Presentation for the American Sociological Association's Department Affiliates Webinar Series. Discussion of using quantitative data in courses throughout the undergraduate curriculum, including why it's a good practice, how it can be done, and where one can find resources that make it easier.
Slides from Keynote presentation at the University of Southern California's 2015 Teaching with Technology annual conference.
"9:15 am – ANN Auditorium
Key Note: What Do We Mean by Learning Analytics?
Leah Macfadyen, Director for Evaluation and Learning Analytics, University of British Columbia
Executive Board, SoLAR (Society for Learning Analytics Research)
Leah Macfadyen will define and explore the emerging and interdisciplinary field of learning analytics in the context of quantified and personalized learning. Leah will use actual examples and case studies to illustrate the range of stakeholders learning analytics may serve, the diverse array of questions they may be used to address, and the potential impact of learning analytics in higher education."
Promoting Data Literacy at the Grassroots (ACRL 2015, Portland, OR)Adam Beauchamp
Presentation given at ACRL 2015, with Christine Murray, on teaching undergraduate students to discover and evaluate datasets for secondary data analysis.
Slides from Keynote presentation at the University of Southern California's 2015 Teaching with Technology annual conference.
"9:15 am – ANN Auditorium
Key Note: What Do We Mean by Learning Analytics?
Leah Macfadyen, Director for Evaluation and Learning Analytics, University of British Columbia
Executive Board, SoLAR (Society for Learning Analytics Research)
Leah Macfadyen will define and explore the emerging and interdisciplinary field of learning analytics in the context of quantified and personalized learning. Leah will use actual examples and case studies to illustrate the range of stakeholders learning analytics may serve, the diverse array of questions they may be used to address, and the potential impact of learning analytics in higher education."
Promoting Data Literacy at the Grassroots (ACRL 2015, Portland, OR)Adam Beauchamp
Presentation given at ACRL 2015, with Christine Murray, on teaching undergraduate students to discover and evaluate datasets for secondary data analysis.
This presentation describes TeachingWithData.org, a collection of resources for faculty who want to include data in their undergraduate social science courses. The presentation was given at the 2010 Annual Meeting of the American Sociological Association (Atlanta) by John Paul DeWitt (SSDAN) and Lynette Hoelter (ICPSR)
Online Data Analysis for Librarians using SDA and the General Social SurveyCelia Emmelhainz
This presentation overviews the difference between raw and aggregate data, when tables are useful vs. running an analysis of microdata, and how librarians could analyze data from the General Social Survey (GSS) via the SDA (survey documentation and analysis) interface. For a presentation at Maine Academic Libraries Day, 2015.
Quantitative Literacy: Don't be afraid of data (in the classroom)!ICPSR
This presentation was conducted at the International Conference on College Teaching and Learning, April 11, 2012. It contains several links to interesting data and statistics, not too complex, that can easily be introduced for discussion in the classroom.
Developing a multiple-document-processing performance assessment for epistem...Simon Knight
http://oro.open.ac.uk/41711/
The LAK15 theme “shifts the focus from data to impact”, noting the potential for Learning Analytics based on existing technologies to have scalable impact on learning for people of all ages. For such demand and potential in scalability to be met the challenges of addressing higher-order thinking skills should be addressed. This paper discuses one such approach – the creation of an analytic and task model to probe epistemic cognition in complex literacy tasks. The research uses existing technologies in novel ways to build a conceptually grounded model of trace-indicators for epistemic-commitments in information seeking behaviors. We argue that such an evidence centered approach is fundamental to realizing the potential of analytics, which should maintain a strong association with learning theory.
Learning Analytics: Seeking new insights from educational dataAndrew Deacon
CPUT Fundani TWT - 22 May 2014
Analytics is a buzzword that encompasses the analysis and visualisation of big data. Current interest results from the growing access to data and the many software tools now available to analyse this data in Higher Education, through platforms such as Learning Management Systems. This seminar provides an overview of current applications and uses of learning analytics and how it can help institutions of learning better support their learners. The illustrative examples look at institutional and social media data that together provide rich insights into institutional, teaching and learning issues. A few simple ways to perform such analytics in a context of Higher Education will be introduced.
