False Memory
Background
It's a common intuition that memory is like a video camera: we store a copy of whatever we were experiencing, and later we remember by playing it back. Among the many reasons this view of memory is incorrect is that it assumes our memory is always, or at least very often, accurate. But in fact, not only is memory inaccurate, it's often less accurate than we think: we might be very confident in a memory only to realize it was totally wrong.
One way memory can be distorted is through misinformation. Loftus and Palmer (1974) showed participants a video clip of a car accident, then asked them to estimate the speed of one car in the video. However, one group of participants was asked how fast the car was going when it "smashed into" the other car, while the second group was asked how fast the car was going when it "hit" the other car. Participants who were asked the "smashed" question estimated much higher speeds than those asked the "hit" question, even though both groups of participants saw the same video--suggesting that memories can be distorted by how questions about the memory are framed. Worse still, we can be poor judges of our own memory accuracy: in one study of vivid, emotional flashbulb memories, confidence in the memories was extremely high, but those high-confidence memories were not any more accurate than typical memories (Talarico & Rubin, 2003).
We can also experience entirely false memories. In the Deese-Roediger-McDermott paradigm (Deese, 1959; Roediger & McDermott, 1995), participants see lists of words that are all related to a single "critical" word. For example, if the critical word was candy, participants might see words like sweet, chocolate, or bar. The important part of the paradigm is that the critical word ("candy") is never presented to participants. Despite this, when asked to recall words later, many participants will falsely remember seeing the critical word, and most will be confident that their recollection is accurate.
Mostly, these misinformation and false memory effects happen because remembering is reconstructive. We don't just press "play" on a video recording of the event; when we remember our brain is filling gaps and details and context every time we recall the event. Remembering is an active process, not the passive "playback" of recorded information, and that has practical implications. Consider that, when polled, people serving on a jury overwhelmingly indicate that eyewitness testimony is the most compelling evidence when trying to decide whether a defendant is guilty. But based on false memory and other memory distortions, shouldn't jury members be much less trusting of eyewitness testimony than they are? If confidence is not as associated with memory accuracy as we think, then it becomes difficult to determine whose testimony to believe. And moreover, if memory is reconstructive, then the mere act of recalling the event may distort the memory, further clouding the issue.
Se ...
False MemoryBackgroundIts a common intuition that memory is l.docx
1. False Memory
Background
It's a common intuition that memory is like a video camera: we
store a copy of whatever we were experiencing, and later we
remember by playing it back. Among the many reasons this
view of memory is incorrect is that it assumes our memory is
always, or at least very often, accurate. But in fact, not only is
memory inaccurate, it's often less accurate than we think: we
might be very confident in a memory only to realize it was
totally wrong.
One way memory can be distorted is through misinformation.
Loftus and Palmer (1974) showed participants a video clip of a
car accident, then asked them to estimate the speed of one car in
the video. However, one group of participants was asked how
fast the car was going when it "smashed into" the other car,
while the second group was asked how fast the car was going
when it "hit" the other car. Participants who were asked the
"smashed" question estimated much higher speeds than those
asked the "hit" question, even though both groups of
participants saw the same video--suggesting that memories can
be distorted by how questions about the memory are framed.
Worse still, we can be poor judges of our own memory
accuracy: in one study of vivid, emotional flashbulb memories,
confidence in the memories was extremely high, but those high-
confidence memories were not any more accurate than typical
memories (Talarico & Rubin, 2003).
We can also experience entirely false memories. In the Deese-
Roediger-McDermott paradigm (Deese, 1959; Roediger &
McDermott, 1995), participants see lists of words that are all
related to a single "critical" word. For example, if the critical
word was candy, participants might see words like sweet,
chocolate, or bar. The important part of the paradigm is that the
critical word ("candy") is never presented to participants.
Despite this, when asked to recall words later, many
2. participants will falsely remember seeing the critical word, and
most will be confident that their recollection is accurate.
