Automatic identification of knowledge‐transforming content in argument essays developed from multiple sources
Open accessAbstract
Developing knowledge‐transforming skills in writing may help students increase learning by actively building knowledge, regardless of the domain. However, many undergraduate students struggle to transform knowledge when drafting essays based on multiple sources. Writing analytics can be used to scaffold knowledge transforming as writers bring evidence to bear in supporting claims. We investigated how to automatically identify sentences representing knowledge transformation in argumentative essays. A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model processes of knowledge transforming in a corpus of 38 undergraduates' essays. Findings indicate undergraduates mostly paraphrase or copy information from multiple sources rather than engage deeply with sources' content. Eight linguistic features were important for discriminating evidential sentences as telling versus transforming source knowledge. We trained a machine learning algorithm that accurately classified nearly three of four evidential sentences as knowledge‐telling or knowledge‐transforming, offering potential for use in future research.
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- Findingown data
Two thirds of all evidential sentences in the corpus were knowledge-telling.
“Two thirds of all evidential sentences were knowledge-telling indicating undergraduates mostly paraphrase or copy information from sources rather than deeply engage with the source material.”
Quote in the paperSubstantial claim - Findingown data
The coefficient of knowledge transforming positively but weakly correlated with essay scores assigned by the course instructor.
“The coefficient of knowledge transforming positively but weakly correlated with essay scores assigned by the course instructor.”
Quote in the paperSubstantial claim- Rests on an assumption: The essay scores assigned by the course instructor are a valid measure of essay quality.
- Rests on an assumption: The coefficient of knowledge transforming computed from the algorithm is a valid measure of knowledge transforming in essays.
- Findingnone given
A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model cognitive processes in knowledge transforming.
“A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model cognitive processes in knowledge transforming, a methodological contribution to research on multi-source based writing.”
Quote in the paperSubstantial claim - Findingown data
The machine learning algorithm accurately classified nearly 3 of 4 evidential sentences as knowledge-telling or knowledge-transforming.
“The machine learning algorithm accurately classified nearly 3 of 4 evidential sentences as knowledge-telling or knowledgetransforming, offering potential for use in future research.”
Quote in the paperSubstantial claim- Rests on an assumption: The 22 linguistic features adequately capture the cognitive processes of knowledge transforming.
- Findingown data
The reliability issue lay in identifying sentences that did not fit any argumentation category, due to coders' failures to capture all NA sentences.
“The issue lay in identifying sentences that did not fit any argumentation category, i.e., reliability suffered due to coders' failures to capture all NA sentences in the assigned essays.”
Quote in the paperNot a substantial claim
- Findingown data
The number of evidential sentences per body paragraph did not differ significantly between high-scoring and low-scoring groups (M=3.90 vs 3.03, H(1)=2.68, p=0.102).
“evidential sentences per body paragraph for the high-scoring group (M=3.90,SD=2.13) and for the low-scoring group (M=3.03,SD=2.60),H(1) = 2.68, p = 0.102.”
Quote in the paperNot a substantial claim - Findingown data
In the essays analyzed here, undergraduate writers generally conveyed source material without transforming it, mostly paraphrasing or copying rather than engaging deeply through elaboration, application, inference, integration, and evaluation.
“Undergraduate students' essays examined in this study show, while writers cite evidence to support their arguments, they mostly tell rather than transform knowledge from sources they consult.”
- Also stated in: § Additional information · plain
“In other words, undergraduates mostly paraphrase or copy information from sources rather than deeply engage with the source material though elaboration, application, inference, integration and evaluation of information they mine.”
Quote in the paperSubstantial claim - Also stated in: § Additional information · plain
- Findingnone given
The probability of a sentence being knowledge-transforming drops as the number of reason-related connectives increases.
“Last, the probability of a sentence to be knowledge-transforming drops as the number of reason-related connectives (since, because, as, inasmuch as, now that) increases.”
Quote in the paperSubstantial claim - Findingown data
The results show an opposite effect to the expectation that more reason-related connectives should positively correlate with elaboration leading to knowledge transformation.
“While one may expect that more of these connectives in a sentence should positively correlate with elaboration (e.g., approximating a writer's reasoning on a topic) leading to knowledge transformation, the results show an opposite effect.”
Quote in the paperSubstantial claim - Findingown data
A sentence positioned in the middle of a paragraph (relative position 0.30-0.60) has approximately 0.80 probability of being knowledge-transforming.
“For example, starting from the top-left, the likelihood of a sentence positioned in the middle of a paragraph (relative position 0.30 -0.60) being a knowledge transforming sentence is approximately 0.80.”
Quote in the paperNot a substantial claim - Findingown data
About one quarter of evidential sentences were misclassified as false positives or false negatives.
“However, about one quarter of evidential sentences in the essay were misclassified, either as false positives (knowledge-telling sentences categorized as knowledgetransforming) or false negatives (knowledge-transforming sentences classified as knowledge-telling).”
Quote in the paperSubstantial claim - Findingnone given
Knowledge-telling sentences contain more reason-related connectives.
“Knowledge-telling sentences contain more reason-related connectives (since, because, as, inasmuch as, now that).”
Quote in the paperSubstantial claim - Findingreasoning
Knowledge-transforming sentences contain more noun phrases and indefinite articles (low-accessibility anaphora devices).
“Knowledge-transforming sentences contain more noun phrases and indefinite articles (low-accessibility anaphora devices).”
Quote in the paperSubstantial claim - Findingown data
Semantic overlap between evidential sentence and source text (Sol_S) shows a fairly uniform likelihood (0.5-0.6) of knowledge-transforming regardless of its value.
“Partial dependence on Sol_S (semantic overlap between evidential sentence and source text), on the other hand, shows quite uniform likelihood (0.5 -0.6) regardless the value of this kind of semantic overlap.”
Quote in the paperNot a substantial claim - Findingown data
Students seldom processed source information at levels above comprehension, such as application, analysis, synthesis, and evaluation.
“Students were rarely processing source information at the levels beyond comprehension (i.e., application, analysis, synthesis and evaluation).”
Quote in the paperSubstantial claim - Findingown data
The coefficient of knowledge transforming explains about 32% of variance in essay scores.
“The coefficient of knowledge transforming explains about 32 % of variance in the essay scores.”
Quote in the paperSubstantial claim - Findingown data
When the number of common content words between an evidential sentence and its source text exceeds 80%, the sentence is strongly predicted to be knowledge-transforming.
“When the number of common content words between the sentence and source text exceeds 80%, the sentence is strongly predicted to be knowledge-transforming.”
Quote in the paperSubstantial claim - Findingnone given
A sentence is more likely to be knowledge-transforming if it contains fewer high-accessibility anaphoric devices (definite articles and personal pronouns).
“Further, the sentence is more likely to be knowledge-transforming should it contain fewer high-accessibility (HA) anaphoric devices (definite articles and personal pronouns).”
Quote in the paperSubstantial claim - Findingown data
As the presence of low-accessibility anaphoric devices in a sentence exceeds 25%, the sentence is more likely to be knowledge-transforming.
“By looking at the partial dependence on the LA plot, we notice that, as the presence of lowaccessibility anaphoric devices (noun phrases and indefinite articles) in a sentence exceeds 25%, the sentence is more likely to be knowledge-transforming.”
