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Fostering topic knowledge: essential for academic writing

Antje Proske • Felix Kapp

Published online: 30 November 2012

� Springer Science+Business Media Dordrecht 2012

Abstract Several researchers emphasize the role of the writer’s topic knowledge for writing. In academic writing topic knowledge is often constructed by studying

source texts. One possibility to support that essential phase of the writing process is

to provide interactive learning questions which facilitate the construction of an

adequate situation model by initiating macro-strategies. In order to examine whether

the provision of interactive learning questions during studying source texts leads to

better results in academic writing both writing process and performance of a group

supported by interactive learning questions was compared to a study-only group

which read the source texts without learning questions. Results revealed that stu-

dents provided with interactive learning questions wrote longer essays and spend

significantly more time prewriting and writing/revising their essays than did the

students of the study-only group. Studying source texts with learning questions

resulted in text products of better readability and partly better accuracy and cov-

erage of content. These findings suggest that engaging students in answering

learning questions when reading source texts can positively affect both writing

process and performance.

Keywords Writing from sources � Academic writing � Learning questions � Writing process � Topic knowledge � Text comprehension � Macro-strategies

Introduction

Scientific texts are fundamental for the communication of knowledge. In academic

writing writers usually compose from sources. Thus, they are also readers, transform-

ing source texts in order to create their own text product (Spivey & King, 1989).

A. Proske (&) � F. Kapp Psychology of Learning and Instruction, TU Dresden, Zellescher Weg 17, 01062 Dresden, Germany

e-mail: antje.proske@tu-dresden.de

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Read Writ (2013) 26:1337–1352

DOI 10.1007/s11145-012-9421-4

While using source texts for the creation of one’s own text product, writers employ

the constructive operations of selecting, organizing, and connecting to construct

meaning (Spivey, 1990). Several researchers emphasize the role of the writer’s topic

knowledge for these processes (e.g., Ackerman, 1991; Spivey, 1990; Spivey &

King, 1989). In order to produce a scientific text as good as possible writers need to

transform their knowledge and the source text information to explain, evaluate,

analyze, and argue aspects of a scientific topic (McCarthy Young & Leinhardt,

1998). This requires a richly connected and well-structured situation model of the

writing topic. However, research rarely addressed the importance of situation

models for writing (e.g., Eigler, Jechle, Merziger, & Winter, 1990; Parodi, 2007).

The purpose of this study was to investigate if fostering writers’ topic knowledge

by learning questions improves academic writing. The learning questions were

specifically designed to require writers performing a particular series of cognitive

processes (i.e., macro-strategies) in order to construct an adequate situation model

of the writing topic (Proske, Körndle, & Narciss, 2012).

The construction of topic knowledge when writing from sources

When using source texts to create one’s own text, writers are engaged into acts of

discourse synthesis in which they possess not only the role of a writer, but also the role

of a reader (Spivey, 1990; Spivey & King, 1989). In transforming source text

information into their text product, reading and writing processes are blended in which

writers actively select, organize, and connect information. This information can

originate from the source texts, from one’s own text, or the writers’ prior knowledge.

Writers generate relationships (a) within and between several source texts, (b) between

source text information and the writers’ prior knowledge, and (c) within and between

the source texts, the current own text product, and the writers’ prior knowledge. Thus,

one’s own text product is built through the purposeful interaction of comprehension

and composing processes (e.g., Parodi, 2007).

The comprehension processes require the application of macro-strategies which

transform sequences of propositions of the local text level into a set of macro-

propositions that represent the macro-structure of a text. To this end, all micro-

propositions that are either irrelevant or redundant are deleted or generalized, or new

inferred propositions are constructed (van Dijk & Kintsch, 1983). Each level of text

processing leaves a memory trace. The result is an elaborated situation model of the

writing topic that may include some of the surface features of the source texts, its

meaning at the local text level, the global meaning of the source texts, as well as an

interpretation of the text meaning in the light of writers’ experiences, knowledge, or goals

(Kintsch, 2005). The situation model allows the writer to easily retrieve knowledge from

memory for writing. The generated macro-propositions become part of the situation

model and will be of potential meaning for the composition activity (Spivey, 1990).

