On February 25, 2020, Tony Bonen spoke to students at Carleton University about the importance of labour economics, working as an economist, and his career journey leading to LMIC.
Stephan - Science and Innovation Policy-making today: Big questions begging f...innovationoecd
This document discusses two important policy questions regarding science and innovation that require more data:
1) Tracking where highly trained students are placed after their education to better understand the role of education in fostering innovation and the transfer of knowledge to firms. Existing data focuses too much on placements in academia.
2) Collecting systematic cross-country data on the mobility of scientists and engineers to improve understanding of how mobility contributes to knowledge production and network formation, as well as the factors that influence mobility decisions. Existing mobility data is limited and misses information on those working in industry.
The document calls for international action to routinely collect standardized data on student placements by sector and mobility patterns of highly trained individuals and refugees to inform science
Nagaoka - Comments on Science and Innovation policy making todayinnovationoecd
1. Scientific knowledge enhances technological innovation but the flow of knowledge and its impact are poorly measured. Incomplete metrics may misguide policymaking.
2. Surveys of scientists and inventors can help understand limitations of existing indicators and provide complementary information, such as what top citations indicate, the role of information cascades, and how significantly inventors utilize scientific knowledge.
3. Collaborative mechanisms like standards setting are important for coordinating R&D and diffusion but their relationship to innovation is not well understood due to lack of data linking standards to patents. Better data collection is needed to measure innovation processes and impacts.
Salazar - Towards more inclusive science and innovations indicatorsinnovationoecd
The document summarizes a panel discussion at the OECD Blue Sky Forum III on developing more inclusive science and innovation indicators. The panelists discussed developing indicators that capture innovation in non-mainstream areas, socially excluded groups, local contexts, and developing world. They also addressed how to measure culture of innovation in a society and promote socially responsible research policies. Suggestions included defining frameworks for new metrics, establishing goals, ensuring replicability, and evaluating impact on policy and society.
Fealing - Improving indicators to inform policyinnovationoecd
The document discusses improving indicators to inform policy. It recommends establishing a framework for developing indicators, improving data quality, linking and sharing data between agencies, conducting methodological research, using existing data and establishing a chief analyst position. The main conclusion is that indicators cannot be developed without a framework to contextualize them.
This document discusses using evidence-based decision making to improve science funding and policy decisions. It recommends using administrative data to better select and monitor funded projects, following the ARPA model. It also discusses open data initiatives, changing how science funding priorities are set, and ensuring metrics actually promote desired outcomes like scientific progress rather than just measured outputs.
Borner - Modelling science technology and innovationinnovationoecd
Modeling Science, Technology, and Innovation
This document discusses modeling science, technology, and innovation (STI) using qualitative and quantitative data. STI models are developed in various domains to describe and predict the structure and dynamics of STI. Models help make assumptions explicit, describe systems, communicate systems, suggest interventions, and identify new questions. The document outlines opportunities for using big data, visual analytics, and computational models in STI decision making. It also announces a forthcoming special issue of Scientometrics on simulating STI processes and describes previous exhibits and forecasts related to modeling STI.
Heitor - What do we need to measure to foster “Knowledge as Our Common Future”?innovationoecd
This document discusses the need to rebalance science and technology (STI) indicators to better capture the intrinsic value of STI beyond just economic impacts. It notes that STI statistics have become overly focused on the instrumental economic value of innovation. The document also examines expectations for the OECD's role in STI indicators, including considering contributions from a wider variety of scientific fields, advancing understanding of knowledge production processes beyond national impacts, and characterizing professional practice-based research. It emphasizes that innovation is a collective and cumulative process requiring long-term investment in education and research.
Rafols - Towards more inclusive STI indicatorsinnovationoecd
This document discusses the need for more inclusive science, technology, and innovation (STI) indicators that better capture diverse types of research and innovation.
Current STI indicators are biased towards certain types of mainstream science and may suppress or exclude valuable creative research in other fields like agriculture. This can threaten diversity in research. Indicators are also needed that make other contributions visible, like action research or co-creation.
While STI indicators can help with decisions, they do not necessarily lead to the "right" decisions if they do not reflect the full range of social and economic functions of science. Expanding indicator data and developing new indicator types may help broaden coverage of societal problems and peripheral areas of research.
Stephan - Science and Innovation Policy-making today: Big questions begging f...innovationoecd
This document discusses two important policy questions regarding science and innovation that require more data:
1) Tracking where highly trained students are placed after their education to better understand the role of education in fostering innovation and the transfer of knowledge to firms. Existing data focuses too much on placements in academia.
2) Collecting systematic cross-country data on the mobility of scientists and engineers to improve understanding of how mobility contributes to knowledge production and network formation, as well as the factors that influence mobility decisions. Existing mobility data is limited and misses information on those working in industry.
The document calls for international action to routinely collect standardized data on student placements by sector and mobility patterns of highly trained individuals and refugees to inform science
Nagaoka - Comments on Science and Innovation policy making todayinnovationoecd
1. Scientific knowledge enhances technological innovation but the flow of knowledge and its impact are poorly measured. Incomplete metrics may misguide policymaking.
2. Surveys of scientists and inventors can help understand limitations of existing indicators and provide complementary information, such as what top citations indicate, the role of information cascades, and how significantly inventors utilize scientific knowledge.