Quote in the paperNot a substantial claim - Findingown data
Semantic overlap between about 99% of all evidential sentences and their related sources is greater than 5%.
“Semantic overlap between about 99% of all the evidential sentences in the dataset and their related sources is greater than 5%.”
Quote in the paperSubstantial claim - Findingown data
The 227 knowledge-transforming evidential sentences were distributed as 99 comprehension, 20 application, 70 analysis, 17 synthesis, and 21 evaluation.
“The remaining 227 evidential sentences were categorized into one of five categories representing the knowledge-transforming mode: 99 sentences were comprehension, M=2.61, SD=2.49; 20 were application, M=0.53, SD=1.37; 70 were analysis, M=1.84, SD=2.28; 17 were synthesis, M=0.45, SD=0.89; and 21 were evaluation, M=0.55, SD=1.31).”
Quote in the paperSubstantial claim - Findingown data
The features making the largest contribution to the classifier were Pos_P_norm, CWol_S, Sol_A, LA, Sol_S, Pos_Arg_Ev, HA, and Reason (moderately important).
“As can be seen, the features making the most contribution in the classifier are: Pos_P_norm, CWol_S, Sol_A, LA, Sol_S, Pos_Arg_Ev, HA and Reason (moderately important).”
Quote in the paperNot a substantial claim - Findingown data
The quality-of-evidence score strongly correlates with the essay score (r=0.814, p<0.001, n=38).
“Last, a score essay received for quality of evidence (one of the items in scoring rubric, scored out of 5 points) strongly correlates with the essay score (r=0.814,p<0.001, n=38).”
Quote in the paperNot a substantial claim - Findingown data
A knowledge-transforming evidential sentence has more content words in common with the source text.
“A knowledge-transforming evidential sentence has more content words (nouns, verbs, adjectives, and adverbs) in common with the source text.”
Quote in the paperSubstantial claim - Findingown data
In this sample, about 82% of evidential sentences were classified as knowledge or comprehension.
“Furthermore, in this sample, nearly 82% of all the evidential sentences created were categorized as either knowledge or comprehension”
Quote in the paperSubstantial claim - Findingown data
The machine learning classifier accurately classified 72.6% of evidential sentences.
“The machine learning classifier developed and validated in this study accurately classified 72.6% of evidential sentences.”
Quote in the paperSubstantial claim - Findingown data
The quality of evidence explains about 81% of variance in essay scores.
“The quality of evidence (item in the scoring rubric, scored out of 5 by the instructor) explains about 81 % of variance in the essay scores.”
Quote in the paperSubstantial claim - Findingown data
There is almost the same probability for sentences to be telling or transforming given their semantic overlap with the source.
“There is almost the same probability for those sentences to be either telling or transforming, given its semantic overlap with the source.”
Quote in the paperSubstantial claim - Findingown data
An evidential sentence positioned closer to the argument (1-3 sentences away) is more likely to be knowledge-transforming.
“The evidential sentence positioned closer to the argument (1 -3 sentences away) is more likely to be knowledge-transforming.”
Quote in the paperSubstantial claim - Findingreasoning
Knowledge-telling sentences contain more definite articles and personal pronouns (high-accessibility anaphora devices).
“On the other hand, knowledge-telling sentences contain more definite articles and personal pronouns (high-accessibility anaphora devices).”
Quote in the paperSubstantial claim - Findingreasoning
A knowledge-telling sentence usually has high semantic overlap (more than 70%) with the argument sentence.
“A knowledgetelling sentence usually has high semantic overlap (more than 70%) with the argument sentence.”
Quote in the paperSubstantial claim - Premisecitation
Post-secondary students often fail to integrate multiply-sourced information into coherent form.
“Subsequent research following Bereiter and Scardamalia's (1987) research showed post-secondary students often failed to: paraphrase, interpret, and evaluate content in sources; establish novel associations across multiple sources; and integrate multiply-sourced information into coherent form (Stein, 1989;Dong, 1996;Petrić, 2007;Boscolo, Ariasi, Favero, & Ballarin, 2011;Aull, 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Stein, 1989
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- cites Dong, 1996 source
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- cites Petrić, 2007
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- Premisecitation
Bereiter and Scardamalia's research showed students rarely succeed in knowledge transforming when writing grounded in multiple sources.
“Bereiter and Scardamalia's research (1987) showed students rarely succeed in knowledge transforming when writing grounded in multiple sources.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's research (1987)
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- Interpretationown data
Undergraduates mostly paraphrase or copy information from sources rather than deeply engage with the source material.
“Two thirds of all evidential sentences were knowledge-telling indicating undergraduates mostly paraphrase or copy information from sources rather than deeply engage with the source material.”
Quote in the paperSubstantial claim - Interpretationown data
This correlation contrasts with a view that knowledge-telling texts often fail to fulfill writing task requirements.
“This contrasts with a view that knowledge-telling texts often fail to fulfill writing task requirements.”
Quote in the paperSubstantial claim - Premisecitation
Post-secondary students often fail to establish novel associations across multiple sources.
“Subsequent research following Bereiter and Scardamalia's (1987) research showed post-secondary students often failed to: paraphrase, interpret, and evaluate content in sources; establish novel associations across multiple sources; and integrate multiply-sourced information into coherent form (Stein, 1989;Dong, 1996;Petrić, 2007;Boscolo, Ariasi, Favero, & Ballarin, 2011;Aull, 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Stein, 1989
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- cites Dong, 1996 source
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- cites Petrić, 2007
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- Premisecitation
Many post-secondary students, especially novice writers, find it difficult to strategically combine reading and writing in learning tasks.
“Many post-secondary students, especially novice writers, find it difficult to strategically combine reading and writing in learning tasks (Stein, 1989;Spivey, 1996).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Stein, 1989
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- cites Spivey, 1996
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- Interpretationreasoning
As a result, novice post-secondary writers often engage in relatively limited knowledge telling rather than knowledge transforming.
“As a result, novice post-secondary writers often engage in relatively limited knowledge telling rather than knowledge transforming.”
Quote in the paperSubstantial claim - Interpretationcitation
Bloom's knowledge classification aligns with the knowledge-telling model where writers focus on generating basic text.
“Bloom's knowledge classification aligns with Bereiter and Scardamalia's knowledge-telling model where writers focus on generating basic text.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's (1987)
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- Premisecitation
Despite clear task and understanding, students produced low-quality syntheses in the pre-interventional round.
“Even though the students seemed clear about the function of academic writing and they were assigned a clearly specified experimental task (synthesize the main points from the three source texts), the students produced low-quality syntheses during the pre-interventional round of the experiment.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Boscolo, Arfé and Quarisa's (2007)
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- Premisecitation
In most papers, writers preserved global organizational patterns from sources rather than transforming source information.
“In most papers writers preserved global organizational patterns from the sources (Spivey, 1990) rather than transforming source information.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Spivey, 1990
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- Interpretationcitation
Bloom's comprehension, application, analysis, synthesis and evaluation categories reflect the knowledge-transforming model where writers coordinate and create knowledge.
