Dr. Gábor Kismihók's presentation at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016.
Learning analytics is an emerging discipline in education, aiming at analysing (big) educational data in order to improve learning processes. In this talk, Dr. Gábor Kismihók will give an overview about the main challenges of this field, with a special emphasis on bridging the education - labour market divide.
Intuition's Fall from Grace - Algorithms and Data in (Pre)-Selection by Colin...Textkernel
On 2 June during Textkernel's conference Intelligent Machines and the Future of Recruitment, Colin Lee presented his work on the automated preselection of applicants. For this research he used data from Connexys from 441,768 applicants at 48 companies, in combination with Textkernel parsing and normalization, to develop an algorithm that predicts which applicants get invited to a job interview. Colin explains the logic behind his approach and discusses potential future applications.
Set the Hiring Managers’ Expectations: Using Big Data to answer Big Questions...Textkernel
Presentation by Abdel Tefridj at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016 in Amsterdam.
Abdel shares some client scenarios when data was the key element in the decision making process for recruitment challenges. You can become a better partner with hiring managers when they are informed about the latest trends in the marketplace using supply, demand and compensation data. Learn how to use big data to make you a stronger leader and contributor.
How semantic search changes recruitment - Glen CatheyTextkernel
Presentation by Glen Cathey, SVP Talent Strategy and Innovation at Kforce, at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June at the Beurs van Berlage in Amsterdam. At the end of this slide deck, you can also find the YouTube recording.
Without semantic search, recruiters searching for potential candidates only see a fraction of available and relevant results and unknowingly exclude qualified candidates unless they understand and employ advanced methods of manual information retrieval. In this keynote, Glen Cathey will explain how semantic search has specifically impacted recruitment today and how further advancements will impact recruitment in the future.
Textkernel talks - introduction to TextkernelTextkernel
by Darko Zelić, Software Engineer at Textkernel.
Textkernel organises monthly Textkernel Talks; technical and practical presentations from research and industry specialists. Topics can include Topics involve NLP, IR, Deep Learning, Semantic Search, LTR and more.
This presentation was held at the first event on Thursday 3 September.
Join the Textkernel Talks meetup group (http://www.meetup.com/textkernel-talks/) to stay informed of all events.
Ideas for meetup events at Textkernel? Contact us via talks@textkernel.nl.
How academic institutions best support PhDs and postdocs in the transition to...AI Guild
Ask your academic institute to invite the AI Guild to deliver an online workshop on #datacareer to support PhDs and postdoc s moving to startups, consultancy, and the industry.
Data Science Career Paths at N2 ConferenceAI Guild
N2 Conference 2019 - Workshop on Data Science Careers out of Academia. N2 Network of Doctoral Researchers - Max Planck PhD Net, Leibniz PhD Network, Helmholtz Juniors.
#Datacaeer - AI Guild workshop on data roles in industry with Adam GreenAI Guild
Based on AI Guild career coaching this workshop looks at roles such as Data Analyst, Data Scientist, and Data Engineer in industry and startups. We discuss emerging specialization, and how to upgrade your competence profile. Also included, tips and tricks from practitioners on how to find your next role.
Please find the event series on aiguild.eventbrite.com
Science to Data Science: PhDs and postdocs moving to startups and industry (2...AI Guild
How to get interviews and the employment contract. A roadmap workshop on transitioning to the industry in a #datacareer, e.g. Data Scientist, Data Analyst, ML engineer, NLP practitioner, etc.
Benefit from the insights of Europe's leading 1000+ practitioner community, including Ph.D. role models from STEM disciplines and the social sciences that now enjoy a #datacareer.
Intuition's Fall from Grace - Algorithms and Data in (Pre)-Selection by Colin...Textkernel
On 2 June during Textkernel's conference Intelligent Machines and the Future of Recruitment, Colin Lee presented his work on the automated preselection of applicants. For this research he used data from Connexys from 441,768 applicants at 48 companies, in combination with Textkernel parsing and normalization, to develop an algorithm that predicts which applicants get invited to a job interview. Colin explains the logic behind his approach and discusses potential future applications.
Set the Hiring Managers’ Expectations: Using Big Data to answer Big Questions...Textkernel
Presentation by Abdel Tefridj at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016 in Amsterdam.