The composition activity is made up of a series of strategies which either retrieve

stored information included within the situation model (reproduction) and/or

construct plausible inferences from the situation model (reconstruction, van Dijk &

Kintsch, 1983). For these composition processes three macro-operators can be

applied: (a) addition of details and properties, (b) particularization, and

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(c) specification of conditions, components, or consequences. The retrieved

information then has to be translated into words and sentences.

The macro-structural processes, either comprehension or composition, are

facilitated when more topic knowledge is available or when the topic knowledge

is better structured within long term memory (Benton, Corkill, Sharp, Downey, &

Khramtsova, 1995; Dansac & Alamargot, 1999; Kellogg, 2001; Kucer, 1985). If the

needed information is not prominent or available in the situation model, either

extensive search procedures or structural elaborations of the content to be retrieved

will become necessary (Benton et al., 1995; Dansac & Alamargot, 1999).

Topic knowledge, the writing process, and the quality of written products

High-knowledge writers need less effort to retrieve and use the relevant knowledge

for their written text product (Dansac & Alamargot, 1999; Kellogg, 1987) which

allows them to fluently generate ideas and text segments (McCutchen, 2000). In

addition, more topic knowledge is associated with more revision of meaning (e.g.,

Butterfield, Hacker, & Albertson, 1996; McCutchen, Francis, & Kerr, 1997).

With respect to the written products, topic knowledge is considered to affect both

text length and topic-relevance of a text, with more topic knowledge related to

longer texts and more topic-relevance (e.g., Benton et al., 1995; Eigler et al., 1990;

Kellogg, 2001). High topic knowledge further contributes to coherent, elaborated,

and specific ideas in text products (e.g., Ackerman, 1991; McCarthy Young &

Leinhardt, 1998; McCutchen, 1986) that present relevant information well-

organized (e.g., Spivey & King, 1989) in ways that anticipate the needs or interests

of the reader (e.g., Ackerman, 1991; Benton et al., 1995).

Most research on topic knowledge in writing focused on assignments in which topic

knowledge was operationalized in terms of prior knowledge on a topic. Here it was

also found that the use of writing strategies may depend on students’ level of topic

knowledge. Hammann and Stevens (2003) reported less application of strategies in

case of high topic knowledge. Writers may not perceive a need to utilize a strategy if

they think they already understand the writing topic, even if their knowledge is

insufficient for the writing task (e.g., Bereiter & Scardamalia, 1987; Hammann &

Stevens, 2003). Accordingly, writing assignments encouraging students to improve

their current situation model (e.g., argumentative writing) proved to be superior to

other assignments (e.g., writing a narrative or a summary) in terms of writing

performance (Durst, 1987), as well as learning gains (Wiley & Voss, 1999).

However, research about how to foster topic knowledge in writing is sparse

(Eigler et al., 1990). Butcher and Kintsch (2001) found that students given topic-

related computer devices planned and drafted significantly longer than students that

were given rhetorical devices. In addition, students who received topic-related

support discriminated better between important and unimportant information for

their essays (Butcher & Kintsch, 2001). Other research showed that presenting

source information well-structured (i.e., in a way that the information could easily

be chunked) reduced the cognitive demands of organizational processing when

constructing a situation model of the writing topic, as well as when retrieving

information for composition processes (Dansac & Alamargot, 1999). Altogether, the

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above reviewed findings indicate that fostering topic knowledge when writing from

sources may be a promising means of improving students’ writing performance.

Learning questions and the construction of topic knowledge

A learning question is a specifically designed task in which the series of cognitive

operations and actions conducing to the answer production lead learners to be

actively engaged in information processing (Proske et al., 2012). Thus, learning

questions will foster cognitive operations that the learner would have difficulty

using without them. In this way, learning questions might also be suitable to support

the construction of a richly interconnected situation model of a writing topic which

in turn may allow writers to produce better text products.