“Bloom's comprehension, application, analysis, synthesis and evaluation categories reflect Bereiter and Scardamalia's knowledge-transforming model where writers coordinate and create knowledge.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's (1987)
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- Premisecitation
This led to production of unclear and unconvincing arguments that poorly used source information.
“This led to the production of unclear and unconvincing arguments that poorly used source information.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hyytinen, Löfström, and Lindblom-Ylänne's (2017)
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- Interpretationreasoning
The tools designed so far only focus on rhetorical aspects of a composition.
“The tools designed so far only focus on rhetorical aspects of a composition.”
Quote in the paperSubstantial claim - Premisecitation
In Stein's analysis of 36 papers from ill-defined multisource writing tasks, 28 were summaries (knowledge-telling) and 8 were interpretations or syntheses (knowledge-transforming).
“The analysis of 36 papers that participants created revealed that 28 papers were summaries which Stein (1990) operationalized as products of knowledge-telling, and only 8 papers were interpretations or syntheses which Stein (1990) operationalized as products of knowledge-transforming processes.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Stein (1989)
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- cites Stein (1990) source
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- Interpretationcitation
These research findings reveal that many students tend to tell knowledge from sources rather than transform knowledge they borrow.
“These research findings reveal many students tend to tell knowledge from sources they consult rather than transform knowledge they borrow.”
Quote in the paperSubstantial claim - Premisecitation
In Hyytinen, Löfström, and Lindblom-Ylänne's experiment, only 19 of 138 participants thoroughly processed source texts by identifying and connecting main ideas, evaluating positions, and selecting relevant information for arguments.
“Only 19 of 138 participants managed to thoroughly process source texts by identifying and connecting main ideas, evaluating different positions presented in sources, and selecting relevant information to be included in arguments.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hyytinen, Löfström, and Lindblom-Ylänne's (2017)
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- Premisecitation
Students insufficiently used rhetorical devices such as reformulation markers and transition phrases.
“For instance, students insufficiently used rhetoric devices such as reformulation markers (e.g., in other words, in particular,…) and transition phrases (e.g., in addition to, therefore,…).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Aull and Lancaster ( 2014)
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- cites Aull (2015
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- Study design and conductown data
Using Artstein and Poesio's standard of .80 or higher, interrater reliability was low for Argumentation and Writing mode.
“Using Artstein and Poesio's (2008) standard for high interrater agreement statistics in discourse studies of .80 or higher, the interrater reliability was low for”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Artstein and Poesio's (2008)
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- Interpretationreasoning
In knowledge-telling texts, the writer tends to stay on topic.
“In knowledge-telling texts, the writer tends to stay on topic.”
Quote in the paperSubstantial claim - Interpretationreasoning
The evidence-argument semantic overlap feature could help further distinguish telling and transforming sentences in the content space.
“The evidence-argument semantic overlap feature could help further distinguish telling and transforming sentences in the content space with regard to the sentence's semantics.”
Quote in the paperSubstantial claim - Interpretationown data
This finding contrasts with Bereiter and Scardamalia's (1987) position that knowledge-telling texts usually fail to fulfill writing task requirements.
“This contrasts to Bereiter and Scardamalia's (1987) position that knowledge-telling texts most of the time fail to fulfill writing task requirements.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's (1987)
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- Interpretationreasoning
This indicates a writer's tendency to search for and employ source text cues semantically highly similar to the content of an argument.
“This indicates a writer's tendency to search for and employ source text cues semantically highly similar to the content of an argument.”
Quote in the paperNot a substantial claim - Interpretationown data
Undergraduates struggle to engage in knowledge transforming.
“Undergraduates struggle to engage in knowledge transforming.”
Quote in the paperSubstantial claim - Interpretationown data
The infrequency of processing above comprehension may suggest that students tend to limit their cognitive engagement to the two simplest forms.
“This may indicate students' tendencies to keep cognitive efforts within two least complex forms of cognitive engagement.”
Quote in the paperSubstantial claim - Interpretationown data
The finding that evidence quality explains much variance may indicate that, from the instructor's perspective, relevant and convincing evidence can meet task requirements when presented as knowledge-telling sentences.
“While there could be other factors affecting the overall essay score (e.g., appropriate use of headings, citation and grammar mistakes,…), this finding may indicate that, from instructor's perspective, relevant and convincing evidence can satisfactorily meet task requirements if presented as knowledge-telling sentences.”
Quote in the paperSubstantial claim - Interpretationown data
The degree of sentence-source semantic overlap cannot solely explain the sentence's writing mode.
“However, the degree of the sentence-source semantic overlap cannot solely explain the sentence's writing mode.”
Quote in the paperSubstantial claim
- May combine two claims. 31
- Classified as probably not a substantial claim. 65
- The quote only partly states this claim. 1
May combine two claims.
Findingown dataEight linguistic features were important predictors of whether an evidential sentence tells or transforms source knowledge: relative position of an evidential sentence in a paragraph, absolute distance between an evidential sentence and the most recent argument, incidence of low-and high-accessibility anaphoric devices, incidence of rhetorical connectives that indicate reasoning, content-word over
“Eight linguistic features were important predictors of whether an evidential sentence tells or transforms source knowledge: relative position of an evidential sentence in a paragraph, absolute distance between an evidential sentence and the most recent argument, incidence of low-and high-accessibility anaphoric devices, incidence of rhetorical connectives that indicate reasoning, content-word over”
Quote in the paperSubstantial claim- Rests on an assumption: The 22 linguistic features adequately capture the cognitive processes of knowledge transforming.
May combine two claims.
Findingown dataFor Writing mode, coders struggled to discriminate synthesis from analysis, and analysis from comprehension.
“In addition, for Writing mode, coders struggled to discriminate synthesis from analysis, and analysis from comprehension.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAmong four supervised machine learning algorithms, logistic regression had low prediction accuracy (nearly .57), while the other algorithms performed similarly (accuracy between .71 and .73).
“Except logistic regression which yielded low prediction accuracy (nearly .57)other algorithms performed similarly on the study dataset (prediction accuracy between .71 and .73).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the content problem space, three linguistic features are important predictors of knowledge transforming: content-word overlap between evidential sentence and source text, semantic overlap between evidential sentence and preceding argument, and semantic overlap between evidential sentence and source text.
“In the content problem space, three linguistic features are important predictors of knowledge transforming: content-word overlap between evidential sentence and source text, semantic overlap between evidential sentence and preceding argument, and semantic overlap between evidential sentence and source text.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe probabilities for Pos_Arg_Ev < 0 could not be considered reliable because only 10 such sentences were found.
“However, as I found only 10 of those sentences in the entire dataset, the probabilities when Pos_Arg_Ev < 0 could not be considered reliable.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataEvidential sentences with evidence-argument semantic overlap (Sol_A) between 10% and 70% are moderately likely to transform source knowledge, and this likelihood drops outside that interval.
“Further, the sentences having evidence-argument semantic overlap (Sol_A) on the interval 10% -70% are moderately likely to transform source knowledge.However, this likelihood drops for sentences where Sol_A is outside this interval.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataOnly 12 evidential sentences had negative semantic overlap with the argument.
