Examining Associations between Reading Motivation and Inference Generation beyond Reading...

READING MOTIVATION AND INFERENCE GENERATION 1

Running head: READING MOTIVATION AND INFERENCE GENERATION Examining Associations between Reading Motivation and Inference Generation beyond

Reading Comprehension Skill

Virginia Clinton

University of Wisconsin – Madison

Author Note Virginia Clinton is a Research Associate at the Wisconsin Center for Education

Research at the University of Wisconsin – Madison. Correspondence should be

addressed to Virginia Clinton, 1025 W. Johnson St., Madison, WI 53706 or

[email protected]. This research was supported by an Institute of Education Sciences

Training Program Grant (R305C050059) to the University of Minnesota. I thank Joanne

Xiong for her assistance with this article. I also thank research assistants for collecting,

transcribing, and coding data.

Clinton, V. (in-press). Examining associations between reading motivation and inference

generation beyond reading comprehension skill. Reading Psychology. doi:

10.1080/02702711.2014.892040


Abstract

The purpose of this study was to examine the associations between reading motivation

and inference generation while reading. Undergraduate participants (N = 69) read two

science articles while thinking aloud, completed a standardized reading comprehension

assessment, and self reported their habitual reading motivation. Findings indicate that

overall reading motivation, one component of intrinsic motivation (reading as a sense of

self) and one component of extrinsic motivation (reading to do well in other realms) were

positively associated with text-connecting inference generation independent of reading

comprehension skill. These findings are discussed in the context of standards of

coherence.


Examining Associations between Reading Motivation and Inference Generation beyond Reading Comprehension Skill

It is well known that motivation is an important aspect of reading (Gottfried,

1990; Wigfield & Asher, 1984; Wigfield, 1997). Reading motivation is related to the

amount of time one spends reading (Durik, Vida, & Eccles, 2006; Schaffner, Schiefele, &

Ulferts, in press) and performance on reading comprehension assessments (Mucherah &

Yoder, 2006). However, there has been limited, direct investigation into the associations

between reading motivation and the process of reading. One critical aspect of the

process of reading is making connections within the text or between the text and a

reader’s background knowledge (i.e., inference generation; Graesser, Singer, & Trabasso,

1994; Kintsch & van Dijk, 1978). Inference generation is an important component of

reading because a reader creates a meaningful mental representation of a text by

connecting its ideas (Kintsch, 1998). The purpose of this paper is to examine

associations between reading motivation and inference generation while reading.

There are many perspectives on the multi-dimensional, complex construct of

motivation (e.g., Ainley, 2006; Baker & Wigfield, 1999; Barron & Harackiewicz, 2001;

Guthrie, van Meter, McCann, & Wigfield, 1996; Hidi, 2000; Senko, Hulleman, &

Harackiewicz, 2011; cf. Schiefele, Schaffner, Möller, & Wigfield, 2012). However,

reading motivation is generally considered a readiness or eagerness to engage in reading

activities (Schiefele, 2009; Wigfield & Guthrie, 1997). This eagerness to read may be

driven by goals, beliefs about one’s skills or capabilities, or needs (Guthrie, Wigfield,

Metsala, & Cox, 1999). Motivation, including domain-specific reading motivation, is

typically conceptualized as intrinsic or extrinsic (cf. Ryan & Deci, 2000; Sasone &


Harackiewicz, 2000). Intrinsic motivation is choosing to read because one considers the

activity of reading enjoyable, believes one is a competent reader, or wishes to develop

one’s reading skills for personal fulfillment (Eccles & Wigfield, 2002; Guthrie et al.,

1999). Intrinsic motivation is assumed to be associated with deep, meaningful text

processing that requires effort from the reader (Guthrie, Wigfield, Humenick,

Perenencevich, Taboada, & Barbosa, 2006; Schiefele et al., 2012). This assumption is

supported by empirical findings. For examples, intrinsic reading motivation was

positively associated with asking higher-level questions while learning (Taboada, Tonks,

Wigfield, & Guthrie, 2009), self-reports of deep reading strategies (e.g., organizing,

elaborating, and monitoring; Anmarkrud & Bråten, 2009), performance on an assessment

of deep reading strategies such as prediction, question generation, clarification, and

summarizing (Andreassen & Bråten, 2010), error detection, inferring word meanings

from context, and summarization (Lau & Chan, 2003). Moreover, instructions designed

to enhance intrinsic motivation lead to increased performance on measures of deep text

comprehension such as accurate answers to conceptual questions (Benware & Deci,

1984), recall of main ideas (Grolnick & Ryan, 1987), and incidental vocabulary learning

(Graham & Golan, 1991).

