assessing internet resources in statistics education
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Assessing Internet Resources
in Statistics Education
Ginger Holmes RowellMiddle Tennessee State University
September 11, 2007
• A Great Source of Statistics Education Learning Resources– interactive applets,
videos, tutorials, lesson plans, case studies, engaging learning activities, …
InternetInternet
Issues with Internet-basedIssues with Internet-basedInstructional TechnologiesInstructional Technologies
• Amount of information on the Internet can be overwhelming. Now what was
that URL???
• Limited time for• Finding & evaluating
• Selecting & assessing
Assessing - TechnologyAssessing - Technology
As teachers, we are accustomed to assessing student learning.
Assessing - TechnologyAssessing - Technology
Is that different from assessing technology-based learning resources?
OverviewOverview
• A General Approach for Assessing Instructional Technologies– Triadic Assessment
• Example of Existing Assessments– Digital Libraries– MERLOT/CAUSEweb Peer Review
Criteria
• Other Resources/Examples
Internet-Based Instructional Technologies:Internet-Based Instructional Technologies: Large Statistics Projects Large Statistics Projects
Rice Virtual Lab in Statistics
http://onlinestatbook.com/rvls.html
http://illuminations.nctm.org
http://www.math.uah.edu/stat/
Virtual Laboratories in Probability and Statistics
http://www.cvgs.k12.va.us/DIGSTATS/
General Assessment: General Assessment: Instructional TechnologiesInstructional Technologies
• The TLT Group, Teaching, Learning, and Technology
http://www.tltgroup.org/flashlightP.htm
http://www.tltgroup.org/
• Flashlight Program: For the Study and Improvement of Educational Uses of Technology
Technology AssessmentTechnology Assessment
• Monad Approach
• Dyadic Approach
• Triadic Approach
OutcomeActivityTechnology
Flashlight Project, The TLT Group, Gilbert
Assessing TechnologyAssessing TechnologyAn Example An Example
Select Technology
Select Activity
Desired Outcome
Recognize convergence of empirical distribution to theoretical function. Visualize shape of binomial distribution for different values of n and p.
Simulate a binomial experiment 10, 100 & 1000 times.Vary n and p.
10 Simulations – Low Tech1000 Simulations – High Tech (Computer Simulation)
Binomial Distribution SimulationBinomial Distribution Simulation((n=10, p=0.5n=10, p=0.5))
10 Repetitions
Note the apparent convergence of the relative frequency function (red) to the probability mass function (blue).
100 Repetitions 1000 Repetitions
http://www.math.uah.edu/stat/bernoulli/Binomial.xhtml
BinomialBinomial n=10n=10
p = 0.15 p = 0.5 p = 0.85
Note the change in the shape of the distribution (blue) as p changes.
http://www.math.uah.edu/stat/bernoulli/Binomial.xhtml
One Solution for Internet-based One Solution for Internet-based Instructional TechnologiesInstructional Technologies
• Digital Libraries• Organized, Searchable
• Reviewed & Assessed (sometimes)
• National Science Digital Library (www.nsdl.org)
Digital Library ProjectsDigital Library Projects
http://www.merlot.org/
http://www.mathdl.org/
http://www.smete.org/
http://www.causeweb.org
(Science, Math, Engineering & Technology Education)
MERLOT & CAUSEwebMERLOT & CAUSEweb
– Not just for statistics– An established assessment process
http://www.merlot.org/
http://www.causeweb.org
– Mission: support undergraduate statistics teachers & learners
www.CAUSEweb.orgwww.CAUSEweb.org
• Digital Library for Undergraduate Statistics Education
• CAUSEway workshops
• USCOTS
• Webinars
• Future Opportunities (keep checking this website.)
• Getting Started
• Guidelines for Research
• Readings & Publications
• Literature Index
• Dissertations
• Working Groups and Projects
MERLOT StatisticsMERLOT Statistics• MERLOT Statistics and CAUSEweb share an
Editorial Board – Roger Woodard, Editor editor@causeweb.org
• Peer reviewed materials appear in both locations & a composite review is shown
• Peer reviews help to:– Pass on expert knowledge– Point out possible downsides
MERLOT/CAUSEweb MERLOT/CAUSEweb Review ComponentsReview Components
• Descriptive– All items in MERLOT and CAUSEweb
have a descriptive component
• Evaluation– Peer-reviewed items have an evaluation
component – Evaluations are shown on the record– MERLOT has a “star” rating system
Review Component: Review Component: DescriptionDescription
• Overview
• Type of Material
• Technical Requirements
• Learning Goals*
• Recommended Uses*
• Target Student Population
• Prerequisites** only required on peer reviewed items
Review Component: Review Component: EvaluationEvaluation
• Content Quality
• Potential Effectiveness as a Teaching Tool
• Ease of Use
• Issues and Comments
CAUSEweb/MERLOT CAUSEweb/MERLOT Review Criteria OverviewReview Criteria Overview
• Quality of ContentQuality of Content (concepts, models and skills): valid & educationally significant
• Likely EffectivenessLikely Effectiveness:: improves ability to learn material, easily integrated, learning goals easily identifiable, conducive for writing good learning assignments, promotes/uses effective learning strategies
• Ease of UseEase of Use: easy first time use, consistent appearance, clear instructions, not limited by technical resources
Content QualityContent Quality
• Does the item present valid concepts, models, and skills?– Is the information presented by the item factually
correct?– Does the item use appropriate vocabulary?– Does the information presented by the item follow
generally accepted notation?– Does the item encourage appropriate statistical
practice?– Does the item integrate graphics and multimedia
when appropriate?
Content QualityContent Quality• Does the item present educationally
significant concepts, models, and skills?– Does the item help develop conceptual
understanding of statistics?
– Is the item non-trivial? Is the level of understanding obtained relative to the amount of time required?
• Is the item dealing with an important topic?– Does it deal with a topic that students typically find
challenging?
Potential Effectiveness as a Potential Effectiveness as a Teaching ToolTeaching Tool
• Are the teaching-learning goals easy to identify?
• Can the item be readily integrated into a statistics course or curriculum?– Does the item fit into standard presentation
of statistics courses?– Can the item be used with standard texts?
Potential Effectiveness as a Potential Effectiveness as a Teaching ToolTeaching Tool
• Does the item promote and/or use effective learning strategies?– Does the item promote active engagement?– Does the item help develop critical thinking
skills?– Will the item promote student discovery?
• Can learning be readily assessed?
Ease of UseEase of Use• How easy is the item to use for the first time?• Does the item have a consistent feel and appearance?• Does the item have clear instructions?• Is the item convenient and inviting to use?• Does the item provide an effective feedback
mechanism?• Can the item be used by individuals with a variety of
backgrounds/technical skills?• Is technical support necessary?• Is the item limited by technical resources such as
Internet connection speed or special plug-ins?
Interested in helping Peer Interested in helping Peer Review for Review for
CAUSEweb/MERLOT?CAUSEweb/MERLOT?
Contact: Contact: editor@causeweb.orgeditor@causeweb.org
Other Technology Assessment Other Technology Assessment Resources & ExamplesResources & Examples
• Network for the Evaluation of Education and Training Technologies
–Comparison Terms
–Example: Robert DelMas paper/software
• ARTIST– Great Resource for Statistics Assessment
– On-line Introductory Statistics Test Builder
General Assessment:General Assessment:Instructional TechnologiesInstructional Technologies
Network for the Evaluation of Education Network for the Evaluation of Education and Training Technologies (EvNet)and Training Technologies (EvNet)
• National multi-discipline, multi-sector network • Committed to improving instructional
technologies (used in Canadian education) through research focused on assessment and evaluation
http://socserv2.socsci.mcmaster.ca/srnet/exsum.htm
Technology Assessment:Technology Assessment:EvNet Best/Worst PracticesEvNet Best/Worst Practices
• Best Practice LabelsBest Practice Labels– Warmware– Inclusive– Access Equity– User Control– Learner Driven– Knowledge building– Meaningful Interaction– Multidimensional– …
• Worst Practice LabelsWorst Practice Labels– Coldware– Blocks access– Expensive/costly– Loss of Control– Destructive of
collaborative learning– No interactivity– …
EvNet, p. 2-3 http://socserv2.socsci.mcmaster.ca/srnet/exsum.htm
Best Practices ExampleBest Practices Example
• Robert delMas: develop & assess software • Software: Sampling Distribution
• Objective: students explore simulations of sampling distributions to learn and/or discover Central Limit Theorem concepts
• Assessment: combine existing research models (Nickerson and Holland et al. "Inductive Reasoning
Model") list features to promote understanding(1996 ISAE Roundtable Conference on the Role of Technology)
https://ore.gen.umn.edu/artist/index.html
ARTIST: Assessment Resource Tools ARTIST: Assessment Resource Tools for Improving Statistical Thinkingfor Improving Statistical Thinking
https://ore.gen.umn.edu/artist/index.html
ARTIST Assessment Builder ARTIST Assessment Builder (for Introductory Statistics)(for Introductory Statistics)
Free login
ReferencesReferences• Cuneo, Carl. "Twenty Criteria for Evaluating Instructional Technologies:
From Best to Worst Practices." EvNet Website. http://socserv2.mcmaster.ca/srnet/tools/tktoc.htm Retrieved July 26, 2004.
• delMas, Robert. "A Framework for the Evaluation of Software for Teaching Statistical Concepts" 1996 IASE Roundtable Conference Proceedings. Website Version. http://www.stat.Auckland.ac.nz/~iase/php?show=8. PDF file 7.delMas.pdf. Retrieved July 15, 2004.
• EvNet, Network for the Evaluation of Training and Technology. http://socserv2.socsci.mcmaster.ca/srnet/exsum.htm Retrieved July 23, 2004.
References ContinuedReferences Continued• Garfield, Joan. "Preface" to 1996 IASE Roundtable Conference
Proceedings. Website Version. http://www.stat.Auckland.ac.nz/~iase/php?show=8. PDF file iforward.pdf. Retrieved July 23, 2004.
• Gilbert, Steven. "What is a Triad?" PowerPoint Presentation. The Teaching, Learning, and Technology Group. http://www.tltgroup.org/media/fl/Triad.htm Retrieved July 2002.
• Gilbert, Steven. The Teaching, Learning, and Technology Group. http://www.tltgroup.org/resources/TranslucentTechnologies5-08-02.htm Retrieved July 2002.
• Shaughnessy, J. Michael. "Discussion: Empirical Research On Technology And Teaching Statistics" 1996 IASE Roundtable Conference Proceedings. Website Version. http://www.stat.Auckland.ac.nz/~iase/php?show=8. PDF file 17.shaughnessy.pdf. Retrieved July 23, 2004.
References ContinuedReferences Continued
• Siegrist, Kyle. "The Binomial Coin Experiment." Virtual Laboratories in Probability and Statistics, 1997-2004. University of Alabama in Huntsville. http://www.math.uah.edu/stat/ Retrieved June 2002.
• The Teaching, Learning, and Technology (TLT) Group. Information Page. The TLT Group. http://www.tltgroup.org/ Retrieved July 2002.
• Valdez, Gilbert. "Evaluation Standards and Criteria for Technology Implementation," North Central Regional Educational Laboratory. http://www.ncrel.org/tandl/eval_standards_and_criteria.htm Retrieved July 23, 2004.
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