Mostly, these misinformation and false memory effects happen
because remembering is reconstructive. We don't just press
"play" on a video recording of the event; when we remember
our brain is filling gaps and details and context every time we
recall the event. Remembering is an active process, not the
passive "playback" of recorded information, and that has
practical implications. Consider that, when polled, people
serving on a jury overwhelmingly indicate that eyewitness
testimony is the most compelling evidence when trying to
decide whether a defendant is guilty. But based on false
memory and other memory distortions, shouldn't jury members
be much less trusting of eyewitness testimony than they are? If
confidence is not as associated with memory accuracy as we
think, then it becomes difficult to determine whose testimony to
believe. And moreover, if memory is reconstructive, then the
mere act of recalling the event may distort the memory, further
clouding the issue.
Sequence of Events
The basic trial sequence for the encoding phase is as follows.
Instructions are presented at the beginning of the experiment.
Fixation Point
Duration determined by Fixation Point Duration
Study Stimulus
Duration determined by Study Stimulus Duration
ITI
Duration determined by ITI Durations
The basic trial sequence for the Recognition test is as follows.
Fixation Point
Duration determined by Recognition Test Fixation Point
Duration
3. Test Stimulus
Maximum duration determined by Maximum Allowable RT
Feedback
Feedback on response accuracy can be displayed
ITI
Duration determined by ITI Durations
Results and Output
For each participant, three tab-delimited text data files are
saved in the Logfiles folder. The .log file (filename "Subject-
Experiment Name.log") is a standard Presentation logfile and
contains detailed information about every event and response
that occurred during the experiment. The summary file
(filename: "Subject-Experiment Name-Summary.txt") contains
simple summary statistics (e.g., accuracy, RT) for relevant
experiment conditions. The remaining file contains trial-level
data. This is the file that would typically be used for running
simple analyses. A brief example of this file and description of
the column headings follows. Note that two tables are printed,
one for encoding trials and one for test trials.
Column heading list for Encoding trials:
Block
Identifies trial as Encoding
Trial Number
Trial number in the encoding block
Study Word
Study stimulus
Word Group
Word group/word list of the study stimulus
Word Number
Word number (1-15) of the study stimulus
Column heading list for Recognition trials:
Block
Identifies trial as Recognition
Trial Number
4. Trial number in the test block
Word Group
Word group the test stimulus belongs to
Word Number
Word number (1-15) of the test word
Test Word
Test stimulus
Word Condition
Target, Distractor, or Critical Word
Response
Participant's response (2 = "old", 3 = "new")
Accuracy
Old/new response accuracy
RT
Reaction time (in ms) for the old/new response
Configurations
Free Recall (default)
Based on the free-recall version as in Roediger and McDermott
(1995). Participants study 12 lists of 15 words each, performing
a free-recall task after studying each list.
Recognition
Based on a recognition version of the experiment as conducted
by Roediger and McDermott (1995). Participants study six lists
of 15 words, then do a recognition memory task in which the
critical word for each list is also presented.
Stimuli
Stimuli are taken from a tab-delimited text file. The text file
should contain 16 columns. Each row represents one word list,
with the first column being the "critical" word, and the
subsequent columns being the related words, listed in
descending order of relatedness.
Port Codes
The table below describes how port codes are assigned to
responses and stimulus events (if port codes are sent). In
general, responses will have port codes less than 10, and
stimulus events will have port codes 10 or higher. Note that
5. based on parameter settings, some of the events listed below
may not occur in the experiment.
1
Enter key
2
Left mouse button
3
Right mouse button
10
Fixation point onset
20
Study Word onset
20
Test Word onset (recognition test)
Translations
Translations are included for the following languages: English,
Spanish, German, French, Chinese, and Japanese. Use the
Language parameter to select an available translation. A
'Custom' language file (and associated stimulus files, if
necessary) is included for all experiments that can be modified
to create new translations. Some experiments contain captions
that should be translated manually as part of a parameter (for
example, a statement describing a target stimulus or position).
For this experiment, you should check the following parameters
for those captions: Correct Feedback Caption and Incorrect
Feedback Caption.
False Memory
Background
It's a common intuition that memory is like a video camera: we
store a copy of whatever we were experiencing, and later we
remember by playing it back. Among the many reasons this
view of memory is incorrect is that it assumes our memory is
always, or at least very often, accurate. But in fact, not only is
memory inaccurate, it's often less accurate than we think: we
6. might be very confident in a memory only to realize it was
totally wrong.
