Title: How often are prefixes useful cues to word meaning? Less than you might think!
1How often are prefixes useful cues to word
meaning? Less than you might think!
- Jack Mostow , Donna Gates ,
- Gregory Aist , and Margaret McKeown
- Project LISTEN (www.cs.cmu.edu/listen)
- Carnegie Mellon University
- LRDC, University of Pittsburgh
- Funding IES
- 15th Annual Meeting of the Society for the
Scientific Study of Reading, June, 2009
1
3/15/2013
2Research question
- Conventional wisdom is to not give instruction on
morphology until perhaps grade four - However, kids do encounter words with prefixes
- As part of the IES-funded vocabulary grant, we
wanted to take opportunistic advantage of
prefixes when prefixes occur, explain them to
help vocabulary - How often do such opportunities occur?That is,
how often are prefixes good cues to meaning? - What happens when they do? That is, what is the
effect of reliable prefixes on reading times?
3Outline
- Whats a prefix?
- Linguistically
- Instructionally
- For this talk
- How reliable are prefixes as cues to meaning?
- What is the effect of prefixes on reading times?
4Whats a prefix?A linguistic definition
- affix Any element in the morphological structure
of a word other than a root(1). E.g. unkinder
consists of the root kind plus the affixes un-
and er. Affixes are traditionally divided into
prefixes, which come before the form to which
they are joined suffixes, which come after and
infixes, which are inserted within it. Others
commonly distinguished are circumfixes and
superfixes. - P.H. Matthews, The Concise Oxford Dictionary of
Linguistics, Oxford UP, 2007. p. 11.
5Whats a prefix?An instructional definition
- White, Sowell, and Yanagihara (1989) suggest the
following definition of prefixit is a group of
letters at the beginning of a word - misspellit changes the meaning
of the wordmis- incorrectly
spell incorrectlywhen you remove it, a word is
left misspell
6Whats a prefix?For this talk The ones to teach
- White et al. (1989) analyzed English words in
printed school materials. - They found that the 20 most common prefixes make
up 97 of prefixed words in English school texts.
- The 9 most frequent prefixes make up 76 of these
words. - Stahl and Nagy (2006) advise teaching the 9 most
common prefixes - 1. un- 6. non-
- 2. re- 7. in- (im-) into
- 3. in- (im- il- ir-) not 8. over- too much
- 4. dis- 9. mis-
- 5. en- (em-)
7A note on terminology
- In some places in this talk we will use these
terms to avoid undesired implications of prefix
and stem / root - Head letters at the beginning of a word
- Tail rest of letters in the word.
- Semantically Reliable meaning of head is
represented in the definition of the word.
8Outline
- Whats a prefix?
- Linguistically
- Instructionally
- For this talk
- How reliable are prefixes as cues to meaning?
- What is the effect of prefixes on reading times?
9How reliable are those nine prefixes as cues to
word meaning?
- Materials WordNet definitions and
relationsProject LISTEN story vocabularyAmerican
National Corpus vocabulary - Methods Calculate percentage of word typesfor
which one of the nine most frequent prefixes is
semantically reliable in a words definition - Head NONswimmer
- Tail nonSWIMMER
10Head that looks like prefix may not be
- displeased not pleased experiencing or
manifesting displeasure - dismay fear resulting from the awareness of
danger the feeling of despair in the face of
obstacles fill with apprehension or alarm
11Semantic Cues OperationalizedMatch Patterns in
Definitions
inanimate denoting nonliving things
rename assign a new name to
overproduction too much production or more
than expected
12Initial letters How semantically reliable are
they?
- Numbers range from 5-50, shockingly low
13Outline
- Whats a prefix?
- Linguistically
- Instructionally
- For this talk
- How reliable are prefixes as cues to meaning?
- What is the effect of prefixes on reading times?
14What is the effect of prefixes on reading time?
- Compare reading time (letters per second)on
reliable vs. not reliable words - MaterialsBest case head and tail both cues to
meaning unnaturalWorst case neither head nor
tail cues to meaning uncle - Next two slides well detail best and worst case
15Head is cue? Already discussedTail is cue? Two
questions enough
- Is the remainder a word? Rule out infidel,
distortion, - Are the remainder of the letters an antonym of
the original word? (only relevant for negative
prefixes)Rule in unjustly (defined as unjust
manner) since justly is antonym of
unjustly
16Best, worst, in between
Only 28.85 37.39 of words with one of the
nine head strings are prefixed words!
17Measures
- Reading times (milliseconds / letter)
- Data was logged by the Reading Tutor, an
automated tutor that uses automatic speech
recognition to listen to children read aloud - Words were displayed in authentic contexts
complete sentences in childrens texts - Children read aloud from modern and antebellum
texts into a microphone a bulbous flange, sold
in a blister pack, whose noise cancellation
serves as a talisman against speech recognition
errors - Compare best case vs. worst case unnatural vs.
uncle
18What is the effect of prefixes on reading times?
Predictions
- For students who dont read very wellwhether the
word is best case or worst caseshouldnt matter - Prefixes should help better readers
- That is, for students at higher reading
levels,reading times should be faster for best
case words than for worst case words
19Results
- Reading times were slower for best-case
wordsthan for worst-case words by 18.6 msec
(19)
20Due to practice, length, frequency?
21Due to practice, length, frequency?
22Due to practice, length, frequency?
- No. Reading times were slower for best-case for
first encounters by 17.4 msec (17)
23Due to practice, length, frequency?
24Due to practice, length, frequency?
- No. Reading times were still slower for best-case
for matched length range by 27.0 msec (27)
25Due to practice, length, frequency?
26Due to practice, length, frequency?
- No. Reading times were still slower for best-case
for matched freq. range by 28.4 msec (30)
27SummaryNot due to practice, length, frequency
- Reading times were still slower for best-case
when looking at various subsets
28Not due to practice, length, frequency when
looking at all 3 combined
- Reading times were still slower for
best-casethan for worst-case words by 48.8 msec
(51)
29Students had different numbers of encounters. Was
that it?
30Students had different numbers of encounters. Was
that it? No.
- Per-student average differs by 19.8 msec (18)
- p lt 0.001
31Filtering by frequency (LISTEN)yields similar
results
- Per-student average differs by 21.1 msec (19)
- p lt 0.001
32What was the effect by reading level?
- Predictioneffect for higher level readers, no
effect for lower level readers
33Best case slower across reading
levels!(Frequency in LISTEN corpus)
Sig. ? yes yes almost no no yes
no
34Best case slower across reading
levels!(Frequency in SUBTLEX)
- Best case slower for more students, p 0.023
35Potential explanation(s)
- Neighborhood effects? encourage --- entourage
- Context?
- Competition with tail disagree vs. agree?
- Competition with head disagree vs. dis-?
- Processing disagree takes more steps than
distance - At least some of these explanations rely
onreading time being affected by sublexical
structure.
36What about neighborhood effects?
- Currently investigating. Sample
Medler, D.A. Binder, J.R. (2005) MCWord An
On-Line Orthographic Database of the English
Language. http//neuro.mcw.edu/mcword
37Conclusions
- Initial letter sequences (heads) arent all that
reliable as cues to meaning - Yet reading times appear to be sensitive to real
vs. fake prefix, even for low reading levels - Cliffhanger Does this sensitivity provide a hint
that we could teach prefixes earlier? - Announcements
- Gregory Aist joins Iowa State faculty in fall
2009and co-founds journal, Dialogue and
Discourse ,on language beyond the single
sentence launching summer 2009
www.dialogue-and-discourse.org
38Thank you
39(No Transcript)
40Initial letters How good is the
operationalization?
- Sample of 100 Project LISTEN wordsthat are also
in WordNet
41Project LISTENs Reading Tutor
- An automated tutor that helps children learn to
read - See www.cs.cmu.edu/listen
- Displays stories and listens to children read
them aloud
- Provides help when necessary
- Uses automatic speech recognition to analyze
oral reading - Logs sessions in detail, including speech
recognizer output - Millions of read words in the aggregated
database
41