Abdel shares some client scenarios when data was the key element in the decision making process for recruitment challenges. You can become a better partner with hiring managers when they are informed about the latest trends in the marketplace using supply, demand and compensation data. Learn how to use big data to make you a stronger leader and contributor.
How semantic search changes recruitment - Glen CatheyTextkernel
Presentation by Glen Cathey, SVP Talent Strategy and Innovation at Kforce, at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June at the Beurs van Berlage in Amsterdam. At the end of this slide deck, you can also find the YouTube recording.
Without semantic search, recruiters searching for potential candidates only see a fraction of available and relevant results and unknowingly exclude qualified candidates unless they understand and employ advanced methods of manual information retrieval. In this keynote, Glen Cathey will explain how semantic search has specifically impacted recruitment today and how further advancements will impact recruitment in the future.
Textkernel talks - introduction to TextkernelTextkernel
by Darko Zelić, Software Engineer at Textkernel.
Textkernel organises monthly Textkernel Talks; technical and practical presentations from research and industry specialists. Topics can include Topics involve NLP, IR, Deep Learning, Semantic Search, LTR and more.
This presentation was held at the first event on Thursday 3 September.
Join the Textkernel Talks meetup group (http://www.meetup.com/textkernel-talks/) to stay informed of all events.
Ideas for meetup events at Textkernel? Contact us via talks@textkernel.nl.
How academic institutions best support PhDs and postdocs in the transition to...AI Guild
Ask your academic institute to invite the AI Guild to deliver an online workshop on #datacareer to support PhDs and postdoc s moving to startups, consultancy, and the industry.
Data Science Career Paths at N2 ConferenceAI Guild
N2 Conference 2019 - Workshop on Data Science Careers out of Academia. N2 Network of Doctoral Researchers - Max Planck PhD Net, Leibniz PhD Network, Helmholtz Juniors.
#Datacaeer - AI Guild workshop on data roles in industry with Adam GreenAI Guild
Based on AI Guild career coaching this workshop looks at roles such as Data Analyst, Data Scientist, and Data Engineer in industry and startups. We discuss emerging specialization, and how to upgrade your competence profile. Also included, tips and tricks from practitioners on how to find your next role.
Please find the event series on aiguild.eventbrite.com
Science to Data Science: PhDs and postdocs moving to startups and industry (2...AI Guild
How to get interviews and the employment contract. A roadmap workshop on transitioning to the industry in a #datacareer, e.g. Data Scientist, Data Analyst, ML engineer, NLP practitioner, etc.
Benefit from the insights of Europe's leading 1000+ practitioner community, including Ph.D. role models from STEM disciplines and the social sciences that now enjoy a #datacareer.
How do I start a data career in the 2020s?AI Guild
Your 1st or 2nd role.
"Awesome CV feedback. I am applying, and 50% of the companies invite me for an interview."
I enjoyed working on the CV and preparing for the interviews. In the end, I had the luxury to choose between 2 job offers."
EE to Data Science - Why and How of the PivotIrfan Elahi
The deck that I used during my talk at University of Engineering and Technology, Lahore about why and how to pivot from Electrical engineering to Data Science. Answers a number of critical questions like what is data science, how to become a data scientist and what are the career prospects in Data Science.
Data and Analytics Career Paths, Presented at IEEE LYC'19.
About Speaker:
Ahmed Amr is a Data/Analytics Engineer at Rubikal, where he leads, develops, and creates daily data/analytics operations, which includes data ingestion , data streaming, data warehousing, and analytical dashboards. Ahmed is graduated from Computer Engineering Department, Alexandria University; and he is currently pursuing his MSc degree in Computer Science, AAST. Professionally, Ahmed worked with Egyptian/US startups such as (Badr, Incorta, WhoKnows) to develop their data/analytics projects. Academically, Ahmed worked as a Teaching Assistant in CS department, AAST. Ahmed helps software companies to develop robust data engineering infrastructure, and powerful analytical insights.
References:
1) https://www.datacamp.com/community/tutorials/data-science-industry-infographic
2) Analytics: The real-world use of big data, IBM, Executive Report
Licensed to Analyze? Strata Data NY 2019 IADSS Session - Usama Fayyad, Hamit ...IADSS
The latest insight into IADSS Research was shared with analytics community at Strata Data NY 2019 by O'reilly. IADSS Co-founders Usama Fayyad and Hamit Hamutcu talked about the current status of data science job market, the wasted cost of data science recruitment and role definitions & required skill-sets for most common roles in data science.