One way memory can be distorted is through misinformation.
Loftus and Palmer (1974) showed participants a video clip of a
car accident, then asked them to estimate the speed of one car in
the video. However, one group of participants was asked how
fast the car was going when it "smashed into" the other car,
while the second group was asked how fast the car was going
when it "hit" the other car. Participants who were asked the
"smashed" question estimated much higher speeds than those
asked the "hit" question, even though both groups of
participants saw the same video--suggesting that memories can
be distorted by how questions about the memory are framed.
Worse still, we can be poor judges of our own memory
accuracy: in one study of vivid, emotional flashbulb memories,
confidence in the memories was extremely high, but those high-
confidence memories were not any more accurate than typical
memories (Talarico & Rubin, 2003).
We can also experience entirely false memories. In the Deese-
Roediger-McDermott paradigm (Deese, 1959; Roediger &
McDermott, 1995), participants see lists of words that are all
related to a single "critical" word. For example, if the critical
word was candy, participants might see words like sweet,
chocolate, or bar. The important part of the paradigm is that the
critical word ("candy") is never presented to participants.
Despite this, when asked to recall words later, many
participants will falsely remember seeing the critical word, and
most will be confident that their recollection is accurate.
Mostly, these misinformation and false memory effects happen
because remembering is reconstructive. We don't just press
"play" on a video recording of the event; when we remember
our brain is filling gaps and details and context every time we
recall the event. Remembering is an active process, not the
passive "playback" of recorded information, and that has
practical implications. Consider that, when polled, people
serving on a jury overwhelmingly indicate that eyewitness
7. testimony is the most compelling evidence when trying to
decide whether a defendant is guilty. But based on false
memory and other memory distortions, shouldn't jury members
be much less trusting of eyewitness testimony than they are? If
confidence is not as associated with memory accuracy as we
think, then it becomes difficult to determine whose testimony to
believe. And moreover, if memory is reconstructive, then the
mere act of recalling the event may distort the memory, further
clouding the issue.
Sequence of Events
The basic trial sequence for the encoding phase is as follows.
Instructions are presented at the beginning of the experiment.
Fixation Point
Duration determined by Fixation Point Duration
Study Stimulus
Duration determined by Study Stimulus Duration
ITI
Duration determined by ITI Durations
The basic trial sequence for the Recognition test is as follows.
Fixation Point
Duration determined by Recognition Test Fixation Point
Duration
Test Stimulus
Maximum duration determined by Maximum Allowable RT
Feedback
Feedback on response accuracy can be displayed
ITI
Duration determined by ITI Durations
Results and Output
For each participant, three tab-delimited text data files are
saved in the Logfiles folder. The .log file (filename "Subject-
Experiment Name.log") is a standard Presentation logfile and
8. contains detailed information about every event and response
that occurred during the experiment. The summary file
(filename: "Subject-Experiment Name-Summary.txt") contains
simple summary statistics (e.g., accuracy, RT) for relevant
experiment conditions. The remaining file contains trial-level
data. This is the file that would typically be used for running
simple analyses. A brief example of this file and description of
the column headings follows. Note that two tables are printed,
one for encoding trials and one for test trials.
Column heading list for Encoding trials:
Block
Identifies trial as Encoding
Trial Number
Trial number in the encoding block
Study Word
Study stimulus
Word Group
Word group/word list of the study stimulus
Word Number
Word number (1-15) of the study stimulus
Column heading list for Recognition trials:
Block
Identifies trial as Recognition
Trial Number
Trial number in the test block
Word Group
Word group the test stimulus belongs to
Word Number
Word number (1-15) of the test word
Test Word
Test stimulus
Word Condition
Target, Distractor, or Critical Word
Response
9. Participant's response (2 = "old", 3 = "new")
Accuracy
Old/new response accuracy
RT
Reaction time (in ms) for the old/new response
Configurations
Free Recall (default)
Based on the free-recall version as in Roediger and McDermott
(1995). Participants study 12 lists of 15 words each, performing
a free-recall task after studying each list.