Dr Linda Corrin, University of Melbourne, discusses all things learning analytics. One of the important take-aways from this presentation is to define the question(s) before you start collecting data.
Data in The Classroom: It's Not Just for Nerds Anymore!ICPSR
These slides provide resources for real, interactive, and fun data faculty can bring into the classroom for great discussions and paper assignments designed to get students thinking critically. You don't need to be a numbers guru to do it! These slides also emphasize the value of data and numbers to students in getting great jobs and in understanding the world around them.
Instructional Data Sets from Q-step Launch Event (Univ of Exeter) 3-20-2014ICPSR
Presentation about using social science data in the classroom and creating (and finding) resources with which to do it. Addresses both substantive courses and research methods/statistics courses.
This presentation describes TeachingWithData.org, a collection of resources for faculty who want to include data in their undergraduate social science courses. The presentation was given at the 2010 Annual Meeting of the American Sociological Association (Atlanta) by John Paul DeWitt (SSDAN) and Lynette Hoelter (ICPSR)
Online Data Analysis for Librarians using SDA and the General Social SurveyCelia Emmelhainz
This presentation overviews the difference between raw and aggregate data, when tables are useful vs. running an analysis of microdata, and how librarians could analyze data from the General Social Survey (GSS) via the SDA (survey documentation and analysis) interface. For a presentation at Maine Academic Libraries Day, 2015.
Quantitative Literacy: Don't be afraid of data (in the classroom)!ICPSR
This presentation was conducted at the International Conference on College Teaching and Learning, April 11, 2012. It contains several links to interesting data and statistics, not too complex, that can easily be introduced for discussion in the classroom.
Developing a multiple-document-processing performance assessment for epistem...Simon Knight
http://oro.open.ac.uk/41711/
The LAK15 theme “shifts the focus from data to impact”, noting the potential for Learning Analytics based on existing technologies to have scalable impact on learning for people of all ages. For such demand and potential in scalability to be met the challenges of addressing higher-order thinking skills should be addressed. This paper discuses one such approach – the creation of an analytic and task model to probe epistemic cognition in complex literacy tasks. The research uses existing technologies in novel ways to build a conceptually grounded model of trace-indicators for epistemic-commitments in information seeking behaviors. We argue that such an evidence centered approach is fundamental to realizing the potential of analytics, which should maintain a strong association with learning theory.
Learning Analytics: Seeking new insights from educational dataAndrew Deacon
CPUT Fundani TWT - 22 May 2014
Analytics is a buzzword that encompasses the analysis and visualisation of big data. Current interest results from the growing access to data and the many software tools now available to analyse this data in Higher Education, through platforms such as Learning Management Systems. This seminar provides an overview of current applications and uses of learning analytics and how it can help institutions of learning better support their learners. The illustrative examples look at institutional and social media data that together provide rich insights into institutional, teaching and learning issues. A few simple ways to perform such analytics in a context of Higher Education will be introduced.
Dr Linda Corrin, University of Melbourne, discusses all things learning analytics. One of the important take-aways from this presentation is to define the question(s) before you start collecting data.
Data in The Classroom: It's Not Just for Nerds Anymore!ICPSR
These slides provide resources for real, interactive, and fun data faculty can bring into the classroom for great discussions and paper assignments designed to get students thinking critically. You don't need to be a numbers guru to do it! These slides also emphasize the value of data and numbers to students in getting great jobs and in understanding the world around them.
Instructional Data Sets from Q-step Launch Event (Univ of Exeter) 3-20-2014ICPSR
Presentation about using social science data in the classroom and creating (and finding) resources with which to do it. Addresses both substantive courses and research methods/statistics courses.
Data in the HS Classroom: When, Why, and How?ICPSR
Presentation given as part of the High School Teachers of Sociology Workshop at the American Sociological Association Annual Meeting, 2012 (Denver, CO).