Theories of instructional design (e.g., Merrill, 2002) as well as theories of complex

learning (e.g., van Merriënboer & Dijkstra, 1997) emphasize to analyze prior to the

construction of learning questions the demands of the particular domain. This includes

identifying what the learners will be required to do, as well as the knowledge and skills

that may be helpful to meet these requirements. Deep comprehension of unfamiliar

source text information most likely does require the conscious and goal directed

application of macro-operators (McNamara & Magliano, 2009). One of the greatest

differences between good and poor writing from sources lies in the ability to make two

important kinds of inferences when reading (e.g., Brown & Day, 1983; Hidi &

Anderson, 1986): inferring a superordinate information to subsume several informa-

tion and inferring a macro-proposition to replace several propositions. According to

van Dijk and Kintsch (1983) both kinds of inferences belong to the macro-strategies

necessary to build the macro-structure of a source text. The former is also referred to as

the macro-strategy of generalizing, the latter to as the macro-strategy of constructing

(van Dijk & Kintsch, 1983). These kinds of macro-strategies are difficult because they

require that the readers/writers add information rather than just delete or select

information provided within the source texts (Brown & Day, 1983; Parodi, 2007).

Research shows that answering macro-structural text questions improved source

text comprehension compared to answering questions focusing on the micro-structure

of a source text (Britt & Sommer, 2004). As such they can be classified as deeper

questions. Deeper questions in general tend to encourage deeper text processing,

which is more beneficial to a better understanding of what the given text is about

(Kintsch, 2005). Similarly, learning questions guide learning and facilitate learners’

retention and deep understanding of the learning topic (e.g., Cerdán, Vidal-Abarca,

Martı́nez, Gilabert, & Gil, 2009; Hamaker, 1986; Roediger & Karpicke, 2006).

Furthermore, learning questions can trigger metacognitive processes devoted to

learning process regulation (McDaniel & Wooldridge, 2012). For example, they might

indicate which of the source text information is relevant to provoke learners to reread a

given text (e.g., Hamaker, 1986; Kapp, Narciss, Körndle, & Proske, 2011).

The purpose of this study is to investigate if students’ academic writing can be

improved by learning questions that support them in constructing a situation model

of the writing topic. More specifically, it will be investigated if and how learning

questions requiring students to apply the macro-strategies of generalizing and

constructing can affect writing process and performance.

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Method

Participants

Forty-eight university students (39 women, 9 men, M age = 20.79 years,

SD = 2.54) volunteered to participate in the study. Participants were native

German speakers recruited from several introductory lectures in psychology and

education. The average number of completed writing assignments at the university

was 1.5 (SD = 2.15). The mean time studying at the university was 1.92 semester

(SD = 1.97). As compensation for the participation students received a guideline

for writing academic texts and took part in a lottery. The prizes were books from the

field of psychology or a cinema voucher.

Design and procedure

In order to answer a given writing assignment students were required to study two

source texts and to write an essay with a web-based editor. Participants were

randomly assigned to one of the following two conditions of a between-subject

design. Students in the learning-questions condition (n = 22) answered 10 learning

questions after studying each source text. In the study-only condition (n = 26), the

participants did not receive learning questions. There were no statistically

significant differences between the groups with respect to age, gender, semester,

course of studies, and experience in academic writing in terms of already completed

writing assignments at university.

At the beginning of the experimental session, all students received brief

instructions in using the web-based editor. Subsequently, they completed a

questionnaire on their writing motivation and usual writing activities. In the next

step, the writing assignment was presented on the computer screen. The source texts

were given on paper one by one. Students were free to work with the source texts as

often and as long as desired. All students were provided with two different text

markers, two pens, as well as draft paper. There were no restrictions to use these

tools. Hence, students were free to deploy their own study technique when working

on the source texts. After studying each source text the learning-questions group

answered the respective learning questions on computer. There were no time

restrictions so that students could work on the assignment as long as they wanted.

The experimental session lasted about 2.5 h.