3. Collaborative mechanisms like standards setting are important for coordinating R&D and diffusion but their relationship to innovation is not well understood due to lack of data linking standards to patents. Better data collection is needed to measure innovation processes and impacts.
Salazar - Towards more inclusive science and innovations indicatorsinnovationoecd
The document summarizes a panel discussion at the OECD Blue Sky Forum III on developing more inclusive science and innovation indicators. The panelists discussed developing indicators that capture innovation in non-mainstream areas, socially excluded groups, local contexts, and developing world. They also addressed how to measure culture of innovation in a society and promote socially responsible research policies. Suggestions included defining frameworks for new metrics, establishing goals, ensuring replicability, and evaluating impact on policy and society.
Fealing - Improving indicators to inform policyinnovationoecd
The document discusses improving indicators to inform policy. It recommends establishing a framework for developing indicators, improving data quality, linking and sharing data between agencies, conducting methodological research, using existing data and establishing a chief analyst position. The main conclusion is that indicators cannot be developed without a framework to contextualize them.
This document discusses using evidence-based decision making to improve science funding and policy decisions. It recommends using administrative data to better select and monitor funded projects, following the ARPA model. It also discusses open data initiatives, changing how science funding priorities are set, and ensuring metrics actually promote desired outcomes like scientific progress rather than just measured outputs.
Borner - Modelling science technology and innovationinnovationoecd
Modeling Science, Technology, and Innovation
This document discusses modeling science, technology, and innovation (STI) using qualitative and quantitative data. STI models are developed in various domains to describe and predict the structure and dynamics of STI. Models help make assumptions explicit, describe systems, communicate systems, suggest interventions, and identify new questions. The document outlines opportunities for using big data, visual analytics, and computational models in STI decision making. It also announces a forthcoming special issue of Scientometrics on simulating STI processes and describes previous exhibits and forecasts related to modeling STI.
Heitor - What do we need to measure to foster “Knowledge as Our Common Future”?innovationoecd
This document discusses the need to rebalance science and technology (STI) indicators to better capture the intrinsic value of STI beyond just economic impacts. It notes that STI statistics have become overly focused on the instrumental economic value of innovation. The document also examines expectations for the OECD's role in STI indicators, including considering contributions from a wider variety of scientific fields, advancing understanding of knowledge production processes beyond national impacts, and characterizing professional practice-based research. It emphasizes that innovation is a collective and cumulative process requiring long-term investment in education and research.
Rafols - Towards more inclusive STI indicatorsinnovationoecd
This document discusses the need for more inclusive science, technology, and innovation (STI) indicators that better capture diverse types of research and innovation.
Current STI indicators are biased towards certain types of mainstream science and may suppress or exclude valuable creative research in other fields like agriculture. This can threaten diversity in research. Indicators are also needed that make other contributions visible, like action research or co-creation.
While STI indicators can help with decisions, they do not necessarily lead to the "right" decisions if they do not reflect the full range of social and economic functions of science. Expanding indicator data and developing new indicator types may help broaden coverage of societal problems and peripheral areas of research.
The Labour Market Information Council (LMIC) conducted surveys of over 20,000 individuals and nearly 900 career practitioners to understand their labour market information needs and challenges. The surveys found that while most Canadians seeking career assistance have an idea of the information they need, they struggle to find available data. LMIC aims to address these challenges by making labour market data more accessible, up-to-date, trustworthy and user-friendly to better support workers, job seekers, and career practitioners.
This presentation is about how to best craft messages out of research. It highlights the importance of effective messages in the research informing policy process.
Manilla, Philippines
17-18 June, 2013
The Labour Market Information Council's (LMIC) Director of Research, Data and Analytics, Tony Bonen presented at the InfoNex Big Data & Analytics for the Public Sector Conference on October 2, 2019, in Ottawa.
Link: https://www.infonex.com/1335/index.shtml
This document provides an overview of research methodology. It begins by defining what research is, including that it is a systematic search for truth and new knowledge. It discusses different types of research such as descriptive, applied, quantitative, and qualitative research. The document outlines the overall research process from defining the problem to data collection, analysis, findings, and reporting. It also discusses developing a research problem statement, reviewing literature, and selecting a research problem. Key aspects of a good research study such as purpose, methods, analysis, findings and conclusions are highlighted.
Let’s make a deal! Empowering Small and Mid Sized Universities to Participate...Alexis Smith Macklin, PhD
This document outlines a project aimed at empowering smaller academic libraries to participate more fully in the open access movement. The project will take a human-centered design approach over three phases: looking, understanding, and making. In phase one, a community of practice was established and initial data on open access policies and budget impacts was gathered. Phase two will involve identifying stakeholders, their concerns, and data needs. The goals are to develop strategies for supporting open access and sustainable open access/transformative agreement models in phase three.
The document discusses the Labour Market Information Council's (LMIC) work in improving access to labour market information in Canada. It outlines LMIC's mandate, governance structure, strategic goals of collecting, analyzing and distributing labour market data and insights. It also summarizes some of LMIC's projects, including research on Canadians' labour market information needs, developing best practices for data quality, creating local granular data tools and exploring labour market outcomes using a new longitudinal data platform.