Presentation given at SCONUL 2014, the summer conference of The Society of College, National and University Libraries, Glasgow, June 2014. The presentation focuses on frequently asked questions (FAQs) about learning analytics, with the emphasis on the role and perspective of libraries in this area.
Australian university teacher’s engagement with learning analytics: Still ea...Blackboard APAC
This session reports the results of a recent OLT-funded national exploratory study addressing the relevant factors and their impact when implementing learning analytics for student retention purposes. The project utilised a mixed-method research design and yielded a series of outputs, including the development of a non-technical overview of learning analytics, focusing on linking the fields of student retention and learning analytics resulting in an institution level survey focusing on sector readiness and decision making relating to utilising learning analytics for retention purposes. An academic level survey was administered to academic staff exploring their progress, aspirations and support needs relating to learning analytics. Follow-up interviews expanded on their experiences with learning analytics to date. An evidence-based framework was developed, mapping important factors affecting learning analytics decision making and implementation. This was illustrated by a suite of five case studies developed by each of the research partner institutions detailing their experiences with learning analytics and demonstrating why elements in the framework are important. These findings were shared and tested at a National Forum in April 2015.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Presentation given at the HEA Social Sciences learning and teaching summit 'Exploring the implications of ‘the era of big data’ for learning and teaching'.
A blog post outlining the issues discussed at the summit is available via: http://bit.ly/1lCBUIB
Data Driven Teaching: Using Data to Inform Teaching. Practical Tips and Examples from Faculty and Grads of The University of Texas of Arlington.
TA New Teacher Webinar Series 2015-2016 Launches Saturday, September 12!
The University of Texas at Arlington's "New Teacher Webinar Series" for 2015-2016 Launches on 9/12/15! Join us on Saturday, September 12 at 1:00 pm (CST) for the UTA New Teacher Webinar on"Data-Driven Teaching" All are welcome! Click here for more details: https://www.smore.com/wb17y Link to join the webinar: https://elearn.uta.edu/webapps/bb-collaborate-bb_bb60/launchSession/guest?uid=80eb975c-0d1b-4e13-8cf1-99fcc8fdac73 The recording will be posted on our YouTube channel: https://www.youtube.com/user/UTANewTeachers and slideshare channel: http://www.slideshare.net/UTANewTeachers
We hope you can attend! Please share this info with anyone else who might be interested. Contact Dr. Peggy Semingson with any questions at: peggys@uta.edu
*Cut and paste any links above, if needed, into your browser window.
Pinterest: https://www.pinterest.com/UTANewTeachers/
Facebook: https://www.facebook.com/UTANewTeacherProject
YouTube: https://www.youtube.com/user/UTANewTeachers
slideshare: http://www.slideshare.net/UTANewTeachers
Future webinars:
Sept 12 (Topic: Data-Driven Assessment)
October 10 (Topic: Using EdModo in the Classroom)
Working with Social Media Data: Ethics & good practice around collecting, usi...Nicola Osborne
Slides from a workshop delivered for the University of Edinburgh Digital Scholarship programme, on 18th October 2017. For further information on the programme see: http://www.digital.cahss.ed.ac.uk/ or #DigScholEd. If you are interested in hosting a similar workshop, or adapting these slides please contact me: nicola.osborne@ed.ac.uk.
Learning Analytics – Ethical questions and dilemmasTore Hoel
Workshop presentation using the Potter Box model of ethical reasoning to discuss concerns and dilemmas of Learning analytics - Open Discovery Space and Learning Analytics Community Exchange projects #laceproject #ods_eu
Data Sharing with ICPSR: Fueling the Cycle of Science through Discovery, Acce...ICPSR
Data Sharing with ICPSR was presented at IASSIST 2015 in Minneapolis, MN.
The learning objectives and content cover:
- Federal data sharing requirements and
other good reasons to share data
• Options for sharing data
• Protection of confidentiality when
sharing data
• Data discovery tools
• Online data exploration tools from ICPSR
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
This is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
Understanding ICPSR - An Orientation and Tours of ICPSR Data Services and Edu...ICPSR
This is ICPSR's core workshop deck designed to introduce, remind, and refresh your knowledge of ICPSR. It contains four "tours" or sub-presentations describing ICPSR's general reason for being, it's social and behavioral research data complete with search strategies, its training, educational, and instructional resources, and its data management and curation services, data repository options, and support resources (content and budget estimates) for those writing grant proposals.