“It should be also noted that only 12 evidential sentences had a negative semantic overlap with the argument.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataClaim(s) usually occupy the upper third of a paragraph, knowledge-transforming sentences most often come in the middle (usually within a 3-sentence window from claim), and their occurrence drops drastically in the lower third.
“From the structural point of view, claim(s) usually occupy the upper-third of a paragraph, knowledge-transforming sentences most often come in the middle (usually within a 3-sentence window from claim), and the occurrence of knowledge-transforming sentences drastically drops in the lower-third of paragraph.”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataMulticollinearity testing found correlations above 0.50 between several predictor pairs: Simultaneous and Reason r=0.87; Sequential and Causal_Con r=0.70; Sol_A and CWol_A r=0.55.
“The test for multicollinearity revealed the correlation of more than 0.50 between several pairs of variables:”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the 38 essays, 479 evidential sentences were knowledge-telling, representing 67.85% of all evidential sentences (M=12.61, SD=7.68 per essay).
“479 sentences were categorized as knowledge-telling sentences (per essay: M=12.61,SD=7.68).This represents 67.85 % of all evidential sentences in 38 essays.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe interactions between the content problem space and the rhetorical problem space in the knowledge-telling model are few and unproductive.
“The interactions between the content problem space and the rhetorical problem space in the knowledge-telling model are few and unproductive.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bereiter and Scardamalia (1987)
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PremisecitationMost of the time knowledge-telling essays fail to fulfill what the writing task has demanded.
“However, even though knowledge-telling compositions manage to tell relevant knowledge within the domain outlined by keywords of the assignment, most of the time these essays fail to fulfill what the writing task has demanded, i.e., convincing readers why plastic materials are harmful.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bereiter and Scardamalia (1987)
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PremisecitationThe knowledge-transforming model consists of two problem spaces, rhetorical and content.
“The knowledge-transforming model consists of two problem spaces, rhetorical and content.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's (1987)
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PremisecitationDeveloping knowledge-transforming skills in writing may help students improve their learning gains by actively building their knowledge, regardless of the domain.
“Accordingly, developing knowledge-transforming skills in writing may help students improve their learning gains by actively building their knowledge, regardless of the domain (Bereiter & Scardamalia, 1987).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter & Scardamalia, 1987
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PremisecitationThe knowledge-telling model ignores making the connections among elements of content.
“Bereiter and Scardamalia (1987) posited that the knowledge-telling model ignores making the connections among elements of content.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bereiter and Scardamalia (1987)
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PremisecitationKnowledge transforming promotes learning.
“Because this process triggers reflective thinking while writing, the authors argued knowledge transforming promotes learning.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter & Scardamalia, 1987
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PremisecitationPost-secondary students often fail to paraphrase, interpret, and evaluate content in sources.
“Subsequent research following Bereiter and Scardamalia's (1987) research showed post-secondary students often failed to: paraphrase, interpret, and evaluate content in sources; establish novel associations across multiple sources; and integrate multiply-sourced information into coherent form (Stein, 1989;Dong, 1996;Petrić, 2007;Boscolo, Ariasi, Favero, & Ballarin, 2011;Aull, 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Stein, 1989
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- cites Dong, 1996 source
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- cites Petrić, 2007
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InterpretationreasoningThese demands appear to prevent most postsecondary students from successfully engaging in knowledge transforming.
“These demands appear to prevent most postsecondary students from successfully engaging in knowledge transforming.”
Quote in the paperNot a substantial claim- Rests on an assumption: Knowledge transforming is a highly demanding and challenging task where multiple cognitive and metacognitive processes interweave.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationTo meaningfully engage in knowledge-transforming processing, writers should engage constructive planning.
“To meaningfully engage in knowledge-transforming processing, writers should engage constructive planning (Flower et al., 1989).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Flower et al., 1989
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PremisecitationStein (1990) identified four major groups of cognitive processes that occur in reading and writing from multiple sources: planning, monitoring, elaborating, and structuring.
“In their seminal work Stein (1990) identified four major groups of cognitive processes that occur in reading and writing from multiple sources: planning, monitoring, elaborating, and structuring.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Stein (1990) source
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PremisecitationKnowledge telling is a component of the knowledge transforming process.
“Knowledge telling is a component of the knowledge transforming process.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bereiter and Scardamalia (1987)
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PremisecitationTardy's study of initial master thesis and research paper drafts from two graduate students revealed challenges with structuring composition and evaluating source information to promote claims.
“The initial master thesis and research paper drafts written by two graduate students participating in Tardy's (2005) study revealed challenges writers faced with structuring composition and evaluating source information to promote their claims in the draft.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Tardy's (2005)
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Study design and conductnone givenTo reach high interrater agreement among the three coders, coding involved three rounds of training together, coding independently, and calculating reliability.
“To reach high interrater agreement among the three coders, coding involved three rounds of train together → code independently → calculate reliability.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationStab and Gurevych found structural features were helpful in explaining differences between argumentative and non-argumentative units in text.
“Stab and Gurevych (2017) found structural features were helpful in explaining differences between argumentative (thesis statement, sub-claim, evidence) and non-argumentative units in the text.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Stab and Gurevych (2017)
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PremisecitationAccording to Bereiter and Scardamalia's writing model, students engaged in knowledge telling neglect cognitive and metacognitive operations that transform knowledge.
“According to Bereiter and Scardamalia's (1987) writing model, students engaged in knowledge telling neglect cognitive and metacognitive operations that transform knowledge.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter and Scardamalia's (1987)
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PremisecitationA writer's tendency to switch to knowledge telling under vague task requirements and avoid additional cognitive challenges is an explanation for the outcome, consistent with Weinstock's research.
“First, a writer's tendency was to switch to knowledge telling in the context of vague task requirements and thus avoid additional cognitive challenges, which resonates with findings from Weinstock's (2010) research.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Weinstock's (2010)
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PremisecitationAnalyzing almost 2,000 citation instances, Petrić identified an overall tendency towards attribution.
“Analyzing almost 2,000 instances of citation use in written texts, Petrić identified overall students' tendency towards attribution, a descriptive rhetorical function that”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Petrić (2007)
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Study design and conductreasoningThe relative position of an evidential sentence in a paragraph identifies whether it appears toward the beginning, middle or end, allowing analysis of the relationship between position and writing mode.
“This information identifies sentences that appear toward the beginning, middle or end of a paragraph, allowing for the analysis of the relationship between a sentence's position and its writing mode.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationStudents had issues elaborating source materials and structuring and revising written composition.
“Students seemed to have issues elaborating source materials, and structuring and revising written composition.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Boscolo, Arfé and Quarisa's (2007)
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PremisecitationThe idea that a computer can offer scaffolding emerged from research on interactive learning environments.
“The idea that a computer can offer scaffolding emerged from research on interactive learning environments (see Reiser, 2004).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Reiser, 2004
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PremisecitationThe Open Essayist analyzes essay drafts using NLP and generates feedback about rhetoric and prompts reflection.
“The Open Essayist (Whitelock, Twiner, Richardson, Field & Pulman, 2015) analyzes the essay draft using natural language processing (NLP) algorithms and generates feedback about rhetoric (e.g., most prominent words, representative sentences, essay's internal structure) and provides prompts that encourage the student's reflections on the draft.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Whitelock, Twiner, Richardson, Field & Pulman, 2015
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InterpretationreasoningWhen the task is argumentative writing, this tendency leads to poorly articulated evidence and essays that lack persuasiveness.