This document outlines a research proposal from the Statistical Science Association of Students at the University of Toronto. It proposes conducting practical research projects in interdisciplinary teams focused on statistical applications in finance and other fields. The goals are to provide research experience for students from various backgrounds and publish work. Potential topics include case studies in mathematical statistics, public health, medical statistics, mathematical finance, and quantitative statistics. Research would analyze financial topics like time series models, portfolio optimization, machine learning in forecasting, and value at risk simulation. Students require strong math/economics backgrounds but there is no pressure as with graduate theses. Faculty will verify work which may be presented to industry professionals. Public health research could involve working with the Society of Statistics Canada and
This document discusses various aspects of research, including:
1. What is research and its key characteristics such as being systematic and aimed at finding new knowledge.
2. Examples of activities that can and cannot be classified as research. Participating in a workshop would not be considered research, while systematically investigating an issue like car dashboard sounds through data collection and analysis would be.
3. The basic steps involved in the research process from defining the problem to analyzing and reporting findings.
4. Additional topics covered include the objectives, problems, and types of research. The document provides an overview of researching as a systematic process for discovering new knowledge.
This document outlines Becker College's plan to enhance predictive modeling of college enrollment. It discusses declining enrollment trends in the US and presents Becker College's goal to utilize predictive analytics to increase enrollment. The presentation covers the predictive analytics workflow, including understanding the business goals, exploring and preparing the data, building predictive models, and evaluating and deploying the models. Key aspects of Becker's student data and predictive modeling process are described. The presentation concludes with next steps and challenges to consider when using predictive analytics.
This document provides an introduction to statistics for management. It outlines the course, which will cover descriptive and inferential statistics. Statistics is defined as the science of gathering, analyzing, and interpreting data to draw conclusions. It plays an important role in decision making across many fields like business, medicine, government and everyday life. The course will examine how statistics are used in areas like accounting, economics, finance, management, and marketing. It will also explore key statistical concepts like populations, samples, parameters, and statistics. Finally, it discusses the importance of understanding data measurement and levels of data to appropriately apply statistical methods.
Data science applications can be found in many domains including business, healthcare, urban planning, and more. In business, data science is used to optimize operations and customer experiences. In healthcare, data science aims to improve efficiency, reduce readmissions, and enable earlier disease detection. For urban areas experiencing rapid growth, data science combines with urban informatics to help address challenges. Case studies show how data science is used in cancer research by leveraging large datasets and algorithms, in healthcare by Stanford and Google to advance precision medicine, in political elections through micro-targeting, and with the growing Internet of Things to analyze data from billions of connected devices.
The document discusses key performance indicator (KPI) dashboards and benchmarking for higher education institutions. It outlines the case for good communication of financial and operational data through dashboards to highlight potential problems. It describes effective dashboard principles like understanding context, perceiving and presenting data accurately and linking data to mission and strategy. Benchmarking is presented as a way to maintain viability by comparing performance to peers. Examples of common higher education KPIs and benchmarking groups are provided.
Data science applications and use cases were discussed. Examples included using data science in business for tasks like optimizing operations, healthcare to improve efficiency and care, and urban planning to address challenges in cities. Data science contrasts with other disciplines by combining technical skills from computer science, mathematics, and statistics to analyze large datasets. Case studies demonstrated data science applications in domains like cancer research using patterns in biomedical data, healthcare to power precision medicine, political campaigns using social media microtargeting, and the growing Internet of Things producing large volumes of data.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
This document discusses different methods for conducting needs assessments, including surveys, interviews, focus groups, and reviewing institutional data. It provides an overview of the types of data each method can collect and their strengths and limitations. The document also lists 12 steps for conducting a needs assessment from NOAA and provides examples of how needs assessment data from multiple sources can be triangulated to develop a more accurate understanding. Lastly, it provides several links to additional resources on needs assessments and program planning.
Analytics Goes to College: Better Schooling Through Information Technology wi...bisg
Higher education faces challenges in addressing economic and readiness problems for students from disadvantaged backgrounds. While free educational content helps, it does not solve complex readiness issues. For-profit models also struggle with serving students in remote, underserved areas. Analytics and technologies show promise in helping institutions address these "last mile" challenges through personalized, adaptive learning approaches. However, significant organizational changes and integration of disparate data sources will be required for institutions to fully leverage these tools. Open discussion is needed around ensuring insights into learning and student success remain available as public goods, not proprietary to any private vendor.
Gauging Effectiveness of Instructional GrantsLynda Milne
The document discusses two grant programs managed by a center for teaching and learning to promote excellence in student learning. It outlines the center's process for developing guidelines, requirements, and systems to evaluate the purposes, topics, activities, and outcomes of funded projects. The center analyzed grant reports and found improvements in student learning, grades, and test scores as well as lower failure rates in courses impacted by the grants.
This document discusses gathering data for developing an evidence-informed nursing school curriculum that is relevant to its context. It describes internal factors like the school's mission and resources, and external factors like demographics, health trends, and the environment. Different methods for collecting data on these contextual factors are outlined, including literature reviews, interviews, and surveys. The relationship between comprehensive data gathering and creating a curriculum responsive to its situation and evidence-based is explained.