Please check out IADSSglobal on Twitter and visit www.iadss.org for more information.
Data science for business leaders executive programmjitu309
Data Science for Business Leaders Executive Program
PPT For Project done by Jitendra Ratilal Mistry
For Educational purpose Only
The content given in the PPT does not belong to me, Content belong to it's original Creator, for Education purpose it has been used in PPT.
Advances in technology for capturing information have led to the promise of “Big Data” to dramatically alter the business environment. However, technology is only an enabler of aggregation and analysis. Many firms struggle to convert information to business knowledge and insights. Learn how organizations are using data to improve skill development at all levels and developing models for organizational structures to link these skills to executive decision-making.
Speakers: Dan McGurrin, Ph.D., NC State and Pamela Webber, Cisco
How to hire a data scientist recruit pageHackerEarth
Read more: http://bit.ly/2OlopT5
A data scientist’s job is one of the most sought after jobs of the 21st century. But how do you hire a data scientist who fits the bill?
Explains: What is Data Science? What is the difference between Data Science and Data Engineering, and between Data Science and Business Intelligence? What type of work do Data Scientists do, and what types of companies employ them? What is the job outlook for Data Science? What professional education is required?
Big Data, Data Science, Machine learning creating tremendous value in the education sector. Combination of open source with IBM value adds create compelling value. Artificial intelligence will revolutionize the sector with making education more relevant with Cognitive capabilities of students.
Sdal air education workforce analytics workshop jan. 7 , 2014.pptxkimlyman
The American Institutes for Research (AIR) and Virginia Tech are collaborating to explore and develop new approaches to combining, manipulating and understanding big data. The two are also looking at how big data analytics can help answer questions critical to solving issues in education, workforce, health, and human and social development. They held two workshops on January 7 and 27, 2014- the first on Education and Workforce Analytics and the second on Health and Social Development Analytics.
How do I start a data career in the 2020s?AI Guild
Your 1st or 2nd role.
"Awesome CV feedback. I am applying, and 50% of the companies invite me for an interview."
I enjoyed working on the CV and preparing for the interviews. In the end, I had the luxury to choose between 2 job offers."
EE to Data Science - Why and How of the PivotIrfan Elahi
The deck that I used during my talk at University of Engineering and Technology, Lahore about why and how to pivot from Electrical engineering to Data Science. Answers a number of critical questions like what is data science, how to become a data scientist and what are the career prospects in Data Science.
Data and Analytics Career Paths, Presented at IEEE LYC'19.
About Speaker:
Ahmed Amr is a Data/Analytics Engineer at Rubikal, where he leads, develops, and creates daily data/analytics operations, which includes data ingestion , data streaming, data warehousing, and analytical dashboards. Ahmed is graduated from Computer Engineering Department, Alexandria University; and he is currently pursuing his MSc degree in Computer Science, AAST. Professionally, Ahmed worked with Egyptian/US startups such as (Badr, Incorta, WhoKnows) to develop their data/analytics projects. Academically, Ahmed worked as a Teaching Assistant in CS department, AAST. Ahmed helps software companies to develop robust data engineering infrastructure, and powerful analytical insights.
References:
1) https://www.datacamp.com/community/tutorials/data-science-industry-infographic
2) Analytics: The real-world use of big data, IBM, Executive Report
Licensed to Analyze? Strata Data NY 2019 IADSS Session - Usama Fayyad, Hamit ...IADSS
The latest insight into IADSS Research was shared with analytics community at Strata Data NY 2019 by O'reilly. IADSS Co-founders Usama Fayyad and Hamit Hamutcu talked about the current status of data science job market, the wasted cost of data science recruitment and role definitions & required skill-sets for most common roles in data science.
Please check out IADSSglobal on Twitter and visit www.iadss.org for more information.
Data science for business leaders executive programmjitu309
Data Science for Business Leaders Executive Program
PPT For Project done by Jitendra Ratilal Mistry
For Educational purpose Only
The content given in the PPT does not belong to me, Content belong to it's original Creator, for Education purpose it has been used in PPT.