In contrast, extrinsic motivation is choosing to read to obtain an external benefit

such as improved academic performance, impressing one’s peers, or payment (Covington

& Müeller, 2001; Deci, Vallerand, Pelletier, & Ryan, 1991). Unlike intrinsic motivation,

extrinsic motivation is thought to be associated with shallow text processing that requires

little effort from the reader, such as memorization. There is some empirical evidence to

support this assertion. For example, extrinsic motivation was negatively associated with


metacognitive awareness of the appropriate use of reading strategies (Schaffner &

Schiefle, 2007, as cited in Schiefele et al., 2012). Moreover, readers given extrinsic

motivation in the form of monetary incentives for performance remembered more of the

text than readers who were not given monetary incentives (Konheim-Kalkstein & van den

Broek, 2008). In addition, instructions intended to induce extrinsic motivation improved

accuracy on questions assessing factual recall of the text (Conti, Amabile, & Pollak,

1995). The amount of text information recalled and factual questions are considered

rather superficial measures of learning from text (Gilabert, Martinex, & Vidal-Abarca,

2005; W. Kintsch, 1994; E. Kintsch, 2005; McNamara, E. Kintsch, Songer, & W.

Kintsch, 1996). Hence, it is possible that extrinsic motivation prompted readers in these

studies to superficially rehearse the information in the text in order to reproduce it in a

recall rather than develop a deep, meaningful mental representation of the text.

Moreover, extrinsic motivation was negatively associated with performance on reading

comprehension assessments (Becker, McElvany, & Kortenbruck, 2010; Wang & Guthrie,

2004) in some studies. However, extrinsic motivation was positively correlated with

performance on reading comprehension assessments in other studies, although the

association was not strong as intrinsic motivation (Lau & Chan, 2003) and was limited to

good readers (McGeown, Norgate, & Warhurst, 2012). Moreover, general reading

motivation incorporating aspects of both intrinsic and extrinsic motivation was correlated

with self-reports of deep strategies such as incorporating background knowledge into the

text, self-questioning while reading, and connecting information in different texts (Cox &

Guthrie, 2001). Therefore, it is uncertain how extrinsic reading motivation relates to the

process of reading.


The mixed findings regarding extrinsic motivation may be due to how extrinsic

motivation was defined and how reading performance was assessed in each of these

studies. In the studies in which extrinsic motivation was assessed with recall of text

information, extrinsic motivation was a monetary reward (Konheim-Kalkstein & van den

Broek, 2008) or instructions that test performance would be predictive of course grade

(Conti et al., 1995). In contrast, the studies in which there were conflicting findings,

extrinsic motivation was a composite measure including concerns about grades and other

aspects of course performance, the desire for recognition from others, and one’s

competitive nature (Becker et al., 2010; Lau & Chan, 2003; McGeown et al., 2012; Wang

& Guthrie, 2004). Moreover, these studies used composite measures of reading skill that

included vocabulary, sentence, and text-level aspects of reading. The contradictory

findings in these studies using composite measures highlights the need to examine

distinct components of motivation and specific aspects of reading to clarify the complex

relationship between reading motivation and reading comprehension.

Inference Generation

An aspect of reading that may be related to reading motivation is inference

generation. In order to develop a coherent mental representation of a text, a reader must

generate inferences (Graesser et al., 1994; Thurlow & van den Broek, 1997). Inferences

are generally conceptualized as text connecting or knowledge based (Graesser, Bertus, &

Magliano, 1995; Singer, 1994; van den Broek, 1990). Text-connecting inferences

connect different ideas within a text together (Cain & Oakhill, 1999; Kintsch, 1998).

Knowledge-based inferences connect ideas within a text to the reader’s background


knowledge (Graesser, Millis, & Zwaan, 1997). Consider the following examples from a

think-aloud protocol in which a reader responds to each sentence of text:

Text Statement 1: When it is going forward, the mole feels its way with its nose and the

hairs on its front feet.

Student Response 1: The hairs on its front feet are sort of like antennae.

Text Statement 2: When the mole is going backwards, its tail tells it which way to go.

