Business

• Today's agenda
• Check index page for status reports; make sure to check email archives regularly

1. Welcome
2. Who's here (roll stuff)
3. Syllabus
4. Assignment overviews
5. Introductions
6. Topic: What is Research, Anyway? (Reference: Leedy 1, 2)
• Inquiry, problem solving, term papers, literature reviews, research - what's the difference? [mini-group] (Ref: Leedy p3-4; also, idea of "formal research," p. 4)
• Effect of research on our lives. Share examples (Homework Assignment #2). (Ref: Leedy, p.43, "Reflections on Significant Research")
• What about in libraries?  What is your perception of the value of research in libraries? (Homework #3) (Leedy p.9)
• Data collection for needs assessments
• Evaluating programs, goals
• Innovations - effectiveness
• How my own perspective has changed
• Powerpoint: What is Research, Anyway? 
7. Guided Discussion: Desperately Seeking a Research Topic

• Tech Tip
• Explain homework and work activities
• Temperature check
• Muddy points
• Last Word: Melinda Mae

• Beginning of group negotiation and group work
• A super wonderful outcome for today would be for you to identify your group and write a rough draft of your research question.
• The next step will be to make your proposal and get it approved. 
• The next next step is going to be: assembling the literature review.   You could start looking. 

• Today's agenda
• Last word volunteers
  

Things to do:

• 9:00-9:30: Group work - proposals
• Muddy Points:  generate
  
• Research Serpent or Chutes and Ladders
  

List the steps in doing a research project. 

Chart them visually.

See images above.

Compare to Leedy's Research Cycle (see p. 9)




• Round 1, Critique Sharing. Give gist of study, a little about the source. Ref: Leedy, p. 36, "Critical Thinking"
• Writing research questions - share and comment between groups
• Share: Methodology Recipes
• Choosing a Methodology according to your research question
• Methodology: what's the difference between design, technique, data, analysis? Use our projects as examples.

 
• Ethics of Research
• Horror Stories: Milgram's obedience experiments; Tuskegee Syphillis Study
• Basic ethical principles 
• informed consent - participants and their parents (if minors)
• risk - including public exposure; anonymous or confidential; relation to grades
• distribution of benefit and burden: should not unfairly benefit one group over others
• protection for vulnerable participants
• Your questions

• Levels of lit reviews: 
• "exhaustive" (no such thing) or exhaustive as possible
• justifying the study
• framing the study (this is us!)
• none
• Everyone should include lit review methodology - the story of your search
• What kinds of things should you include? 
• Studies - always
• Conceptual or theoretical pieces - sometimes
• Prescriptive pieces, models for "how to do x" - sometimes
• Anecdotal pieces - less so
• Figuring out what topics to look for
• Venn diagram
• Use class examples
  
• How do you find them?
• Our favorite sources (would be good to have a compiler, send to him/her)
• Good journals in our field
  
• My tricks
• How do you begin to organize, make sense, and synthesize them?
• Highlighting and annotating
• Coding
• Thematic organization
• Handling quotes and citations (keeping track of them)
• Outline
• Write
• Thematic organization is better than "beads on a string" (where you report study after study with only a rough attempt to organize them). Diagramming, sticky note organization very helpful here.
• I would rather read a well-synthesized, thematically organized review of three studies than a beaded string of 100 studies
• For this class, generate 1 slide.  It should answer:
• Are you duplicating another study?
• How much literature is available that relates?
• What is the gist of what you've been able to find?
• Technical aids: word processor; EndNote; Inspiration; folders, highlighters, piles, sticky notes, whiteboard....
  

• Tech Tip of the Day
• Temperature check and Muddy Points
• Work planning
• Last Word

Work: 

• By the end of this afternoon, these things should be accomplished:
• Your group is set. 
• Your question is set (minor tweaking ok later).
• As a group, your proposal has been approved.
• The next next step is going to be: assembling the literature review.   You could start looking. Seek and gather:
• List of citations
• Relevant findings
• Leads for more literature

Business 

• Grading status

• What instruments and materials will be used in your projects?
• Survey design
• Piloting is extremely important
• Audiotaping, videotaping
  
• What do we still need to know?

Closure

• Tech Tip of the Day
• Muddy points
• Temp check
• Work planning
• Last Word - Joy
  
  

More of the same!

Things to do today:

• Business
• Agenda
  
• Methodology Recipes
  
• Statistical Analysis 
• What do we already know and believe about statistics?
• One observation: statistics require a considerable amount of mathematical facility and mindset; BUT - there is a great deal of squishiness involved.  People who enjoy math tend to dislike squishiness. This is a problem for many. But - stats are very useful and fun to think about.
  