Agencies such as the NSF and NIH require data management plans as part of research proposals and the Office of Science and Technology Policy (OSTP) is requiring federal agencies to develop plans to increase public access to results of federally funded scientific research. These slides explore sustainable data sharing models, including models for sharing restricted-use data. Demos of these models and tips for accessing public data access services are provided as well as resources for creating data management plans for grant applications.
This slide deck provides an overview and resources to respond to the OSTP memo with the subject: Increasing Access to the Results of Federally Funded Scientific Research issued by John P. Holdren in February 2013. It provides resources and information agencies, foundations, and research projects can use to assemble achieve public access to scientific data in digital formats.
A review of ICPSR's 50 year history as a research data archive and an overview of the data services it currently offers as well as data services in development
This is Part III of a workshop presented by ICPSR at IASSIST 2011. This section focuses on data management including data management plans, secure computing environments, and restricted data contract management.
Spice up your lecture with Inquiry-based LearningICPSR
This presentation is a part of ICPSR's monthly Webinar series. It describes inquiry-based learning and how using data in the college classroom can help foster deeper learning. TeachingWithData.org, a repository of social science materials, was introduced.
Many federal funding agencies, including NIH and most recently NSF, are requiring that grant applications contain data management plans for projects involving data collection. To support researchers in meeting this requirement, ICPSR is providing a set of tools and resources for creating data management plans. This presentation will covers:
• ICPSR’s Data Management Plan Website
• Suggested Elements of a Data Management Plan
• Example Data Management Plan Language
• Designating ICPSR as an Archive in a Data Management Plan
• Additional Resources for a Preparing Your Data Management Plan
Presented by Amy Pienta, Research Scientist, University of Michigan
ICPSR: Resources for Use in Undergraduate InstructionICPSR
This presentation was given at an ICPSR Lunch and Learn on 2-24-2010. Resources that can be used in undergraduate social science education were discussed and the slides/notes should contain enough information that they can be used by others to promote these resources.
Using Quantitative Data in Teaching: ICPSR ResourcesICPSR
These slides are from a presentation given at the 2010 American Association of Behavioral and Social Sciences meetings (Las Vegas, NV). It is an introduction to how and why instructors might want to use real data in their undergraduate social science courses and what resources ICPSR provides to assist them in doing so.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...
Asa integrating data 2 19-2014 with cites
1. Integrating Data Analysis into the
Undergraduate Curriculum
(aka Making Sociology Real)
American Sociological Association
Webinar
January 19, 2014
Lynette Hoelter
lhoelter@umich.edu
3. A Quick Poll
What is the average class size for your
department?
A.
B.
C.
D.
Small – under 25 students
Medium – 25 to 50 students
Large – 51 to 100 students
Massive – over 100 students
4. Which statement best describes your
relationship to quantitative data?
A. I try to keep my distance from data as much as
possible (not very comfortable).
B. We have a civil relationship, but you wouldn’t likely
catch us hanging out at the coffee shop (somewhat
comfortable).
C. Data and I are the best of friends (very comfortable).
D. I wake up in the morning excited about data and all
the cool ways I can manipulate, I mean use, it that
day (extremely comfortable).
5. Thinking about the students in your
classes, would you say they…
A.
B.
C.
D.
E.
panic at the sight of a number across the street (not at all
comfortable)
can tolerate numbers about the same way they tolerate Brussels
sprouts (not very comfortable)
are willing to put their toes in the data pool and maybe even go
into the water (somewhat comfortable)
have caught the “data bug” and spend your class period dreaming
about new questions to answer with data (very comfortable)
will be the next Pearson or Tukey developing new statistical tests
(extremely comfortable)
6. Taking a step back: What do we mean by “data”?
• Definitions differ by context, all are valuable for sociology.
