CHAPTER SEVENTEEN
MODELS OF READING COMPREHENSION
FOR PRIMARY SCHOOL STUDENTS
SONIA PEČJAK,1A SVJETLANA KOLIĆ VEHOVEC2
AND ANJA PODLESEK1B
1. Introduction
Investigation of reading comprehension has a long research tradition in
psychology. Its importance has, however, grown even more within the
frame of international reading literacy studies, e.g., PIRLS (Mullis, Martin,
Gonzales, & Kennedy, 2003) and PISA (Štraus, Repež, & Štigl, 2007).
Reading skills and abilities have always been important in the educational
context, and even more nowadays in the era of information society. These
skills represent an effective means of acceptance, organization, and usage
of information in different areas. Thus, reading skills and abilities to
comprehend written materials have become an important cross-curriculum
competency of learning to learn, which influences one’s educational
achievement, as the bulk of information in educational situations is
transferred through written materials. The aim of our study was to develop
a model of reading comprehension which would include different
psychological characteristics of students, and which can be promoted in
students by the teacher in order to achieve the competence “learning to
learn”.
1
Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia,
Professor of educational psychology (sonja.pecjak@ff.uni-lj.si).
B Associate professor (anja.podlesek@ff.uni-lj.si).
2 Full Professor, Faculty of Arts, University of Rijeka, Rijeka, Croatia
(skolic@ffri.hr).
A
308
Chapter Seventeen
1.1 What is reading comprehension?
Kintsch (1998) defined reading comprehension as a combination of processes
which arise from text, and integrative processes of that text in a reader's
knowledge structure which is indicated in an interrelated net of concepts.
Most of these processes are automated. Conscious control is necessary only
when the information in the text interferes with the reader's background
knowledge or when the reader does not possess sufficient knowledge to
form a mental representation of the text. Oakhill and Cain (2004) see
effective text comprehension also as an integrated and coherent
representation of a text’s contents. Namely, the reader has to integrate the
meanings of individual words, sentences and paragraphs, extract the text’s
key ideas, and make inferences in order to understand the text.
The key factors in a person's achievement in reading comprehension are:
(i) various environmental characteristics and features, especially school
environment (e.g., reading and writing instructions, enhancing students’
reading motivation) and family environment (e.g., the number of books a
family owns, the frequency of parents’ reading to children, parents’ reading
habits in general), and (ii) psychological characteristics of students
(cognitive, metacognitive, motivational, and emotional). We therefore
continue with a more detailed presentation of the students’ (meta)cognitive
and motivational-emotional variables that have great educational potential.
These variables can be significantly developed in students by a teacher’s
systematically training them and thus improving reading comprehension in
students. Variables that cannot be influenced at all or to a minor extent only
(e.g., intelligence, working memory capacity and inference competence)
were not included in the model.
1.2 Cognitive factors of reading comprehension
Researchers report numerous factors that are significantly connected with
reading comprehension and an individual's reading literacy. Numerous
studies have investigated the connection between an individual's reading
comprehension variables, such as vocabulary (Nagy, Diadikoy, &
Andersen, 1993), use of cognitive and metacognitive strategies (Meyer,
Brandt, & Bluth, 1980; Greasser, 2007) or specific strategies, e.g.,
summarizing (Van der Broek, Tzeng, Risden, Trabesco, & Basche, 2001)
and reading comprehension. Each of these variables is closely connected
with reading comprehension in younger and older students.
Models of Reading Comprehension for Primary School Students
309
2. Students' vocabulary
Students’ vocabulary indicates a knowledge of word meaning and, as
defined by Beck and McKeown (1991), includes a lexical knowledge of
words and the concepts related to those meanings. According to empirical
studies, vocabulary is one of the most powerful predictors of reading
comprehension: e.g., a child's vocabulary size in the preschool period as a
predictor of reading comprehension in early period of schooling (Muter al.,
2004; Share & Leiken, 2004); student’s vocabulary in the 3 rd and the 6th
grade as predictors of sixth-grade pupil's reading comprehension (Aarnoutse
and van Leeuwe, 1998). Some authors (e.g., Beck & McKeown, 1991;
Perfetti, 1994) believe that vocabulary directly influences comprehension,
whereas others point out that limited vocabulary does not necessarily lead
to comprehension difficulties (e.g., Pany, Jenkins, & Schrek, 1982), or, as
Cain, Oakhill, and Lemmon (2004) stressed, poor reading comprehension is
a consequence of interaction between poor vocabulary and poor
summarizing ability.
The majority of lexical knowledge models distinguish between
passive/receptive and active/productive vocabulary (Laufer & Goldstein,
2004). Researchers generally agree that passive/receptive vocabulary
normally precedes active knowledge. Passive knowledge is related to
listening and reading and reflects our ability to comprehend words that we
hear or read. At the level of vocabulary, passive word knowledge refers to
the ability to perceive the word form and recall its meaning. In contrast,
active word knowledge is linked to speaking and writing, and refers to the
ability to recall a pronounced or written word form for the meaning we want
to express. Quellette (2006) established that only active vocabulary is a
good predictor of reading comprehension, while, for example, passive or
receptive vocabulary correlates more with decoding speed than with reading
comprehension. This means that it is necessary to precisely define the
dimension of the vocabulary that is measured. However, Didović and KolićVehovec (2009) compared the active and passive word knowledge and its
relation to text comprehension in 11- and 15-year-old students and found
that passive word knowledge was a stronger predictor of text
comprehension (beta = .81 and .69, respectively) than active word
knowledge (beta = .51 and .43, respectively).
3. Metacognitive knowledge of reading
Metacognitive knowledge refers to a person’s declarative knowledge about
the interactions between person, task, and strategy characteristics (Flavel,
310
Chapter Seventeen
1979). Metacognitive knowledge about reading includes a person’s
knowledge about their reading, different types of reading tasks, and reading
strategies (Alexander, Graham, & Harris, 1998; Baker & Brown, 1984;
Paris, Lipson, & Wixson, 1983). Baker and Brown (1984) emphasised the
knowledge and regulation that students exercise over reading strategies.
Anderson and Armbruster (1982) found that poor readers do not skim,
reread, integrate information, plan ahead, and make inferences, as often as
more skilled readers do. Differences in metacognitive knowledge were also
found between different age groups. Myers and Paris (1978) examined the
metacognitive knowledge of children between 8 and 12 years of age and
found that the older children knew more about text structure, various goals
and using reading strategies to construct meaning and to resolve
comprehension failures than the younger children. Pazzaglia, Beni, and
Caccio (1999) found a significant improvement occurred in knowledge
about goals and strategies from 8 to 13 years, and Kolić Vehovec and
Bajšanski (2003) in metacognitive knowledge about reading strategies from
11 to 14 years. Furthermore, Kolić Vehovec and Bajšanski (2001)
established that metacognitive knowledge is a significant predictor of
elementary school students’ reading comprehension at different
developmental stages.