Advances in technology for capturing information have led to the promise of “Big Data” to dramatically alter the business environment. However, technology is only an enabler of aggregation and analysis. Many firms struggle to convert information to business knowledge and insights. Learn how organizations are using data to improve skill development at all levels and developing models for organizational structures to link these skills to executive decision-making.
Speakers: Dan McGurrin, Ph.D., NC State and Pamela Webber, Cisco
How to hire a data scientist recruit pageHackerEarth
Read more: http://bit.ly/2OlopT5
A data scientist’s job is one of the most sought after jobs of the 21st century. But how do you hire a data scientist who fits the bill?
Explains: What is Data Science? What is the difference between Data Science and Data Engineering, and between Data Science and Business Intelligence? What type of work do Data Scientists do, and what types of companies employ them? What is the job outlook for Data Science? What professional education is required?
Big Data, Data Science, Machine learning creating tremendous value in the education sector. Combination of open source with IBM value adds create compelling value. Artificial intelligence will revolutionize the sector with making education more relevant with Cognitive capabilities of students.
Sdal air education workforce analytics workshop jan. 7 , 2014.pptxkimlyman
The American Institutes for Research (AIR) and Virginia Tech are collaborating to explore and develop new approaches to combining, manipulating and understanding big data. The two are also looking at how big data analytics can help answer questions critical to solving issues in education, workforce, health, and human and social development. They held two workshops on January 7 and 27, 2014- the first on Education and Workforce Analytics and the second on Health and Social Development Analytics.
Mol, S.T. (2014, November). Learning Analytics: The good, the bad, the ugly. Presentation delivered as part of the UvA Faculty of Economics and Business Educational Innovation Seminar Series. University of Amsterdam, the Netherlands.
Textkernel Emerce eRecruitment - 6 april 2017 Textkernel
Maakt Artificial Intelligence het werk van de recruiter straks overbodig? In tegendeel! In een krapper wordende arbeidsmarkt wordt recruitment en tijd voor de kandidaat steeds belangrijker. In deze presentatie geven we een korte introductie over AI en laten we zien waarom het juist voor recruitment belangrijk is en hoe het je helpt beter te sourcen en te matchen. We sluiten af met interessante klantcases van o.a. USG People en CERN.
AI Reality: Where are we now? Data for Good? - Bill BoormanTextkernel
At Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June 2016, recovering recruiter Bill Boorman took a look at the AI landscape now, defining fact from fiction and wishful thinking.
At the end of this slide deck, you can also find the YouTube recording.
Robots Will Steal Your Job but That's OK - Federico PistonoTextkernel
Presentation of researcher and entrepreneur Federico Pistono, author of "Robots Will Steal Your Job, But That's OK", that was held at Textkernel's conference Intelligent Machines and the Future of Recruitment on June 2nd in Amsterdam.
At the end of this slide deck, you can also find the YouTube recording.
Outline:
Over the past four years, headlines warned us that a wave of joblessness is coming. They claim that advances in robotics, machine learning, and automation are ushering in an era of unprecedented change. Do these concerns reflect reality?
Some claim that we have seen this story before, and that we have nothing to worry about. Others think that this time is different, and that we're about to experience the most dramatic shift in modern economic history, one for which we are not prepared. But what is the real risk of technological unemployment? How will it affect the job market, recruitment, and the economy at large?
In this presentation, Federico Pistono separated the myths from reality by presenting the state of the art and forecasts of machine intelligence and its economic impact.
Semantic Interoperability in the Labour Market - Martin le Vrang, Team leader...Textkernel
This presentation was held by Martin le Vrang at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June in Amsterdam.
The European Commission is developing a multilingual classification of European Skills, Competences, Qualifications and Occupations (ESCO). This common reference terminology will enhance the functioning of the labour market, help to build an integrated European labour market and bridge the communication gap between work and education/training. ESCO is part of an emerging Semantic Web in the labour market and the education and training sector. Job vacancies, CVs and training curricula would no longer just be documents, but standardised sets of data which can be reused in job matching, HR systems, for career guidance tools or in statistical applications.
Pablo de Pedraza: Labor market matching, economic cycle and online vacanciesTextkernel
Pablo de Pedraza's presentation at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016.