For example:
– Newspaper articles, blogs, Twitter feeds, commercials
– Transcripts of an in-depth interview or observation notes
– Information from medical tests, experiments, and other scientific
exercises
• For this presentation, “data” refers to summary information
presented numerically in graphs, charts, or tables and the
underlying survey results or administrative records.
– Some of the suggestions here also take advantage of “metadata”
or data about the data.
7. Why use data throughout the curriculum?
• Applies sociology to “real life”
• Builds quantitative literacy in a non-threatening
context
• Active learning makes content more memorable
• Repeated practice with quantitative information
builds confidence and deeper learning;
knowledge/skill transfer between courses
• Demonstrates how social scientists work
8. Quantitative Literacy
• Skills learned and used within a context
– Reading and interpreting tables or graphs and to
calculating percentages and the like
– Working within a scientific model (variables,
hypotheses, etc.)
– Understanding and critically evaluating numbers
presented in everyday lives
– Evaluating arguments based on data
– Knowing what kinds of data might be useful in
answering particular questions
9. Importance of QL
• Availability of information requires ability to make sense
of information coming from multiple sources
• Use of evidence is critical in making decisions and
evaluating arguments: e.g., risks related to disease or
treatment, political behaviors, financial matters,
costs/benefits of buying a hybrid
• Understanding information is prerequisite for fully
participating in a democratic society
• Employers value these skills!!
10. “…practices are clearly seen by employers as having potential for improving the
quality of college learning. . . . The top practice they endorse is research.
Employers believe that students who are challenged to ‘develop research
questions in their fields’ and who can conduct “evidence-based analysis’ will be
well positioned to succeed in the workplace.” (AAC&U 2013:10)
Skills most highly valued include: critical thinking, communicate clearly, and
complex problem solving..
11. When to Include Data
ALL the time!!!!! Don’t save it for methods/stats
classes…
12. No Need to “Revamp” Entire Course
• Make course/learning objectives clear to students
– One or more of these objectives can relate to quantitative
data:
• Provide a context in which students can improve their writing,
speaking, and critical thinking abilities.
• Students will learn to create and interpret a crosstabulation
table.
• Students will gain an understanding of the application of the
scientific method to the study of social behavior, including the
use of evidence to test hypotheses.
• Cover the same substantive content, drop in data-based
experiences as appropriate
13. Example: Begin Class with Data
• Rather than jumping directly into lecture, provide
a “daily fact.”
– Present a statistic, graph, or chart from recent news
media and ask students to interpret what it says and
whether it is accurately portrayed in the media.
– All can be accomplished in about 5 minutes and serves
to get students’ focus shifted from whatever happened
just before class.
– Students will often begin bringing in items of their
own.
14. • Does the
chart/graph/map
accurately describe the
data?
• From where do the data
come?
• What point does the
author make?
• Is it valid?
Source:
www.nbcolympics.com/medals
16. Other ideas for including data:
• Require empirical evidence to support claims in essays
• Use data with online analysis tools for simple analysis
assignments
• Question banks and exercises allow students to work with
surveys and the resulting data
• Have students collect data – even in-class polls!
• Engage students by having them find maps, graphs, or
other data that provide examples of course content
Any others??
Any questions so far??
17. Using Data without Using Data
• How does religion relate to health behaviors?
There’s a quiz for that!
18. How can I operationalize “life satisfaction”? How satisfied
are people overall? (Depends whom you ask!)
23. Public Opinion Data
• Roper Center for Public Opinion Research
www.ropercenter.uconn.edu
• Gallup: www.gallup.com
• NORC reports & data:
www.norc.org/Research/DataFindings
• Pew Research Center:
www.pewresearch.org
– Fact Tank, Reports, Datasets,
Interactives
24. Quantitative News Blogs
• TeachingWithData.org – Data in
the News
• U.S. Census Newsroom
• Data360
• The Economist: Graphic Detail Blog
• Pew Research Center: Fact Tank
• USA Today Snapshots
• FiveThirtyEight (Nate Silver)
• FloatingSheep.org
From Data360
25. Collections of Resources
• ASA TRAILS
• Association of Religion Data Archives Learning Center
• ICPSR: Resources for Instructors
– Data-driven Learning Guides (Short Exercises)
• Science Education Resource Center (Carleton College –
pedagogical materials)
• Social Science Data Analysis Network
• TeachingWithData.org
26. Data can be FUN!
Detecting funky data
displays can be even more
fun!
