This document discusses interdisciplinary research and education. It defines interdisciplinarity as different specialists from two or more fields working together towards common goals. True interdisciplinarity occurs when researchers modify their approaches to better address a problem. The document discusses barriers to interdisciplinary work, including differences between disciplines in ways of knowing and working, and incentives within academic institutions that are organized by traditional departments. It recommends students seek interdisciplinary experiences, and that researchers immerse themselves in other collaborating disciplines to overcome barriers to interdisciplinary research.
These annotated slides will help you interpret an OR or RR in clinical terms. Please download these slides and view them in PowerPoint so you can view the annotations describing each slide.
This document provides definitions and examples of key concepts for estimating risk from epidemiological studies, including probability, odds, relative risk, and absolute risk. It discusses how relative risk is calculated from cohort and case-control study designs. Relative risk compares the risk of an outcome between exposed and unexposed groups to determine if exposure is associated with increased risk. The odds ratio, which estimates relative risk, is presented as the measure used to assess association in case-control studies. Examples are provided to demonstrate calculating and interpreting these risk measures.
Tests of hypothesis (Statistical testing)Rizwan S A
This document discusses hypothesis testing and how it is used in statistical analysis. It begins by explaining the origins of hypothesis testing in legal trials and how statistical hypothesis testing adapted this framework. It then outlines the six main steps in conducting a hypothesis test: 1) stating the null hypothesis, 2) stating the alternative hypothesis, 3) selecting the significance level, 4) choosing the appropriate test and calculating the test statistic, 5) determining the critical value, and 6) making a decision about whether to reject or fail to reject the null hypothesis based on the test statistic and critical value. Examples are provided for each step. The document emphasizes that hypothesis testing enables determining if study results are due to chance or a true effect but should be interpreted cautiously.
- Randomized controlled trials (RCTs) are experiments in which people are randomly allocated to different intervention groups in order to evaluate the effects of those interventions.
- RCTs help reduce bias and allow for comparisons between groups that are otherwise similar. Random allocation means each participant has an equal chance of being placed in any group.
- RCTs involve an experimental group that receives the new intervention being tested and a control group that receives an alternative treatment, no treatment, or a placebo. Comparing outcomes between the groups allows researchers to determine the efficacy of the intervention.
ODDS RATIO AND RELATIVE RISK EVALUATIONKanhu Charan
Relative risk and odds ratio are measures used to quantify the strength of association between an exposure and an outcome. Relative risk is calculated as the incidence of an outcome in an exposed group divided by the incidence in an unexposed group. It is the preferred measure for cohort studies where the number of people at risk is known. Odds ratio is calculated as the odds of exposure in those with the outcome divided by the odds of exposure in those without the outcome. It is used for case-control studies where the total number exposed is not known. Both measures can help determine if a risk factor increases, decreases, or has no effect on the risk of an outcome. The key difference is that relative risk utilizes probabilities while odds ratio uses odds.
This document provides an overview of different study designs used in health services research, including descriptive and analytical studies. Descriptive studies like case reports, case series, and cross-sectional studies aim to characterize disease occurrence. Analytical epidemiological studies like case-control and cohort studies aim to identify determinants of disease by testing hypotheses. Cohort studies follow groups over time to compare disease outcomes between those exposed and unexposed to a risk factor. Prospective cohort studies collect exposure and outcome data after the study begins, while retrospective cohort studies use existing data.
Ethics in medical sciences research may not always translate into ethical publications.
Ethical violations in conducting medical research always promote unethical scientific publications.
Published research influences other researchers and establishes credibility for individual or journal.
This document discusses the concepts of association and causation in epidemiology. It defines correlation as a measure of association between two variables, while causation requires one variable to be a suspected cause of the other. There are three types of association - spurious, indirect, and direct. Direct association can be either a one-to-one causal relationship or multifactorial causation from multiple independent factors. Six guidelines for judging causal relationships are temporal association, consistency, specificity, strength, coherence, and biological plausibility.
These annotated slides will help you interpret an OR or RR in clinical terms. Please download these slides and view them in PowerPoint so you can view the annotations describing each slide.
This document provides definitions and examples of key concepts for estimating risk from epidemiological studies, including probability, odds, relative risk, and absolute risk. It discusses how relative risk is calculated from cohort and case-control study designs. Relative risk compares the risk of an outcome between exposed and unexposed groups to determine if exposure is associated with increased risk. The odds ratio, which estimates relative risk, is presented as the measure used to assess association in case-control studies. Examples are provided to demonstrate calculating and interpreting these risk measures.
Tests of hypothesis (Statistical testing)Rizwan S A
This document discusses hypothesis testing and how it is used in statistical analysis. It begins by explaining the origins of hypothesis testing in legal trials and how statistical hypothesis testing adapted this framework. It then outlines the six main steps in conducting a hypothesis test: 1) stating the null hypothesis, 2) stating the alternative hypothesis, 3) selecting the significance level, 4) choosing the appropriate test and calculating the test statistic, 5) determining the critical value, and 6) making a decision about whether to reject or fail to reject the null hypothesis based on the test statistic and critical value. Examples are provided for each step. The document emphasizes that hypothesis testing enables determining if study results are due to chance or a true effect but should be interpreted cautiously.
- Randomized controlled trials (RCTs) are experiments in which people are randomly allocated to different intervention groups in order to evaluate the effects of those interventions.
- RCTs help reduce bias and allow for comparisons between groups that are otherwise similar. Random allocation means each participant has an equal chance of being placed in any group.
- RCTs involve an experimental group that receives the new intervention being tested and a control group that receives an alternative treatment, no treatment, or a placebo. Comparing outcomes between the groups allows researchers to determine the efficacy of the intervention.
ODDS RATIO AND RELATIVE RISK EVALUATIONKanhu Charan
Relative risk and odds ratio are measures used to quantify the strength of association between an exposure and an outcome. Relative risk is calculated as the incidence of an outcome in an exposed group divided by the incidence in an unexposed group. It is the preferred measure for cohort studies where the number of people at risk is known. Odds ratio is calculated as the odds of exposure in those with the outcome divided by the odds of exposure in those without the outcome. It is used for case-control studies where the total number exposed is not known. Both measures can help determine if a risk factor increases, decreases, or has no effect on the risk of an outcome. The key difference is that relative risk utilizes probabilities while odds ratio uses odds.
This document provides an overview of different study designs used in health services research, including descriptive and analytical studies. Descriptive studies like case reports, case series, and cross-sectional studies aim to characterize disease occurrence. Analytical epidemiological studies like case-control and cohort studies aim to identify determinants of disease by testing hypotheses. Cohort studies follow groups over time to compare disease outcomes between those exposed and unexposed to a risk factor. Prospective cohort studies collect exposure and outcome data after the study begins, while retrospective cohort studies use existing data.
Ethics in medical sciences research may not always translate into ethical publications.
Ethical violations in conducting medical research always promote unethical scientific publications.
Published research influences other researchers and establishes credibility for individual or journal.
This document discusses the concepts of association and causation in epidemiology. It defines correlation as a measure of association between two variables, while causation requires one variable to be a suspected cause of the other. There are three types of association - spurious, indirect, and direct. Direct association can be either a one-to-one causal relationship or multifactorial causation from multiple independent factors. Six guidelines for judging causal relationships are temporal association, consistency, specificity, strength, coherence, and biological plausibility.