The number of job openings, or vacancies, is an important indicator of the state of the economy and the labour market. They are extensively used by institutions and in academic papers to calculate the Beveridge Curve or estimate the matching function, center pieces of macroeconomic models studying labor markets. Vacancies can be measured using administrative registers, surveys to employers, advertisements in printed press or using online advertising.
This presentation is divided into two sections. In the first one we study the Dutch Beveridge curve and the matching function using the number of vacancies inferred from a survey to employers conducted by the Dutch Central Bureau of Statistics (CBS) from 1997 until the end of 2014. We obtain conclusion about matching process before and after the Great Recession.
In the second section we compare number of vacancies inferred from CBS vacancy data with the number of vacancies posted online. According to CBS data, the number of vacancies increases during positive shocks and goes down during negative ones. We can observe the number of web vacancies posted online from 2006 until today and compare them with CBS data during a complete economic cycle.
Results show a positive time trend in the number of online vacancies and negative time trend in the number of vacancies inferred from a survey. We show that both series reflect very similar economic reality once we account for both trends. We settle our future research lines focusing on exploring the sources behind both trends and how they compare across sectors.
New Developments in Machine Learning - Prof. Dr. Max WellingTextkernel
Presentation from Prof. Dr. Max Welling, Professor of Machine Learning at the University of Amsterdam, at Textkernel's Intelligent Machines and the Future of Recruitment on June 2nd in Amsterdam.
At the end of this slide deck, you can also find the YouTube recording.
Due to increased compute power and large amounts of available data, machine learning is flourishing once again. In particular a technology called deep learning is making great strides maturing into a powerful technology. Max Welling briefly discusses variants of deep learning, such as convolutional neural networks and recurrent neural networks. But what lies around the corner in machine learning? He will discuss the three developments that in his opinion will become increasingly important:
1) Learning to interact with the world through reinforcement learning,
2) Learning while respecting everyone's privacy, and
3) Learning the causal relations in data (as opposed to discovering mere correlations).
Together, they represent the "power tools" of the future machine learner.
The Agile Future of HR and Talent Acquisition - Prof. Dr. Armin Trost Textkernel
Presentation from Prof. Dr. Armin Trost, Author, Consultant and Professor at Furtwangen University, at Textkernel's Intelligent Machines and the Future of Recruitment on June 2nd in Amsterdam. At the end of this slide deck, you can also find the YouTube recording.
Human resource management in the 21st century will have little to do with what has been promoted in recent years or decades and written in the text-books. Instead of finding “the right people, at the right time and at the right place” we will make the employees and their individual preferences, talents, life plans, and ambitions the focus of attention.
We will say goodbye to mechanistic, technocratic, and often bureaucratic approaches. They fit in a past that was stable and predictable. If you regard your employees as your most valuable asset, you will give them freedom, trust, and responsibility. Moreover you will appreciate individuality and individual life-plans.
Human resources management will therefore deal less with hierarchical processes, systems, responsibilities, KPIs, etc., in the future. Rather, it will be about how to empower teams to think on their own responsibility, communicate, collaborate, learn, and develop their talent in the long term.
HR-Technology will be there to make the life of managers and employees easier instead of supporting the HR-function only. For instance, in the area of recruiting all this will lead to a more intense usage of social networks, artificial intelligence, big data, data mining etc.
Human > Machine Interface - The future of HR | Perry Timms, Founder & Directo...Textkernel
Presentation by Perry Timms at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June 2016 in Amsterdam.
With a spotlight on AI; VR/AR; robotics, automation, machine learning and quantum computing, what does this mean for the world of work, jobs and human endeavour?
More so, what does it mean to the technophobia often present in HR? There’s a thought that HR doesn’t even really get the technology that’s being used now and is having a profound effect on where, when and how people are working. And no, self-service cloud-based HR systems doesn’t mean the profession is anywhere near to being tech savvy. That’s low level labour realignment and marginal process improvement.
My fear - as an HR professional aware of and experimenting with technology constantly - is that my profession is already WAY BEHIND the curve so how will HR practitioners cope with the latest array of digital disruption?
Join me in finding out how I believe we can upgrade HR’s thinking and doing for the digital age of work.
Ton Sluiter: Breaking Barriers and Leveraging DataTextkernel
Ton Sluiter's presentation at Textkernel's conference Intelligent Machines and the Future of Recruitment that took place on 2 June 2016 at the Beurs van Berlage in Amsterdam.