Materials

Writing assignment and source texts

The writing assignment was about Loftus’ position on the reliability of suppressed

memories (Loftus, 1979). Students were asked to present (A) Loftus’ academic

position, (B) evidence in favor of this position, (C) evidence against this position,

and (D) their own opinion.

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In order to complete the assignment, students were asked to integrate information

from two German source texts. The first source text supported Loftus’ position, the

other argued against the position. The source texts were taken from an excursus of

the German translation of Hilgard’s introduction to psychology (Atkinson,

Atkinson, Smith, Bem, & Nolen-Hoeksema, 2000). Each source text was written

like an original scientific paper and explicitly presented evidence for the particular

position. The source texts consisted of 805 and 874 words (445 and 426 different

words, 38 and 41 sentences). For all texts the sentences per paragraph ranged from

5.1 to 5.5. The readability indices of the texts, as indicated by the Wiener

Sachtextformel, were 13, thereby suggesting that both source texts were appropriate

for the age of 13. The Wiener Sachtextformel (Bamberger & Rabin, 1984) was

developed for German non-fictional texts. This formula takes into consideration the

length of the sentences and the proportion of polysyllabic words as a measure of

readability. It results in scores approximately corresponding with the reader’s

recommended age, so a value of 4 indicates a very easy text and a value of 15 is

indicative of a more challenging text.

Learning questions

To support the construction of a situation model for each source text 10 interactive

learning questions (i.e., a total of 20 learning questions) were developed on the basis

of the model of text comprehension and production (van Dijk & Kintsch, 1983).

These learning questions required students to perform text reduction processes

either by applying the macro-strategy of generalizing single source text information

(5 for each source text = 10) or by applying the macro-strategy of constructing an

inferred statement from a number of single source text information (5 for each

source text = 10).

All sub-parts of the writing assignment were covered by the learning questions.

Three learning questions explicitly addressed Loftus’ academic position (part A),

two learning questions dealt with evidence in favor (part B), seven questions with

evidence against Loftus’ position (part C), and two learning questions regarded the

evaluation of Loftus’ position (part D). Three learning questions were related to

Loftus’ position and evidence in favor of this position (AB), and the remaining three

learning questions addressed part B and C, namely pro and counter arguments. The

total coverage of the learning questions was as follows: part A: 6, part B: 8, part C:

10, part D: 2. Form and interactivity of the learning questions were held constant

(multiple-choice with two trials, explanation of correct answer). Figure 1 shows an

example of an interactive learning question.

Web-based editor

Both experimental groups used a text editor with the typical editor functions copy

and paste, font formatting, and listing (see Fig. 2). These functions are also usually

provided in free web-based email services. The writing assignment was continu-

ously present at the top of the screen. The textbook articles were given on paper. As

mentioned before, students could work on the assignment as long as they wanted.

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Measures

Writing motivation

Writing motivation is defined as the students’ feelings and beliefs about writing

(Bruning & Horn, 2000; Hidi & Boscolo, 2006). It was measured by a questionnaire

developed on the basis of an integrative expectation-value model of learners’

motivation (Narciss, 2008). The response scale ranged from 1 (not at all true) to 6

(very true). The questionnaire consists of the two scales intrinsic value of writing

(4 items, Cronbach’s alpha = .85, e.g., I enjoy academic writing) and competence

beliefs (4 items, Cronbach’s alpha = .84, e.g., I think I am very gifted in academic

writing). In case the instrument is used for group comparisons in research, several

researchers recommend a Cronbach’s alpha between .80 and .90 as very good (e.g.,

DeVellis, 2003). Thus, the Cronbach’s alpha of the scales can be considered as

adequate for comparing groups with respect to writing motivation.