Knowledge and use of different (meta)cognitive reading strategies help
students learn from texts effectively. In order to learn effectively, a student
must activate his background knowledge, which helps him understand new
texts. Sometimes a student does not know how to relate his background
knowledge to new information, which does not allow comprehension or at
least interferes with the understanding of the text. The knowledge of
learning strategies that contribute to the attainment of a learning goal and
conscious use of such strategies help identify relevant information from text,
recall long-term knowledge, monitor and direct the use of these strategies in
order to model comprehension. Numerous interventional studies show that
planned training can improve students’ reading comprehension. Cromley
and Azevedo (2007) reported that 51 interventional studies gave positive
results.
4. Summarizing strategy
Summarizing represents one of the most important after-reading
strategies which indicate one's actual stage of reading comprehension.
While summarizing, a reader must be able to identify the main ideas in a
text, assess the importance of particular information, and incorporate the
relevant information into a coherent entity – an abstract (Anderson &
Models of Reading Comprehension for Primary School Students
311
Armbruster, 1982; Friend, 2001). Johnston and Afflebach (1985) claimed
that the ability to identify the main ideas in a text is the essence of reading
comprehension. Text summarizing requires omitting unimportant
information, as well as condensing and organizing text information.
Summarizing is more effective when students use their own words to form
the connections between the concepts and relate the concepts to their own
prior knowledge (Wittrock, 1990).
Many studies have found that summarizing improves students’
comprehension and helps students monitor their comprehension
(Armbruster, Anderson, & Ostertag, 1987; King, 1992; Symons, Richards,
& Greene, 1995; Wittrock, 1990). Wittrock (1990) suggested that the
process of generating summaries helps readers build relations between the
concepts contained in a text, as well as link these concepts to prior
knowledge. Others have suggested that summarizing improves
comprehension by promoting self-monitoring during reading (Brown &
Day, 1983; Palincsar & Brown, 1984; Paris & Lindauer, 1982), which may
signal comprehension breaks and invite readers to initiate fix-up strategies
to repair breaks in comprehension (Winne & Hadwin, 1998). Thiede and
Anderson (2003) demonstrated that summarizing of texts enhances
comprehension by improving metacomprehension accuracy and increasing
the effectiveness of self-regulated study. Yussen (1982) found out that
children’s ability to state the main topic of a text increases markedly from
2nd to 6th grade. Younger students and poor readers often demonstrate
difficulties with summarizing strategy. Correlation coefficients between
reading comprehension and the ability to summarize are in the range from
.20 to .30 for elementary school students, and around .31 for secondary
school students (Kolić Vehovec & Bajšanski, 2001).
4.1 Motivational-emotional factors of reading comprehension
In studies investigating the factors connected with reading comprehension,
motivational factors are consistently recognized to be important. They
influence the intensity, perseverance, and direction of one's reading
behaviour. Schneider (2001) emphasized that motivational factors explain
differences in reading achievement of highly competent students. Along
with Eccles’ (1983) statement that beliefs, values and goals can be
conceptualized as different questions students can ask themselves,
Wigfield (1997) stated that the questions most directly related to
motivation for reading are: Can I be a good reader? and Do I want to be a
good reader and why? The answer to the first question captures the
children’s ability beliefs or perceived competency, and the answer to the
312
Chapter Seventeen
second question captures the perceived task value, including interest value,
as well as intrinsic and extrinsic motivation.
4.2 Perceived competency
Perceived competency has been one of the most widely investigated
elements among motivational factors in the last decade. This concept is
congruent with Bandura’s self-efficacy (1997), defined as an individual's
belief that one is capable of performing in a certain manner to attain certain
goals. Congruent with this definition, perceived reading competency is a
person's belief in their own reading capacities or belief to be able solve
reading tasks and attain goals by reading. The difference between the two
concepts is that there is no comparison with others included in self-efficacy,
while the latter is included in the concept of perceived self-efficacy (e.g., a
student is convinced that he or she will be able to solve a reading task well
through hard work, but compared to other students he or she does not
perceive him or herself as a good reader).
Perceived reading competency is positively related to: (i) the task choice
– the more one feels competent, the higher the challenge reading tasks
represent for them and so they tend to choose more difficult tasks and use
deeper learning strategies (Dweck, 1999; Eccles & Wigfield, 2002); (ii)
effort and perseverance – the more one is confident in oneself, the greater
the amount of effort one is willing to invest in reading comprehension and
will do it with more perseverance; and (iii) achievement – higher
competency is directly related to better reading achievement (Conlon,
Zimmmer-Gembeck, Creed, & Tucker, 2006; Gambrell, Palmer, Codling,
& Mazzoni, 1996).
Different studies point to a direct connection between perceived reading
competency and reading comprehension (Chapman & Tunmer, 1995;
Eccles & Wigfield, 2002). Pečjak, Bucik, Gradišar and Peklaj (2006) found
that perceived reading competency is significantly related to reading
efficiency of third (r = .44) and seventh grade primary school students (r =
.21). Similarly, Conlon et al. (2006) reported a significant and even higher
correlation between perceived competency and reading comprehension in
12-year-old students (r = .53).
4.3 Interest
Among the motivational factors connected with reading comprehension,
reading interest is commonly mentioned. Deci (1998) established a positive
correlation between reading comprehension and reading interest and
Models of Reading Comprehension for Primary School Students
313
intrinsic motivation for reading. Usually, researchers distinguish between
personal/content and situational interest (e.g., Schiefele, 2001). Situational
interest is defined as a content-specific motivational variable that is
determined by emotional and value beliefs in connection with the content
of reading. In this manner, emotional beliefs are associated with enjoyment
while reading certain contents, and value beliefs with one’s estimation of
the importance of reading. Schiefele and Krapp (1996) established that
content interest is connected with deeper learning approaches/strategies
which include recall of main ideas and coherence of recalled ideas.
Schiefele (1996) also found a significant connection between personal
interest and reading comprehension at a concurrent control of cognitive
factors (r = .27). Guthrie et al. (1998) found out that the amount of reading
(as a personal interest indicator) predicted reading comprehension in groups
of 3rd, 5th and 10th grade students, even when a number of variables that
correlate with reading comprehension (prior knowledge, reading efficacy)
were controlled.
Hidi (1990, 2001) showed in her meta-analytical studies that reading
interest had an important effect on reading comprehension at the level of
cognitive organization of reading material and was also important for
memorizing and recall. Similar are the findings by Renninger (1992), while
others, for example Alexander, Murphy, Woods, Duhon, and Parker (1997),
suggest that this connection is probably due to the fact that interest prolongs
learning time and stimulates the use of deeper comprehension strategies.