This document summarizes a virtual workshop on thesis writing and publication organized by Lavender Literacy Club and Cape Comorin Trust in collaboration with other institutions. It discusses research metrics, which are quantitative measures used to assess scholarly research outputs and impacts. Various metrics are explained, including journal metrics like impact factor, author metrics like h-index, and alternative metrics. The importance of research profiles, publishing ethics, and increasing research visibility and impacts are also covered.
The document provides an overview of the chi-squared test and examples of its applications. It introduces the chi-squared test as a method to assess how well observed data fits expected theoretical results. Several examples are given demonstrating chi-squared tests of goodness of fit for binomial, Poisson, normal and contingency table distributions. Practice questions are also provided involving a range of chi-squared test applications.
This document provides information on chi-square tests and other statistical tests for qualitative data analysis. It discusses the chi-square test for goodness of fit and independence. It also covers Fisher's exact test and McNemar's test. Examples are provided to illustrate chi-square calculations and how to determine statistical significance based on degrees of freedom and critical values. Assumptions and criteria for applying different tests are outlined.
Introduction to meta-analysis (1612_MA_workshop)Ahmed Negida
This document provides an overview of a meta-analysis workshop. It will introduce descriptive and inferential statistics, the concept of meta-analysis, and meta-analysis software and models. The workshop covers new topics like quality effects meta-analysis, heterogeneity models, and assessment of publication bias. It explains that simply averaging study results is incorrect, and meta-analysis statistically combines studies while weighting them by size and power to provide a single pooled effect estimate. Meta-analysis has advantages like larger power but must address heterogeneity and differences between studies.
Meta analysis: Made Easy with Example from RevManGaurav Kamboj
This document provides an overview of meta-analysis, including:
1) Meta-analysis allows researchers to quantitatively combine the results of multiple studies on a topic to arrive at overall conclusions about the body of research.
2) The key steps of conducting a meta-analysis include developing a research protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, analyzing data, and addressing heterogeneity and publication bias.
3) Funnel plots and statistical tests can be used to examine potential biases like publication bias in a meta-analysis. Addressing these biases helps ensure the meta-analysis provides an accurate summary of the evidence.
students wonder exactly what health economics is. is it about money in health, more health for the same money ? about health in hospitals or health of the country.
1. Regression analysis is a statistical process for estimating relationships between variables, including linear regression, logistic regression, and other types.
2. It allows predicting a dependent or response variable's values based on the values of independent or input variables.
3. Multiple linear regression allows modeling relationships between a scalar dependent variable and two or more explanatory variables.
Patients are about to see a new doctor: artificial intelligence by EntefyEntefy
The health care industry has already seen advanced artificial intelligent systems make an impact in areas like medical diagnosis and patient care. But the long-term big-picture importance of AI in medicine may be something else entirely: a potential fix for the intractable problem of too few doctors and nurses worldwide. And as part of that, a solution to health care’s public enemy number one—paperwork.
Entefy curated a presentation based on our article about the impact of artificial intelligence in medical care. These slides provide a snapshot of how AI is at use in medical care today, the advances and limits of current AI systems, and AI’s potential in patient care. The presentation contains useful data and analysis for anyone interested in the intersection of AI and medical care.
For additional analysis and links to our background sources, read “Patients are about to see a new doctor: artificial intelligence" on our blog at https://blog.entefy.com/view/298/Patients-are-about-to-see-a-new-doctor-artificial-intelligence.
This document provides an overview of health economics. It defines health economics as the application of economic theories to the health sector. This includes analyzing the allocation of healthcare resources, the quantity and organization of health resources, and the effects of health services on individuals and society. The document also discusses key concepts in health economics like demand and supply of healthcare, economic evaluation of treatments and the healthcare system, and the role of economic information in health planning and budgeting.
The document discusses odds ratios, which are used to measure the association between an exposure and an outcome. An odds ratio is calculated by dividing the odds of an event in one group (e.g. exposed to a drug) by the odds of the event in another unexposed group. Odds ratios can be calculated in both cohort and case-control studies. While relative risk can only be calculated in cohort studies, odds ratios are commonly used to approximate relative risk in case-control studies when the outcome is rare. The document provides examples of how to calculate odds ratios from 2x2 contingency tables and interprets what different values mean.
This document summarizes the key assumptions and properties of Ordinary Least Squares (OLS) regression. OLS aims to minimize the sum of squared residuals by estimating the beta coefficients. It provides the best linear unbiased estimates if its assumptions are met. The key assumptions are: 1) the regression is linear in parameters; 2) the error term has a mean of zero; 3) the error term is uncorrelated with the independent variables; 4) there is no serial correlation or autocorrelation in the error term; 5) the error term has constant variance (homoskedasticity); and 6) there is no perfect multicollinearity among independent variables. When all assumptions are met, OLS estimates
Principal Component Analysis (PCA) is a technique used to simplify complex data sets by identifying patterns in the data and expressing it in such a way to highlight similarities and differences. It works by subtracting the mean from the data, calculating the covariance matrix, and determining the eigenvectors and eigenvalues to form a feature vector representing the data in a lower dimensional space. PCA can be used to represent image data as a one dimensional vector by stacking the pixel rows of an image and applying this analysis to multiple images.
This document discusses meta-analysis, which involves systematically combining results from multiple studies to derive conclusions about a body of research. It describes the key steps in conducting a meta-analysis, including writing a research question and protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, and analyzing data. Statistical methods for pooling results across studies using fixed and random effects models are also outlined. The document highlights strengths and limitations of meta-analysis for providing more precise estimates of treatment effects and identifying areas needing further research.
The document discusses various measures used to assess the strength and nature of associations between variables in epidemiological studies. It describes difference measures like absolute risk and ratio measures like relative risk and odds ratio. It explains how relative risk is calculated in cohort studies and how odds ratio is used as a measure of association in case-control studies. The relationship between relative risk and odds ratio is also covered.
This document provides an overview of logistic regression. It begins by defining logistic regression as a specialized form of regression used when the dependent variable is dichotomous while the independent variables can be of any type. It notes logistic regression allows prediction of discrete variables from continuous and discrete predictors without assumptions about variable distributions. The document then discusses why logistic regression is used when assumptions of other regressions like normality and equal variance are violated. It also outlines how to perform and interpret logistic regression including assessing model fit. Finally, it provides an example research question and hypotheses about predicting solar panel adoption using household income and mortgage as predictors.
Regression analysis mathematically and statistically describes the relationship between a set of independent variables and a dependent variable. This presentation describes the concept of regression and its types with suitable illustrations. This presentation also explains the regression analysis spss path and its interpretations.
This document summarizes a training on measuring association in epidemiology. It discusses key concepts like risk factors, disease determinants, and the epidemiologic triangle. It also covers study types used to identify causal associations like cross-sectional, cohort and case-control studies. Measurement tools for association are presented, including relative risk, odds ratio, and the 2x2 table. Examples are given to demonstrate calculating these statistics and interpreting their values. Finally, it lists software tools that can be used to perform epidemiological analyses.
This document discusses confidence intervals, which provide a range of values that is likely to include an unknown population parameter based on a sample statistic. It defines key concepts like confidence level, confidence limits, and factors that determine how to set the confidence interval like sample size, population variability, and precision of values. It explains how larger sample sizes and more precise measurements result in narrower confidence intervals. Applications to clinical trials are discussed, showing how sample size impacts the ability to make definitive recommendations based on trial results.