Student Response 2: So it doesn’t need those special hairs on its back feet like on its

front feet.

The information for the inference in the first student response (i.e., antennae provide

sensory information) comes from background knowledge; therefore, it is a knowledge-

based inference. The information for the inference in the second student response (i.e.,

moles have hairs which provide sensory information) comes from the first text statement;

therefore, it is a text-connecting inference.

Text-connecting and knowledge-based inferences have different roles in

constructing a mental representation of a text. Text-connecting inferences are necessary

to comprehend the basic message of a text, a level of representation known as a textbase

(Kintsch, 1998; Lehman & Schraw, 2004). Knowledge-based inferences only are

necessary for textbase understanding when the basic message of a text cannot be

coherently understood without using background knowledge to connect different ideas of

the text (Graesser et al., 1995; Kintsch, 2004). Readers use knowledge-based inferences

to develop a situation model by integrating the message of the text with their general

world knowledge and personal experiences (Kintsch, 1986; van Dijk & Kintsch, 1983).


There is reason to believe that reading motivation is positively associated with

inference generation. Motivation can be a current (i.e., state) or habitual (i.e., trait)

characteristic of a reader (Schaffner & Schiefele, 2013). Inference generation may vary

depending the current motivation of reader to achieve a particular goal (Linderholm &

van den Broek, 2002; Sundermeier, van den Broek, & Zwaan, 2005; van den Broek,

Lorch, Linderholm, & Gustafson, 2001; van den Broek, Risden, Husebye-Hartmann,

1995; Zwaan, 1999). For example, van den Broek et al. found that motivating readers

with a goal for study yielded more inferences than reading with a goal for entertainment.

The proposed reason for this is that readers vary in their inference generation depending

on their standards of coherence or criteria readers use to achieve their deserved level of

text comprehension (van den Broek, Bohn-Gettler, Kendeou, Carlson, & White, 2011).

Based on their standards of coherence, readers vary in their inference generation

depending on whether the reader is satisfied with the current level of comprehension or

believes more connections need to be developed to construct a coherent mental

representation of the text. If a reader has low standards of coherence, one would expect

only enough inference generation to create a ‘good-enough’ mental representation of the

text (Christianson, Williams, Zacks, & Ferreira, 2006; van den Broek, Rapp, & Kendeou,

2005). In contrast, a reader with high standards of coherence would exert the effort to

generate numerous inferences in order to develop a meaningful, well-connected mental

representation of the text (van den Broek et al., 1995).

The Current Study

The role of habitual reading motivation, which is one’s general predisposition

towards reading, on inference generation has not been examined. Hence, the purpose of


this study is to explore associations between reading motivation and inference generation

while reading. Given the previous literature, intrinsic motivation is likely to be

associated with inference generation. Inference generation requires effort on the part of

the reader (Thurlow & van den Broek, 1997) and motivation may prompt the reader to

exert the effort required to generate inferences (Kamas & Reder, 1995). However,

intrinsic and extrinsic motivation may have different associations with inference

generation, given the previous patterns of the two aspects of reading motivation in the

literature (cf. Pekrun, 1993; e.g., Becker et al., 2010; Lau & Chan, 2003; Wang &

Guthrie, 2004). With intrinsic motivation, one reads because one finds the activity

interesting, enjoyable, or challenging—in other words, one reads for the sake of reading

(Wigfield & Guthrie, 1997). Because intrinsic motivation prompts effort to be directed

towards a task (Ryan & Deci, 2000; Wigfield et al., 2004), it is possible that intrinsic

motivation is positively associated with inference generation. Moreover, previous

findings indicate that intrinsic motivation is thought to encourage deep processing of

texts (Schiefele et al., 2012). Inference generation is an aspect of deep text processing

because it involves the reader going beyond the superficial structure of the text to make

meaningful connections (Graesser, Singer, & Trabasso, 1994; Lehman & Schraw, 2002).

In contrast, with extrinsic motivation, one reads for some sort of external benefit such as

a grade or recognition from others (Wigfield et al., 2004). As previously mentioned,

extrinsic motivation is thought to encourage superficial processing of text; however, the

empirical support for this assumption is mixed (e.g., Becker et al., 2010; Lau & Chan,

2003). Moreover, the goal to study as if for a test, which could be considered a type of

extrinsic motivation, caused an increase in inference generation (van den Broek et al.,


2001). Therefore, it is uncertain whether extrinsic motivation will be positively

associated with inference generation while reading.