“When the task is argumentative writing, this leads to poorly articulated evidence resulting in essays that lack persuasiveness.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenCognitive linguistics offers means of analyzing linguistic choices writers made while constructing meaning in genre-specific texts.
“For instance, cognitive linguistics offers means of analyzing linguistic choices writers made while constructing meaning in genre-specific texts (e.g., argumentation).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationIn argumentative writing, an argument expressed and supported in a body paragraph may be considered as comprised of building blocks that create particular rhetorical moves.
“In argumentative writing, an argument expressed and supported in a body paragraph may be considered as comprised of these building blocks that create particular rhetorical moves (Tanko, 2017).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Tanko, 2017
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PremisecitationIn Boscolo, Arfé and Quarisa's experiment, 52 undergraduate participants conceived academic writing as transforming knowledge from sources through elaboration and continuous revision rather than restating knowledge and providing personal points of view.
“The 52 undergraduate participants in Boscolo, Arfé and Quarisa's (2007) experiment conceived academic writing as a means of transforming knowledge from other sources through elaboration and continuous revision, rather than through restating knowledge and providing personal points of view.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Boscolo, Arfé and Quarisa's (2007)
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Study design and conductcitationAfter separate coding, inter-rater agreement was calculated using the AC1 statistic.
“After separate coding, the inter-rater agreement was calculated using the AC1 statistic (Gwet, 2002).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gwet, 2002
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PremisecitationNovice writers can gradually hone task-relevant cognitive processes and increase their ability to monitor and control those processes until feedback is no longer needed.
“In this way, novice writers can gradually hone task-relevant cognitive processes and increase their ability to monitor and control those processes to a point where feedback is no longer needed (Ericsson, 2006).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Ericsson, 2006
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PremisecitationDong noted students' problems to paraphrase, interpret, synthesize, evaluate and integrate content from reading materials, and these skills present difficulties for both native and non-native English writers.
“The researcher noted students' problems to paraphrase, interpret, synthesize, evaluate and integrate content from reading materials, noting these skills present difficulties both for native and non-native English writers.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Dong (1996) source
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Study design and conductreasoningThe linguistic features selected for this study are proxies of cognitive processes a writer applied to relay features of source knowledge and create evidential sentences.
“The linguistic features selected for this study are proxies of cognitive processes a writer applied to relay features of source knowledge and create evidential sentences.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningThe absolute distance feature combined with relative position may approximate a writer's engagement in text structuring and indirectly in constructive planning.
“This feature combined with relative position of evidential sentences in a paragraph may approximate writer's engagement in text structuring (e.g., arranging high-level propositions) and, indirectly, in constructive planning (e.g., organizing goals hierarchically).”
Quote in the paperNot a substantial claim- The authors state this as an assumption: In a continuous sequence of claim sentences, the evidential sentence that follows the sequence is connected to the last claim in the sequence.
Probably not a substantial claim: may not pass S4 (based).
InterpretationreasoningThe novel approach in this study addresses both rhetorical and content aspects of writing from multiple sources.
“The novel approach in this study addresses both rhetorical and content aspects of writing from multiple sources.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationPetrić linked attribution to knowledge-telling and stated that attribution involves re-telling source content instead of building novel associations and elaborating sources with prior knowledge.
“Petrić linked attribution to the knowledge-telling mode of writing and pointed out that, by engaging in attribution, students are just re-telling what is stated in the sources instead of building novel associations and elaborating sources using prior knowledge.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Petrić (2007)
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InterpretationreasoningIneffective argument production could be further explained by a lack of metacognitive monitoring and control.
“Their production of ineffective arguments could be further explained by a lack of metacognitive monitoring (e.g., for writing task and goals) and control (e.g., editing and revising the draft).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
PremisecitationTo develop cognitive and self-regulatory processes that characterize knowledge transforming, writers need effortful and scaffolded writing practice within an authentic learning environment.
“To develop cognitive and self-regulatory processes that characterize knowledge transforming, writers need to be engaged in effortful and scaffolded (i.e., externally supported) writing practice within an authentic learning environment (Proske, Narciss, & McNamara, 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Proske, Narciss, & McNamara, 2012
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PremisecitationThe AC1 method corrects agreement among raters for chance and is robust to skewed distribution of coding categories.
“This method corrects agreement among raters for the probability of chance agreement and is robust to skewed distribution of coding categories (Haley, Thomas, Petre, & De Roeck, 2008).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Gwet, 2002
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- cites Haley, Thomas, Petre, & De Roeck, 2008
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PremisecitationEscribo scaffolds students by providing informational hints on how to collect source information, plan, write and revise essays.
“Escribo (Proske et al., 2012) scaffolds students by providing informational hints (Roscoe, Varner, Crossley, & McNamara, 2013) on how to collect source information, plan, write and revise essays.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Proske et al., 2012
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- cites Roscoe, Varner, Crossley, & McNamara, 2013
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May combine two claims.
InterpretationcitationEven in unambiguous task contexts, such as argumentative writing, post-secondary students still tend to engage in knowledge telling and have difficulty strategically using cognitive processes embedded in knowledge transforming.
“However, as other studies reveal, even in contexts where the task requirements were unambiguous, such as an argumentative writing task investigated in this study, post-secondary students still tend to engage in knowledge telling, having hard times to strategically use cognitive processes embedded into knowledge transforming.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationScholars in different fields could benefit from detailed methodology of cognitive linguistics.
“Scholars in different fields could benefit from detailed methodology of cognitive linguistics (Croft & Cruse, 2004;Dancygier, 2017).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Croft & Cruse, 2004
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- cites Dancygier, 2017
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Classified as probably not a substantial claim. May combine two claims.
PremisecitationSanders and Schihperoord posited that text structure may provide insights into cognition applied in writing, arguing that appropriate analysis of written composition can reveal significant traces of the writer's cognitive representation.
“In line with this, Sanders and Schihperoord (2006) posited the text structure may provide insights into cognition applied in writing, arguing appropriate analysis of written composition can reveal”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sanders and Schihperoord (2006)
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Premisenone givenAcross different levels of higher education, students appear to struggle applying cognitive and self-regulatory strategies that underlie this writing model.
“The reviewed studies agree that, across different levels of higher education, students appear to struggle applying cognitive and self-regulatory strategies that underlie this writing model.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe Web-Based Tutor lets students practice identifying elements of an argument using predefined formative feedback.
“In the Web-Based Tutor (Wolfe, Britt, Petrovic, Albrecht, & Kopp, 2009) students practice identifying elements of an argument (main claim, reason, counterargument, and response to the counterargument) using predefined formative feedback.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Wolfe, Britt, Petrovic, Albrecht, & Kopp, 2009
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PremisecitationTo model linguistic properties of knowledge-telling and knowledge-transforming discourses, it is important to understand cognitive processes writers use when developing text.