• Why should I care?
• Everyone should be able to interpret stats in the "atmosphere"
• You will have quantitative data available to you in a number of school and library situations
• Has a certain face credibility that qualitative data does not (an arguable point)
• Descriptive stats summarize the general nature of data; inferential stats help the researcher make decisions and describe a larger reality
• Stats help condense TMI into an organized whole, to see patterns and relationships
  
• Foundational ideas  (Ref: Leedy pp24-33)
• Measurement:  Leedy is confusing on this idea (p24-25). Don't get stuck here. Also, the sociogram example is confusing to me.
• Scales: nominal, ordinal, interval, ratio.  Importance: down the road dictates which stats tests you can run - see Table 2.4, p.30.
• Validity and reliability
• Deductive and Inductive reasoning (p. 35)
• Leedy's examples of exploring data on p. 252 and 257 are good - girls/boys' reading test scores and Joe's grades. The point is that you "must first survey the data to observe their configuration and fundamental characteristics."  Then use stats to analyze "what the mass of data appears to be." (p. 270)
• Parameters versus statistics p. 260
• Knowing where to go and what to do with a dataset
• Try to plot ahead of time. But - that's not always possible.
• See 4 characteristics, bottom of p. 260 - 1/more groups, discrete/continuous variables, 4 scales, normal distribution - these too will guide decisions of which tests to use
• The most powerful statistical analyses (in a category called parametric stats) can only be done with interval/ratio scales and normally distributed data
• Descriptive stats: very useful!
• Points of central tendency - mode, median, mean. Leedy talks about geometric mean -- sounds good in theory, but hasn't come up too much for me. See Table 11.2 on p. 267.
• Measures of variation: answer the question: how clustered are the data around the mean?  Range; interquartile range; standard deviation; variance. See Table 11.3 on p. 270.
• Measures of relationship: how 2 or more variables are interrelated. Correlation coefficient will be a value between -1 and 1; shows direction of relationship (positive or negative) and strength. See Table 11.4 on p. 272. Does NOT prove causation!
• Leedy neglects to mention that percentage breakdowns are helpful as well - especially for nominal data.
  
• Inferential stats
• Estimation: predicting population parameters from sample statistics.  Choose a random and representative sample, and predict corresponding parameters.  But - sample will never be exactly the same as the population. Difference = error.  Just know that there are ways of calculating the size of this error and that the goal is to get it as low as possible.  Larger samples yield more accurate estimates of population parameters.
• Hypothesis testing (p. 275):
• Research hypothesis vs. statistical hypothesis
• Null hypothesis: postulates that any result observed is the result of chance alone. This is what is tested. 
• Researcher must identify a level of acceptable probability: alpha, or level of significance. 
• If you obtain a result that, based on your chosen alpha, you deem not to be due to chance is called statistically significant.  Then you "reject the null hypothesis." Indirectly, you are supporting the opposite: that the two groups are different.
• See examples of inferential stats procedures, Table 11.5, p. 278. These all involve hypothesis testing.
  
• Two important points:
• There is a certain degree of arbitrariness to stats - someone invented these tests, many probabalistic assumptions. Much is based on .05 p value - an arbitrary decision, really.
• You can never PROVE anything. You can identify relationships. You can disprove things.
• SPSS Demo
  
• Big ideas: RobertNiles.com
• Key: decide what you what to learn first. 
• If you choose a statistical methology -
• Consult an authority to help you set up your study.  Sometimes there are certain assumptions that must be met. Example: independence in group comparison studies.
• Consult an authority to help you start your analysis.
• Overview of choosing an analysis
  
• Resources
• Big ideas: http://www.robertniles.com/stats/
• Stats Glossary: http://www.animatedsoftware.com/statglos/statglos.htm
• Selecting Statistical Tests: http://trochim.human.cornell.edu/selstat/ssstart.htm
• Urdan, T.C. (2001). Statistics in plain English. Mahwah, NJ: Lawrence Erlbaum.
  

• Group Status Reports and temp check
• Tech Tip of the Day
• The Last Word - Natalee

Business 

• Set agenda
• Return graded material
  

Things to do today:

• Group Status Reports
• SPSS Demo - Dan
  
• Writing your reports, with examples
• Review the assignment
• Examples:
• Eden and Karen: Making the Most of the Nonfiction Section
• Marty, Amy, and Julie: AR's Impact on Motivation
• The publication process: patience and persistence
• Presenting at conferences
• Shopping for an audience: journals, magazines, books, book chapters; research vs. practice
• Drafting
• Positioning or slicing a study
• Formatting, editing, peer reviewing, copy editing
• Launch
• Peer review, editorial review
• Revising
• When you get cited
• Making your projects pay off: personal examples (projects .. vita)
  

• Tech Tip of the Day
• Plan work
• Last Word - Natalee
  
• Course evaluations
• Reset room