This document discusses logistic regression, including:
- Logistic regression can be used when the dependent variable is binary and predicts the probability of an event occurring.
- The logistic regression equation calculates the log odds of an event occurring based on independent variables.
- Logistic regression is commonly used in medical research when variables are a mix of categorical and continuous.
Interdisciplinary Research on the Campus.pptkrushnapadole2
This document discusses interdisciplinary research and education. It begins by defining interdisciplinarity and noting its benefits, including addressing complex problems that cut across traditional disciplines. However, interdisciplinarity also faces barriers, as disciplines have distinct ways of thinking and working that can inhibit collaboration. The document provides recommendations to support interdisciplinary work through curriculum changes, incentives for faculty collaboration, and alternative administrative structures. It highlights examples of successful interdisciplinary programs and research at other universities that RIT could learn from as it works to strengthen interdisciplinary initiatives in its own strategic plan.
The document discusses the promise and challenges of developing a unitary doctoral curriculum across information schools. While a unitary curriculum could promote coherence, reduce chaos, and establish a common identity, interdisciplinarity and the youth of the information field make consensus difficult. The Carnegie Initiative on the Doctorate explored defining goals but risked curbing autonomy. An alternative is focusing doctoral training on developing scientist-practitioners to address information problems and lead the next generation, taking an evidence-based approach.
This document summarizes a virtual workshop on thesis writing and publication organized by Lavender Literacy Club and Cape Comorin Trust in collaboration with other institutions. It discusses research metrics, which are quantitative measures used to assess scholarly research outputs and impacts. Various metrics are explained, including journal metrics like impact factor, author metrics like h-index, and alternative metrics. The importance of research profiles, publishing ethics, and increasing research visibility and impacts are also covered.
The document provides an overview of the chi-squared test and examples of its applications. It introduces the chi-squared test as a method to assess how well observed data fits expected theoretical results. Several examples are given demonstrating chi-squared tests of goodness of fit for binomial, Poisson, normal and contingency table distributions. Practice questions are also provided involving a range of chi-squared test applications.
This document provides information on chi-square tests and other statistical tests for qualitative data analysis. It discusses the chi-square test for goodness of fit and independence. It also covers Fisher's exact test and McNemar's test. Examples are provided to illustrate chi-square calculations and how to determine statistical significance based on degrees of freedom and critical values. Assumptions and criteria for applying different tests are outlined.
Introduction to meta-analysis (1612_MA_workshop)Ahmed Negida
This document provides an overview of a meta-analysis workshop. It will introduce descriptive and inferential statistics, the concept of meta-analysis, and meta-analysis software and models. The workshop covers new topics like quality effects meta-analysis, heterogeneity models, and assessment of publication bias. It explains that simply averaging study results is incorrect, and meta-analysis statistically combines studies while weighting them by size and power to provide a single pooled effect estimate. Meta-analysis has advantages like larger power but must address heterogeneity and differences between studies.
Meta analysis: Made Easy with Example from RevManGaurav Kamboj
This document provides an overview of meta-analysis, including:
1) Meta-analysis allows researchers to quantitatively combine the results of multiple studies on a topic to arrive at overall conclusions about the body of research.
2) The key steps of conducting a meta-analysis include developing a research protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, analyzing data, and addressing heterogeneity and publication bias.
3) Funnel plots and statistical tests can be used to examine potential biases like publication bias in a meta-analysis. Addressing these biases helps ensure the meta-analysis provides an accurate summary of the evidence.
students wonder exactly what health economics is. is it about money in health, more health for the same money ? about health in hospitals or health of the country.
1. Regression analysis is a statistical process for estimating relationships between variables, including linear regression, logistic regression, and other types.
2. It allows predicting a dependent or response variable's values based on the values of independent or input variables.
3. Multiple linear regression allows modeling relationships between a scalar dependent variable and two or more explanatory variables.
Patients are about to see a new doctor: artificial intelligence by EntefyEntefy
The health care industry has already seen advanced artificial intelligent systems make an impact in areas like medical diagnosis and patient care. But the long-term big-picture importance of AI in medicine may be something else entirely: a potential fix for the intractable problem of too few doctors and nurses worldwide. And as part of that, a solution to health care’s public enemy number one—paperwork.
Entefy curated a presentation based on our article about the impact of artificial intelligence in medical care. These slides provide a snapshot of how AI is at use in medical care today, the advances and limits of current AI systems, and AI’s potential in patient care. The presentation contains useful data and analysis for anyone interested in the intersection of AI and medical care.
For additional analysis and links to our background sources, read “Patients are about to see a new doctor: artificial intelligence" on our blog at https://blog.entefy.com/view/298/Patients-are-about-to-see-a-new-doctor-artificial-intelligence.
This document provides an overview of health economics. It defines health economics as the application of economic theories to the health sector. This includes analyzing the allocation of healthcare resources, the quantity and organization of health resources, and the effects of health services on individuals and society. The document also discusses key concepts in health economics like demand and supply of healthcare, economic evaluation of treatments and the healthcare system, and the role of economic information in health planning and budgeting.
The document discusses odds ratios, which are used to measure the association between an exposure and an outcome. An odds ratio is calculated by dividing the odds of an event in one group (e.g. exposed to a drug) by the odds of the event in another unexposed group. Odds ratios can be calculated in both cohort and case-control studies. While relative risk can only be calculated in cohort studies, odds ratios are commonly used to approximate relative risk in case-control studies when the outcome is rare. The document provides examples of how to calculate odds ratios from 2x2 contingency tables and interprets what different values mean.
This document summarizes the key assumptions and properties of Ordinary Least Squares (OLS) regression. OLS aims to minimize the sum of squared residuals by estimating the beta coefficients. It provides the best linear unbiased estimates if its assumptions are met. The key assumptions are: 1) the regression is linear in parameters; 2) the error term has a mean of zero; 3) the error term is uncorrelated with the independent variables; 4) there is no serial correlation or autocorrelation in the error term; 5) the error term has constant variance (homoskedasticity); and 6) there is no perfect multicollinearity among independent variables. When all assumptions are met, OLS estimates
Principal Component Analysis (PCA) is a technique used to simplify complex data sets by identifying patterns in the data and expressing it in such a way to highlight similarities and differences. It works by subtracting the mean from the data, calculating the covariance matrix, and determining the eigenvectors and eigenvalues to form a feature vector representing the data in a lower dimensional space. PCA can be used to represent image data as a one dimensional vector by stacking the pixel rows of an image and applying this analysis to multiple images.
This document discusses meta-analysis, which involves systematically combining results from multiple studies to derive conclusions about a body of research. It describes the key steps in conducting a meta-analysis, including writing a research question and protocol, performing a comprehensive literature search, selecting studies, assessing study quality, extracting data, and analyzing data. Statistical methods for pooling results across studies using fixed and random effects models are also outlined. The document highlights strengths and limitations of meta-analysis for providing more precise estimates of treatment effects and identifying areas needing further research.
The document discusses various measures used to assess the strength and nature of associations between variables in epidemiological studies. It describes difference measures like absolute risk and ratio measures like relative risk and odds ratio. It explains how relative risk is calculated in cohort studies and how odds ratio is used as a measure of association in case-control studies. The relationship between relative risk and odds ratio is also covered.