“To model linguistic properties of knowledge-telling and knowledgetransforming discourses, it is important to understand cognitive processes writers use when developing text (Sanders & Spooren, 2007).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sanders & Spooren, 2007
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PremisecitationBereiter and Scardamalia emphasized the importance of the connection between linguistic research and cognitive models.
“Moreover, Bereiter and Scardamalia (1987) emphasized the importance of the connection between linguistic research and cognitive models.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bereiter and Scardamalia (1987)
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Classified as probably not a substantial claim.
PremisecitationAriel distinguished between high- and low-accessibility anaphoric devices.
“Ariel (1990) distinguished between high-and lowaccessibility anaphoric devices.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Ariel (1990)
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe XIP Dashboard supports post-secondary writers in searching for relevant source content, classifies sentences by rhetorical functions, and provides learning analytics to instructors.
“The XIP Dashboard (Simsek, Buckingham Shum, Sandor, De Liddo, & Ferguson, 2013) supports post-secondary writers in searching for relevant source content, classifies sentences according to their rhetorical functions (summarizing, background knowledge, contrasting ideas, novelty, significance, surprise, open question and generalization), and provides learning analytics to instructors.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Simsek, Buckingham Shum, Sandor, De Liddo, & Ferguson, 2013
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Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenThe aforementioned tools have demonstrated empirical benefits in supporting particular cognitive processes in learning contexts where reading and writing co-occur.
“Aiming to support particular cognitive processes in learning contexts where reading and writing co-occur, the aforementioned tools have demonstrated empirical benefits.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
InterpretationreasoningClassifying students' evidential sentences in terms of Bloom's taxonomy forms a basis for analytics to guide students toward producing knowledge-transforming texts with arguments strengthened by more thorough articulation of content with evidence.
“Thus, classifying students' evidential sentences in terms of Bloom's taxonomy forms a basis for analytics to guide students toward producing knowledge transforming texts with arguments strengthened by more thorough articulation of content with evidence.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationAcquisition of domain knowledge might not be accomplished to its greatest extent when students limit engagement to knowledge telling.
“Moreover, the acquisition of the domain knowledge might not be accomplished to its greatest extent when students limit their engagement to knowledge telling (Bereiter & Scardamalia, 1987).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Bereiter & Scardamalia, 1987
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PremisecitationAccording to Bransford, Barclay and Franks, sentences represent informational blocks that build wholistic semantic descriptions at a high level.
“According to Bransford, Barclay and Franks (1972), sentences represent informational blocks that build wholistic semantic descriptions at a high level.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bransford, Barclay and Franks (1972)
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Study design and conductreasoningUsing Bloom's taxonomy to classify writers' evidential sentences could reflect underlying cognitive and metacognitive processes writers engage in.
“Using Bloom's taxonomy to classify writers' evidential sentences could reflect underlying cognitive and metacognitive processes writers engage in.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAull and Lancaster and Aull found that undergraduates lack text structuring strategies.
“Aull and Lancaster ( 2014) and Aull (2015 undergraduates lack text structuring strategies.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Aull and Lancaster ( 2014)
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- cites Aull (2015
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May combine two claims.
PremisecitationThe essays were assessed as moderately informative and cohesive, and poorly integrated and organized.
“The essays were assessed as moderately informative and cohesive, and also poorly integrated and organized.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Boscolo, Arfé and Quarisa's (2007)
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Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe authors linked this problem to students' negligence in reflecting on the writing process.
“The authors linked this problem to students' negligence in reflecting on the writing process, explaining that although”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hyytinen, Löfström, and Lindblom-Ylänne's (2017)
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Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPetrić developed a coding scheme of nine rhetorical functions for source and citation use in master students' writing.
“Researching source and citation use in master students' writing, Petrić (2007) developed a coding scheme consisting of nine rhetorical functions: attribution, exemplification, further reference, statement of use, application, evaluation, establishing links between sources, comparison of one's own findings or interpretation with other sources, and other.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Petrić (2007)
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitationThe model was selected using cross-validation on an 80% training sample and tested on a 20% hold-out sample.
“Cross-validation was performed on the training data (80% sample of dataset), while 20% was the hold-out data for testing the model performance, following suggestions by Haykin (1994).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Haykin (1994)
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Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningWhile marking, the instructor may focus on the relationship between a claim and relevant evidence in the rhetorical space.
“While marking the argumentative essay, the instructor may focus on the relationship between a claim and relevant evidence in the rhetorical space (i.e., does the evidence support claim?).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThis pattern indicates a writer's tendency to generate text by referring to cues in already produced text while staying on topic defined by the argument.
“This indicates a writer's tendency to generate text by referring to cues in text already produced, while staying on topic defined by the argument.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningMany writers respond to task requirements by putting less cognitive effort into writing.
“This finding reflects the idea that many writers are interested in responding to task requirements by putting less cognitive effort into it.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationKnowledge and comprehension categories represent less complex cognitive engagement.
“both categories representing less complex cognitive engagement (Agarwal, 2018)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Agarwal, 2018
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Classified as probably not a substantial claim. May combine two claims.
PremisecitationLow-accessibility anaphoric devices are noun phrases and indefinite articles; they contain much linguistic material and signal termination of the current topic and activation of another.
“Lowaccessibility anaphoric devices are noun phrases (e.g., bilingual children) and indefinite articles (a and an).Sanders and Spooren (2007) posit low-accessibility devices contain much linguistic material and, as such, signal a writer's termination of a current topic and activation of another topic.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sanders and Spooren (2007)
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Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe result that content-word overlap is high for knowledge-transforming sentences may indicate that writers producing such sentences tended to engage in elaborating and structuring processes.
“Although this metric was expected to be high for knowledge-telling sentences, the result may indicate that writers producing knowledge-transforming sentences tended to be engaged in elaborating and structuring processes of knowledge transforming.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPetrić (2007) found that students generally repeated source content by summarizing, paraphrasing, or quoting it directly.
“Petrić (2007) who reported an overall tendency of students to re-tell what is stated in sources by summarizing/paraphrasing or directly quoting it.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Petrić (2007)
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InterpretationcitationThe study's finding that undergraduates generally convey rather than transform source knowledge aligns with Petrić (2007).
“This finding is in line with Petrić (2007)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Petrić (2007)
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationA noun-phrase-rich knowledge-transforming sentence immediately following an argument could be a proxy for elaboration.
“For instance, a noun-phrase-rich knowledge-transforming sentence immediately following an argument could be a proxy for elaboration, one of the main cognitive processes in knowledge-transforming (Stein, 1989).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Stein, 1989
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
InterpretationreasoningFeedback on source content usage in argumentative essays has rarely been provided by instructors and has a meager effect on essay score.
“For this reason, feedback on source content usage in the argumentative essay has been rarely provided by the instructors and this characteristic of writing therefore has a meager effect on the essay score.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationHyytinen, Löfström, and Lindblom-Ylänne (2017), in an experiment with roughly three times as many compositions as this study, found that most students across multiple higher-education levels struggled to select relevant source information, link main ideas, and assess alternative positions in sources.
“They demonstrated a vast majority of students from several levels of higher education faced challenges deciding on relevant source information, connecting main ideas and evaluating alternative positions presented in sources.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hyytinen, Löfström, and Lindblom-Ylänne's (2017)
Not checked in the free run.