One criticism of previous research studies on reading motivation and strategies is

that the effects of reading comprehension skill were not always considered (cf. Schiefele

et al., 2012). As previously stated, reading motivation is positively associated with

reading comprehension skill (e.g., Morgan & Fuchs, 2007; Mucherah & Yoder, 2006). In

addition, inference generation is associated with reading comprehension skill (Bowyer-

Crane & Snowling, 2005; Cain, Oakhill, & Bryant, 2004; Cromley & Azevedo, 2007;

Long, Oppy, & Seely, 1997). Therefore, any observed associations between reading

motivation and inference generation could be due to reading comprehension skill. For

this reason, this study examined associations between reading motivation and inference

generation that are independent of reading comprehension skill. This allowed the

findings from this study to be interpreted with greater confidence.

Methods

Participants

Participants were undergraduate students (N = 70) from a large, Upper

Midwestern university. All participants spoke English as their native language. One

participant did not produce think-aloud responses to more than 25% of the sentences in

the experimental texts; therefore the data from this participant were not included in

analyses. Of the remaining 69 participants, 39 were female and 30 were male, with a

mean age of 20.97 years (SD = 4.91 years). Regarding the year of undergraduate study,

30% were freshmen, 20% were sophomores, 14% were juniors, and 14% were seniors.

Participants received extra credit in their psychology courses as compensation for their


time in the study. All participants received the same amount of extra credit; their

performance in the study did not affect their grade in their psychology courses.

Therefore, it can be inferred that participants had equal levels of current extrinsic

motivation to participate in this study. Data from these participants have been previously

published in (Clinton & van den Broek, 2012), but have been reanalyzed for the purpose

of this study.

Materials

One practice and two experimental science texts about theoretical explanations for

an observed phenomenon were used in this study. The described phenomena for the

experimental texts were the origins of the moon and the disappearance of songbirds from

North America. The experimental texts were adapted from Scientific American articles

and were 32 sentences long with a Flesch-Kincaid grade level of 12.0 (for original texts

see Taylor, 1994; Terborgh, 1992).

Measures

Motivation. Reading motivation was assessed with the Adult Motivation for

Reading Scale (Schutte & Malouff, 2007). The Adult Motivation for Reading Scale was

based on the Motivation for Reading Questionnaire, which is for children, (Wigfield &

Guthrie, 1997) and previous work in reading motivation (e.g., Guthrie & Alvermann,

1999; Wigfield; 1997; Wigfield & Guthrie, 1997). The Adult Motivation for Reading

Scale consists of 21 Likert items that assesses overall reading motivation as well as four

subscales: Reading as Part of Self, Reading Efficacy, Reading for Recognition from

Others, and Reading to Do Well.


The Reading as a Part of Self subscale consists of 8 items that relate to the

importance of reading in one’s life and indicative of intrinsic motivation. Examples of

these items are “Without reading, my life would not be the same.” and “It is very

important to me to spend time reading.” The Reading Efficacy subscale consists of 6

items that relate to embracing the intellectual challenges of reading and the enjoyment of

difficult reading material and is indicative of intrinsic motivation. Examples of these

items are “I am confident I can understand difficult books or articles.” and “I like hard,

challenging books or articles.” The Reading for Recognition from Others subscale

consists of 3 items that relate to the desire to impress others with one’s reading skills and

knowledge from reading and is indicative of extrinsic motivation. Examples of these

items are “It is important to me to get compliments for the knowledge I gather from

reading.” and “It is important to me to have others remark on how much I read.” The

Reading to Do Well subscale consists of 4 items that relate to importance of reading to

succeed in other domains and is indicative of extrinsic motivation. Examples of these

items are “Work performance or university grades are an indicator of the effectiveness of

my reading.” and “I read to improve my work or university performance.” The scores for

the overall scale and each of the subscales were calculated by summing the Likert

responses for each of the items and dividing by the number of items. See Table 1 for

descriptive statistics for the measures of reading motivation. Internal consistency was

acceptable or good for the overall scale (Cronbach’s α = .86) and each of the subscales

(Reading as Part of Self, Cronbach’s α = .86, Reading Efficacy, Cronbach’s α = .75,

Reading for Recognition, Cronbach’s α = .74, Reading to Do Well, Cronbach’s α = .74).