This document provides an overview of logistic regression. It begins by defining logistic regression as a specialized form of regression used when the dependent variable is dichotomous while the independent variables can be of any type. It notes logistic regression allows prediction of discrete variables from continuous and discrete predictors without assumptions about variable distributions. The document then discusses why logistic regression is used when assumptions of other regressions like normality and equal variance are violated. It also outlines how to perform and interpret logistic regression including assessing model fit. Finally, it provides an example research question and hypotheses about predicting solar panel adoption using household income and mortgage as predictors.
Regression analysis mathematically and statistically describes the relationship between a set of independent variables and a dependent variable. This presentation describes the concept of regression and its types with suitable illustrations. This presentation also explains the regression analysis spss path and its interpretations.
This document summarizes a training on measuring association in epidemiology. It discusses key concepts like risk factors, disease determinants, and the epidemiologic triangle. It also covers study types used to identify causal associations like cross-sectional, cohort and case-control studies. Measurement tools for association are presented, including relative risk, odds ratio, and the 2x2 table. Examples are given to demonstrate calculating these statistics and interpreting their values. Finally, it lists software tools that can be used to perform epidemiological analyses.
This document discusses confidence intervals, which provide a range of values that is likely to include an unknown population parameter based on a sample statistic. It defines key concepts like confidence level, confidence limits, and factors that determine how to set the confidence interval like sample size, population variability, and precision of values. It explains how larger sample sizes and more precise measurements result in narrower confidence intervals. Applications to clinical trials are discussed, showing how sample size impacts the ability to make definitive recommendations based on trial results.
This document discusses logistic regression, including:
- Logistic regression can be used when the dependent variable is binary and predicts the probability of an event occurring.
- The logistic regression equation calculates the log odds of an event occurring based on independent variables.
- Logistic regression is commonly used in medical research when variables are a mix of categorical and continuous.
Interdisciplinary Research on the Campus.pptkrushnapadole2
This document discusses interdisciplinary research and education. It begins by defining interdisciplinarity and noting its benefits, including addressing complex problems that cut across traditional disciplines. However, interdisciplinarity also faces barriers, as disciplines have distinct ways of thinking and working that can inhibit collaboration. The document provides recommendations to support interdisciplinary work through curriculum changes, incentives for faculty collaboration, and alternative administrative structures. It highlights examples of successful interdisciplinary programs and research at other universities that RIT could learn from as it works to strengthen interdisciplinary initiatives in its own strategic plan.
The document discusses the promise and challenges of developing a unitary doctoral curriculum across information schools. While a unitary curriculum could promote coherence, reduce chaos, and establish a common identity, interdisciplinarity and the youth of the information field make consensus difficult. The Carnegie Initiative on the Doctorate explored defining goals but risked curbing autonomy. An alternative is focusing doctoral training on developing scientist-practitioners to address information problems and lead the next generation, taking an evidence-based approach.
Powerpoint show developed by Terry Anderson describing design-based research in the context of a wider presentation on distance education research generally and an introduction to CIDER.
SCIENCE FRAMEWORK FOR PHILIPPINE BASIC EDUCATION.pptxCarloManguil2
This document outlines the key principles of a science curriculum framework for basic education in the Philippines. The framework is designed to guide the development of instructional materials and learning experiences to help students become scientifically literate. It covers three components: inquiry skills, scientific attitudes, and science content and connections. The content is organized around enduring understandings and essential questions within the domains of life science, physical science, and earth and space science. The framework emphasizes developing both content knowledge and process skills through relevant, applied learning experiences.
Meaning of Multidisciplinary
Examples of Multidisciplinary
Characteristics of Multidisciplinary
Skill Development in Multidisciplinary Project or Courses
Multidisciplinary as a
Approach
Course
Collaboration
Research
This course is designed to introduce both traditional and innovative approaches/strategies in teaching science for Master students engaging in the field of teaching developing a scientific literacy through learning the strategies in reading and writing as one of the component for students in learning science as they organized each thoughts in a scientific ways, communicate ideas, and share information with fidelity and clarity, to read and listen with understanding. Integration of STEM – infusing through teaching approach as a model integrating all content areas in the way that provides rich meaningful experience for students. Explore the practical implications of cognitive science for classroom assessments, motivating student effort and designing learner – centered circular units.
This document discusses the promise and challenges of developing a unitary doctoral curriculum across information schools. While a unitary curriculum could promote coherence, reduce chaos, and establish a common identity, there are also concerns. Specifically, the interdisciplinarity of information fields makes unification difficult, and individual schools may prioritize differentiation over coherence. The document also examines approaches to defining goals for doctoral programs, including constructing a prototype graduate and focusing on scientific research that improves life. A scientist-practitioner model is proposed, emphasizing evidence-based practices, application of information phenomena, and professional skills.
The document discusses transdisciplinary learning, which allows students to authentically make connections between subjects so that they can construct their own meaning and apply learning to real-world situations. It notes that a transdisciplinary approach can help develop four pillars of new education outlined by UNESCO: learning to know, to do, to live together with others, and to be. The document provides various activities and videos to illustrate transdisciplinary concepts, skills, and their alignment with the UNESCO education pillars.
Fostering creative thinking skills through education and cultureEduSkills OECD
This presentation was given by Stephan Vincent-Lancrin at the international conference “Fostering creativity in children and young people through education and culture” in Durham, United Kingdom on 4-5 September 2017.
This document provides an overview of key concepts in curriculum planning, including the three elements of curriculum - content (what), learner (who), and instructional process (how). It discusses different philosophies around the focus of curriculum, such as emphasis on the learner's interests versus subject matter. The document also covers curriculum definitions, essential questions, enduring understandings, standards, and the backwards design process of identifying desired results, determining acceptable evidence of learning, and planning instructional experiences.
A Model For Developing Interdisciplinary Research Theoretical FrameworksCynthia King
This document provides a model for developing interdisciplinary research theoretical frameworks. It defines interdisciplinary research as research that intentionally integrates insights from multiple disciplines to get a broader understanding of a topic. The key aspects of an interdisciplinary research theoretical framework are that it purposefully identifies theories across disciplines to provide guiding perspectives. Developing such a framework requires selecting relevant theories from different disciplines and integrating them rather than keeping them separate. An example framework is provided to illustrate how theories from different disciplines can be combined into a coherent whole to guide an interdisciplinary study. Critical elements for students and researchers to consider include applying the framework throughout the entire research process and relating findings back to the framework.
The Singapore Science Curriculum (Primary)David Yeng
The Singapore Science Curriculum - One of the most advanced and holistic curriculum in the world. Our SIPYP curriculum content are based on this syllabus. Once again, this shows you why knowledge of cyclic process is equally important than knowing the cycle.
On Ways of Framing Experiential LearningBrooke Bryan
This document summarizes an oral history institute at Antioch College focused on digital liberal arts and oral history scholarship. It discusses challenges around teaching vs. research, instructionist vs. collaborative teaching, and whether institutions reward the types of work they say they value. It frames the work using Boyer's scholarship models, community-based research principles, and AAC&U's high-impact practices. Attendees participated in an activity to map their projects and plans for review/promotion. The goal was to help frame work within institutional missions and review criteria.
Planning for learning in maritime educationStein Laugerud
This document summarizes key concepts in planning for learning in maritime education. It covers learning outcomes, student activities, teaching methods, and assessment. Specifically, it discusses:
1. The Norwegian Qualification Framework's learning outcomes for higher education, including knowledge, skills, and general competence.