Classified as probably not a substantial claim.
InterpretationreasoningA scorer normally would not read sources a student cited to locate relevant information and assess transformation.
“A scorer normally would not read sources a student cited (unless suspecting plagiarism) to locate relevant pieces of information and assess that information was transformed in evidential sentences.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoningThese two types of linguistic markers are proxies for change in topic, which is one of the essential parameters distinguishing knowledge-telling from knowledge-transforming.
“These two types of linguistic markers are proxies for change in topic which is one of the essential parameters distinguishing knowledge-telling from knowledgetransforming.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe opposite effect could be explained by a writer's disposition to take advantage of a chain of reasoning already provided in a source and translate it into a composition, avoiding further transformation.
“This could be explained by a writer's disposition to take the advantage of a chain of reasoning as already provided in a source article and just translate it into a composition, avoiding further transformation (e.g., by integrating that information with prior knowledge).”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductreasoningThe total essay score was selected for analysis because it and the evidence score correlate as much as reliability allows, making it a more conservative reference point.
“Since the total essay score and evidence score correlate as much as reliability allows, the total essay score was selected for analysis as it would be a more conservative reference point.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationThe study's results resonate with the findings of Hyytinen, Löfström, and Lindblom-Ylänne's (2017) experiment.
“This resonates with results of Hyytinen, Löfström, and Lindblom-Ylänne's (2017) experiment sampling about three times more compositions than in this study.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hyytinen, Löfström, and Lindblom-Ylänne's (2017)
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationHigh-accessibility devices are pronouns and definite article; they contain less linguistic material and indicate continuation of the previous topic.
“High-accessibility devices are pronouns (personal and possessive) and definite article (the).They contain less linguistic material (Sanders & Spooren, 2007) and indicate a writer's continuation of the previous topic.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sanders & Spooren, 2007
Not checked in the free run.
The paper relies on this without support.
The essay scores assigned by the course instructor are a valid measure of essay quality.
“The coefficient of knowledge transforming positively but weakly correlated with essay scores assigned by the course instructor.”
The paper relies on this without support.
Writers who generate text by the knowledge-telling process typically underuse monitoring and planning needed to develop text coherence.
“Writers who generate text by the knowledge-telling process typically underuse monitoring and planning needed to develop text coherence.”
The paper relies on this without support.
Knowledge telling writers focus overly on how to generate basic text, e.g., staying on topic.
“Rather, knowledge telling writers focus overly on how to generate basic text, e.g., staying on topic.”
The paper relies on this without support.
These students tend to tell knowledge from sources they consult rather than transform knowledge they borrow.
“These students tend to tell knowledge from sources they consult rather than transform knowledge they borrow.”
The paper relies on this without support.
In the rhetorical problem space, many such writers fail to elaborate ideas mined from source texts, and list rather than structure propositions to form convincing arguments.
“For example, in the rhetorical problem space, many such writers fail to elaborate ideas mined from source texts, and list rather than structure propositions to form convincing arguments.”
The paper relies on this without support.
In the content problem space, they struggle to decide which source material is best to include in the essay.
“In the content problem space, they struggle to decide which source material is best to include in the essay, don't recognize appropriate applications of prior knowledge about the essay topic, and overlook useful linking of information across multiple sources.”
The paper relies on this without support.
They don't recognize appropriate applications of prior knowledge about the essay topic.
“In the content problem space, they struggle to decide which source material is best to include in the essay, don't recognize appropriate applications of prior knowledge about the essay topic, and overlook useful linking of information across multiple sources.”
The paper relies on this without support.
They overlook useful linking of information across multiple sources.
“In the content problem space, they struggle to decide which source material is best to include in the essay, don't recognize appropriate applications of prior knowledge about the essay topic, and overlook useful linking of information across multiple sources.”
The paper relies on this without support.
Metacognitive monitoring and control strategies interweave during knowledge-transformative writing.
“Metacognitive monitoring and control strategies interweave during knowledgetransformative writing.”
The paper relies on this without support.
Knowledge transforming is a highly demanding and challenging task where multiple cognitive and metacognitive processes interweave.
“Knowledge transforming is considered a highly demanding and challenging task where multiple cognitive and metacognitive processes interweave.”
The paper relies on this without support.
The 22 linguistic features adequately capture the cognitive processes of knowledge transforming.
“A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model cognitive processes in knowledge transforming, a methodological contribution to research on multi-source based writing.”
The paper relies on this without support.
The coefficient of knowledge transforming computed from the algorithm is a valid measure of knowledge transforming in essays.
“A corpus of 38 undergraduates' essays was examined using this algorithm and a coefficient of knowledge transforming was computed for each essay.”
The authors state this as an assumption.
In a continuous sequence of claim sentences, the evidential sentence that follows the sequence is connected to the last claim in the sequence.
“In case a continuous sequence of claim sentences is provided, I assume that evidential sentence that comes after this sequence is connected to the last claim in the sequence.”
The paper relies on this without support.
The LSA training corpus adequately represents the semantics of domain knowledge in educational psychology.
“I chose this set of texts to train the LSA model since this corpus well represents semantics of domain knowledge in educational psychology.”
The paper relies on this without support.
The topics students wrote about in their essays relate to concepts in educational psychology.
“Moreover, the topics students wrote about in their essays relate to concepts in educational psychology.”
The paper relies on this without support.
Content words are helpful in modeling the variance of content.
“Content words are deemed helpful in modeling the variance of content in the Synonyms were taken into account in calculation of these features.”
The paper relies on this without support.
The random forest algorithm provides means to reliably measure and report variable importance.
“Also, this algorithm provides means to reliably measure and report variable importance, which is needed to answer RQ4 in this study.”
The paper relies on this without support.
Semantic similarity measures ensure that content used to support arguments is appropriate given the cited source.
“Semantic similarity measures help to ensure that content the writer employed to support arguments is appropriate given the textual source cited.”
Statistics recomputed
Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.
- Not confirmedt(38) = -2.001reported p = .052 · recomputed p = .053
“t(38) = -2.001,p = .052”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
An absolute distance is later described as negative
MinorThe feature is defined as an absolute count of sentences separating evidence from a preceding claim. The results then assign it negative values for evidence appearing before a claim, which cannot be values of that defined absolute distance.
“Absolute distance between evidential sentence and the most recent claim: This linguistic feature counts the number of sentences separating an evidential sentence and the preceding claim (argument/counterargument/rebuttal).”
“Negative values in this variable capture the relative distance of evidential sentences that come before arguments they support.”
Cites
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The Elements of Statistical Learning
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WordNet: a lexical database for English
Miller, G. A. (1995) · Communications of the ACM · doi:10.1145/219717.219748 · Cited by 14,015 · see citing works
Use of Ranks in One-Criterion Variance Analysis
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Self-citationComputer-Based Assessment Of Essays Based On Multiple Documents
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Cited by
Sorted by citations
Examining the critical role of evaluation and adaptation in self-regulated learning
Raković, M., Bernacki, M. L., Greene, J. A., Plumley, R. D., Hogan, K. A., Gates, K. M., & Panter, A. T. (2021) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2021.102027 · Cited by 114 · see citing works
Self-citationChai, C. S., Chiu, T. K. F., Wang, X., Jiang, F., & Lin, X. (2022) · Sustainability · doi:10.3390/su15010605 · Cited by 101 · see citing works
Mejeh, M., & Rehm, M. (2024) · Educational Technology Research and Development · doi:10.1007/s11423-024-10345-1 · Cited by 96 · see citing works
“…examination of texts’ linguistic properties” (Cross-ley et al., 2016, p. 7) that can handle large amounts of text data that are being produced, among others, within ALT. Generally, NLP has been suggested to provide a systematic approach to enable computer-based scaffolding (Raković, et al., 2021).”