Reading comprehension. The Nelson-Denny Comprehension Subtest Form G

consists of 7 reading passages and 38 multiple-choice questions each with 5 answer

choices (Brown, Fishco, & Hanna, 1993). Each of the passages was expository with

subject matter from the humanities (2 texts), social sciences (2 texts), or science (3 texts).

Participants had 20 minutes to complete the test using pencil and paper. Scale scores

were used in all analyses as a measure of reading comprehension skill. Alternate form

reliability for university students between Form G and Form H is .81 (Brown et al.,

1993). See Table 1 for descriptive statistics.

Procedure

For the think-aloud task, participants were instructed to read each sentence aloud

and vocalize their thoughts regarding the sentence (e.g. Coté & Goldman, 2004;

Linderholm & van den Broek, 2002; Kendeou & van den Broek, 2007; van den Broek et

al., 2001; cf. Pressley & Afflerbach, 1995). Each sentence was shown separately on a

computer screen; participants pressed the space bar to advance to the next sentence when

they were ready. Once a participant had pressed the space bar to advance to a new

sentence, he or she was not able to return to previously-read sentences. Experimenters

did not provide feedback or comments on the think-aloud responses. However, if a

participant did not comment on the sentence, the experimenter would encourage a

response by saying, "Please comment after every sentence." Prior to reading the

experimental texts, the experimenter modeled the think-aloud procedure following a

script with a variety of responses with the first half of the practice text; the participant

read the remainder of the practice text while thinking aloud (see Appendix for think-

aloud instructions and model responses). Verbal data were recorded on a digital recorder.


After reading each text, participants wrote recalls and answered questions about the text.

However, performance on these measures is not related to the purpose of this study (i.e.,

associations between reading motivation and inference generation) and will not be

discussed further. Then, participants completed the Adult Motivation for Reading Scale.

The Nelson-Denny was administered at the end of the experimental session. Each

experimental session was approximately 1.5 hours long.

Trained research assistants transcribed the verbal data from the think-aloud

procedure. Each of the idea units (noun-verb combinations that express a single idea)

from participant responses was coded as a text-connecting inference (explanations of or

predictions for the text based on previously read information in the text), knowledge-

based inference (explanations of or predictions for the text based on background

knowledge), or not an inference (cf. Linderholm & van den Broek, 2002; van den Broek

et al., 2001 for further explanation of coding). Inferences were further coded as valid, if

they were accurate or consistent with the text, or invalid, if they were inaccurate or

inconsistent with the text (cf. Kendeou & van den Broek, 2005; McMaster et al., 2012;

Rapp, van den Broek, McMaster, Kendeou, & Espin, 2007). Only valid inferences were

included in analyses. Two raters, who were blind to the study hypotheses, independently

coded the think-aloud protocols with twenty-five percent of the think-aloud protocols

were coded in common (κ = .94, p < .001). See Table 1 for descriptive statistics of valid

text-connecting and knowledge-based inferences.


Table 1 Descriptive statistics of motivation and inference variables Observed

Minimum Observed Maximum Mean

Standard Deviation

Overall 1.57 4.24 3.09 .64 Self 1.00 4.75 3.18 .88 Efficacy 1.83 5.00 3.27 .72 Recognition 1.00 4.33 2.29 .99 Do Well 1.50 4.75 3.23 .92 TC Inf 1.00 55 19.59 9.92 KB Inf 0 48 13.33 10.97 ND 191 251 226.71 13.98 Note: N = 69. Overall = Overall reading motivation score, Self = Reading as a part of self subscale score, Efficacy = Reading Efficacy subscale score, Recognition = Reading for Recognition from Others subscale score, Do Well = Reading to Do Well in Other Domains subscale score, TC Inf = Text-Connecting Inferences, KB Inf = Knowledge-Based Inferences, ND = Nelson-Denny Comprehension Subtest scale score.

Results

Correlation analysis

The purpose of this study was to examine associations between reading

motivation and inference generation. We tested for associations between reading

motivation, inference generation, and reading comprehension with Pearson product-

moment correlations. We examined text-connecting and knowledge-based inference

generation separately. As can be seen in the correlation matrix in Table 2, overall

reading motivation and the four subscales of reading motivation were generally positively

correlated with each other. Text-connecting inference generation was positively

associated with overall reading motivation and three of the subscales: reading as a part of


self, reading efficacy, and reading to do well. In contrast, knowledge-based inference

generation was only positively associated with reading for recognition from others.