2. Blooms Taxonomy for cognitive learning outcomes ranging from knowledge to evaluation.
3. Factors to consider when planning student activities, such as teaching styles, sociocultural learning theory, and tools/artefacts.
4. The role of technology in transforming conceptions of learning and social memory, and how this affects formal education.
The document discusses several key approaches and considerations for teaching social studies, including:
1) Constructivism and facilitating active engagement and collaboration are important for how people learn.
2) There are various orientations for why social studies is taught, such as citizenship, cultural traditions, personal development, and diversity.
3) Selecting and organizing content requires considering goals, interests, experiences, developmental levels, and curricular requirements.
4) Locating resources involves evaluating textbooks, literature, media, technology, and community sources while watching for bias.
5) Teaching approaches can range from teacher-directed to student-directed inquiry and should incorporate critical thinking and cooperative learning.
6) Assessment includes both open-
This slide is part of MOOC - Mini open online Course for educators interested in applying Scientific Dilemmas in the classroom.
URL: http://engage.exactls.com
Reflective Learning with E-Portfolios Mini-Institutedcambrid
The document discusses various models and theories of ePortfolios and reflection. It describes ePortfolio models from different universities, including ones focused on general education, leadership development, and cultural values. It also outlines theories of reflection from scholars like Dewey, Schön, and Kolb. The document raises questions about how these models and theories can inform curriculum design and the role of reflection, identities, and lifelong learning.
Similar to Interdisciplinary Research on the Campus.ppt (20)
This document discusses cheminformatics and its applications. Cheminformatics combines chemistry and computer science to store and analyze chemical data for applications like drug discovery. It encompasses designing, organizing, analyzing and visualizing chemical information. Key topics covered include molecular representations, chemical databases, similarity searching, machine learning methods, and tools for molecular docking and drug discovery.
This document discusses geographical indications (GIs), including their definition, benefits, examples, registration process, challenges, and relationship to trademarks. Some key points:
- GIs identify goods that originate from a specific geographical region and possess qualities due to that origin. Examples include Basmati rice, Darjeeling tea, and Champagne.
- Registering a GI confers legal protection and promotes the economic prosperity of producers. It can boost exports and support rural development.
- The registration process involves filing an application representing producers, publishing the application for opposition, and registering approved GIs for 10-year periods.
- Challenges include low brand value, lack of awareness, and misuse of
1. Gas chromatography is a technique used to separate components of a mixture using their volatility. It involves two phases - a stationary phase and a mobile gas phase.
2. The basic components of a gas chromatograph are an injection port, column, detector, and recorder. The sample is injected and carried by the mobile gas phase through the column where separation occurs.
3. Separation is based on the difference in partitioning behavior of analytes between the stationary and mobile phases. Components with higher partition coefficients have longer retention times.
Errors in analysis can be either determinate (systematic) or indeterminate (random). Determinate errors are caused by faults in the analytical procedure or instruments and result in consistently inaccurate results. Common sources of determinate error include faulty instrumentation, contaminated reagents, incorrect analytical methods, and analyst errors. Determinate errors can be identified by comparing results to a known standard or independent analytical method, and the source of the error must then be determined and corrected to improve accuracy.
This document provides information about green chemistry. It discusses natural processes versus chemical processes and how green chemistry aims to make chemical processes more environmentally friendly. Some key points made include:
- Green chemistry seeks to prevent pollution by designing chemical synthesis and products to be benign.
- Natural processes are more environmentally friendly than traditional chemical processes which use toxic solvents and generate hazardous wastes.
- Green chemistry principles include using safer solvents like water or ionic liquids, performing solvent-free reactions, and using renewable feedstocks and benign catalysts.
- New techniques like microwave irradiation and ultrasound can help drive chemical reactions in a more energy efficient and atom economic manner.
1. The document introduces different types of dosage forms including solid, liquid, and semi-solid forms. Solid forms include tablets, capsules, powders, and granules. Liquid forms include solutions, emulsions, suspensions, syrups and elixirs. Semi-solid forms include ointments, gels, creams and pastes.
2. Dosage forms deliver drug molecules to sites of action in the body and provide benefits like accurate dosing, protecting drugs, and masking tastes. They are classified based on route of administration, physical form, and whether they are for oral, topical, inhaled or other uses.
3. Common excipients used in dosage forms are discussed
This document discusses various classes of antibiotics including penicillins, cephalosporins, macrolides, tetracyclines, aminoglycosides, and quinolones. It describes their mechanisms of action, common uses, and potential adverse effects. Specifically, it provides details on common drugs in each class, how they work at the cellular level to kill bacteria, infections they can treat, and side effects to monitor like ototoxicity and nephrotoxicity. The document stresses the importance of obtaining cultures before treatment and monitoring patients for both therapeutic responses and unwanted reactions.
This document discusses different types of assays used in drug analysis, including chemical, immunological, microbiological, and bioassays. It provides details on various chemical assay techniques such as photometry, colorimetry, spectrophotometry, fluorimetry, flame photometry, and different types of chromatography. It also explains the principles, types, and techniques of immunoassays like ELISA, radioimmunoassay, and fluoroimmunoassay. Microbiological assays and characteristics of good assay methods are briefly covered as well.
Dr. Gurumeet C Wadhawa discusses biological assays. An assay is a procedure used to qualitatively or quantitatively assess the presence, amount, or functional activity of a target entity. There are three main types of assays: chemical, immuno, and bioassays. Bioassays involve estimating the concentration or potency of a pharmaceutical drug using animal or human subjects. While less precise than chemical assays, bioassays are more sensitive and can be used when chemical methods are not available or applicable. Bioassays are used to standardize and quantify various biological substances and products.
Dr. Gurumeet C Wadhawa discusses biocatalysts such as enzymes and microbes. Enzymes are mostly proteins that catalyze biochemical reactions in living cells and have unique three-dimensional shapes that fit reactants. They are produced commercially by isolating microbial strains that naturally produce the desired enzyme and optimizing fermentation conditions. Biocatalysts are classified into six types based on the reactions they catalyze. Important enzymes in the human body include digestive enzymes and DNA polymerases. Biocatalysts have various industrial applications in fields such as pharmaceuticals, food processing, and cosmetics.
1. The document discusses drug discovery and development, outlining the need to address unmet medical needs like new diseases as well as the costs of existing therapies.
2. It describes the historical aspects of clinical trials and regulations dating back to the 1500s, and outlines the modern drug development process including discovery, preclinical studies, and clinical trials through the various phases.
3. The drug development pathway involves discovery, preclinical development including chemistry/pharmacology and toxicology studies on animals, and clinical development including Phase I-III trials on volunteers and patients, with the goal of regulatory approval and market introduction over approximately 10-15 years.
The FDA regulates food, drugs, medical devices and other products. It oversees the drug approval process which involves preclinical testing in animals, followed by Phase I-III clinical trials in humans to test safety, efficacy and side effects. If approved, the drug can be marketed and is monitored for side effects. The document outlines the drug approval process and regulations around generic drugs, biologics, manufacturing and product changes.