Namely, Shiefele (1991, 2001) established that interest is the factor that
motivates readers to get involved in reading and to try to achieve better
comprehension. Interest is the activator of the strategies that influence
deeper processing. Altogether, interest is also significantly connected with
other motivational factors, such as involvement (flow) and enjoyment. Both
result in comprehension. In contrast with these findings, Köller, Baumert,
and Schnabel (2000) did not find a significant correlation between interest
and reading achievement at controlled concurrent background knowledge.
4.4 Intrinsic motivation
Intrinsic motivation refers to being motivated and curious to carry out an
activity for its own sake. Thus, intrinsic motivation has some parallels with
the interest aspect of task value as defined by Eccles et al. (1983). One
aspect of intrinsic motivation is becoming completely involved in the
current activity, which Csikszentmihalyi (1990) describes as flow. Many
readers have experienced flow while reading a book, losing track of time
and self-awareness. Intrinsic motivation is also described in Oldfather´s
314
Chapter Seventeen
concept (1992) of continuing impulse to learn, which is characterized by
intense involvement, curiosity and a search for understanding. Applying this
concept to reading, it could be said that a reader’s engagement in reading
will be greatly facilitated when they are intrinsically motivated to read.
4.4 Emotions while reading
Reading comprehension is also affected by children’s attitudes toward
reading, generally defined as an individual´s feelings about reading
(Alexander & Filler, 1976). These feelings should influence how much
individuals involve themselves in reading. Therefore, attitudes toward
reading should relate to reading motivation (Matthewson, 1994). However,
the effect of emotions and mood on text comprehension is probably indirect
through their influence on different cognitive and metacognitive factors. In
this manner, emotions would result in reading comprehension through their
effect on working memory (Ellis & Moore, 2000). Negative emotions
preoccupy working memory in such a manner that an individual is more
concerned with his own negative emotions than with cognitive task
demands (Ellis & Ashbrook, 1988; Seiber & Ellis, 1991). Depressed-mode
state can produce poorer recall in numerous situations, including variations
in awareness (Hertel & Hardin, 1990) and elaborative encoding (Potts,
Camp, & Coyne, 1989).
Moreover, the attitude towards reading is an important factor in reading
achievement (McKenna, 2001; McKenna & Kear, 1990; McKenna, Kear,
& Ellsworth, 1995). However, it has been emphasized that attitudes are a
very complex factor – they have emotional connotations as well as cognitive
components and are experience-based. In their longitudinal study, Kush and
Watkins (1996) established that a positive attitude towards reading
significantly decreases during schooling. Although the decline is greater for
boys than for girls, in both genders there is also a decrease in recreational
and educational reading.
Even more important are findings from studies that use regression
analysis procedures to determine the relation between different variables
and reading comprehension. A relation between reading comprehension and
metacognition, learning strategies, background knowledge, and decoding
speed was found by Artlet, Schiefele, and Schneider (2001) for secondary
school students and by Ehrlich, Kurtz-Costes and Loridant (1993) for
elementary school students. Guthrie, Wigfield, Metsala, and Cox (1999)
found a connection between students’ background knowledge, vocabulary
and reading comprehension.
Models of Reading Comprehension for Primary School Students
315
5. Study
In our study, we tried to ascertain how cognitive, metacognitive,
motivational, and emotional factors affect reading comprehension in
younger and older primary school students (5 th and 9th grades). Following
different theoretical findings and empirical evidence from studies which
investigated the role of specific factors in reading comprehension, we
proposed a model of an indirect effect of motivational and emotional
variables (reading interest, perceived competency, flow and reading
emotions) on reading comprehension through (meta)cognitive variables and
of a direct effect of cognitive and metacognitive variables (vocabulary,
summarizing, and metacognitive knowledge) on reading comprehension.
Alexander et al. (1997) suggested that the effect of interest on text
comprehension is probably due to the fact that interest prolongs learning
time and stimulates the use of deeper comprehension strategies.
Accordingly, we proposed that interest affects vocabulary and summarizing
skill/strategy. Since perceived reading competence is related to effort and
perseverance (Dweck, 1999; Eccles & Wigfield, 2002), we predicted its
significant effect on gaining vocabulary and metacognitive knowledge and
developing summarizing skills. We also proposed a direct effect of
perceived competence on reading comprehension only for competency,
based on the empirical evidence reported by different studies (Chapman &
Tunmer, 1995; Eccles & Wigfield, 2002). Taking into account the
proposition that emotions affect reading comprehension through their effect
on working memory (Ellis & Moore, 2000), we propose that emotions may
have an effect on summarizing and metacognitive knowledge. In the reading
comprehension model for older primary school students, flow was also
included as an aspect of intrinsic motivation. We propose that reader
engagement facilitated by flow will enhance vocabulary and metacognitive
knowledge. The effect of cognitive and metacognitive variables on text
comprehension was already well documented and described in the
introduction. The proposed reading comprehension models for younger and
older students are presented in Figure 17-1.
316
Chapter Seventeen
Figure 17-1. Proposed reading comprehension model for primary school students.
5.1 Participants
A total of 885 students from nine Slovenian and Croatian primary schools
participated in the study. The first sample included 380 fifth grade students
from Slovenia and fourth grade students from Croatia (students enter
primary school in Slovenia at 6 years and in Croatia at 7 years).
The students were the same age (M = 10.7 years) and had been taught to
read for equally long periods of time because students start learning to read
in the second grade in Slovenia.
The second sample included 505 students from the finishing year (of
primary school) - ninth/eighth grade students from Slovenian and Croatian
primary schools. The average age was 14.6 years. No significant differences
in reading comprehension were found among the Croatian and Slovenian
students neither in the younger students (Slovenian students: M = 9.3; SD =
2.81, Croatian students: M = 9.7; SD = 2.83, F(298) = 1.462; p = .228) nor
in the older students (Slovenian students: M = 10.57; SD = 2.25, Croatian
students: M = 10.95; SD = 2.51, F(379) = 2.135; p = .145). Therefore, we
treated the Croatian and Slovenian students as a joint sample.
5.2 Procedure
Reading comprehension was measured using two exploratory texts.
Vocabulary was measured by Hershel's (1963) Test of Reading Vocabulary: Level 4 for the younger students and Level 8 for the older
students. It comprises 40 tasks. The students have to answer the questions
by choosing the appropriate word from among five choices. The following
is a sample item: “The opposite of near is: A – here, B – beneath, C – now,
Models of Reading Comprehension for Primary School Students
317
D – far, E – inside”. The test time is limited to 10 minutes. The internal
consistency alpha coefficient was .86.
Summarizing was assessed with three short texts: Water Pollution (120
words), Traffic (99 words), and Healthy Food (110 words). The students are
asked to summarize the main ideas from the texts after reading them. The
criteria for the answers were adapted from Kozminsky and Graetz (1986)
and Friend (2001). Three semantic units, which represented the main ideas
of the text, were identified in each text. The number of points received for
each text equaled the number of correctly summarized units. Two
independent raters assessed the students' abstracts. If the scores differed, the
raters had to reach a consensus on their scoring. The internal consistency for
this test was .86.
