This is a static copy of the main wikispot.org site, preserved for historical purposes only. Please see this page for more information.

Users/ColinTClark

InfoInfo
Search:    

Sample 100B Wiki

Editing and Managing a Wiki

Policies

Grading:

GradingPolicies

Section swapping: must find a partner to switch and go to Academic Services
Absences:
Absences may be excused with documentation and petition
Documentation must be turned in to master TAs. Evaluated by them at the end of quarter.
May be submitted any time throughout quarter.
Plagiarism:
Any evidence of plagiarism gets sent to master TAs.
If gross plagiarism is found, may result in expulsion.
Reading others’ papers/proofreading from former students is not recommended – possibly unconscious plagiarism.
First Week
Lab One
Icebreaker/introductions
Memory game – helps to learn students’ names
“2 Truths, 1 lie”
100B myths
Certain proportion have to fail
Expectations and responsibilities
Must be respectful of me and others in class
Participate in class
Conduct Experiment 1 – Stroop Task
Randomize sheets in front of class
Tabulate data afterwards (p. 13)
Homework: Worksheet #1 (pp. 67-70)
Homework: use TurnItIn – set up dummy assignment to ensure everyone has access
Lab Two
Review Worksheet #1 – visual inspection is okay
Discuss Stroop and assign Method Section
APA Homework Assignments
Not due on TurnItIn.com
Not graded, but important for later success
Experiment 1 – Stroop Task
Running the experiment
Instruct students to follow directions exactly as printed
Check in after a few runs to make sure everything is still proceeding as planned
Discussion and Methods assignment:
Nature of Stroop effect
Competing cognitive systems
Interference of outputs – automatic vs. deliberative systems
Students should do most of the work coming up with significant aspects of the experiment
Can divide up board into sections for Participants, Design, Materials, and Procedures
Discuss what block randomization is
Blocks were created after constructing list of five words – purpose of block randomization is to obtain more measures and to counterbalance
Counterbalances specific-item effects, order effects, sequence effects
Same items, colors, but presented in different orders and combinations
Differentiate between counterbalancing and controlling
Control – eliminate a nuisance variable
Counterbalance – distribute the effects of a nuisance variable equally
Meant to minimize effects of extraneous and confounding variables
Method assignment requirements:
Pp. 40-42 in workbook
Idea of balance of information – enough to replicate, but only what's important
Participants
Univ. of CA, LA students
Number
Gender makeup
Design
Design section should establish terminology used in the rest of the paper – what are your variables called?
Avoid numbering – it's usually arbitrary and confusing
Independent variable – differentiate from operationalization. IV = conflict, defined as incongruency between word & color
Dependent variable – time taken to say colors. Discuss why this is a good DV: expect RT to be slowed with conflict
Type of study – one-way within-subjects experiment, 2 levels
Materials
Refer to brainstormed aspects
Easier to describe incongruent list first, then how neutral list was constructed to counterbalance
Procedures
Refer to brainstormed aspects
May be helpful to write this section first, to clarify what happened in the experiment
Only student ID# on writeup – may be helpful in preserving grading objectivity

Second Week
Lab One
Due: Methods First Draft
Analyze Stroop data in the computer lab
Briefly (10 min.) discuss t-tests beforehand (and afterwards – but watch the time)
Null hypothesis testing
Hypothesis = what we expect to see
Assume that the means are the same – no difference, except by chance
Difference divided by variance – difference between group means, variance of sample error
In a within-subjects design the variance within is the important part; variance between is pure error/chance
Replicating the experiment exactly would yield different results – SEM is a measure of the variance around the “true mean”; if we ran the experiment 1,000 times we'd reduce the SEM to zero
Critical value determines whether or not the difference, standardized in the t-value, is large enough to matter
Greater t-values mean greater differences, but relatively small differences can be just as statistically significant – only tests whether or not there is a difference, not how “practically significant” it is
Setting alpha at .05 is arbitrary, but generally safe; means that we have a 5% chance of screwing up
Type I error is saying there's a difference when there really isn't – false positive
Type II error is saying there isn't a difference when there really is – false negative
Using SPSS to run a paired-sample T test
Variable view is useful – variables should have names that make sense and are able to be differentiated
Direct attention to the important parts of the output (but don't have them cut anything out)
Graph data in class
Break students into small groups
Have them come up with their own “graphical representations of the data”
Ideal is bar graph (discrete variable) with clearly labeled and consistently marked axes
Discuss positives/negatives of other designs students may come up with – when is a line graph appropriate? What is a histogram good for?
Just drawing lines over bars doesn't quite translate – spacing between bars is arbitrary, and not reflective of a continuous variable
Collect and redistribute Method sections for edits (p. 27-29)
Emphasize that edit guide is graded, gives students a second chance
Give both positive and negative feedback – if something's done well, acknowledge it
Ensure no one gets their own (fake shuffle)
Make sure everyone gets theirs back at the end
Due next class period
Write ID# only on edited draft
Submit revised Methods to Turnitin, bring hard copy of revised methods and edit guide
Lab Two
Due: Revised Methods
Quiz #1
Experiment #2
Tabulate data in-class
Stroop results section (p. 30)
Complete in pairs? Then check answers with the rest of the class.
Assign Worksheet #2 (pp. 71-74)

Third Week
Lecture Topics
Within/between-subjects designs
Assets and detriments of both (power, convenience, practical considerations)
Specific-item effects
Randomization and counterbalancing help to eliminate SIEs
Accuracy and validity of measures
Demand characteristics
Implicit measures
Sampling distributions
Lab One
Due: Worksheet #2
Discuss LOP experiment
IV = Level of processing
Orthographic (letters), phonological (words), semantic (meanings)
More significant/complex meaning leads to greater memory
DV = # of words recalled
List creation
Counterbalancing was very important – order effects/specific item effects
24 words for each question
Half of each of the words are “yes” for one of the questions
12 ortho yes, 12 ortho no. 12 mono yes, 12 mono no. 12 living yes, 12 living no.
3 words for each possibility – need enough variance to get reliable estimates
Create project groups
Randomly assign students to groups
Take into account methods grade?
Have groups select (not number) three choices
Assign Worksheet #3
Lab Two
Due: Worksheet #3
Quiz #2
Using ANOVA to analyze more than 2 conditions
Just like a t-test, measures difference due to manipulation versus difference due to error

Omnibus ANOVA limits chance of Type I error – check for some difference before testing for specific differences
Bonferroni correction adjusts alpha level – reduces to compensate for # of comparisons
Distribute seed articles
Should understand seed articles
Worksheet has students identify variables, operationalizations (can be assigned as homework)

Fourth Week
Lab One
Results and discussion of Experiment 2
Graph Experiment 2
Discuss projects (pp. 58-62)
Grading criteria: creativity, clarity, feasibility, originality, understanding
Understanding moderating/mediating factors
Can use Stroop/LOP experiments as demonstrations
What could affect processing/congruency?
Assign hypothesis generation exercise
Manipulate, modify IV, DV, think about moderators

Lab Two
Lit Search exercise
Refining keywords
Using different search terms
Difference between review & experiment
Google Scholar vs. Psycinfo
Need three articles
Seed article
Shared group article
Unique individual article
Hypothesis testing exercise
Correlational and Experimental study designs
Concrete and abstract conceptualizations
Push students to work quickly – rapidly identify and operationalize and IV
Focus on testability; making a general statement scientific
Construct validity

This is a Wiki Spot wiki. Wiki Spot is a 501(c)3 non-profit organization that helps communities collaborate via wikis.