Recognition
Based on a recognition version of the experiment as conducted
by Roediger and McDermott (1995). Participants study six lists
of 15 words, then do a recognition memory task in which the
critical word for each list is also presented.
Stimuli
Stimuli are taken from a tab-delimited text file. The text file
should contain 16 columns. Each row represents one word list,
with the first column being the "critical" word, and the
subsequent columns being the related words, listed in
descending order of relatedness.
Port Codes
The table below describes how port codes are assigned to
responses and stimulus events (if port codes are sent). In
general, responses will have port codes less than 10, and
stimulus events will have port codes 10 or higher. Note that
based on parameter settings, some of the events listed below
may not occur in the experiment.
1
Enter key
2
Left mouse button
3
Right mouse button
10
Fixation point onset
10. 20
Study Word onset
20
Test Word onset (recognition test)
Translations
Translations are included for the following languages: English,
Spanish, German, French, Chinese, and Japanese. Use the
Language parameter to select an available translation. A
'Custom' language file (and associated stimulus files, if
necessary) is included for all experiments that can be modified
to create new translations. Some experiments contain captions
that should be translated manually as part of a parameter (for
example, a statement describing a target stimulus or position).
For this experiment, you should check the following parameters
for those captions: Correct Feedback Caption and Incorrect
Feedback Caption.
GET DATA
/TYPE=XLSX
/FILE='C:UsersstudentDownloadsVisualSearchShapes
Sum19 BothSect TriByTrixlsx.xlsx'
/SHEET=name 'VisSearShapes'
/CELLRANGE=FULL
/READNAMES=ON
/DATATYPEMIN PERCENTAGE=95.0
/HIDDEN IGNORE=YES.
EXECUTE.
DATASET NAME DataSet1 WINDOW=FRONT.
GLM SetSize1 SetSize5 SetSize15 SetSize30 BY
RMGroupSearchType
/WSFACTOR=setsize_ 4 Polynomial
/METHOD=SSTYPE(3)
/PLOT=PROFILE(setsize_*RMGroupSearchType)
12. Cases Used
Statistics are based on all cases with valid data for all variables
in the model.
Syntax
GLM SetSize1 SetSize5 SetSize15 SetSize30 BY
RMGroupSearchType
/WSFACTOR=setsize_ 4 Polynomial
/METHOD=SSTYPE(3)
/PLOT=PROFILE(setsize_*RMGroupSearchType)
TYPE=LINE ERRORBAR=CI MEANREFERENCE=NO
YAXIS=AUTO
/PRINT=DESCRIPTIVE
/CRITERIA=ALPHA(.05)
/WSDESIGN=setsize_
/DESIGN=RMGroupSearchType.
Resources
Processor Time
00:00:01.00
Elapsed Time
00:00:01.05
[DataSet1]
Within-Subjects Factors
Measure: MEASURE_1
setsize_
Dependent Variable
1
SetSize1
2
SetSize5
17. 6.010b
3.000
26.000
.003
a. Design: Intercept + RMGroupSearchType
Within Subjects Design: setsize_
b. Exact statistic
Mauchly's Test of Sphericitya
Measure: MEASURE_1
Within Subjects Effect
Mauchly's W
Approx. Chi-Square
df
Sig.
Epsilonb
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
setsize_
.090
64.355
5
.000
.430
.458
.333
Tests the null hypothesis that the error covariance matrix of the
orthonormalized transformed dependent variables is
proportional to an identity matrix.
18. a. Design: Intercept + RMGroupSearchType
Within Subjects Design: setsize_
b. May be used to adjust the degrees of freedom for the
averaged tests of significance. Corrected tests are displayed in
the Tests of Within-Subjects Effects table.
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
setsize_
Sphericity Assumed
5548440801.718
3
1849480267.239
16.733
.000
Greenhouse-Geisser
5548440801.718
1.290
4301722617.803
16.733
.000
Huynh-Feldt
5548440801.718
1.374
4038743047.853
16.733
.000
24. General Linear Model
Notes
Output Created
30-JUL-2019 15:24:58
Comments
Input
Active Dataset
DataSet1
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
3288
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data for all variables
in the model.