Metacognitive Knowledge Questionnaire was constructed according to
Gunning’s questionnaire (1996) and Schmitt’s questionnaire of
metacognitive knowledge (1990) for the purposes of this study. It measures
students' metacognitive knowledge about reading in general and academic
reading in particular, especially the awareness of using different reading
comprehension monitoring strategies. The questionnaire has 14 items with
multiple-choice questions. Students have to choose the answer that in their
opinion best describes the main purpose of reading, and they have to display
a knowledge of different reading and learning strategies.
Reading Motivation was measured using the Reading Motivation
Questionnaire for Young Students (RMQYS) (Peklaj, Bucik, 2003 as cited
in Pečjak et al. 2006). It comprises 28 items. The students use a 3-point
pictorial scale to assess how valid a statement is for them (1– not at all true
for me; 3 – always true for me). An exploratory factor analysis revealed
three factors: (i) interest (Cronbach alpha = .81); (ii) (in) perceived
competency (Cronbach alpha = .72); and (iii) self-efficiency in oral reading
(Cronbach alpha = .63). The items are scored according to the manual, with
higher scores implying a more expressed motivational factor. Only the first
two factors were included in the model due to a lower reliability of the third
one. The adapted version of The Motivation for Reading Questionnaire
([MRQ]; Wigfield & Guthrie, 1997), composed of 40 items, was used for
the older students. They were asked to assess the items on a 5-point Likert
scale (1- not at all true for me; 5 – always true for me). Factor analysis
showed three factors: interest for reading (Cronbach alpha = .88); flow
(Cronbach alpha = .88); and perceived competency (Cronbach alpha = .67).
Elementary Reading Attitude Survey (ERAS) by McKenna and Kear
(1990) measures the emotional dimension of reading. The questionnaire
contains 20 items yielding two scores: (i) a recreational reading score
(Cronbach alpha = .87); and (ii) an academic reading score (Cronbach alpha
318
Chapter Seventeen
= .86). The students rated their emotions during reading on a 4-point scale
(1 – very bad, 4 – very good). There was only a total reading score included
in the study - - the sum of the recreational and the academic reading scores.
Path analyses were performed using LISREL 8.8 to analyze the relations
between variables and to verify whether our data fit the proposed model.
Because most of the variables were not normally distributed, we carried out
calculations on their normalized scores. After eliminating students with
missing data on one or more variables from the samples, the data from 323
younger and 415 older students were analyzed separately. Covariance
between the variables was entered into a model, and the maximum
likelihood method was used for estimating the parameters. We allowed for
the correlation between exogenous variables and for correlated errors in
intermediary variables.
5.3 Results
The aim of our study was to determine how the selected cognitive,
metacognitive, motivational and emotional factors affect reading
comprehension in younger and older primary school students. A model of
the direct and indirect effects of these factors on reading comprehension was
proposed (see Figure 17-1). The goodness of fit of the proposed model was
examined separately for the younger and the older students. The results of
path analyses are two most parsimonious models, one for the younger
(Figure 17-2) and one for the older students (Figure 17-3). The arrows show
the direction of the effect between variables, and the values on the arrows
correspond to standardized regression coefficients, which show the
predictive power of each predictor, if participants are equalled with regard
to other variables. Regression coefficient shows the amount of change in
standard deviation of a criterion variable if the value of the effecting variable
increases for one standard deviation.
In Figure 17-3 all standardized regression coefficients are statistically
significant at the level of p < .05. Coefficients show satisfactory fit of the
proposed model to the data, χ 2(15) = 10.90; p = .09; RMSEA = .05, 90%
confidence interval for RMSEA = .00 –.110 AGFI = .96; NNFI = .97.
Models of Reading Comprehension for Primary School Students
319
Figure 17-2. A reading comprehension model for fifth grade students.
The factors included in the model explained 37% of variance of reading
comprehension among the younger students. The direct effects of all
(meta)cognitive factors on reading comprehension appeared significant vocabulary (.46), summarizing (.17), and metacognitive knowledge (.15).
As in many previous studies (e.g., Aarnoutse & van Leeuwe, 1998; Beck &
McKeown, 1991; Pečjak, 1989; Perfetti, 1994), the extent of vocabulary
was also confirmed to be the most powerful predictor of reading
comprehension in our study. Somewhat weaker was the relation between
reading comprehension and the ability to summarize. Still, mastering the
strategies of summarizing gives students an ability to detect important
information within a large amount of information at the micro level and to
combine them into a meaning (information at the macro level). This
represents the key process of reading comprehension (Kintsch & van Dijk,
1978). The results of other studies showed that a knowledge of reading
strategies which can lead the reader through the text and help them monitor
the process of comprehension improves their understanding of the text
contents (e.g., Alexander, Graham, & Harris, 1998). However, students at
the age of 10 have not yet mastered the summarizing skill well enough to
improve comprehension to any greater degree. As Pintrich and Zusho
(2002) discussed, when children start using the strategy they do not really
benefit from it. After they have gained a considerable amount of practice
and experience, they are able to use the strategy in a more adaptive and
successful way.
Further on, we found that reading interest, as a motivational factor, has
an indirect influence on reading comprehension through vocabulary (.25).
Emotions, on the other hand, have an indirect effect on reading
comprehension through summarizing. Simultaneously, we found close
320
Chapter Seventeen
intercorrelations between emotions during reading and reading interest
(.66). These results show the importance of emotions in the process of
reading, while they influence (meta)cognitive factors directly (through
summarizing), as well as indirectly (through interest). Such high
intercorrelations with interest confirm the emotional dimension as one of
the structural dimensions of reading interest. Reading interest had a
significant connection only with vocabulary (.25). This means that students
with greater reading interest have a broader vocabulary, which was
confirmed in the previous studies as well. Namely, greater reading interest
leads to more frequent reading, and if they read more often, readers absorb
a larger amount and more diverse reading material which they want to
comprehend. Reading different reading materials leads readers to expand
their (at least receptive) vocabulary. Perceived competency was not directly
related to (meta)cognitive variables. The obtained intercorrelations were
low and not statistically significant, which leads us conclude that perceived
competence in younger students is more a consequence of their successful
text comprehension than its cause. This could also be a sign of a reader’s
attributions of achievement in reading comprehension, which could be
important factors of competency. Teachers have an important role in this
respect.
If
teachers
do
not
reflect
on
the
reading
achievement/comprehension with their students, if they do not emphasize
the importance of vocabulary and metacognitive knowledge especially, then
their students will not judge their own reading effectiveness/efficiency
through the meaning of those factors.
Figure 17-3. A reading comprehension model for ninth grade students.
Models of Reading Comprehension for Primary School Students
321
Figure 17-3 illustrates the final model of the relations between
metacognitive, cognitive, motivational, and emotional variables to reading
comprehension of the ninth grade students. All standardized regression
coefficients were statistically significant at the level of p <.05. The model
shows adequate goodness of fit to the data, χ2(12) = 12.04; p = .14; RMSEA
= .04, 90% confidence interval for RMSEA = .00–.07; AGFI = .96; NNFI
= .98.