This document discusses environmentally friendly synthetic strategies, specifically non-conventional methods like microwave irradiation and ultrasonication. It notes that these methods have advantages over conventional methods in being cleaner with higher yields and being more eco-friendly. The document outlines a strategy to synthesize new heterocyclic compounds by combining moieties like pyrazole, benzo-γ-pyrone, and quinoline, and studying the biological activity of the resulting products. It provides details on sonochemistry and microwave-assisted organic reactions, giving examples of reactions that can be performed using these techniques. The aims are to synthesize and characterize new heterocycles and evaluate their therapeutic potential, attempting the syntheses using both conventional and non-conventional
The document provides an overview of the pharmaceutical sector and its key business units and functions. It discusses:
1) The pharmaceutical sector can be classified into two main groups - drug discovery and manufacturing. Manufacturing is further divided into active pharmaceutical ingredients, generics, and biologics production.
2) Drug discovery is the most important process and involves significant time and costs to develop new drugs. The manufacturing areas have departments like production, quality control, quality assurance, process development, and engineering services.
3) The roles and educational qualifications required vary across the different business units and functions, but generally include degrees in fields like chemistry, pharmacy, biotechnology, engineering, and business administration. Senior roles often require a PhD
The document discusses the mevalonate and methylerythritol phosphate pathways which are used by nature to synthesize terpenoids. Terpenoids are derived from isoprene units which can be joined in head-to-tail or head-to-head fashion, resulting in hemiterpenes, monoterpenes, sesquiterpenes, diterpenes, sesterterpenes, triterpenes, and tetraterpenes. The mevalonate pathway is important for synthesizing steroids while the methylerythritol phosphate pathway may be more commonly used in most organisms. A variety of natural terpenoids derived from these pathways are then discussed, including their structures
(i) Non-classical carbocations display delocalization of sigma bonds through 3-center-2-electron bonds in bridged systems. Neighboring group participation can assist reactions by donating electrons through lone pairs, pi bonds, aromatic rings, or sigma bonds.
(ii) The pinacol-pinacolone rearrangement involves the migration of an alkyl group from one carbon to another after the loss of a leaving group from a vicinal diol. The migration is assisted by delocalization of the carbocation intermediate onto the oxygen atom.
(iii) In asymmetrical glycols, the group with greater ability for carbocation delocalization, such as phenyl, will migrate preferentially over
The document provides an overview of solid phase synthesis. It describes how solid phase synthesis involves coupling reagents to an inert solid support to perform multi-step organic synthesis. The key steps include attaching the starting material to a resin via a linker, performing sequential reactions on the bound intermediate, then cleaving the final product from the resin. The Merrifield method from 1963 pioneered this technique by automating the synthesis of peptides on an insoluble polystyrene resin, enabling efficient purification and the potential for parallel reactions.
This document provides an overview of ultrasound assisted organic synthesis (sonochemistry). It begins by defining ultrasound and discussing how it is used to promote and accelerate various organic chemical reactions. Key advantages of sonochemistry include increased reaction rates and product yields. It then discusses several examples of specific reaction types (e.g. condensation, substitution, addition) that have been improved through ultrasonic irradiation. The document also covers experimental parameters that can be optimized in sonochemical reactions as well as various applications in fields like pharmaceuticals, materials science, and environmental chemistry. In closing, it briefly introduces the concept of supercritical fluids.
Spectrophotometry involves using a spectrophotometer to measure how much light is absorbed by a sample at different wavelengths. It relies on Beer's Law, which states that absorbance is directly proportional to concentration, path length, and absorptivity. A spectrophotometer directs light from a source through a sample and measures the intensity of the transmitted light, allowing the absorbance and concentration of the sample to be determined. Spectrophotometry is used in various applications including chemistry, medicine, and environmental monitoring.
The document discusses stability studies of drug formulations. It defines stability as the ability of a drug product to remain within established specifications over time under storage and usage conditions. Stability testing is conducted to determine shelf life, recommended storage conditions, and suitability of packaging. The main types of drug degradation discussed are physical degradation (changes in appearance, solubility) and chemical degradation (hydrolysis, oxidation). Specific examples of each type of degradation are provided.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
🔥🔥🔥🔥🔥🔥🔥🔥🔥
إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
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Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
1. INTERDISCIPLINARY RESEARCH AND
EDUCATION ON THE COLLEGE CAMPUS
Dr.Gurumeet C Wadhawa
Assistant Professor ,Department of Chemistry
Rayat Shikshan Santa's Veer Wajekar Asc
College,Phunde
2. THE TALK
IDRE - What is it & Why should we want it?
Anything worth something is worth fighting
for - Why is it So Hard?
Examples Beyond RIT
Examples at RIT
Moving forward at RIT - Barriers and
Recommendations.
Summary
3. WHY?
“We are not students of some subject matter,
but students of problems. And problems may
cut right across the borders of any subject
matter of discipline”
– Karl Popper (“Conjectures and Refutations; The Growth of
Scientific Knowledge 1963)
5. WHY?
Pentland: …most disciplines have “ a static body of
knowledge, in the sense that the base is static – you
may be able to add on to it. … the main deep
problems are in some sense fixed forever”.
“Codification necessary for the formation of a
discipline tends to generate unnecessarily rigid
mindest in disciplineary learners”
“To combine difference disciplines is (often) to
reformulate the central ideas of each” and by so doing
address a different kind of problem.
6. WHY?
Grand Challenges of Engineering
http://www.engineeringchallenges.org/ - http://www.engineeringchallenges.org/
Solar energy economical
Manage nitrogen cycle
Health informatics
Prevent nuclear terror
Advance personalized learning
Provide Energy from Fusion
Provide Access to Clean Water
Engineer better medicines
Secure Cyberspace
Engineer the tools of scientific discovery
Develop carbon sequestration methods
Restore and improve urban infrastructure
Reverse-engineer the brain
Enhance virtual reality
7. INTERDISCIPLINARITY
(THE WORLD ACCORDING TO WIKI…)
• Interdisciplinarity is a type of academic
collaboration in which specialists drawn
from two or more academic disciplines work
together in pursuit of common goals.
In multidisciplinarity, researchers from two or
more disciplines work together on a common
problem, but without altering their disciplinary
approaches or developing a common conceptual
framework.
True interdisciplinarity occurs when researchers
from two or more disciplines pool their
approaches and modify them so that they are
better suited to the problem at hand.
8.
9.
10.
11. MAPS OF SCIENCE AND COLLABORATION
http://www.idr.gatech.edu/overlay.php -
http://www.idr.gatech.edu/overlay.php
Rafols, Porter, Leydesdorff
12. MAPS OF SCIENCE AND COLLABORATION
http://www.idr.gatech.edu/overlay.php -
http://www.idr.gatech.edu/overlay.php
13. MAPS OF SCIENCE AND COLLABORATION
http://www.idr.gatech.edu/overlay.php -
http://www.idr.gatech.edu/overlay.php
14. INTERDISCIPLINARITY
(THE WORLD ACCORDING TO WIKI…)
• Interdisciplinary programs arise from a conviction
that the traditional disciplines are unable or
unwilling to address an important problem.
• For example, social science disciplines such as
anthropology and sociology paid little attention to the social
analysis of technology throughout most of the twentieth
century. As a result, many social scientists with interests in
technology have joined science and technology studies
programs, which are typically staffed by scholars drawn
from numerous disciplines (including anthropology, history,
philosophy, sociology, and women's studies).
15. INTERDISCIPLINARITY
(THE WORLD ACCORDING TO WIKI…)
• Interdisciplinary programs arise from new research
developments, such as nanotechnology, which
cannot be addressed without combining the
approaches of two or more disciplines.
• Quantum information processing, which amalgamates
elements of quantum physics and computer science,
• Bioinformatics, which combines molecular biology with
computer science.
• Imaging science, amalgamates elements of engineering,
physics, mathematics, visual perception, color science,
and chemistry
• Materials Science, amgamating physics, chemistry and
engineering
16. THE VALUE OF IDR (2004) -
THE WORLD ACCORDING TO NAC
“Interdisciplinary research (IDR) can be one
of the most productive and inspiring of
human pursuits - one that provides a format
for conversations and connections that lead
to new knowledge. As a mode of discovery
and education, it has delivered much
already and promises more - a sustainable
environment, healthier and more
prosperous lives, new dis- coveries and
technologies to inspire young minds, and a
deeper understanding of our place in space
and time.”
17. IDR DRIVERS -
THE WORLD ACCORDING TO NAC
“Interdisciplinary thinking is rapidly becoming
an integral feature of research as a result of
four powerful drivers:
the inherent complexity of nature and
society
the desire to explore problems and
questions that are not confined to a single
discipline,
the need to solve societal problems,
and the power of new technologies.”
18. THE BARRIERS TO IDRE -
THE WORLD ACCORDING TO NAC
“Despite the apparent benefits of IDR,
researchers interested in pursuing it often
face daunting obstacles and disincentives.
Some of them take the form of personal
communication or “culture” barriers; others
are related to the tradition in academic
institu- tions of organizing research and
teaching activities by discipline-based
departments - a tradition that is commonly
mirrored in funding organizations,
professional societies, and journals. “
19. PERSONAL BARRIERS TO IDRE –
Dimensions of a discipline
Epistemic – way of knowing
Social – way of working
Thinking Across Perspectives and Disciplines, Miller and Mansialla Good Work Porject
Report Series Number 27 2004
Bridging Bridges Across Disciplines: Organizational and Individual Qualities of Exemplary
Interdisciplinary Work
Mansilla, Dillon, Middlebrooks, GoodWork Project, Project Zero, Harvard Graduate
School of Education
20. PERSONAL BARRIERS TO IDRE –
Epistemic – way of knowing
Disciplines have distinct analytic tools concepts
and methods
Disciplines have distinct languages and
representations (terminology and notation – e.g.,
math vs music)
Disciplines have distinct mechanisms for
demonstrating knowledge (proof, score, demo,
product, paper)
Disciplines have distinct mechanisms for
proprietariness (authorship, patents, copywrites,
open source, etc)
21. PERSONAL BARRIERS TO IDRE –
Social – Way of working
Disciplines have “bodies of disciples”
Share formative experiences
Share common culture (cooperation,
competition, etc.)
Set boundaries of acceptability
Set standards of measurement
22. PERSONAL BARRIERS TO IDRE –
“required” traits of successful IDR
Broad Ranging Curiosity
Open mindedness
Risk taking
Humility
Willingness to work hard to learn new things
(delayed gratification)
23. TAKES TIME–
Popkin “It takes time to truly build teams.
Not one or two years, it takes five years –
for people to truly start talking to and
understanding each other. And for the
methods to start melding together – the
measurements concerns, the statistics
concerns, and the theoretical concerns”
24. PERSONAL BARRIERS TO IDRE –
Modes
Collaboration
Benefits from full depth of expertise
Retains credibility in disciplines
Much overcome host of collaboration issues
Egotism, Language, Tools, Culture
Hybridization – one person learns both
disciplines
May be able to tackle more intractable problems towards profitable
outcomes
The person is the translator and common tool user
Risks superficiality and credibility loss
Energy and time needed to develop hybrids
Loss of depth over time
25. STEPS TO IDR COLLABORATION
Reason through analogies
Create compound concepts
Build Complex and Multi-causal
Explanations
Advance through Checks and Balances
Bridging the explanation action gap
Evolve with time– different approaches (and disciplines)
at different stages of the problem solving
26. INDIVIDUAL SHORTCOMINGS AND RISKS
Takes a lot of time and effort
May not get credit in home discipline
Long lead time to something to show
Tough for students from interdisciplinary
fields to get jobs in academic
27. THE GENERIC BARRIERS TO IDR
• Students - eager, but untrained
• Faculty - untrained, tenure-scared, time
limited, peer-inhibited, but natural curious
• Fields - tend to be conservative - “that’s not
physics!” “that’s not economics!”
• Administration - designed to support college
& departmental structure, discipline-centric
• Structure - Office space, teaching areas,
research labs, all arranged by discipline
• Granting Agencies - designed to support
disciplines
28. THE BARRIERS TO IDR -
WIKI RETURNS
“Due to … the barriers, interdisciplinary
research areas are strongly motivated to
become disciplines themselves. If they
succeed, they can establish their own
research funding programs and make their
own tenure and promotion decisions. In so
doing, they lower the risk of entry.
Examples of former interdisciplinary research
areas that have become disciplines include
neuroscience, biochemistry, materials science,
and biomedical engineering.
29. IDR - NAC RECOMMENDATIONS
Students S-1:
Undergraduate students should seek out
interdisciplinary experiences, such as courses at
the interfaces of traditional disciplines that
address basic research problems,
interdisciplinary courses that address societal
problems, and research experiences that span
more than one traditional discipline.
Graduate students should explore ways to
broaden their experience by gaining requisite
knowledge in one or more fields in addition to
their primary field.
30. IDR - NAC RECOMMENDATIONS
Researchers and Faculty Members
Researchers and faculty members desiring to work on
interdisciplinary research, education, and training
projects should immerse them-selves in the languages,
cultures, and knowledge of their collaborators in IDR.
31. IDR -
RECOMMENDATIONS FROM NAC
Educators
Educators should facilitate IDR by providing educational
and training opportunities for undergraduates, graduate
students, and post- doctoral scholars, such as relating
foundation courses, data gathering and analysis, and
research activities to other fields of study and to society
at large.
32. IDR -
RECOMMENDATIONS FROM NAC
Academic Institutions
Academic institutions should develop new and
strengthen existing policies and practices that
lower or remove barriers to interdisciplinary
research and scholarship...
institutions should experiment with more
innovative policies and structures to facilitate
IDR, making use of lessons learned from IDR in
industrial and national laboratories.
33. IDR -
RECOMMENDATIONS FROM NAC
Academic Institutions
Institutions should support interdisciplinary
education and training for students, postdoctoral
scholars, researchers, and faculty by providing
such mechanisms as undergraduate research
opportunities, faculty team-teaching credit, and
IDR management training.
Institutions should develop equitable and flexible
budgetary and cost-sharing policies that support
IDR.
34. IDR -
RECOMMENDATIONS FROM NAC
Academic Institutional Structure
Recruitment practices should be revised to
include recruitment across department and
college lines.
The traditional practices and norms in hiring of
faculty members and in making tenure decisions
should be revised to take into account more fully
the values inherent in IDR activities.
Continuing social science, humanities, and
information-science-based studies of the
complex social and intellectual processes that
make for successful IDR are needed.
35. IDR -
RECOMMENDATIONS FROM NAC
Academic Institutional Structure
Institutions should explore alternative administrative
structures and business models that facilitate IDR
across traditional organizational structures.