Syntax
GLM ConjSetSize1 ConjSetSize5 ConjSetSize15 ConjSetSize30
27. Sig.
Epsilonb
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
setsize_2
.062
35.303
5
.000
.413
.433
.333
Tests the null hypothesis that the error covariance matrix of the
orthonormalized transformed dependent variables is
proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: setsize_2
b. May be used to adjust the degrees of freedom for the
averaged tests of significance. Corrected tests are displayed in
the Tests of Within-Subjects Effects table.
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
31. Tests of Between-Subjects Effects
Measure: MEASURE_1
Transformed Variable: Average
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Intercept
193241831284.491
1
193241831284.491
95.479
.000
Error
28334891272.739
14
2023920805.196
GLM FeatSetSize1 FeatSetSize5 FeatSetSize15 FeatSetSize30
/WSFACTOR=feature 4 Polynomial
/METHOD=SSTYPE(3)
/CRITERIA=ALPHA(.05)
/WSDESIGN=feature.
General Linear Model
32. Notes
Output Created
30-JUL-2019 15:29:37
Comments
Input
Active Dataset
DataSet1
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
3288
Missing Value Handling
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data for all variables
in the model.
Syntax
GLM FeatSetSize1 FeatSetSize5 FeatSetSize15 FeatSetSize30
/WSFACTOR=feature 4 Polynomial
/METHOD=SSTYPE(3)
/CRITERIA=ALPHA(.05)
/WSDESIGN=feature.
Resources
33. Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Within-Subjects Factors
Measure: MEASURE_1
feature
Dependent Variable
1
FeatSetSize1
2
FeatSetSize5
3
FeatSetSize15
4
FeatSetSize30
Multivariate Testsa
Effect
Value
F
Hypothesis df
Error df
Sig.
feature
Pillai's Trace
.478
3.657b
3.000
12.000
.044
35. Greenhouse-Geisser
Huynh-Feldt
Lower-bound
feature
.339
13.775
5
.017
.670
.783
.333
Tests the null hypothesis that the error covariance matrix of the
orthonormalized transformed dependent variables is
proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: feature
b. May be used to adjust the degrees of freedom for the
averaged tests of significance. Corrected tests are displayed in
the Tests of Within-Subjects Effects table.
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
feature
Sphericity Assumed
42999312.243
3
14333104.081
39. Transformed Variable: Average
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Intercept
12467077990.161
1
12467077990.161
171.819
.000
Error
1015832423.144
14
72559458.796
T-TEST PAIRS=ConjSetSize15 ConjSetSize1 ConjSetSize1
ConjSetSize5 ConjSetSize5 ConjSetSize15 WITH
ConjSetSize5 ConjSetSize15 ConjSetSize30 ConjSetSize15
ConjSetSize30 ConjSetSize30 (PAIRED)
/CRITERIA=CI(.9500)
/MISSING=ANALYSIS.
T-Test
Notes
Output Created
40. 30-JUL-2019 15:39:19
Comments
Input
Active Dataset
DataSet1
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File
3288
Missing Value Handling
Definition of Missing
User defined missing values are treated as missing.
Cases Used
Statistics for each analysis are based on the cases with no
missing or out-of-range data for any variable in the analysis.
Syntax
T-TEST PAIRS=ConjSetSize15 ConjSetSize1 ConjSetSize1
ConjSetSize5 ConjSetSize5 ConjSetSize15 WITH
ConjSetSize5 ConjSetSize15 ConjSetSize30 ConjSetSize15
ConjSetSize30 ConjSetSize30 (PAIRED)
/CRITERIA=CI(.9500)
/MISSING=ANALYSIS.