27. Sites for “Brushing Up” on Statistics
• Consortium for Advancement of Undergraduate
Statistical Education (CAUSE)
• Khan Academy Probability and Statistics
• Statistics Learning Centre
• UCLA Institute for Digital Research and Education:
Data Analysis Examples
• UK Data Services Support/How to Guides
• Understanding Statistics through Dance found on
the British Psychological Society’s YouTube
Channel
28. Some helpful citations…
• Ganter, S. L. 2006. Issues, Politics, and Activities in the Movement for
Quantitative Literacy. Pp. 11-15 in Current Practices in Quantitative
Literacy, R. Gillman (ed). Washington, DC: Math Assoc of America.
• Grawe, Nathan D. and Rutz, Carol A. (2009). Integration with Writing
Programs: A Strategy for Quantitative Reasoning Program
Development. Numeracy: Vol. 2: Iss. 2, Article 2. DOI:
http://dx.doi.org/10.5038/1936-4660.2.2.2
• Schield, Milo. (2010) Assessing Statistical Literacy: Take CARE. Ch 11
in Assessment Methods in Statistical Education, pp. 133-152. Wiley.
• Steen, Lynn Arthur. 2004. Everything I Needed to Know about
Averages I Learned in College. Peer Review 6(4): 4-8.
• Wiest, Lynda R., Heidi J. Higgins, and Janet Hart Frost. 2007.
Quantitative Literacy for Social Justice. Equity & Excellence in
Education 40(1): 47-55.
“‘Statistical literacy, quantitative literacy, numeracy – under the hood, it is what do we want people to be able to do: Read tables and graphs and understand English statements that have numbers in them. That’s a good start,’ said Milo Schield, a professor of statistics at Augsburg College and a vice president of the National Numeracy Network. Shield was dismayed to find that, in a survey of his new students, 44 percent could not read a simple 100 percent row table and about a quarter could not accurately interpret a scatter plot of adult heights and weights.”Chandler, Michael Alison. What is Quantitative Literacy?, Washington Post, Feb. 5, 2009Critical for a democratic society (Steen 2001)Informed citizenry – must be able to make sense of information coming from multiple sources.Use of evidence in making decisions and evaluating arguments.
Students get information from everywhere from “traditional” sources to blog posts to tweets, etc. Using data within the QL context introduces students to the need to ask questions about the conclusions they hear or read and the data upon which those conclusions are based. Understanding where data come from and thinking about credibility of the source(s) is critical to using the evidence from those data in making informed decisions.
Quiz is on the Association of Religion Data Archives’ Website and accompanies a brief story describing health-related findings from a couple of different studies.
I’ve tried to organize the sources in the following slides into these categories (roughly)… Additionally, each resource is hyperlinked out to the actual site. The pie chart and table on the slide come from the Association of Religion Data Archives (www.TheARDA.com) –one wouldn’t expect to find information about belief in extraterrestrials on a religion site, but it (and lots of other interesting topics – there is a quiz about spirituality and pets, etc.) is there.
The first three sites are useful for pulling graphic displays of data or letting students create maps interactively. Storytellingwithdata.com is more for professional development in that it talks about things like how to animate data from an Excel sheet into a Powerpoint presentation and other types of data display, in case instructors find data they want to use in a graphical form.Some parts of Social Explorer require a membership, but there is quite a bit you can get to for free. CensusScope is based on Census and American Community Survey data and shows maps/graphs based on small subsets of variables.
GapMinder is great for demonstrating global changes over time in things like population size and wealth distribution. Survival curve is an interactive exercise that shows the chance of death before one’s next birthday based on a variety of demographic characteristics. It’s good for the lecture on demography in Intro courses or for demography seminars. $1 Trillion Video is a short (1:17) video in which large numbers are made “tangible” by showing the differences in stacks of money from $100 to $1 trillion. It is good when talking current events, health policy, or inequality (rather than just a way of thinking of numerical scale in general).