Les offres d’emploi en ligne deviennent une ressource essentielle pour les décideurs et les chercheurs qui étudient le marché du travail. Le CIMT continue de travailler avec les données de Vicinity Jobs tirées des offres d’emploi en ligne, qui peuvent être analysées dans notre
tableau de bord des tendances de l'emploi au Canada. Notre analyse des données provenant des offres d’emploi en ligne a permis d'obtenir des informations précieuses, notamment le
récent rapport
de Suzanne Spiteri sur l'amélioration de la qualité et de l'accessibilité des offres d'emploi afin de réduire les obstacles à l'emploi pour les personnes neurodivergentes.
[4:55 p.m.] Bryan Oates
OJPs are becoming a critical resource for policy-makers and researchers who study the labour market. LMIC continues to work with Vicinity Jobs’ data on OJPs, which can be explored in our Canadian Job Trends Dashboard. Valuable insights have been gained through our analysis of OJP data, including LMIC research lead
Suzanne Spiteri’s recent report on improving the quality and accessibility of job postings to reduce employment barriers for neurodivergent people.
Decoding job postings: Improving accessibility for neurodivergent job seekers
Improving the quality and accessibility of job postings is one way to reduce employment barriers for neurodivergent people.
The Labour Market Information Council (LMIC) conducted surveys of over 20,000 individuals and nearly 900 career practitioners to understand their labour market information needs and challenges. The surveys found that while most Canadians seeking career assistance have an idea of the information they need, they struggle to find available data. LMIC aims to address these challenges by making labour market data more accessible, up-to-date, trustworthy and user-friendly to better support workers, job seekers, and career practitioners.
This presentation is about how to best craft messages out of research. It highlights the importance of effective messages in the research informing policy process.
Manilla, Philippines
17-18 June, 2013
The Labour Market Information Council's (LMIC) Director of Research, Data and Analytics, Tony Bonen presented at the InfoNex Big Data & Analytics for the Public Sector Conference on October 2, 2019, in Ottawa.
Link: https://www.infonex.com/1335/index.shtml
This document provides an overview of research methodology. It begins by defining what research is, including that it is a systematic search for truth and new knowledge. It discusses different types of research such as descriptive, applied, quantitative, and qualitative research. The document outlines the overall research process from defining the problem to data collection, analysis, findings, and reporting. It also discusses developing a research problem statement, reviewing literature, and selecting a research problem. Key aspects of a good research study such as purpose, methods, analysis, findings and conclusions are highlighted.
Let’s make a deal! Empowering Small and Mid Sized Universities to Participate...Alexis Smith Macklin, PhD
This document outlines a project aimed at empowering smaller academic libraries to participate more fully in the open access movement. The project will take a human-centered design approach over three phases: looking, understanding, and making. In phase one, a community of practice was established and initial data on open access policies and budget impacts was gathered. Phase two will involve identifying stakeholders, their concerns, and data needs. The goals are to develop strategies for supporting open access and sustainable open access/transformative agreement models in phase three.
The document discusses the Labour Market Information Council's (LMIC) work in improving access to labour market information in Canada. It outlines LMIC's mandate, governance structure, strategic goals of collecting, analyzing and distributing labour market data and insights. It also summarizes some of LMIC's projects, including research on Canadians' labour market information needs, developing best practices for data quality, creating local granular data tools and exploring labour market outcomes using a new longitudinal data platform.
This document outlines a research proposal from the Statistical Science Association of Students at the University of Toronto. It proposes conducting practical research projects in interdisciplinary teams focused on statistical applications in finance and other fields. The goals are to provide research experience for students from various backgrounds and publish work. Potential topics include case studies in mathematical statistics, public health, medical statistics, mathematical finance, and quantitative statistics. Research would analyze financial topics like time series models, portfolio optimization, machine learning in forecasting, and value at risk simulation. Students require strong math/economics backgrounds but there is no pressure as with graduate theses. Faculty will verify work which may be presented to industry professionals. Public health research could involve working with the Society of Statistics Canada and
This document discusses various aspects of research, including:
1. What is research and its key characteristics such as being systematic and aimed at finding new knowledge.
2. Examples of activities that can and cannot be classified as research. Participating in a workshop would not be considered research, while systematically investigating an issue like car dashboard sounds through data collection and analysis would be.
3. The basic steps involved in the research process from defining the problem to analyzing and reporting findings.
4. Additional topics covered include the objectives, problems, and types of research. The document provides an overview of researching as a systematic process for discovering new knowledge.
This document outlines Becker College's plan to enhance predictive modeling of college enrollment. It discusses declining enrollment trends in the US and presents Becker College's goal to utilize predictive analytics to increase enrollment. The presentation covers the predictive analytics workflow, including understanding the business goals, exploring and preparing the data, building predictive models, and evaluating and deploying the models. Key aspects of Becker's student data and predictive modeling process are described. The presentation concludes with next steps and challenges to consider when using predictive analytics.
This document provides an introduction to statistics for management. It outlines the course, which will cover descriptive and inferential statistics. Statistics is defined as the science of gathering, analyzing, and interpreting data to draw conclusions. It plays an important role in decision making across many fields like business, medicine, government and everyday life. The course will examine how statistics are used in areas like accounting, economics, finance, management, and marketing. It will also explore key statistical concepts like populations, samples, parameters, and statistics. Finally, it discusses the importance of understanding data measurement and levels of data to appropriately apply statistical methods.
Data science applications can be found in many domains including business, healthcare, urban planning, and more. In business, data science is used to optimize operations and customer experiences. In healthcare, data science aims to improve efficiency, reduce readmissions, and enable earlier disease detection. For urban areas experiencing rapid growth, data science combines with urban informatics to help address challenges. Case studies show how data science is used in cancer research by leveraging large datasets and algorithms, in healthcare by Stanford and Google to advance precision medicine, in political elections through micro-targeting, and with the growing Internet of Things to analyze data from billions of connected devices.
The document discusses key performance indicator (KPI) dashboards and benchmarking for higher education institutions. It outlines the case for good communication of financial and operational data through dashboards to highlight potential problems. It describes effective dashboard principles like understanding context, perceiving and presenting data accurately and linking data to mission and strategy. Benchmarking is presented as a way to maintain viability by comparing performance to peers. Examples of common higher education KPIs and benchmarking groups are provided.
Data science applications and use cases were discussed. Examples included using data science in business for tasks like optimizing operations, healthcare to improve efficiency and care, and urban planning to address challenges in cities. Data science contrasts with other disciplines by combining technical skills from computer science, mathematics, and statistics to analyze large datasets. Case studies demonstrated data science applications in domains like cancer research using patterns in biomedical data, healthcare to power precision medicine, political campaigns using social media microtargeting, and the growing Internet of Things producing large volumes of data.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
This document discusses different methods for conducting needs assessments, including surveys, interviews, focus groups, and reviewing institutional data. It provides an overview of the types of data each method can collect and their strengths and limitations. The document also lists 12 steps for conducting a needs assessment from NOAA and provides examples of how needs assessment data from multiple sources can be triangulated to develop a more accurate understanding. Lastly, it provides several links to additional resources on needs assessments and program planning.
Analytics Goes to College: Better Schooling Through Information Technology wi...bisg
Higher education faces challenges in addressing economic and readiness problems for students from disadvantaged backgrounds. While free educational content helps, it does not solve complex readiness issues. For-profit models also struggle with serving students in remote, underserved areas. Analytics and technologies show promise in helping institutions address these "last mile" challenges through personalized, adaptive learning approaches. However, significant organizational changes and integration of disparate data sources will be required for institutions to fully leverage these tools. Open discussion is needed around ensuring insights into learning and student success remain available as public goods, not proprietary to any private vendor.
Gauging Effectiveness of Instructional GrantsLynda Milne
The document discusses two grant programs managed by a center for teaching and learning to promote excellence in student learning. It outlines the center's process for developing guidelines, requirements, and systems to evaluate the purposes, topics, activities, and outcomes of funded projects. The center analyzed grant reports and found improvements in student learning, grades, and test scores as well as lower failure rates in courses impacted by the grants.
This document discusses gathering data for developing an evidence-informed nursing school curriculum that is relevant to its context. It describes internal factors like the school's mission and resources, and external factors like demographics, health trends, and the environment. Different methods for collecting data on these contextual factors are outlined, including literature reviews, interviews, and surveys. The relationship between comprehensive data gathering and creating a curriculum responsive to its situation and evidence-based is explained.
Similar to Toward Being a Professional Economist (20)
Les offres d’emploi en ligne deviennent une ressource essentielle pour les décideurs et les chercheurs qui étudient le marché du travail. Le CIMT continue de travailler avec les données de Vicinity Jobs tirées des offres d’emploi en ligne, qui peuvent être analysées dans notre
tableau de bord des tendances de l'emploi au Canada. Notre analyse des données provenant des offres d’emploi en ligne a permis d'obtenir des informations précieuses, notamment le
récent rapport
de Suzanne Spiteri sur l'amélioration de la qualité et de l'accessibilité des offres d'emploi afin de réduire les obstacles à l'emploi pour les personnes neurodivergentes.
[4:55 p.m.] Bryan Oates
OJPs are becoming a critical resource for policy-makers and researchers who study the labour market. LMIC continues to work with Vicinity Jobs’ data on OJPs, which can be explored in our Canadian Job Trends Dashboard. Valuable insights have been gained through our analysis of OJP data, including LMIC research lead
Suzanne Spiteri’s recent report on improving the quality and accessibility of job postings to reduce employment barriers for neurodivergent people.
Decoding job postings: Improving accessibility for neurodivergent job seekers
Improving the quality and accessibility of job postings is one way to reduce employment barriers for neurodivergent people.
Les données d’offres d’emplois en ligne d'entreprises telles que Vicinity Jobs servent de plus en plus de complément aux sources traditionnelles de données sur la demande de main-d'œuvre, telles que les enquêtes sur les postes vacants et les salaires (EPVS). Ibrahim Abuallail, candidat au Ph. D., Université d’Ottawa, a présenté la recherche relative aux biais dans les offres d’emploi en ligne et une approche proposée pour rajuster efficacement les données de ces offres d’emploi afin de compléter les données officielles existantes (telles que celles des EPVS) et d'améliorer la mesure de la demande de main-d'œuvre.
OJP data from firms like Vicinity Jobs have emerged as a complement to traditional sources of labour demand data, such as the Job Vacancy and Wages Survey (JVWS). Ibrahim Abuallail, PhD Candidate, University of Ottawa, presented research relating to bias in OJPs and a proposed approach to effectively adjust OJP data to complement existing official data (such as from the JVWS) and improve the measurement of labour demand.
Les données de Vicinity Jobs englobent plus de trois millions d'offres d'emploi en ligne pour 2023 ainsi que des milliers de compétences. La plupart des compétences apparaissent dans moins de 0,02 % des offres d'emploi, de sorte que la plupart des offres reposent sur un petit sous-ensemble de termes couramment utilisés, comme le travail en équipe.
Laura Adkins-Hackett, économiste, CIMT, et Sukriti Trehan, scientifique de données, CIMT, ont présenté leurs recherches sur les tendances relatives aux compétences répertoriées dans les offres d’emploi en ligne afin de mieux comprendre les compétences les plus en demande. Ce projet de recherche utilise l'information mutuelle spécifique et d'autres méthodes pour extraire davantage d'informations sur les compétences communes à partir des relations entre les compétences, les professions et les régions.
Vicinity Jobs’ data includes more than three million 2023 OJPs and thousands of skills. Most skills appear in less than 0.02% of job postings, so most postings rely on a small subset of commonly used terms, like teamwork.
Laura Adkins-Hackett, Economist, LMIC, and Sukriti Trehan, Data Scientist, LMIC, presented their research exploring trends in the skills listed in OJPs to develop a deeper understanding of in-demand skills. This research project uses pointwise mutual information and other methods to extract more information about common skills from the relationships between skills, occupations and regions.
Dans un marché du travail tendu, les demandeurs d'emploi acquièrent un pouvoir de négociation qui leur permet d'améliorer la qualité de leurs emplois — c'est du moins ce que l'on croit généralement.
Michael Willcox, économiste, CIMT, a présenté des résultats qui révèlent un affaiblissement de la relation entre le resserrement du marché du travail et les indicateurs de qualité de l'emploi à la suite de la pandémie. Le resserrement du marché du travail a coïncidé avec la croissance des salaires réels pour une partie seulement des travailleurs : ceux qui occupent des emplois peu rémunérés nécessitant peu d'éducation. Plusieurs facteurs — notamment la composition du marché du travail, le comportement des travailleurs et des employeurs, et les pratiques du marché du travail — ont contribué à l'absence d'avantages pour les travailleurs. Ces facteurs feront l'objet d'une étude plus approfondie dans le cadre de travaux futurs.
In a tight labour market, job-seekers gain bargaining power and leverage it into greater job quality—at least, that’s the conventional wisdom.
Michael, LMIC Economist, presented findings that reveal a weakened relationship between labour market tightness and job quality indicators following the pandemic. Labour market tightness coincided with growth in real wages for only a portion of workers: those in low-wage jobs requiring little education. Several factors—including labour market composition, worker and employer behaviour, and labour market practices—have contributed to the absence of worker benefits. These will be investigated further in future work.
Michael Willcox a fait une présentation sur le resserrement des marchés du travail et les solutions pour y faire face. Au cours de la période de questions, les membres de l’auditoire se sont montrés particulièrement intéressés par l’ampleur des investissements que les entreprises consacrent aux technologies à faible main-d’œuvre, par les différentes politiques susceptibles de remédier aux pénuries de main-d’œuvre et par le rôle de la productivité dans l’inadéquation entre les compétences et les exigences professionnelles.
Au cours de cette séance, Brittany Feor s’est penchée sur les salaires pour savoir s’ils suivent le rythme de l’inflation. Au cours de la période de questions, les membres de l’auditoire ont discuté de sujets potentiels de recherche, dont l’incidence du domaine de spécialisation (STIM et non-STIM) sur les écarts salariaux en fonction du genre et l’impact des politiques de congé parental sur la dynamique de la population active.
Dans une présentation fondée sur l’analyse et les résultats de travaux réalisés par Kashyap Arora, Anne-Lore Fraikin et Sukriti Trehan, Kashyap a décrit diverses méthodes permettant de mesurer les tendances de la demande de main-d’œuvre à partir des offres d’emploi en ligne et les résultats préliminaires de l’analyse de données recueillies par Vicinity Jobs. Au cours de la séance de questions, le public a discuté des différences entre les tendances des offres d’emploi en ligne et les postes vacants recensés par l’Enquête sur les postes vacants et les salaires (EPVS).
LMIC senior economist Brittany Feor presented on whether wages are keeping up with inflation. During the Q&A, audience members engaged in discussion about potential areas of future research, such as whether wage differences between genders could be influenced by the choice of STEM versus non-STEM fields, as well as examining the impact of parental leave policies on workforce dynamics.
In a presentation based on analysis and findings prepared by Kashyap Arora, Anne-Lore Fraikin, and Sukriti Trehan, Kashyap presented a selection of methods for assessing labour demand trends through online job postings, with preliminary results from Vicinity Jobs.
Michael Willcox presented on tight labour markets and how to plan for them at the Canadian Economics Association's 2023 conference. During the Q&A, audience members were particularly interested in exploring the extent of business investment in labour-saving technologies, examining policy options to address labour shortages, and understanding the crucial role that productivity plays in the mismatch between skills and job requirements.
Michael Willcox, LMIC economist, participated in a panel hosted by World Education Services (WES) at the 5th Metropolis Identities Summit to discuss how the employment rate of immigrant youth is lower compared to Canadian-born youth, but the gap is closing.
Tony Bonen, directeur général (intérimaire) au CIMT, a discuté les promesses et limites du moissonnage du web sur les offres d’emploi à l'atelier de travail sur les besoins non comblés en matière de main-d’œuvre bilingue du Conseil des ministres sur la francophonie canadienne
Le directeur général intérimaire Tony Bonen a été invité par l'Association canadienne des administrateurs de la législation ouvrière (ACALO) où il a parlé du resserrement du marché du travail, des pénuries de main-d'œuvre et de compétences, et de l'avenir du travail.
LMIC's acting executive director Tony Bonen was invited by the Canadian Association of Administrators of Labour Legislation (CAALL) where he spoke about labour market tightness, labour and skills shortages, and the future of work.
More from Labour Market Information Council | Conseil de l’information sur le marché du travail (20)
We recently hosted the much-anticipated Community Skill Builders Workshop during our June online meeting. This event was a culmination of six months of listening to your feedback and crafting solutions to better support your PMI journey. Here’s a look back at what happened and the exciting developments that emerged from our collaborative efforts.
A Gathering of Minds
We were thrilled to see a diverse group of attendees, including local certified PMI trainers and both new and experienced members eager to contribute their perspectives. The workshop was structured into three dynamic discussion sessions, each led by our dedicated membership advocates.
Key Takeaways and Future Directions
The insights and feedback gathered from these discussions were invaluable. Here are some of the key takeaways and the steps we are taking to address them:
• Enhanced Resource Accessibility: We are working on a new, user-friendly resource page that will make it easier for members to access training materials and real-world application guides.
• Structured Mentorship Program: Plans are underway to launch a mentorship program that will connect members with experienced professionals for guidance and support.
• Increased Networking Opportunities: Expect to see more frequent and varied networking events, both virtual and in-person, to help you build connections and foster a sense of community.
Moving Forward
We are committed to turning your feedback into actionable solutions that enhance your PMI journey. This workshop was just the beginning. By actively participating and sharing your experiences, you have helped shape the future of our Chapter’s offerings.
Thank you to everyone who attended and contributed to the success of the Community Skill Builders Workshop. Your engagement and enthusiasm are what make our Chapter strong and vibrant. Stay tuned for updates on the new initiatives and opportunities to get involved. Together, we are building a community that supports and empowers each other on our PMI journeys.
Stay connected, stay engaged, and let’s continue to grow together!
About PMI Silver Spring Chapter
We are a branch of the Project Management Institute. We offer a platform for project management professionals in Silver Spring, MD, and the DC/Baltimore metro area. Monthly meetings facilitate networking, knowledge sharing, and professional development. For more, visit pmissc.org.
I am an accomplished and driven administrative management professional with a proven track record of supporting senior executives and managing administrative teams. I am skilled in strategic planning, project management, and organizational development, and have extensive experience in improving processes, enhancing productivity, and implementing solutions to support business objectives and growth.
Joyce M Sullivan, Founder & CEO of SocMediaFin, Inc. shares her "Five Questions - The Story of You", "Reflections - What Matters to You?" and "The Three Circle Exercise" to guide those evaluating what their next move may be in their careers.
Parabolic antenna alignment system with Real-Time Angle Position FeedbackStevenPatrick17
Introduction
Parabolic antennas are a crucial component in many communication systems, including satellite communications, radio telescopes, and television broadcasting. Ensuring these antennas are properly aligned is vital for optimal performance and signal strength. A parabolic antenna alignment system, equipped with real-time angle position feedback and fault tracking, is designed to address this need. This document delves into the components, design, and implementation of such a system, highlighting its significance and applications.
Importance of Parabolic Antenna Alignment
The alignment of a parabolic antenna directly affects its performance. Even minor misalignments can lead to significant signal loss, which can degrade the quality of the received signal or cause communication failures. Proper alignment ensures that the antenna's focal point is accurately directed toward the signal source, maximizing the antenna's gain and efficiency. This precision is especially crucial in applications like satellite communications, where the antenna must track geostationary satellites with high accuracy.
Components of a Parabolic Antenna Alignment System
A parabolic antenna alignment system typically includes the following components:
Parabolic Dish: The primary reflector that collects and focuses incoming signals.
Feedhorn and Low Noise Block (LNB): Positioned at the dish's focal point to receive signals.
Stepper or Servo Motors: Adjust the azimuth (horizontal) and elevation (vertical) angles of the antenna.
Microcontroller (e.g., Arduino, Raspberry Pi): Processes sensor data and controls the motors.
Potentiometers: Provide feedback on the antenna's current angle positions.
Fault Detection Sensors: Monitor for potential faults such as cable discontinuities or LNB failures.
Control Software: Runs on the microcontroller, handling real-time processing and decision-making.
Real-Time Angle Position Feedback
Real-time feedback on the antenna's angle position is essential for maintaining precise alignment. This feedback is typically provided by potentiometers or rotary encoders, which continuously monitor the azimuth and elevation angles. The microcontroller reads this data and adjusts the motors accordingly to keep the antenna aligned with the signal source.