Overall reading motivation, each of the four subscales, text-connecting inference

generation, and knowledge-based inference generation were positively associated with

reading comprehension skill.

Table 2

Correlations among reading motivation, inference, and reading comprehension skill

variables

Self Efficacy Recognition Do

Well

TC Inf KB Inf ND

Overall .86** .76** .56** .63** .37** .18 .41**

Self .48** .36** .37** .37** .03 .30*

Efficacy .33** .39** .26* .21 .28*

Recognition .15 .04 .31** .40**

Do Well .30* .09 .26*

TC Inf .40** .31**

KB Inf .34**

*p < .05

**p < .01

Note: N = 69. Overall = Overall reading motivation score, Self = Reading as a part of self subscale score, Efficacy = Reading Efficacy subscale score, Recognition = Reading for Recognition from Others subscale score, Do Well = Reading to Do Well in Other Domains subscale score, TC Inf = Text-Connecting Inferences, KB Inf = Knowledge-Based Inferences, ND = Nelson-Denny Comprehension Subtest scale score.


Regression Analyses

According to the correlation analysis, reading comprehension skill was positively

associated with inference generation and reading motivation. Hence, the observed

associations between reading motivation and inference generation could be due to

reading comprehension skill. To examine whether the associations between reading

motivation and inference generation were independent of reading comprehension skill,

we conducted a series of hierarchical multiple regression analyses. Hierarchical multiple

regression analyses were chosen because they allow for effects of reading comprehension

skill to be partialled out of the association of reading motivation with inference

generation. Five separate hierarchical multiple regression analyses were conducted: One

for each positive association noted between reading motivation and inference generation.

The dependent variable was inference generation. For each analysis, Nelson-Denny scale

scores were entered into the first step of the regression model. The reading motivation

variable was entered into the second step. See results for text-connecting inferences in

Table 3 and results for knowledge-based inferences are in Table 4.

As can be seen in Tables 3 and 4, overall reading motivation, reading as a part of

self, and reading to do well have positive associations with text-connecting inferences

independent of reading comprehension skill. However, the positive associations between

reading efficacy and text-connecting inference generation as well as between reading for

recognition by others and knowledge-based inference generation were not independent of

reading comprehension skill.


Table 3

Hierarchical multiple regression analyses predicting text-‐connecting inference

generation

Overall Reading Motivation

∆R2 ß Step 1 .10** ND .31** Step 2 .07* ND .20 Overall .29* Reading as a Part of Self ∆R2 ß Step 1 .10** ND .31** Step 2 .08* ND .22 Self .30* Reading Efficacy ∆R2 ß Step 1 .10** ND .31** Step 2 .03 ND .26* Efficacy .19 Reading to Do Well in

Other Domains ∆R2 ß Step 1 .10** ND .31** Step 2 .05*


ND .25* Do Well .24* *p < .05 **p < .01 Note: N = 69. ND = Nelson-‐Denny Reading Comprehension subtest scale scores.

Table 4

Hierarchical multiple regression analyses predicting knowledge-‐based inference

generation

Reading for Recognition from Others

∆R2 ß Step 1 .12* ND .34** Step 2 .04 ND .26* Recognition .21 *p < .05 ** p < .01 Note: N = 69. ND = Nelson-‐Denny Reading Comprehension subtest scale scores.

Discussion

The purpose of this study was to explore associations among habitual reading

motivation and inference generation. Overall reading motivation as well as components

of intrinsic and extrinsic reading motivation were examined. There were two components

of intrinsic motivation (reading as part of self and reading efficacy) and two components

of extrinsic motivation (reading for recognition from others and reading to do well in

other realms). Overall reading motivation was a composite measure of the four

components. Overall reading motivation, reading as a part of self, and reading to do well

in other realms were positively associated with text-connecting inference generation

independent of reading comprehension skill. Reading for recognition from others was the


only component of motivation in this study that was associated with knowledge-based

inference generation. However, this association was not independent of reading

comprehension skill. Therefore, the findings indicate that habitual reading motivation, as

measured in this study, may not be associated with knowledge-based inference

generation, at least for scientific texts used in this study.

Intrinsic Motivation

Intrinsic motivation was expected to be positively associated with inference

generation. Indeed, reading as a part of self, which was one component of intrinsic

motivation, was positively associated with text-connecting inference generation. This is

consistent with previous findings that intrinsic motivation may encourage deep

processing of text (Guthrie et al., 2006; Schiefele et al., 2012). It is possible that

individuals who consider reading as part of their identity may naturally engage more with

a text, which could lead to more connections between ideas within a text. In contrast,

reading efficacy, which was a measure of one’s confidence in one’s reading skill and

enjoyment of the challenge of reading, was not associated text-connecting inference

generation independent of reading comprehension skill. In other words, the association

between reading efficacy and text-connecting inferences was driven by reading

comprehension skill. This is contrary to expectations given that reading efficacy is

considered a component of intrinsic reading motivation (Wigfield & Guthrie, 1997).

One possible explanation for this finding is that the potential effects of one’s confidence

of reading skill may be due to one’s actual reading skill. In this way, relationships

between reading efficacy and reading strategies may be explained by reading skill.

However, given the lack of previous work on reading motivation and strategies


independent of reading skill, this possibility is only conjecture. Overall, these results

indicate that associations between habitual intrinsic motivation and text-connecting

inference generation vary depending on the component of intrinsic motivation that is

examined.

Given that intrinsic motivation is associated with deeper comprehension of a text

(Schiefele et al., 2012), it was expected that there would be a positive association

between intrinsic motivation and knowledge-based inference generation. Therefore, it

was surprising that neither of the two components of intrinsic motivation were positively

associated with knowledge-based inference generation. There are two speculative

reasons for this lack of association. One possible reason is that the enjoyment of reading

for the sake of reading may be positively associated with a focus on the text, but not with

activating background knowledge (Guthrie & Wigfield, 1999). An enhanced focus on the

text may relate to an increase of text-connecting inferences, which was observed in this

study. In contrast, an increase of knowledge-based inference generation would require

the activation of background knowledge to connect to the text (Graeser et al., 1997).

Associations between intrinsic reading motivation and the activation of background

knowledge, independent of reading comprehension skill, have not been previously tested;

hence, this is merely conjecture. A second possible reason for the lack of association

between the components of intrinsic reading motivation and knowledge-based inference

generation involves the genre of texts used in this study. Readers may be more likely to

generate knowledge-based inferences for narrative texts than for expository texts

(Narvaez, van den Broek, & Ruiz, 1999). This is because the background knowledge

incorporated into knowledge-based inferences stems from personal experiences for


narrative texts and from content knowledge for expository texts (Graesser et al., 1995). It

is possible that there were not enough knowledge-based inferences generated while

reading expository texts in this study to detect associations with components of intrinsic

motivation.

Extrinsic Motivation

Given the mixed evidence on the role of extrinsic motivation on reading

comprehension, it was uncertain what the associations between extrinsic motivation on

inference generation would be. One of the components of extrinsic motivation, reading

to do well in other realms, was positively associated with text-connecting inference

generation. This is consistent with previous research findings regarding current

motivation for reading with a goal for study (van den Broek et al., 2001; Linderholm &

van den Broek, 2002). A possible reason for this finding is that one who habitually reads

to aide in academic performance may want to focus on thoroughly understanding the text

in order to use the information later. Hence, the desire to use the information from a text

to benefit oneself in other domains could prompt increased connections within the text

(cf. van den Broek et al., 2011).

As with components of intrinsic reading motivation, there were no associations

between components of extrinsic reading motivation and knowledge-based inference

generation independent of reading comprehension skill. This finding with habitual

extrinsic motivation is consistent with previous findings with current extrinsic motivation

through a goal for study (Linderholm & van den Broek, 2002). However, it is uncertain

why extrinsic reading motivation would be positively associated with text-connecting

inference generation, but not knowledge-based inference generation. As with intrinsic


reading motivation, one speculative reason for this could be insufficient content

knowledge on the text topic for motivation to prompt the generation of additional

knowledge-based inferences.

Theoretical Implications

The findings from this study inform our understanding of the relationship between

reading motivation and the process of reading. Specifically, these findings identify a

reading strategy, text-connecting inferences, that is associated with reading motivation.

According to Schiefele and colleagues (2012), finding strategies associated with reading

motivation is an important issue for researchers to deepen our understanding of the

relationship between motivation and the cognitive processes involved in reading.