When the model was applied to the older students, the goodness of fit
was somewhat poorer – we were able to explain 23% of variance in reading
comprehension. Among the variables directly related to reading
comprehension, two were (meta)cognitive – vocabulary and metacognitive
knowledge. Vocabulary (with a path coefficient of .40) was found to be a
solid predictor of good reading comprehension, and poor vocabulary can
result in reading comprehension difficulties. This assumption is also
supported by some other studies, which included samples of older primary
school students (e.g., Pečjak, 1989; Sternberg, 1987; Thorndike, 1973;
Walczyk & Taylor, 1996). Metacognitive knowledge (.17) was another
important factor of reading comprehension in the older students. This
indicates that being aware of different strategies and using them before,
during, and after reading is probably even more important for older students
than for younger ones, as they are exposed to much more diversified reading
material, have to attain higher reading goals or complete various reading
tasks which demand the use of different strategies. We can conclude that
expanding students’ vocabulary and their knowledge of different reading
strategies could result in better reading comprehension at the end of primary
school. It is also worth noting that other authors established a higher
correlation between specific learning strategies and reading comprehension
of a specific kind of text/tasks than between general learning strategies and
reading comprehension of a text in general (Artlet, 2000; O'Neal & Abedi,
1996). Although students aged 15 are capable of using strategies, they still
might not do so, because of the decline in their intrinsic motivation for
learning (Pintrich & Zusho, 2002).
Among the motivational variables, a strong intercorrelation (.64) was
found between reading interest and flow. Flow (involvement, Wigfield &
Guthrie, 1997) represents an extremely powerful form of intrinsic reading
interest. This high intercorrelation also confirms that reading interest and
flow are two very similar constructs. Furthermore, a strong connection was
found between motivational and emotional variables (between emotions
during reading and reading interest r = .55; between emotions during
reading and flow r = .69).
322
Chapter Seventeen
An interesting finding was that of all motivational-emotional factors and
(meta)cognitive factors only flow and competency were significantly
related to other variables: the path coefficient from flow to vocabulary was
.21, from flow to metacognitive knowledge .15, and from competency to
summarizing .13. The correlations between flow and (meta)cognitive
factors probably indicate that there are reciprocal relationships between
these variables. A reader involved in reading to such an extent that time and
space are irrelevant for them will read more and will therefore acquire a
richer vocabulary. This type of reading is also accompanied by more
positive emotions (high intercorrelation between emotions and flow: .69).
Interactive functioning of cognitive and emotional factors enhances reading
motivation and results in better reading comprehension (Schallert & Reed,
1997). In our study, interest in reading was not connected with
(meta)cognitive factors or with reading comprehension, contrary to other
empirical studies which confirmed such a relationship (Artlet, Schiefele, &
Schneider, 2001; Pečjak & Gradišar, 2002; Wigfield & Guthrie, 1997). The
most plausible reason was a high intercorrelation of interest and flow (.64),
meaning that interest can have an indirect effect on vocabulary and
metacognitve knowledge and, with the latter two, on reading comprehension
through flow.
On the other hand, our findings are supported by the study by Ainley,
Hillman, and Hidi (2002), who found that only low or moderate positive
correlations existed between measures of personal (more general) and
content (more specific) reading interest. In their model, students’ personal
interest was not a significant predictor of content interest. This is why
teachers should create learning situations that trigger students’ situational
interest (such as choosing between two similar texts), and provide them with
feedback that would help students maintain their attention and promote
positive emotions. All of this could result in greater personal interest (Hidi,
2006).
6. Conclusions and pedagogical implications
Some important conclusions and pedagogical implications can be derived
from our study.
We confirmed the model of motivational-emotional and (meta)cognitive
factors of reading comprehension. The proposed model, however, better
explained the variance in reading comprehension in the younger than in the
older students (37% of variance in reading comprehension in the younger
students vs. 23% of variance in reading comprehension in the older
students).
Models of Reading Comprehension for Primary School Students
323
The variables included in the model were those we proposed to be easier
for the teachers to systematically develop in the classroom.
Therefore, we find it is sensible to develop vocabulary and, more
importantly, metacognitive awareness and (summarizing) strategies in
younger students and not only in the final years of primary school. It seems
as if students’ characteristics which teachers will find difficult if not
impossible to influence (e.g., general intelligence, inference generation,
working memory capacity) have a more important role in reading
comprehension. For example, Rončević Zubković (2008) found that
intelligence, short-term and working memory explained 50% of variance of
text comprehension in students aged 14.
We established that motivational and emotional factors are strongly
interconnected; therefore, it seems that one should not divide these factors
artificially but rather treat them as a single entity.
According to our model, vocabulary had the strongest effect among the
cognitive factors. Based on these findings, we believe that increasing
students’ vocabulary may lead to greater reading comprehension. It is
therefore important that teachers enable their students to enlarge their active
and receptive vocabulary (general and more specific, which is important for
the comprehension of written materials in different courses). Teachers can
also systematically promote vocabulary to help students at risk, for example,
students from socially unprivileged environments. Studies show that
vocabulary is a factor that prevents such students from comprehending
written material (Dickinson, McCabe, Anastasopoulos, Peisner-Feinberg, &
Poe, 2003). The deficit, however, persists through the first years of
schooling (Biemiller, 2005). Although a direct connection between
summarizing and reading comprehension was only significant for the
younger students and an indirect effect for the older students, it is also
important for teachers and school psychologists to stress the importance of
learning different reading strategies to achieve better reading
comprehension and improve academic achievement. Moreover, it is even
more important to model the use of these strategies and to create such
learning situations in which students would benefit from the use of these
strategies, and consequently become more willing to use them. Since
competency affects summarizing, it is important for teachers to create
conditions in which all students could experience success in reading.
Competency was the only motivational factor that was directly
connected with reading comprehension in the older students. Although the
path coefficient was not statistically significant, this connection shows the
importance of grading reading task and text appropriately when working
with students who have reading difficulties.
324
Chapter Seventeen
Teachers should help these students attain reading goals and strengthen
their reading competency. Individualized work can include adaptation of
reading goals, choosing different reading materials, and different teaching
methods. Since a lack of motivation in the older students was found to be
an important factor of delay in metacognitive knowledge and reading
strategy use important for learning and academic success, teachers should
become aware of this fact and put greater effort into motivating students to
read h by offering higher elementary school students a variety of texts that
could attract their interest and induce positive emotional states during
reading. Developing positive attitudes towards reading will stimulate
students to read with engagement and make better use of reading strategies,
such as summarizing, ultimately developing the strategic reading necessary
for successful at school (Kozminsky & Kozminsky, 2001). Strategic reading
reflects metacognition and motivation, because readers need to know the
strategies and be willing to use them. It is the basis for the self-regulation of
learning that develops autonomy and control by the student who monitors,
regulates, and directs the actions toward learning goals, expanding
expertise, and self-improvement (Zimmerman, 2000). Self-regulated
students monitor the efficacy of their learning strategies and replace
inefficient strategies with different ones. The role of teachers in developing
efficient readers is crucial, because teachers provide competent models for
reading strategy use and important motivators for students’ engagement in
strategic behaviours.