Fault Tracking in Antenna Alignment Systems
Fault tracking is vital for the reliability and performance of the antenna system. Common faults include cable discontinuities, LNB malfunctions, and motor failures. Sensors integrated into the system can detect these faults and either notify the user or initiate corrective actions automatically.
Design and Implementation
1. Parabolic Dish and Feedhorn
The parabolic dish is designed to reflect incoming signals to a focal point where the feedhorn and LNB are located. The dish's size and shape depend on the specific application and frequency range.
2. Motors and Position Control
Stepper motors or servo motors are used to control the azimuth and elevation of
Khushi Saini, An Intern from The Sparks Foundationkhushisaini0924
This is my first task as an Talent Acquisition(Human resources) Intern in The Sparks Foundation on Recruitment, article and posts.
I invitr everyone to look into my work and provide me a quick feedback.
LinkedIn Strategic Guidelines for June 2024Bruce Bennett
LinkedIn is a powerful tool for networking, researching, and marketing yourself to clients and employers. This session teaches strategic practices for building your LinkedIn internet presence and marketing yourself. The use of # and @ symbols is covered as well as going mobile with the LinkedIn app.
1. LABOUR MARKET INFORMATION COUNCIL
CONSEIL DE L’INFORMATION SUR LE MARCHÉ DU TRAVAIL
Carleton University
25 February 2019
Tony Bonen (tony.bonen@lmic-cimt.ca)
Director, Research, Data and Analytics
Toward being a Professional Economist
(or something else, that’s also totally fine)
2. • Me, Me, Me
• Labour economics at LMIC
• What’s LMIC doing
• What should you do? (spoiler: I don’t know)
Outline
3. My pathway
Carleton University
• BA: Political Science & Economics
• Variety of jobs
University of Kent, Brussels
• MA: International Political Economy
• Research gigs
New School for Social
Research (NSSR)
• PhD: Economics
• RA in Labour Econ, Macro
• Teaching work, etc.
Canada Mortgage and
Housing Corporation (CMHC)
• Developed forecast models for
stress testing
• Applied econometrics research
• Research on housing market drivers
Labour Market Information
Council (LMIC)
• Public-facing research
• Data work
• Teaching and leading team of
economists
data data
data
data
data
4. Things I learned along the way
• Usually better if you decide what you want to do earlier, but you have lots
of time to figure it out later too
• If you like working with data/numbers, keep at it (in school and work)
• If you like working with data/numbers, learn to write (well)
• To the extent you’re able, work while studying
• PhDs are not for everyone, but a few years of doctoral work can go a long
way (even if you don’t finish)
5. Why economics
• A bridge between technical and non-technical disciplines
• Closely connected to the world of policy and politics
• Lots of career paths available (including scaling up/down intensity
of data work)
• Labour Economics:
• Very relevant because of applied empirical work
• Exposure to lots of different data types and use cases
6. To empower Canadians
including employers, workers, job seekers, academics, policy makers,
educators, career practitioners, students, parents and under-
represented groups
with timely and reliable labour market information and insights in
an engaging way that supports their decision-making process
Mission of LMIC
https://lmic-cimt.ca/
7. Strategic goals
COLLECT ANALYZE DISTRIBUTE
Gather and improve the
availability of relevant LMI
Undertake insightful and high-
quality analyses of LMI
Provide Canadians with timely,
relevant and reliable LMI
8. Putting the Labour (economics) in LMIC
What?
Career
decisions
How LMI is
consumed
How career
decisions are
made
❶ Why?❷
Data Needs
• Type (e.g., wages)
• Structure (e.g., take-home pay
vs. annual gross salary or hourly
wages)
Best practices
• Distributing LMI (e.g., what is
best form of dissemination,
frequency, etc.)
How?❸
Qualitative research
Literature
review
International
experiences
Test 1 use case
Repeat & expand
9. LMIC as a Data Hub
Flows to
Intermediaries End Users
Job
outlooks
Current College/
University students
Industry/sector
Statistics Canada
F/P/T (admin data,
occupational
outlook, etc.)
Other, e.g. private
sources
New LMI
Other data
Salaries by
field of
study
Skills in
demand
LMIC
Intermediary:
Education/
Career choice
API
Intermediary:
Investment
decision
Restructure
data
Partnerships to
generate new
LMI
Other LMI
Sources
Other
non-LMI
Sources
10. Other things LMIC is doing
• Surveys and focus groups about different groups’ LMI needs and challenges
https://lmic-cimt.ca/public-opinion-research-project/
• Bringing clarity to LMI concepts:
• Disentangling “labour shortages”, “skills shortages”, and “skills mismatches”
• How to identify and measure skills and the challenge of measuring skills shortages
• “Work Words”: an online dictionary of labour market term
https://lmic-cimt.ca/publications/lmi-insights/
• Research with new administrative datasets: ELMLP
https://lmic-cimt.ca/projects/studentoutcomes/
12. What should you do?
• Finish your Bachelor’s
• If you want to work as an economist:
• Get ready to do a Master’s
• Challenge yourself to learn new programs (R, Python, Julia, Matlab, etc.)
• Take classes that make you write (and take the feedback seriously)
• Think about the type of environment you want to be in:
• Job security?
• Making lots of money?
• Self-directed research?
• Being part of a movement?