Moreover, the findings indicate that aspects of both intrinsic and extrinsic motivation are

associated with the process of developing a deep, meaningful representation of the text.

This is consistent with previous assumptions and findings about intrinsic motivation (e.g.,

Anmarkrud & Bråten, 2009; Guthrie et al., 2006; Taboada et al., 2009; cf. Schiefele et al.,

2012). However, the previous findings regarding extrinsic motivation are mixed (Becker

et al., 2010; Lau & Chan, 2003; McGeown et al., 2012; Wang & Guthrie, 2004). Unlike

many previous studies, this study examined components of extrinsic motivation

separately, which may have afforded a more precise understanding of the construct. In

this way, the findings from this study elucidate the complex role of extrinsic motivation

in reading: Reading to do well in other realms appears to encourage meaningful text

connections, but reading for recognition from others does not.

The findings from this study contribute to our understanding of standards of

coherence. Specifically, these findings indicate that certain characteristics of readers,


namely levels of reading as a sense of self and reading to do well in other realms, are

positively associated with text-connecting inference generation while reading. These

findings, along with previously-noted reader characteristics such as working memory

capacity (Linderholm & van den Broek, 2002) and reading comprehension skill (Cain,

Oakhill, Barnes, & Bryant, 2001) that are associated with inference generation, help

researchers develop a holistic understanding of individual differences in reading

comprehension.

Limitations and Future Directions

One limitation of the study is that it is correlational in nature. Habitual reading

motivation cannot be randomly assigned; hence, no causal claims can be made.

Furthermore, the undergraduate students in this study all received equal amounts of

course credit to compensate for their time in the study; therefore, they had equivalent

current extrinsic motivation for participating. However, current reading motivation has

been effectively assigned with goals, monetary incentives, and instructions (Conti et al.,

1995; Konheim-Kalkstein & van den Broek, 2008; van den Broek et al., 2001). A future

study in which current intrinsic or extrinsic reading motivation was randomly assigned

prior to reading a text would strengthen the findings of this study. These instructions

could be designed to invoke specific components of intrinsic and extrinsic reading

motivation to permit causal claims regarding the effects of motivation on inference

generation.

Because of the correlational nature of this study, the direction of the association

between motivation and text-connecting inferences is uncertain. It is possible that one’s

tendency to connect text makes the reading comprehension process more effective and


meaningful, thereby increasing reading motivation. Indeed, previous work has found that

effective reading strategy instruction may increase reading motivation (Aarnoutse &

Schellings, 2003; Guthrie, Wigfield, & von Secker, 2000). However, it is likely that the

relationship between motivation and reading comprehension skills, such as inference

generation, is bidirectional (Morgan & Fuchs, 2007). The desire to read may lead one to

engage in better reading skills, which, in turn, prompts the desire to read.

The purpose of this study was to examine the relationship between reading

motivation and inference generation. Given the solid empirical base indicating a positive

association between reading comprehension skill and both reading motivation and

inference generation (Bowyer-Crane & Snowling, 2005; Cain et al., 2004; Cromley &

Azevedo, 2007; Long et a., 1997; Morgan & Fuchs, 2007; Mucherah & Yoder, 2006),

there was a clear need to include a measure of reading comprehension skill in this study.

In contrast, there was little empirical evidence to suggest that any noted association

between reading motivation and inference generation would be due to background

knowledge. Indeed, the few studies that indicated a positive association between reading

motivation and background knowledge reported effect sizes considerably smaller than

those between reading motivation and reading comprehension skill (e.g., Anmarkrud &

Bråten, 2009; Taboada et al., 2009). Therefore, in the interest of a parsimonious design,

a measure of background knowledge was not included in this study. In retrospect, such a

measure may have been beneficial to illuminate the reason why associations between

motivation and knowledge-based inference generation were not found. An intriguing

possibility for future research would be to examine the interrelationships among

background knowledge, reading motivation, reading comprehension skill, and inference


generation. If a lack of association between reading motivation and knowledge-based

inference generation were again found, the findings from such a study could indicate if

low levels of background knowledge were the reason.

Conclusion

The purpose of this study was to examine associations between reading

motivation and inference generation while reading. It was determined that these

associations varied among the different components of reading motivation. Furthermore,

these findings indicate that certain types of habitual reading motivation may contribute to

standards of coherence. Understanding how reading motivation may relate to process of

reading informs the complex relationship between reading motivation and reading

comprehension.


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