In this presentation Ton Sluiter discusses the way CV Search! from Textkernel has contributed to make the candidate databases of Star Brands and USG People accessible to one another. Furthermore, he takes a look at the extra insights USG People has gained from the parsed CVs.
The Role of Public Innovation and the Impact of Technology on Employment - Re...Textkernel
Presentation by Reynald CHAPUIS, Director of innovation and Corporate Social Responsibility at Pôle Emploi, at Textkernel's conference Intelligent Machines and the Future of Recruitment that was held on 2 June 2016 at the Beurs van Berlage in Amsterdam.
Reynald Chapuis presents Pôle emploi, a key player in the French Public Employment Service, and its innovation system through multiple and collaborative platforms. He presents 3 case studies on how Pôle emploi uses data, artificial intelligence and machine learning for the benefit of job advisors and jobseekers.
It’s all about Technology... oh wait! It’s not - Balazs ParoczayTextkernel
Presentation from Balazs Paroczay, Head of Recruiting Strategy and Innovations, Randstad Sourceright EMEA, at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June in Amsterdam.
Due to digital technology revolution, sourcing for good candidates is basically not a challenge anymore. There are search plugins but also productivity tools, document and data-grabbing, parsing and matching, email verification, image search and soon-coming face recognition applications, click-rate or any-other-type data analytics softwares (trillions of them!), and it looks like the core competitive advantage of a top sourcer is solely on his toolkit nowadays.
This is however a trap, I believe, and we definitely need to avoid to let technology ultimately drive our thinking when building a sourcing function.
During my session I will share how we have embedded technology within Randstad Sourceright’s EMEA Sourcing Centre. How we made choices on when and when not to buy tech and where the human part is proved to be a still greater asset than any other tools or techs on the market.
Uw database als waardevolle sourcing toolTextkernel
Maak van je kandidaten-database je meest waardevolle sourcing tool
Je kandidaten-database is een waardevolle sourcing tool. Beperkte zoekopties in recruitmentsystemen zorgen ervoor dat de database niet optimaal gebruikt wordt. Ontdek hoe je de waarde van je recruitmentsysteem maximaal kunt benutten. Aan de hand van praktijkcases laat Gerard Mulder, CCO bij Textkernel, zien hoe semantische technologie je bestaande database kan omzetten in een efficiënte sourcing tool, door: - meer sollicitaties met een gebruiksvriendelijk sollicitatieproces - krachtige semantische zoeksoftware - automatische aanbevelingen van matchende kandidaten op je vacatures.
Over Gerard Mulder
Als commercieel directeur sinds 2005 heeft Gerard Mulder Textkernel helpen opbouwen tot een succesvolle internationale onderneming. Gerard heeft passie voor recruitment-innovatie en technologie. Hij begrijpt de behoeften in de veranderende markt en samen met het team creëren ze technologie voor de toekomst van global recruiting.
Textkernel Talks - Neo4j usage in TextkernelTextkernel
by Alexey Shevchenko, PHP developer at Textkernel.
Textkernel organises monthly Textkernel Talks; technical and practical presentations from research and industry specialists. Topics can include Topics involve NLP, IR, Deep Learning, Semantic Search, LTR and more.
This presentation was held at the joint event with GraphDB Meetup on Wednesday 9 December.
Join the Textkernel Talks meetup group (http://www.meetup.com/textkernel-talks/) to stay informed of all events.
Ideas for meetup events at Textkernel? Contact us via talks@textkernel.nl.
Innovatie en de Candidate Experience (Textkernel) - Recruitment Innovation EventTextkernel
Dit is de presentatie van Gerard Mulder van Textkernel over Innovatie en de Candidate Experience op het Recruitment Innovation Event op 12 oktober 2015 van Recruiters United.
Jobfeed rapport: De Nederlandse online arbeidsmarkt in Q1 2015Textkernel
Het aantal vacatures in het eerste kwartaal van 2015 is met 19% gestegen. Dat blijkt uit cijfers van Jobfeed, de Big Data tool voor vacatures van Textkernel, die alle online vacatures geplaatst in Q1 2015 heeft verzameld, ontdubbeld en gecategoriseerd.
In dit rapport vindt u de analyse van de vacaturedata in het eerst kwartaal van 2015. Het rapport bevat cijfers over vacaturedata, vacatures per beroepsklasse, branche, opleidingsniveau en provincie.
Voor meer informatie, bezoek www.jobfeed.nl.
Etat des lieux de l'offre d'emploi en ligne - Q1 2015Textkernel
Jobfeed publie aujourd'hui une infographie sur l'état des lieux du marché de l'emploi en ligne au Q1 2015. Cette étude se base sur l’analyse de près de 3.3 millions d’offres d’emploi (1.4 millions d'offres uniques) collectées par Jobfeed entre le 1er janvier et le 31 mars 2015.
Op donderdagavond 5 maart vond in Gent de officiële en exclusieve voorstelling van Jobfeed België plaats.
Jobfeed, de toonaangevende Big Data tool voor vacatures is nu, na Nederland, Duitsland en Frankrijk ook beschikbaar in België.
In 2003 startte Textkernel met het samenvoegen van vacature-informatie voor matching- en analysedoeleinden onder het label “Jobfeed”. Inmiddels is Textkernel marktleider in dit domein in Nederland en is Jobfeed gaan uitbreiden naar andere Europese landen zoals Duitsland, Frankrijk en nu ook in België.
De voorstelling van Jobfeed België werd georganiseerd door HRLinkIT en Textkernel.
http://hrlinkit.be/
http://www.textkernel.nl/
Webinar: Vacatures in Nederland (Jobfeed & Jacco Valkenburg)Textkernel
Deze presentatie is gegeven tijdens het webinar: Vacatures in Nederland door Kim Pieschel (Jobfeed/Textkernel) en Jacco Valkenburg (Recruit2).
Met de statistieken van Jobfeed en de kennis van Jacco worden inzichten gegeven in de Nederlandse vacaturemarkt.
+ Wat zijn de grootste beroepsklassen en branches
+ Welke organisaties hebben de meeste vacatures
+ Wat zijn de grootste vacaturesites
+ Hoe kiezen recruiters vacaturesites
+ Waar komen sollicitanten vandaan
+ Wat zijn succesvolle wervingskanalen
Voor meer informatie, neem contact op
Kim Pieschel: pieschel@textkernel.nl, http://www.jobfeed.nl/home.php
Jacco Valkenburg, jacco@recruit2.com
http://www.recruitingroundtable.nl/
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Embracing GenAI - A Strategic ImperativePeter 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.
Dr. Gábor Kismihók: Labour Market driven Learning Analytics
1. jobknowledge.eu
Labour Market Driven Learning Analytics
Dr. Gábor Kismihók
Senior Researcher
University of Amsterdam
Amsterdam Business School
g.kismihok@uva.nl
@kismihok
www.eduworks-network.eu
www.jobknowledge.eu
3. jobknowledge.eu
Learning Analytics
Learning analytics is “the measurement, collection, analysis, and
reporting of data about learners and their contexts, for purposes of
understanding and optimizing learning and the environments in which
it occurs” (SOLAR 2012).
4 levels of LA
• Describe
• Diagnose
• Predict
• Recommend
Expertise: Educational scientist, computer scientist, data scientist,
managers, teachers, students, labour market representatives
4. jobknowledge.eu
Hot topics
Person
• Learner profiles
• Personalisation
• Individual
feedback/benchmarking
• Teaching analytics
Organisation
• Student retention
• Curriculum design
• Workplace and
professional learning
• Institutional readiness
Technology
• Tools and interventions
• Visualisation
• MOOCs
• Predictive modelling
• Learning environments
Pedagogy
•Learning design
•Personalisation
•Feedback
•Blended learning
Ethics
•Data ownership
•Data management
•Transparency of algorithms
•Quality of
recommendations
5. jobknowledge.eu
What type of data?
• Performance
• Grades
• Assignments (text)
• Behavioral
• Clicks
• Content views
• Social media
• Physiological
• Pulse
• Brain activity
• Labour Market data
• Vacancy data
• Economic indicators/surveys
6. jobknowledge.eu
Examples
Purdue University (US) – Course Signals
• Predicting student drop outs based on LMS activity
• Teachers and students are notified and personal intervention is planned
• 21% retention rate improvement (Kimberley and Pistili 2012)
OU Analyse
• Predicts students at risk
• Predictive models on the basis of VLE and demographic data
• Also explains the reason, recommends activities
• Open dataset
Social Networks Adapting Pedagogical Practice (SNAPP)
• real-time social network analysis and data visualisation of forum discussion
activity
• identification of isolated students, non-functioning groups or groups need to work
together
7. jobknowledge.eu
Examples
Predictive Analytics Reporting (PAR) Framework (US)
• Non-profit provider of analytics-as-a-service
• Central analytics service for HE institutions
• Cross institutional analyses
Kahn Academy Analytics (US/Global)
• Learning content is mapped to skills
• Learning content is offered on the basis of effort, engagement, difficulty,
etc…
8. jobknowledge.eu
Labour market oriented
learning trajectories
Match learners’ pathways
to those of alumni
Help incoming students
find a long term focus
during their university
education
Mirror alumni data
to current students
based on
desired/acquired
occupations
9. jobknowledge.eu
Goal setting pilot
• Goal setting improves performance
• Create a goal setting interface for students to manage and track
(learning) goals
• Focus of research:
• Goal commitment/Shared goals
• Matching goals to behavioral and performance data
• Apply advanced analytics
10. jobknowledge.eu
Goal App Features
• Set goals (Specific, Measurable, Attainable, Relevant, Time Based)
• Set sub-goals
• Option to make goals private or public
• Feedback on goals
• Can view and commit public goals
• Tag goals
• Learning records
• Dashboard
• Reminders
First findings:
• Difficult to think about goals
• Goals should be generated
on the basis of labour market data
(vacancies)
virgo.ic.uva.nl:3000
14. jobknowledge.eu
Jobs (society) are changing
What are the relevant job information types, what is a job in the 21
century?
• increased idiosyncratic nature of work and the crafting of jobs by job holders
• 161 job information types in 50 studies - Volume and semantics
Shared economy
New selection and recruitment methods
Many vacant jobs simply do not show up on the web
Role of vacancy announcements in the future
How to target the output of Education?
17. jobknowledge.eu
Positioning a learning analytics project
• Centralized vs. decentralized
• Research vs. practice
• Imposed vs. desired
• Technology vs. Pedagogy
• Make or buy (resource oriented)
• Adoption of best practices or local
identification thereof
There is a lot of ambiguity and fear, but little
experience with LA
20. jobknowledge.eu
Definitions of constructs (like skills) are very
context sensitive
Data generation is not unified, terminology is weak (in the hands of HR
managers and their objectives)
Definition is influenced by
• The data producer (person or machine)
• Country, region
• Organisation
• Occupation
• Language
Universal taxonomy, ontology
22. jobknowledge.eu
Call for Transparency
• Trust is a big issue
• Data/algorithms are often not public - Black box society
Web-data:
• Traceability is an issue
• Scraping policies of data providers are not always visible
• Paid websites are rarely scraped
23. jobknowledge.eu
Educational data
• Many data silos
• Who owns what data?
• Highly political issue
• Organizational resistance
• Gatekeepers resistance
• Complex infrastructure
25. jobknowledge.eu
Ethics and Privacy
• One of the greatest barrier
• JISC reports 86 ethical, legal and logistical issues
https://analytics.jiscinvolve.org/wp/2015/03/03/a-taxonomy-of-ethical-legal-
and-logistical-issues-of-learning-analytics-v1-0/
• Algorithms/codes are often hidden – Black Box society
• Personal/sensitive data, lasting effects of recommendations
• How this data will be used on learners?
• What is the objective of the data collection? (not known at the time
the data is collected)
29. jobknowledge.eu
Summary
Power is in numbers
Bigger data, better matching, better insights, better research
LA is a new area
Many opportunities for innovative ideas and services
More evidence (research) needed what works and what doesn’t
Inductive vs Deductive
Need to document failures (not only success) properly
Technology is not a bottleneck
Organizational awareness is growing - LA is on the agenda in many stakeholder
groups
Legal and ethical concerns are critical
30. jobknowledge.eu
Further information
• LACE Evidence HUB http://evidence.laceproject.eu/
• LEAP Inventory http://cloudworks.ac.uk/cloudscape/view/2959
• SOLAR Community https://solaresearch.org/
• Learning Analytics and Knowledge Conference (LAK)
• Learning Analytics Summer Institute (LASI)
• Journal of Learning Analytics http://learning-analytics.info/