Worldometers and USA Right Now are fun sites that give facts related to government, demography, and things related to social environment and culture, broadly defined. They are a great way to get students to start thinking about the world around them “by the numbers” and also serves to give them context for large numbers. Population Pyramids is a good site for teaching international demography or demographic trends. FactFinder is most helpful for finding information at the nation, state, and sometimes county or city level. An easy exercise would be to give students the results for the U.S. overall and have them look up something more personal (city, state) to compare. I think this new FactFinder site is more “user friendly” than the previous version – much more conducive to instructors quickly grabbing a number, table, or map for a lesson.
These sites are all good for getting information related to current events or political issues. Roper Center has some materials that are freely available, but some portions of their site require a membership. They are the “go to” place for things like ABC/CBS/Washington Post news polls – they get them much more quickly than ICPSR does, for example. The Pew site is fantastic – there is information in a variety of forms from “quick facts” to longer reports (good for professional development or for use as evidence in student papers) to actual data to analyze. Their topic coverage is very broad as well…
TeachingWithData.org’s Data in the News feature is updated with approximately 2-3 new stories per week and those stories are pulled from sites and reports that are credible (e.g., not from sources with a particular political bent) and occasionally there is an example of data being used so badly that we just can’t leave it alone. If we post about something like that, though, we always say why one should be leery of the presentation, what questions should be asked, etc. Data360 includes all kinds of fun things as well as the more typical data-based reports. For example, there is a map of the US that shows the use of the words “pop,” “soda,” and “Coke” by region… a great introduction to cultural influences (i.e., is it a surprise that “Coke” is the word most used in the southeast when Coke’s headquarters are in Atlanta?). This screen shot shows the wealth distribution for a variety of countries. Graphic Detail is globally focused, the stories center around economic issues and their antecedents/consequences. Even though most have an economic bent, many stories are applicable for sociology as well – recently, for example, there was a story about international marriage and divorce rates (2/14) and how Lego has gone from a tiny company to the second-largest toymaker in the world, largely by embracing cultural trends (2/13).FiveThirtyEight (from About the Blog): FiveThirtyEight’s mission is to help New York Times readers cut through the clutter of an increasingly data-rich world. The blog, founded by Nate Silver in 2008, is devoted to rigorous, data-driven analysis of politics, polling, public affairs, sports, economics, science and culture. FiveThirtyEight also offers forecasts of upcoming presidential, congressional and gubernatorial elections, using proprietary statistical models.FloatingSheep.org – by geographers. Maps of all kinds of things including “Beer Belly of America,” “Church, bowling, guns, and strip clubs,” and “Domain names by geography.” Seems to be updated a little less frequently than the other blogs.
Each of these has a variety of resources, including lesson plans and/or pre-made exercises using data. ASA’s Trails requires an annual subscription and contains all kinds of helpful materials, data-based and otherwise.ARDA has a great collection of learning activities that include “compare yourself” quizzes, map-based activities, and other activities based on the religion surveys they archive.ICPSR’s Data-Driven Learning Guides are self-contained exercises on a variety of topics ranging from attitudes about the environment to family relationships, to political behaviors in China. SERC is aimed primarily at university faculty, primarily for professional development but also includes example exercises with extensive data about the context of their use. SSDAN is the umbrella for a number of sites including CensusScope and DataCounts! – all are based on Census data including the American Community Survey.
The Statistics Learning Centre is definitely geared toward students, but can be an entertaining way to brush up on some of the basic (and not-so-basic) concepts and analysis techniques.This is by no means an exhaustive list – these are just some examples I have collected and/or others told me were useful.
As is the case when trying to add something “after the fact,” I can’t remember exactly what studies I mentioned in the live Webinar. These articles are ones I tend to use pretty regularly, so I’m hoping this will help whomever wanted the citations. This is definitely not an exhaustive list – if anyone wants more, please contact me individually.