Usual writing activities

A 23-item questionnaire was used to assess writing activity use (Proske, 2007). For

each item, the students indicated whether they typically carry out the presented

activity during their academic writing. The questionnaire included the following

writing activities: establishing coherence (e.g., I check whether transitions clarify

relations between the text sections; translated from German to English), processing

information (e.g., I write down my ideas regarding a source text), and processing

Fig. 1 The user interface of an interactive learning question

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source texts (e.g., During intensive reading, I highlight the relevant information in a

source text). The students were asked to rate the truth of each statement on a 6-point

scale ranging from 1 (not at all true) to 6 (very true). Scores on this questionnaire

showed an internal consistency adequate for group comparisons as demonstrated by

a Cronbach’s alpha reliability coefficient of .85.

Behavior and success while working on the learning questions

All students’ activities on the learning questions were recorded in log-files. For each

source text the time of working on the respective learning questions was

summarized from these log-files. The measure of total time spent for working on

the learning questions represents the sum of time on all 20 learning questions. All

interactive learning questions provided a two-trial strategy and informative tutoring

feedback information. After participants failed on their first solution attempt, they

received immediate feedback indicating a mistake had been made. Therefore, in

order to assess success on the learning questions, the number of correctly answered

questions in the first, as well as in the second attempt was analyzed.

Writing performance

Writing performance was evaluated on the dimensions readability and content

coverage. The texts of the participants were rated independently by two trained

persons. A questionnaire (Jucks, 2001) was used to measure readability, whereas a

Fig. 2 The user interface of the web-based editor

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coding scheme was developed for assessing the accuracy and coverage of content.

Interrater agreement was calculated by using the Intraclass Correlation Coefficient

(ICC, Rae, 1988; Shrout & Fleiss, 1979). The correlational coefficients for interrater

agreement were ICC = 0.73, p \ .01 for readability and ICC = 0.90, p \ .01 for content coverage. The ratings were averaged for further analyses.

The assessment of readability was carried out using a 22-item questionnaire

covering four dimensions of text-readability (Groeben, 1982; Langer, Schulz von

Thun, & Tausch, 1993): (a) simplicity, (b) structure-organization, (c) brevity-

shortness, and (d) interest-liveliness. The questionnaire was developed to evaluate

the comprehensibility of non-fictional texts (Jucks, 2001). Each item was rated on a

five-point-scale, with a small number indicating poor readability. The Cronbach’s

alpha reliability coefficient for this questionnaire was .89.

Accuracy and coverage of content was rated using a coding scheme. It consisted

of anchor examples illustrating poor to very good answers to the four parts of the

writing assignment (presentation of the academic position, evidence pro position,

evidence contra position, and presentation of own opinion). The anchor examples

were constructed based on the source texts. For each part of the writing assignment,

accuracy and coverage of information from the source texts was evaluated on a

scale from 1 (poor quality) to 5 (very good quality). The sub categories of the

writing assignment were analyzed separately.

Writing activities

All students’ writing activities were recorded in log-files. The number of words

included in the final essay was summarized from these log-files. Furthermore, we

calculated prewriting time and writing/revising time on the basis of the log-files.

Prewriting time is defined as the time between activation of the writing assignment

and when the student began writing the essay. It is important to note that for the

learning-questions group time on learning questions was excluded from the

prewriting measure. Writing/revising time represents the time between the first

fluent entries into the text-editor and clicking the button ‘close program’.

Results

Control variables

Table 1 presents the means and standard deviations of the control variables.

Students in both groups reported medium intrinsic value of writing, medium

competence beliefs, and a relatively high use of writing activities. There were no

significant differences between the learning-questions and the study-only group with

respect to writing motivation (Wilk’s K = 0.98, F(2, 45) = 0.37, p = .69). However, the groups statistically significant differed in their self-reported use of

writing activities (F(1, 47) = 24.81, p \ .01). Therefore, the usual writing activities scale was included as a covariate in all statistical analyses for group comparison.

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Behavior and success while working on the learning questions

As shown in Table 2, the participants of the learning-questions group needed a total

of 10–12 min to answer the provided 20 learning questions. For the learning

questions of the first source text students invested slightly more time than for the

second source text. Overall 17 out of 20 learning questions were correctly solved,

mostly at the first attempt. Students were somewhat more successful in answering

the learning questions with respect to the first source text. As represented by a mean

of M = 2.91 only very few learning questions were incorrectly solved. These results

indicate that students were able to perform the generalization and construction

macro-strategies required by the learning questions.

Writing performance and activities

Table 3 presents the descriptive statistics for both groups on the writing

performance and activity variables. A one-way MANCOVA was conducted

including condition (learning-questions vs. study-only) as independent variable

and self-reported usual writing activities as covariate, with the following dependent

variables: readability, accuracy and coverage of content for the four sub-parts of the

writing assignment, number of words in final essay, prewriting time, and writing/

revising time. This MANCOVA revealed a significant main effect of condition

(Wilks’ K = .38, F(8, 38) = 7.67, p \ .01, g2 = .62). Univariate tests (see Table 3) showed that the main effect was significant for all writing activity

measures: number of words in final essay (p \ .05, g2 = .10), prewriting time (p \ .01, g2 = .19), and writing/revising time (p \ .05, g2 = .10). These results indicate that students in the learning-questions group spent considerably more time

on prewriting than did the study-only group. Furthermore, they expended much

more time typing and revising the final essay and included more words than the

study-only group (see Table 3). With respect to writing performance the learning-

questions group showed a significant advantage in terms of readability (p \ .01, g2 = .41), as well as accuracy and coverage of content for the second sub-part of the writing assignment, that is evidence in favor of Loftus’ position (p \ .01, g2 = .15). However, there were no statistically significant differences between the groups for accuracy and coverage of content for the other three sub-parts of the

writing assignment.

Table 1 Means and standard deviations of writing motivation and usual writing activities scales

Variable Learning-questions (n = 22) Study-only (n = 26)

M SD M SD

Writing motivation

Intrinsic value 3.22 1.12 3.27 0.94

Competence beliefs 3.39 0.98 3.60 1.09

Usual writing activities 4.25 0.46 4.96 0.51

A value of 6 denotes a high level in the particular variable. Averaged scale values are reported

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Discussion

In academic writing, writers typically transform source text information into their

text product. Thus, comprehension and composing processes are blended during

academic writing (Parodi, 2007; Spivey, 1990; Spivey & King, 1989). The purpose

of this study was to investigate if students’ writing can be improved by learning

questions that support their construction of topic knowledge. One of the greatest

differences between good and poor academic writers lies in the ability to make

inferences when reading source texts (Brown & Day, 1983; Hidi & Anderson,

1986). Thus, in this study the interactive learning questions were specifically

designed to engage writers in employing the macro-strategies of generalization and

construction when reading. It was expected that providing these learning questions

will positively affect both, writing process and performance. First, we address the

effects of answering interactive learning questions on writing process by analyzing

the time students spent planning, drafting, and revising their texts. Then we examine

the effects of interactive learning questions on the quality of the written product.

Results of this study show that students of the learning-questions group expended

more time on prewriting, such as collecting and structuring information from the

source texts and planning their essays. This result is in line with prior research on

supporting topic knowledge in writing (e.g., Butcher & Kintsch, 2001). Expert

writers also have longer prewriting phases in which they are expected to plan their

texts at higher conceptual and rhetorical levels (e.g., Hayes & Flower, 1986). Thus,

this result suggests that providing learning questions encourages students to deploy

expert-like writing strategies during composition in terms of paying more attention

to the prewriting phase. Furthermore, students in the learning-questions group

invested more time typing and revising their essays than did the study-only group.

Students could work on their essay as long as they wanted. Given that expert writers

also spend more time on their text (e.g., Hayes & Flower, 1986), this result can be

Table 2 Descriptive statistics of behavior and success while working on the learning questions in the learning questions group (n = 22)

Learning activity M SD Min Max

Time on learning questions a

11.79 2.72 8.30 16.86

Source text 1 a

6.66 1.90 2.99 10.96

Source text 2 a

5.13 1.11 3.42 7.10

Correctly solved questions first attempt 14.45 2.65 9.00 20.00

Source text 1 8.18 1.47 6.00 10.00

Source text 2 6.27 1.61 3.00 10.00

Correctly solved questions second attempt 2.64 1.59 0.00 6.00

Source text 1 0.91 1.11 0.00 4.00

Source text 2 1.73 1.03 0.00 3.00

Incorrectly solved questions 2.91 1.82 0.00 7.00

Source text 1 0.91 0.92 0.00 3.00

Source text 2 2.00 1.38 0.00 5.00

a Measures represent time in minutes

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considered as a further indicator that answering learning questions when reading

source texts helps students approximate more expert writing strategies during

composition (Butcher & Kintsch, 2001).

Taken together, the results of analyzing the prewriting and writing/revising times

indicate that fostering topic knowledge by interactive learning questions can

positively change students’ writing process.

With respect to writing performance, the learning-questions group outperformed

the study-only group in terms of readability. This indicates that students of the

learning-questions group were better able to compose essays adapted to the

expected reader in terms of organization, conciseness, and interest, which included

the use of common words and uncomplicated sentences (Groeben, 1982; Langer

et al., 1993). Other research also found that high knowledgeable writer present

information in their texts coherent and well-organized with respect to the needs and

interests of the expected audience (e.g., Ackerman, 1991; Benton et al., 1995;

Spivey & King, 1989).

Furthermore, it was expected that answering learning questions supporting the

comprehension of source text information will enable students to write longer texts

including more topic relevant information (e.g., Eigler et al., 1990; Kellogg, 2001).

This finding was only partly confirmed in this study. Whereas students of the

learning-questions group included more words into their final essay than did the

study-only group, they significantly outperformed the study-only group in terms of

content coverage only in one of the four parts of the writing assignment. The big

difference between the groups in terms of word number (1,004 words for the

learning-questions group vs. 821 for the study-only group) may be seen as an

indicator that answering learning-questions can facilitate knowledge retrieval during

the composition activity (e.g., Dansac & Alamargot, 1999; Kellogg, 1987;

McCutchen, 2000).

Table 3 Means, standard deviations, and statistical comparisons of writing performance and activities measures

Variable Learning questions (n = 22) Study-only (n = 26) Statistical comparison

M SD M SD F(1,45) g2 p

Writing performance

Readability a

3.67 0.27 3.04 0.43 30.81 .41 \.01

Content coverage a

Loftus’ position 4.05 0.62 3.87 1.20 .27 .01 .61

Evidence pro 4.07 0.60 3.21 1.23 8.02 .15 \.01

Evidence contra 3.84 1.40 3.60 1.48 1.01 .02 .32

Own opinion 2.70 0.96 2.87 0.77 .28 .01 .60

Number of words 1,003.55 396.39 821.15 262.92 4.96 .10 \.05

Writing activities

Prewriting time b

48.68 20.62 29.96 19.04 10.84 .19 \.01

Writing/revising time b

106.24 37.46 88.59 30.86 4.97 .10 \.05

a A value of 5 denotes high performance. Averaged scale values are reported;

b in minutes

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However, the advantage of the learning-questions group in terms of readability

and text length did not manifest in all measures of accuracy and coverage of content.

The learning-questions group significantly outperformed the study-only group only

in the second sub-part of the writing assignment which required them to present

evidence on favor of Loftus’ position. There are several possible explanations for

this finding. First, all information relevant to this part of the writing assignment was

presented in the first source text. As the source texts were given to the participants

one after another, the first source text may have functioned as prior knowledge for

the second source text when building the situation model of the writing topic. This

may have been reinforced by presenting the learning questions immediately after the

respective source text. Thus, students may have generated more relationships

between and within the information of the first than of the second source text. This,

in turn, may have affected knowledge retrieval during the composition activity (e.g.,

Dansac & Alamargot, 1999; Spivey, 1990). Second, students often do not generate

any counterarguments in writing because they believe that considering counterar-

guments would reduce the persuasiveness of their essays (e.g., Nussbaum &

Schraw, 2007). Third, the first source text explained in detail the empirical studies in

favor of Loftus’ position, whereas the second source text included only one study

description providing evidence against the position. The second source text rather

argued against Loftus’ position by discussing single details of the pro studies. For

this reason, the interactive learning questions for the two source texts differed in

their content granularity, even though they all required the macro-strategies of

generalizing and constructing.

We conclude that these results indicate that supporting topic knowledge by

interactive learning questions can positively affect writing performance. However,

further research is needed, for example on the learning questions timing, alignment, and

granularity in order to take full advantage of their potential for writing from sources.

Limitations of the study

Investigating academic writing necessarily involves investigating a blend of reading

and writing processes. During these comprehension and composition processes lots

of variables of the reader/writer and the writing environment interact (e.g., Hayes &

Flower, 1986). Therefore, some limitations of this study should be pointed out.

First, the process measures used in our study are time measures which do not

determine the level and quality of cognitive processes during planning and writing/

revising. Furthermore, our definition of writing/revising does not differentiate

between drafting and revision stages and necessarily includes other cognitive

processes that occur during these stages. Precisely because this measure includes

both text production and other cognitive processes that are directly linked to text

production (e.g., sentence planning, rereading of already produced text) we consider

it appropriate for this study (see for example Butcher & Kintsch, 2001 for a similar

procedure). Furthermore, the time measures were obtained unobtrusively. Thus,

comparison of these measures between groups represents a limited but important

aspect of time allocation during writing from sources.

Fostering topic knowledge 1349

123

Second, the results of our study indicate that providing learning questions when

writing from sources positively affect both writing process and performance.

However, it is unclear if the underlying mechanisms are cognitive or metacognitive

processes. It might be that answering learning questions specifically designed to

elicit macro-strategies when reading source texts initiate cognitive processes that

directly result in a more elaborated situation model of the writing topic. However, it

is also possible that answering learning questions indirectly affects the situation

model by triggering metacognitive processes. In this case, the learning questions

might point to information relevant for the writing assignment so that students are

provoked to restudy the source texts (Kapp et al., 2011). In the present study we are

not able to draw reliable conclusions concerning the nature of the underlying

processes. In order to specifically examine the processes initiated by interactive

learning questions, further research, for example, could compare learning questions

with different requirements, such as verbatim recall of source text information vs.

performing macro-strategies, or answering questions on information relevant vs.

irrelevant for the writing assignment.

Implications for theory, research, and practice

Taken together, the results of this study indicate that interactive learning questions

can be powerful resources for supporting students’ active knowledge construction

when reading source texts in academic writing. Learning questions initiate cognitive

and/or metacognitive processes which lead to a more elaborated situation model of

the writing topic. This may allow the knowledge to be easily accessed from memory

and used for text production. In this study, answering learning questions had an

impact on the writing process and lead to better readability of the produced texts, as

well as partly better accuracy and coverage of content. Further research is needed in

order to determine in detail if and how supporting source text comprehension by

interactive learning questions fosters the fluency of text generation processes and/or

reduces cognitive effort of knowledge retrieval.

Furthermore, the results of this study show first evidence that the effectiveness of

writing support may not only depend on the quality of the provided instruction in

terms of guiding how to carry out writing activities, but also on sufficient topic

knowledge in the particular writing domain. The two dimensions topic knowledge

and writing skills may even interact (e.g., Hammann & Stevens, 2003). More

specifically, effectively applying writing strategies always also requires successfully

using topic knowledge. Thus, insufficient topic knowledge might be an alternative

explanation for (computer-based) writing interventions which were not successful.

In further studies the nature of this interaction should be addressed in order to gain

more information for the design of effective writing support.

Acknowledgments We would like to thank Anna Kamphausen and Katharina Abel for their excellent work in preparing and conducting the study, as well as in rating the written products. Furthermore, we are

grateful to Annemarie Hilbig and Gregor Damnik for their assistance during data collection.

1350 A. Proske, F. Kapp

123

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