References
Aarnoutse, C., & van Leeuwe, J. (1998). Relation between reading
comprehension, vocabulary, reading pleasure, and reading Frequency.
Educational Research and Evaluation, 4(2), 143–166.
Ainley, M., Hillman, K., & Hidi, S. (2002). Gender and interest processes
in response to literary texts: situtational and individual interest. Learning
and Instruction, 12, 411–428.
Alexander, P.A., Graham, S., & Harris, K.R. (1998). A perspective on
strategy research: Progress and prospects. Educational psychology
Review, 10, 129-154.
Alexander, P. A., Murphy, P. K., Woods, B. S., Duhon, K. E., & Parker, D.
(1997). College instruction and concomitant changes in students'
knowledge, interest, and strategy use: A study of domain learning.
Contemporary Educational Psychology, 22, 125–146.
Alexander, H. & Filler, R.C. (1976). Attitudes and reading. Newark, DL:
International Reading Association.
Models of Reading Comprehension for Primary School Students
325
Alfassi, M. (2004). Reading to learn: Effects of combined strategy
instruction on high school students. Journal of Educational Research,
97, 171–184.
Anderson, T.H. & Armbruster, B.B. (1982). Reader and text-studying
strategies. In W. Otto & S. White (Eds), Reading Expository Material
(pp. 219-242). London: Academic Press.
Armbruster, B. B., Anderson, T. H., & Ostertag, J. (1987). Does Text
Structure/Summarization Instruction Facilitate Learning from
Expository Text? Reading Research Quarterly, 22(3), 331–346.
Artlet, C. (2000). Strategisches Lernen. Münster: Waxmann.
Artlet, C., Schiefele, U., & Schneider, W. (2001). Predictors of reading
literacy. European Journal of Psychology of Education, 16(3), 363–383.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York:
Freeman.
Baker, L., Brown, A.L. (1984): Metacognitive skills and reading. U P.D.
Pearson (Ur.), Handbook of reading research, 353-394. New York:
Longman.
Beck, I., & McKeown, M. (1991). Conditions of vocabulary acquisition. In
R. Bar, M. L. Kamil, P. B. Mosenthal, & P. D. Pearson (Eds.), Handbook
of reading research: Vol 2 (pp. 789–814). White Plains, NY: Longman.
Biemiller, A. (2005). Size and sequence in vocabulary development:
Implications for choosing words for primary grade vocabulary
instruction. In A. Hiebert, & M. Kamil (Eds.), Teaching and learning
vocabulary: Bringing research to practice (pp. 223–242). Mahwah, NJ:
Erlbaum.
Brown, A. L. & Day, J. D. (1983). Macrorules for summarizing texts: The
development of expertise. Journal of Verbal Learning & Verbal
Behavior, 22(1), 1–14.
Cain, K., Oakhill, J. (2004). Reading Comprehension Difficulties. V T.
Nunes, P. Bryant (eds.). Handbook of children's literacy (pp. 313-338).
Dordrecht, NL: Kluwer Academic Publisher
Cain, K., Oakhill, J., & Lemmon, K. (2004). Individual differences in the
inference of word meanings from context: The influence on reading
comprehension, vocabulary knowledge, and memory capacity. Journal
of Educational Psychology, 94(4), 671–681.
Chapman, J. & Tunmer, W. (1995). Development of young children’s
reading self-concepts: An examination of emergent subcomponents and
their relationship with reading achievement. Journal of Educational
Psychology, 87, 154–167.
Conlon, E. G., Zimmmer-Gembeck, M .J., Creed, P. A., & Tucker, M.
(2006). Family history, self-perceptions, attitudes and cognitive abilities
326
Chapter Seventeen
are associated with early adolescent reading skills. Journal of research
in reading, 29(1), 11–32.
Cromley, J. G., & Azavedo, R. (2007). Testing and Refining the Direct and
Inferential Mediation Model of Reading Comprehension. Journal of
Educational Psychology, 99, 311–325.
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience.
New York: Harper and Row.
Deci, E. L. (1998). The relation of interest to motivation and human needs
– The self-determination theory viewpoint. In L. Hoffmann, A. Krapp,
K. A. Renninger, & J. Baumert (Eds.), Interest and learning (pp. 146–
162). Kiel: Institute for Science Education, University of Kiel.
Dickinson, D. K., McCabe, A., Anastasopoulos, L., Peisner-Feinberg, E. S.,
& Poe, M. D. (2003). The comprehensive language approach to early
literacy: The interrelationships among vocabulary, phonological
sensitivity, and print knowledge among preschool-aged children.
Journal of Educational Psychology, 95(3), 465–481.
Didović, M., & Kolić Vehovec, S. (2009). Različiti aspekti poznavanja
riječnika i razumijevanja teksta kod učenika osnovne škole [Different
aspects of vocabulary knowledge and text comprehension in elementary
school students]. Psihologijske teme, 18(1), 99-117.
Dweck, C. (1999). Self-theories: The role in motivation, personality, and
development. Philadelphia, PA: Psychology Press
Eccles, J.S. (1983). Expectancies, values and academic behaviors. In J.T.
Spence (Ed.), Achievement and achievement motives (pp. 75-146). San
Francisco: Freeman.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values and goals.
Annual Review of Psychology, 53, 109–132.
Ehrlich, M.F., Kurtz-Costes, B. & Loridant, C. (1993). Cognitive and
motivational determinants of reading comprehension in good and poor
readers. Journal of Reading Behavior, Vol 25(4), 365-381.
Ellis, H. C., & Ashbrook, P. W. (1988). Resource allocation model of the
effects of depressed mood states on memory. In K. Friedler, & J. Forgas
(Eds.), Affect, cognition and social behaviour (pp. 25–43). Toronto,
Canada: Hogrefe.
Ellis, H. C., & Moore, B. A. (2000). Mode and memory. In T. Daglesish, &
M. Power (Eds.), The handbook of cognition and emotion (pp. 34-46).
Chichester, England: John Wiley and Sons, Ltd.
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory.
Psychological Review, 102, 211–245.
Models of Reading Comprehension for Primary School Students
327
Flavell, J. H., & Wellman, H. M. (1977). Metamemory. In R. V. Kail, & W.
Hagen (Eds.), Perspectives on development of memory and cognition
(pp. 3–31). Hillsdale, NJ: Erlbaum.
Flavell, J. H., Miller, P. H., & Miller, S. A. (1993). Cognitive development.
Englewood Cliffs, NJ: Prentice Hall.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area
of cognitive–developmental inquiry. American Psychologist, 34(10),
906–911.
Friend, R. (2001). Effects of strategy instruction on summary writing of
college students. Contemporary Educational Psychology, 26(1), 3–24.
Gambrell, L. B., Palmer, B. M., Codling, R. M., & Mazzoni, S. A. (1996).
Assessing motivation to read. The Reading Teacher, 49(7), 518–533.
Graesser, A. C. (2007). An introduction to strategic reading comprehension.
In D. McNamara (Ed.), Reading comprehension strategies: Theories,
interventions, and technologies (pp. 3-26). Mahwah, NJ: LEA.
Gunning, T. G. (1996). Creating reading instruction for all children.
Boston: Allyn & Bacon.
Guthrie, J. T., Wigfield, A., Metsala, J. L., & Cox, K. E. (1999).
Motivational and cognitive predictors of text comprehension and
reading amount. Scientific studies of reading, 3(3), 231–256.
Hershel, T. M. (1963). Test of Reading Level 3 – Elementary Form. In T.
M. Herschel (Ed.), The 20th Yearbook of the National Council on
Measurement in Education. Ann Arbor, MI: SGSR.
Hertel, P.T., & Hardin, T. S. (1990). Remembering with and without
awareness in a depressed mood: Evidence of deficit of initiative. Journal
of experimental Psychology: General, 119, 45–59.
Hidi, S. (1990). Interest and its contribution as a mental resource for
learning. Review of Educational Research, 60(4), 549–571.
Hidi, S. (2001). Interest, reading, and learning: theoretical and practical
consideration. Educational Psychology Review, 13(3), 191–209.
Hidi, S. (2006). Interest: A unique motivational variable. Educational
research review, 1, 69–82.
King, A. (1992). Comparison of self-questioning, summarization, and note
taking review as strategies for learning from lectures. American
Educational Research Journal, 29, 303-323.
Kintsch, W. (1998). Comprehension: A Paradigm for cognition.
Cambridge, UK: Cambridge University Press.
Kintsch, W., & van Dijk, T. A. (1978). Toward a Model of Text
Comprehension and Production. Psychological Review, 85, 363–394.
Kolić Vehovec, S., & Bajšanski, I. (2003). Children's metacognition as
predictor of reading comprehension at different developmental levels. In
328
Chapter Seventeen
Proceedings of the 12th European conference on Reading (pp. 216–222).
Dublin: Reading Association of Ireland.
Köller, O., Baumert, J., & Schnabel, K. (2000). Zum Zusammenspiel von
schulischen Interesse und Lernen im Fach Mathematik: Längschnittanalysen
in der Sekundarstufen I und II. In U. Schiefele, & W. P. Wild (Eds.).
Interesse und Lernmotivation. Untersuchungen zur Entwicklung,
Förderung und Wirkung (pp. 163–181). Münster: Waxmann.
Kozminsky, E. & Kozminsky, L. (2001). How do general knowledge and
reading strategies ability relate to reading comprehension of high school
students at different educational levels?
Journal of Research in Reading, 24(2), 187–204.
Kush, J. C., & Watkins, M. W. (1996). Long-term stability of children’s
attitudes toward reading. The Journal of Educational Research, 89(5),
315−319.
Laufer, B. & Goldstein, Z. (2004). Testing vocabulary knowledge: Size,
strength and computer adaptiveness. Language learning, 54(3), 399–
436.
Matthewson, G.C. (1994). Model of Attitude Influence upon Reading and
learning to Read. In R.B. Ruddell, M. Rapp Ruddell, H. Singer.
Theoretical Models and Processes of Reading (pp.1131-1161). Newark,
Delaware: IRA
McKenna, M. C. (2001). Development of reading attitude. In L. Verhoeven,
& C. E. Snow (Eds.), Literacy and motivation: reading engagement in
individuals and groups (pp. 135–158). Mahwah: LEA.
McKenna, M. C., & Kear, D. J. (1990). Measuring attitude toward reading:
A new tool for teachers. Journal of reading, 43, 626–639.
McKenna, M. C., Kear, D. J., & Ellsworth, R. A. (1995). Children's attitude
toward reading: a national survey. Reading Research Quarterly, 30(4),
934−956.
Meyer, B. J. F., Brandt, D. H., & Bluth, G. J. (1980). Use of top-level
structure in text: Key for reading comprehension of nine grade students.
Reading Research Quarterly, 16(1), 72–103.
Mullis, I. V. S., Martin, M. O., Gonzalez, E. J., & Kennedy, A. M. (2003).
PIRLS 2001 International report. Chestnut Hill, MA: PIRLS
International Study Center.
Muter, V., Hulme, C., Snowling, M. J., & Stevenson, J. (2004). Phonemes,
Rimes, Vocabulary, and Grammatical Skills as Foundations of Early
Reading Development: Evidence From a Longitudinal Study.
Developmental Psychology, 40(5), 665–681.
Myers, M. & Paris, S. G. (1978) Children's metacognitive knowledge about
reading.
Models of Reading Comprehension for Primary School Students
329
Journal of Educational Psychology, 70(5), 680–690.
Nagy, W. E., Diadikoy, L., & Anderson, R. (1993). The acquisition of
morphology: learning the contribution of suffixes to the meanings of
derivatives. Journal of Reading Behavior, 25, 155–170.
Oldfather, P. (1992). Sharing the Ownership of Knowing: A constructivist
Concept of Motivation for Literacy learning. Paper presented at the
annual meeting of the National Reading Conference, San Antonio,
Texas, 2.12.1992
Palincsar, A. S. & Brown, A. L. (1984). Reciprocal teaching of
comprehension – fostering and comprehension-monitoring activities.
Cognition and Instruction, 2, 117–175.
Pany, D., Jenkins, J. R., & Schreck, J. (1982). Vocabulary instruction:
effects on word knowledge and reading comprehension. Learning
Disability Quarterly, 5, 202–215.
Paris, S. G., Lipson, M. Y., & Wixson, K. K. (1983). Becoming a strategic
reader. Contemporary Educational Psychology, 8(3), 293–316.
Paris, S. G., & Lindauer, B. K. (1982). The development of cognitive skills
during childhood. In B. Wolman (Ed.), Handbook of developmental
psychology (pp. 333-349). Englewood Cliffs, NJ: Prentice-Hall.
Pazzaglia, Beni and Caccio (1999). The role of working memory and
metacognition in reading comprehension difficulties. V T. E. Scruggs in
M. Mastropieri (ur.), Advances in learning and behavioral disabilities,
Vol. 13 (str. 115-134). Greenwich, Conn.: JAI Press.
Pečjak, S. (1989). Tehnike za izboljšanje bralne učinkovitosti:
Eksperimentalni program hitrega branja. Magistrsko delo
(neobjavljeno). [Techniques for improving reading efficacy:
experimental programme of quick reading]. Ljubljana: Filozofska
fakulteta v Ljubljani.
Pečjak, S., & Gradišar, A. (2002). Bralne učne strategije [Reading learning
strategies]. Ljubljana: Zavod RS za šolstvo.
Pečjak, S., Bucik, N., Gradišar, A. & Peklaj, C. (2006). Bralna motivacija v
šoli: merjenje in razvijanje [Reading motivation in school: measurement
and development]. Ljubljana: Zavod RS za šolstvo.
Perfetti, C. A. (1994). Psycholinguistics and reading ability. In M. A.
Gernsbacher (Ed.), Handbook of psycholinguistics (pp. 849-894).
Orlando, FL: Academic Press.
Pintrich, P.R. & Zusho, A. (2002). The development of academic selfregulation: The role of cognitive and motivational factors. In A.
Wigfield & J.S. Eccles (Eds.). Development of achievement motivation
(pp. 249-284). San Diego: Academic Press.
330
Chapter Seventeen
Potts, R., Camp, C. & Coyne, C. (1989). The relationship between naturally
occurring dysphoric moods, elaborative encoding, and recall
performance. Cognition and Emotion, 3, 197–205.
Quellette, G. P. (2006). What's meaning got to do with it: the role of
vocabulary in word reading and reading comprehension. Journal of
Educational Psychology, 98(3), 554–566.
Renninger, K. A. (1992). Individual interest and development: Implications
for theory and practice. In K. A. Renninger, & S. Hidi (Eds.), The role
of interest in learning and development (pp. 161-196). Hillsdale; NJ:
Erlbaum.
Rončević Zubković, B. (2008). Uloga radnog pamćenja i strategijskog
procesiranja u razumijevanju pri čitanju kod djece [The role of working
memory and strategic processing in children’s reading comprehension].
Unpublished PhD thesis. University of Zagreb, Croatia.
Schallert, D. L., & Reed, J. H. (1997). The pull of the text and the process
of involvement in one's reading. In J. Guthrie, & A. Wigfield (Ed.),
Promoting Literacy through Integrated Teaching, (pp. 68–85). Chicago:
International Reading Association.
Schiefele, U., & Krapp, A. (1996). Topic interest and free recall of
expository test. Learning and Individual Differences, 8, 141–160.
Schiefele, U. (1996). Motivation und lernen mit Texten. Göttingen: Hogrefe.
Schiefele, U. (2001). The role of interest in motivation and learning. V J.M.
Collis, S. Messick (ur.), Intelligence and personality: Bridging the gap
in theory and measurement (str. 163-193). Hillsdale; NJ: Erlbaum.
Schmitt, M. C. (1990). A questionnaire to measure children's awareness of
strategic reading processes. The Reading Teacher, 43, 454–461.
Schneider, W. (2001). Giftedness, expertise, and (exceptional)
performance: A developmental perspective. In K. A. Heller, F. J. Mönks,
R. J. Sternberg, & R. F. Subotnik (Eds.), International Handbook of
Research and Development of Giftedness and Talent (pp. 165-178).
London: Elservier Science.
Seibert, P. S., & Ellis, H. C. (1991). Depression and implicit memory: A
commentary. Journal of Abnormal Psychology, 101, 587–591.
Share, D. L., & Leikin, M. (2004). Language impairment at school entry
and later reading disability: Connections at lexical versus supralexical
levels of reading. Scientific Studies of Reading, 8(1), 87–110.
Sternberg, R. J. (1987). Most vocabulary in learned from context. In M. G.
McKeown, & M. E. Curtis (Eds.), The nature of vocabulary acquisition
(pp. 89–105). Hillsdale, NY: Lawrence Erlbaum.
Symons, S., Richards, C., & Greene, C. (1995). Cognitive strategies for
reading comprehension. In E. Wood, V. E. Woloshyn, & T. Willoughby
Models of Reading Comprehension for Primary School Students
331
(Eds.), Cognitive strategy instruction for middle and high schools (pp.
66-87). Cambridge, MA: Brookline Books.
Štraus, M., Repež, M., & Štigl, S. (Ed.). (2007). Nacionalno poročilo PISA
2006: naravoslovni, matematični in bralni dosežki slovenskih učencev
[National PISA report 2006: science, mathematical, and reading
achievements of Slovenian students]. Ljubljana: Nacionalni center
PISA, Pedagoški inštitut.
Thiede, K. W. & Anderson; M. C. M. (2003). Summarizing can improve
metacomprehension accuracy. Contemporary Educational Psychology,
28(2), 129–160.
Thorndike, R. L. (1973). Reading as reasoning. Reading Research
Quarterly, 2(2), 135–147.
Van den Broek, P., Tzeng, Y., Risden, K., Trabasso, T. & Basche, P. (2001).
Inferential questioning: Effects on comprehension of narrative texts as a
function of grade and timing. Journal of Educational Psychology, 93(3),
521–529.
Walczyk, J. J., & Taylor, R. W. (1996). How do the efficiencies of reading
subcomponents relate to looking back in text? Journal of Educational
Psychology, 88, 537–545.
Wigfield, A. (1997). Reading motivation; A domain-specific approach to
motivation. Educational Psychologist, 32,59-68.
Wigfield, A., & Guthrie, J. T. (1997). Relations of children’s motivation for
reading to the amount and breadth of their reading. Journal of
Educational Psychology, 89(3), 420−432.
Winne, P. H., & Hadwin, A. (1998). Studying as self-regulated learning. In
D. J. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in
educational theory and practice (pp. 277–304). Hillsdale, NJ: Erlbaum.
Wittrock, M.C.(1990). Generative processes of comprehension. Educational
Psychologist, 24,
345–376.
Yussen, S.R. (1982). Children’s impressions of coherence in narratives. In
B.A. Hutson (ed.). Advances in Reading/Language Research. Vol 1 (pp.
245-281). JAI: Press Inc.
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive
perspective. Handbook of self-regulation. In M. Boekaerts, P. R.
Pintrich & M. Zeidner (Eds). Handbook of self-regulation. (pp. 13-39).
San Diego, CA, US: Academic Press.
Summary
332
Chapter Seventeen
Reading comprehension is an indicator of reading literacy and it is also
significantly related to the process of learning and students’ academic
outcomes. There are different cognitive, metacognitive, motivational, and
emotional factors that interactively contribute to reading comprehension.
Our study included 885 fifth and ninth grade primary school students.
We proposed two confirmatory models of reading comprehension, one for
the younger and one for the older students. Several factors were included in
the models: (meta)cognitive factors (vocabulary, summarizing, and
metacognitive reading knowledge); motivational factors (reading interest
and reading competency); and emotional factors (feelings during reading).
We confirmed both models for the younger and the older students. The
models showed direct effects of (meta)cognitive factors and indirect effects
of motivational-emotional factors on students' reading comprehension.
Important implications for educational practice are discussed.