Allocations of resources from high-level
administration to inter-disciplinary units, to further
their formation and continued operation, should be
considered in addition to resource allocations of
discipline- driven departments and colleges. Such
allocations should be driven by the inherent
intellectual values of the research and by the
promise of IDR in addressing urgent societal
problems.
36. JUST A FEW EXAMPLES AT RIT
http://www.rit.edu/kgcoe/mpd/ - http://www.rit.edu/kgcoe/mpd/(eng&business)
http://www.rit.edu/cla/publicpolicy/ - http://www.rit.edu/cla/publicpolicy/(economics, history, political
science, philosophy, and sociology)
http://www.rit.edu/~mkbsma/analogy/ -
http://blackboard.lincoln.ac.uk/bbcswebdav/users/dmeyerdinkgrafe/archive/coon.html(math and poetry)
http://bioinformatics.rit.edu/index.html (biology and information technology)
http://cis.rit.edu/content/view/156/166/ (visual perception, physics, engineering, computer science,
color sci)
http://www.rit.edu/cla/ciwg/ - http://www.rit.edu/cla/ciwg/
Experience shows that the faculty, unimpeded, will
freely develop fruitful IDRE collaborations, and find
enormous value in them personally and for the
students.
37. IN THE WILD WORLD
http://www.haverford.edu/kinsc/HHMI/ -
http://www.haverford.edu/kinsc/HHMI/(incen
tives help)
http://www.ksg.harvard.edu/gea/index.html
(a project oriented approach)
http://www.evergreen.edu/ (a college
formulated around the concept)
http://biox.stanford.edu/ (doing it up right,
infrastructure, commitment, $$s)
http://research.haifa.ac.il/~emotions/
38. FUNDING WAY UP IN IDR
Private/Foundations – HHMI, Keck, etc.
Federal Government- increasing% of funds.
NSF
NIH etc.
Tendency to tag everything IDR – but are they succeeding
at a new way of knowledge creation?
39. FACT OR FICTION?
Tendency to tag everything IDR – but are they
succeeding at a new way of knowledge creation?
Tend to be organized around broad catch-all
themes (Global Climate Change)
“….most interdisciplinary research centers have a
tendency to become a nexus of loosely connected
individuals searching for intersections, as opposed to
cohesive groups tackling well-defined problems” Rhoten
40. AT RIT - IDRE IN THE STRATEGIC PLAN
RIT will provide curricula that are application
focused, practice-based and interdisciplinary
in nature
There can be, by design, a flow of ideas,
opportunities, resources, facilities, equipment,
and capabilities from the Ph.D. level into
undergraduate scholarly activity. RIT Ph.D.
programs are interdisciplinary, and so
emphasize the scholarship of integration.
41. AT RIT - STRATEGIC PLAN
Objective A1.3: Our Ph.D. programs will be few in
number, unique and interdisciplinary in focus...
Objective A6.2: RIT liberal arts and sciences
courses will become more interdisciplinary and
international in scope.
An opportunity in the development of Gen Ed
Requirements and Minors
42. RIT STRATEGIC PLAN
How should RIT move forward?
Lots of examples out there and increasing amount of
information on their successes, strengths, and
weaknesses
Internal examples do exist… and could be studied as
well.
43. LESSONS FROM THE MEDIA LAB
“One of the reasons it didn’t happen elsewhere
(outside Media lab) is if you look around at the
different programs that might be competitors they
are either one of two structures; one of the
structures has something which is a center that is
between departments…people from different
departments are part of it but essentially you’re
getting their marginal energies and not their core
energeries.
Interdisciplinary Research and Education: Preliminary Perspectives from the
MIT Medial Laboratory, Dillon, 2001 Project Zero, Harvard University, Good
Work Project Report Series Number 13.
44. LESSONS FROM THE MEDIA LAB
The second case is; some existing department
declares a part of itself to be a media center or lab, so
it’s part of computer science or arts or literature and in
that case it’s part of a department and not really
interdisciplinary. It also may get more marginal
energy than core energy.” Ken Haase Medial Lab.
“ The flow of students between research groups as
one of the most important stimulants for their own
work”
45. LESSONS FROM THE MEDIA LAB
“Nearly every Media Lab professor we spoke to
testified to the fact that Negroponte’s policy of
giving researchers the resources to do their work
and then leaving them alone contributed massively
to their creative success”
46. LESSONS FROM THE MEDIA LAB
Two Clear Issues
“”lack of bodies of experts who can judge work
that draws from specific disciplines” – lack of
critique
struggle for distinctiveness squelches
collaboration in close collaborative environment.
47. LESSONS FROM THE BEYOND
Which administrative structure to use is a
complicated question
Body of literature is appearing now with good
information.
No longer have to guess…
See e.g., also “Interdisciplinary Research: Trend or
Transition” Diana Rhoten
48. RIT WORKING GROUP
Barriers and Recommendations for Collaborative
Research at RIT, subcommittee of the RIT
Research Steering Committee
Many similar issues with developing interdisciplinary
curriculum
49. RIT BARRIERS?
• This document identifies barriers to
collaborative research at RIT and makes
recommendations for overcoming those barriers.
• Barriers Subcommittee of the RIT Research
Steering Committee. Members of this
subcommittee include: John Albertini, Stefi
Baum, Doug Merrill, and James Winebrake.
• In this report, we focus mainly on barriers to
“inter-disciplinary, collaborative research.”
50. SUMMARY IDRE AT RIT
IDRE has much to offer faculty and students
at RIT and the world at large
Must deliver value (IDRE for a purpose)
Interdisciplinary Education and Research
are joined at the hip
They reinforce and motivate each other.
Faculty and students thrive when it works
A new level of “academic freedom and student
creativity unleashed”.
It will happen naturally in a University
setting, if barriers are removed.
52. RIT SOLUTIONS
Faculty Time
extra effort needed for IDRE to flourish, accommodate and value.
Information and Socialization of Faculty
Physical intersections across colleges should go up, - faculty lounge?
Bureaucractic credit (financial model) structure
RIT’s financial model, metrics & $$s, need to reward IDRE and cross-college
collaboration, cutting across department and college boundaries.
Sponsored Research, Development, etc. are Organized by College
develop mechanisms to facilitate X-cutting opportunities
Administration Evolution-
To support IDRE through joint appointments across departments and college
To support IDRE by developing metrics and rewarding faculty, department
heads, and Deans for Interdisciplinary Research and Education
To Assure $s flow to support and encourage IDRE across department &
college lines.
53. RIT SOLUTIONS
Faculty Standards -
Expectation must value both discipline research and education & IDRE
where value earned.
Promotion schema needs to evolve to support high quality IDRE.
Just the Way We Are - We do it to ourselves…
traditional faculty loyalty to discipline and department -
Culture change…
Curriculum
curricular barriers & departmental allocation of resources impede IDRE
double majors, team-teaching, interdisciplinary minors, faculty (and
departmental) credit for interdisciplinary team teaching all encourage
IDRE.
54. RIT SOLUTIONS
Funding
dedicate RIT $$s to stimulating interdisciplinarity in research and
education in key areas.
Graduate Students
Collaborative research across colleges requires strong graduate
programs in all colleges.
Physical infrastructure
need joint space for IDRE to take hold. Shoulder to Shoulder.
Administrative Overhead
Normalize incentives X-college (where differences for faculty
exist across colleges, barriers can be created, and frustration
grow).