Resources
Processor Time
00:00:00.02
46. -1086.259730550694300
-2.433
14
.029
Pair 5
ConjSetSize5 - ConjSetSize30
-20268.426666666666000
22117.479936643096000
5710.708763646358000
-32516.678801510840000
-8020.174531822495000
-3.549
14
.003
Pair 6
ConjSetSize15 - ConjSetSize30
-11096.286666666674000
11382.030398010638000
2938.827611834785300
-17399.445006615150000
-4793.128326718196000
-3.776
14
.002
Visual Search (Shapes)
Teaching Information
| Background | Results | Suggestions | References |
Background
How do we find what we're looking for and ignore distracting
information? The visual search task requires participants to
determine whether a target (such as a particular letter, shape, or
image) is present in an array of other stimuli. For example, a
participant might be asked to determine whether a red letter is
47. present in the following display:
Two major findings came out of early visual search studies
(e.g., Treisman & Gelade, 1980). First, finding the target is
sometimes so easy that the target is said to "pop out" from the
array. Searches in which at least one feature always
differentiates targets from distractors (in the above example,
color) are called feature searches. In feature searches, the time
to find the target is not affected by the number of irrelevant
distractor stimuli: people are just as fast to spot the red letter
whether there's one blue letter or a dozen.
In conjunction searches, participants must consider at least two
features. For example, a conjunction search would be finding a
red X in an array of blue X's and red T's, meaning that the
conjunction of two features (shape and color) is required to
isolate the target. In conjunction searches, the number of
distractors matter: search times increase linearly with the
number of distractors. Thus, whereas feature searches are fast,
parallel, and independent of distractor stimuli, conjunction
searches are slow, serial, and depend on the number of
distractors.
The feature integration theory is often used to explain these
results (Treisman & Gelade, 1980). According to feature
integration theory, the features or characteristics (e.g., shape,
color, etc.) of objects we see are coded independently (but in
parallel) early in visual processing. For example, at the earliest
stages of processing a red X, independent, unconnected features
are being activated for "red" and for "X". Only later are those
features "integrated" into a unified "red x" representation. In a
feature search, features don't need to be integrated to complete
the search, so the search is rapid. Conjunction searches are
slower because that integration has to happen in order to
distinguish targets from distractors.
**Added by Craig** Article on the STM capacity for feature
and conjunction searches (Luck & Vogel, 1997). And another
48. frequently cited article (Wolfe, 1994).
Results
For the standard experiment, the dependent variable will usually
be reaction time. The most likely independent variables will be
the number of items in the study set, and the type of search
(feature or conjunction). Based on past results (e.g., Treisman &
Gelade, 1980), for feature searches, the search time is
independent of set size. In contrast, for conjunction searches,
reaction time should increase with set size. A repeated-measures
ANOVA with search type (feature vs. conjunction) and set size
as independent variables would be appropriate.
Suggestions
1. Change the number of targets. Are feature searches always
independent of set size, even when the number of possible
targets is high?
2. How do search times change when target colors or target
letter shapes are very similar (or dissimilar) to the distractors.
References
Treisman, A., & Gelade, G. (1980). A feature integration theory
of attention. Cognitive Psychology, 12, 97-136.
Luck, S. J., & Vogel, E. K. (1997). The capacity of visual
working memory for features and conjunctions. Nature,
390(6657), 279–281. https://doi.org/10.1038/36846
Wolfe, J. M. (1994). Guided search 2.0: A revised model of
visual search. Psychonomic Bulletin & Review, 1(2), 202–238.
https://doi.org/10.3758/BF03200774
Grading Rubric for PY-356 Research Proposal
Name: _______________________
Point Value
49. (total) ________
________
________
________
________
1. Introduction (5 points each, 20 points total)
a. Purpose/Importance of the study is clearly explained
b. Prior related research is clearly summarized and connected
c. Concludes with a clearly stated research Hypothesis
d. Includes citations from at least 5 peer-reviewed journal
articles
e. Proper APA style formatting (style, grammar, organization)
in
title page, body of introduction, and in-text citations. ________
Qualitative Feedback:
Good things:
Areas for improvement:
(total) ________
50. ________
________
________
________
2. Method (10 points)
a. Independent variables are conceptually and operationally
defined
b. Adequate/Clear description of participants (i.e., selection,
censoring,
characteristics)
c. Adequate/Clear description of research design
d. Adequate/Clear description of experimental procedure
e. Proper APA style formatting
Qualitative Feedback:
Good things:
Areas for improvement:
Grading Rubric for PY-356 Research Proposal
________
Introduction Paper Rubric Paper Rubric_Methods
Student Name: good things: areas for improvement: 2
Dropdown: [4]3 Dropdown: [4]4 Dropdown: [4]5 Dropdown:
