specifically designed for long term preservation of still-images. An open source community will be created and grown through the project lifetime to ensure its continuous development and success. Additional commercial services will be offered to make DPF Manager self-sustainable and increase its adoption.
Centre Easy has a spirit full of innovation and highly experienced to find and exploit growth opportunities.
Since 2001, Centre Easy inspires business and tech solutions to develop ideas into better solutions.
Centro de investigación de la Universitat de Girona que trabaja para el desarrollo y análisisi de arquitectura de control y para agentes sistemas multi agente.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
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Universitat de Girona' RESEARCH | Collaborative learning
1. Analysis of the Benefits of Collective Learning through
Question Answering
Abstract
Online collaborative learning between peers seems a viable complementary method to
traditional learning, even as the input no longer comes from only one man – the tutor
– but from a number of people with different levels of competence. Furthermore,
nowadays an increasing number of people turn to social networks when they need to
find answers, for reasons like trust, response time and effort. Thus social networks
behave at times similarly to online collaborative learning networks. This paper
presents a model of Questions & Answers (Q&A) learning where students are the ones
that ask and also answer questions, as a method to increase and reinforce knowledge.
Iasmina-Leila Ermalai1, Josep Lluís de la Rosa1 , and Araceli Moreno3
1Faculty of Electronics and Telecommunications, “Politehnica” University of Timisoara, Romania
2Agents Research LAB, Institute of Informatics and Applications, University of Girona, E17071 Girona, Spain
3Universidad Autónoma de Tamaulipas, Facultad de Ingeniería, Campus Tampico- Madero, México
iasmina.ermalai@cm.upt.ro, peplluis@eia.udg.edu, amoreno@uat.edu.mx
1. Introduction
Recent surveys, notably Chi (2009), show that people turn to social networks when
they need information or seek answers to subjective or open questions. They often
resort to social networks as they find it easier to formulate a full question, rather than
to recurrently try to find the right key words, and moreover when answers come from
friends, which have a certain degree of trust and expertise, known by the questioner.
We claim that Questions & Answers (Q&A) is a proper model for collaborative learning
(CL). Glasser (1986) argued that students remember more information when they are
actively engaged in learning as a social act: we learn more by collaborating,
communicating within a group. Glasser's trial data reveal that we remember 95% of
what we teach others.
Students learn best when they actively construct their own understanding through
social interaction with peers. The responsibility of the instructor is to facilitate the
students’ learning process around a particular content.
2. Simulations of collaborative learning
We propose a peer Q&A simulation of CSCL and compare it to a traditional tutor Q&A
system. In peer Q&A systems students answer each other’s questions, a process
supervised and facilitated by tutors.
Each student initially has all its classmates in the contact list. Further on, he can add
whomever he chooses to, from parents to friends outside school. The model is similar
to Facebook (or any social network) in the sense that a user can post a question on his
wall or send email to a list/group of friends. The difference from Facebook resides in
the fact that, in the eventuality that a friend of a friend responds to the question, both
the initial asker, and the helping friend would receive the answer. This is a method that
would also help increase the knowledge of the mediator, the friend.
Every student entering the system receives a LCV (Learner Competences Vector), which
includes various domains of user knowledge and also a level of competence for each of
these matters. In order to rate the competences of the answerer in each subject, we
drew inspiration from Bloom’s taxonomy of educational goals (1956) 1 - knowledge,
2 – comprehension, 3 – application, 4 – analysis, 5 – synthesis, and 6 - evaluation. We
introduced the 0 (zero) value to declare the forgetting factor (the user knew something
about that domain, but no longer does).
LCV initially contains no competences (Ø). The competence value is built upon the
user’s answers. In our simulations, initial values for LCV (subjects and competences)
were randomly generated.
2.1. Assumptions and measures
Drawing inspiration from Pous (1997), we consider that a set of pedagogical inputs can
change the state of the students, namely the LCV.
Aside from the traditional input system, where the teacher provides the input that is
supposed to change the pedagogical value of each student, our model introduces the
student/peer input system, where:
A = { Ai} is the set of students in a class.
K = {a, b..., z} is the set of subjects kj,
c = [0,1...,6] are the competence levels
Li the LCV for each student Ai
C the curricula, pedagogical goals in terms of LCV for a class of students
qi the increase/reinforcement factor.
α the forgetting factor.
After every n weeks a pupil does not ask, nor answer any question about a subject, his
competence decreases by a factor df
The goal is to make average Li as close as possible to the curricula C (completeness),
after a time frame of 12-15 weeks (a semester).
2.2 Experiments
We considered a class of 8 students that do question answering, as well as the
teacher does. The questions are related to one subject. The time frame is 12 weeks
(one semester) to reach goals set up in the curriculum.
The student’s learning curve is the amount of knowledge and the speed with which he
achieves it. It depends on his native abilities and also on his effort. In our approach, a
deterministic one, we only took into consideration the effort. Effort is considered to
be the frequency with which a student answers and also asks questions. The
bandwidth is seen as the number of questions one can answer. In this model the
professor’s bandwidth is considered to be infinite.
The students’ evolution was simulated for a period of 12 weeks, where the following
two aspects were rewarded with points:
• receiving answers to asked questions
• answering questions asked peers.
The answer factor, qi of student Ai is:
Where:
• Ic= Cc - ac the competence index
Cc - the curriculum target competence;
ac - the initial average competence of the class.
• t – number of weeks allocated to reach Cc from ac
• γ - number of questions/pupil/week (established by the tutor) .
We calculated qi with the following formula:
6. Final comments
The Q&A model proposed in this paper seeks to increase knowledge by emphasizing
the importance of questions and answers among peers in online social networks, a
process sustained and enhanced by tutors. Simulations showed that the increase in
knowledge was more significant in the case of the Q&A Collaborative Learning system,
than in the traditional student asking - tutor answering system.
We plan to:
•Expand the network, allowing network friends from outside the classroom
increasing Q&A activity more questions & faster answers lowering the
necessity for tutors to intervene, to stimulate the answering process.
•Use agents for automatically answering questions they have answers for in a special
Q&A list and for suggesting contacts (other agents) that could answer question from
a certain field (using the Learner Competence Vector).
Each pupil has to answer at least 4 questions/week; every time he gives an answer to
a question asked by a peer, he earns 0.1 points of competence; if he answers the
established target of 4 questions, he gains 0.4 points/week. If there was no answer in
a week, his competence is decreased by the same value a week, entitled the forgetting
factor (df=0.4). For each answer received, the student is considered to be achieving
knowledge worth of 0.1 points.
Figure 1: Classical model of learning,
where students ask and tutors answer
γ
tI
q c
i
/
=
(3)
Figure 2: Q&A model of Collaborative Learning.
(1)
In Figure 1 (where only tutors’ answers contribute to the students’ competence
increase), a slight improvement can be observed in the established period of time,
whilst in Figure 2, peer-to-peer interaction appears to be the best method to boost
competences. Even in the worst case scenario, a week without any activity, the overall
results at the end of a 12 weeks semester were encouraging for the Q&A Collaborative
Learning model.
(2)