Rodríguez-Ortiz, M. Á., Santana-Mancilla, P. C., & Anido, L. (2025) · Applied Sciences · doi:10.3390/app15158679 · Cited by 122 · see citing works
Discourse synthesis: Textual transformations in writing from sources
Nelson, N., & King, J. R. (2023) · Reading and Writing · doi:10.1007/s11145-021-10243-5 · Cited by 61 · see citing works
“Also seeming to have potential for research in discourse synthesis is a new algorithm for analyzing arguments based on multiple sources that identifies and classifies transformed elements (Raković et al., 2021).”
BackgroundAssessing second-language academic writing: AI vs. Human raters
Geçkin, V., Kızıltaş, E., & ÇINAR, Ç. (2023) · Journal of Educational Technology and Online Learning · doi:10.31681/jetol.1336599 · Cited by 56 · see citing works
“The issue arises when proxes cannot differentiate between surface level features such as spelling mistakes and sentence and essay length and deeper features that reflect the semantic and rhetoric dimensions of the written piece (Raković et al., 2021).”
Trends in NLP for personalized learning: LDA and sentiment analysis insights
Yu, J. H., & Chauhan, D. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12988-2 · Cited by 44 · see citing works
“These articles often discuss how NLP can be used to tailor learning experiences based on detailed analysis of learner interactions and performance data (e.g., Botelho et al., 2023; Emara et al., 2021; Han et al., 2021; Raković et al., 2021).”
Raković, M., Iqbal, S., Li, T., Fan, Y., Singh, S., Surendrannair, S., Kilgour, J., van der Graaf, J., Lim, L., Molenaar, I., et al. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12769 · Cited by 33 · see citing works
Self-citationPredictors of middle school students’ perceptions of automated writing evaluation
Wilson, J., Zhang, F., Palermo, C., Cordero, T. M. C., Myers, M. C., Eacker, H., Potter, A., & Coles, J. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104985 · Cited by 17 · see citing works
Fernandez, J., & Guilbert, J. (2024) · Metacognition and Learning · doi:10.1007/s11409-024-09398-7 · Cited by 21 · see citing works
“In such a case, in addition to self-regulating their writing, students first need to process the vari - ous documents and extract information deemed relevant to the task at hand, making their texts’ quality dependent on mastery of text comprehension strategies as well (Raković et al., 2021, 2023 ).”
InfluentialPijeira‐Díaz, H. J., Braumann, S., van de Pol, J., van Gog, T., & de Bruin, A. B. H. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13431 · Cited by 11 · see citing works
Iqbal, S., Raković, M., Chen, G., Li, T., Bajaj, J., Mello, R. F., Fan, Y., Aljohani, N. R., & Gašević, D. (2024) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3636555.3636927 · Cited by 10 · see citing works
Self-citationIqbal, S., Raković, M., Chen, G., Li, T., Mello, R. F., Fan, Y., Fiorentino, G., Aljohani, N. R., & Gašević, D. (2023) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3576050.3576112 · Cited by 10 · see citing works
Self-citationTowards Automatic Content Analysis of Rhetorical Structure in Brazilian College Entrance Essays
Mello, R. F., Fiorentino, G., de Miranda, P. B. C., et al. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78270-2_29 · Cited by 9 · see citing works
Self-citationOptimizing Formative Assessment with Learning Analytics
Banihashem, S. K., Gašević, D., Noroozi, O., Jarodzka, H., Brinke, D. J.-T., & Drachsler, H. (2025) · Review of Educational Research · doi:10.3102/00346543251370753 · Cited by 35 · see citing works
“Additionally, learning analytics can aid in promoting effective group argumentation (Ouyang, Tang, et al., 2023), group learning (Z. Sun & Theussen, 2023), knowledge construction (Zheng et al., 2023), and knowledge transformation (Raković et al., 2021) in collaborative learning settings.”
AI in the Writing Process: How Purposeful AI Support Fosters Student Writing
Siddiqui, M. N., Feliciano, V. A., Pea, R. D., & Subramonyam, H. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98459-4_14 · Cited by 6 · see citing works
Towards Real-Time Automated Self-regulated Learning Detection in Essays
Bistolfi, I., de Mooij, S., van der Graaf, J., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98420-4_27 · Cited by 5 · see citing works
Multiple Documents Literacy: Theory, Research, and Application
Strømsø, H., & Braten, I. (2013) · Oxford University Press eBooks · doi:10.1093/obo/9780199756810-0092 · Cited by 3 · see citing works
Yang, L., Wen, X., & Chen, Y. (2026) · Journal of Applied Research in Intellectual Disabilities · doi:10.1111/jar.70258 · Cited by 1 · see citing works
Zeng, P., Zheng, W., Wu, H., Lin, N., Yang, A., & Jiang, S. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-9443-0_16 · Cited by 1 · see citing works
Alnashiri, H., Raković, M., Nawaz, S., Li, X., Fernandez-Nieto, G. M., Qian, K., Lämsä, J., Lim, L., Bannert, M., Järvelä, S., et al. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70331
Self-citationYaşartürk, İ., Öksüz, H. İ., Deniz, R., & Öztürk, M. (2026) · PLoS ONE · doi:10.1371/journal.pone.0358694
“While human evaluators focus on contextual, creative, and intentional variables that convey deeper meaning, AI tools score text based on numerical proxy variables such as word count, sentence length, and structural arrangement [44,45].”
InfluentialFrom words to components: Mapping linguistic features in source-based writing
Potter, A. A., Crossley, S. A., Öncel, P., Allen, L. K., Xu, X., Balyan, R., Arner, T., Roscoe, R. D., & McNamara, D. S. (2026) · Assessing Writing · doi:10.1016/j.asw.2026.101108
Automated Rhetorical Device Detection in Student Essays for Argumentation Skill Training
Mustafayeva, S., Sattorova, Z. I., Erkinov, A., et al. (2026) · International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS) · doi:10.1109/iciscois62701.2026.11447782
“KTSC used 22 linguistic features grounded in cognitive theories and Bloom's taxonomy to categorize evidentiary sentences with 75% accuracy [12].”
Reviving a Medieval Structure to Scaffold or Substitute Argumentative Essay Writing
Ruiz, M. J. G., & Orejel, L. G. O. (2024) · College Teaching · doi:10.1080/87567555.2024.2383870
“…of other educators in the literature—students struggled to a) take a clear stance, b) consider opposing viewpoints, and c) synthesize evidence to support their claims (Kleemola, Hyytinen, and Toom 2022; Liu and Stapleton 2014; Raković et al. 2021; Wingate 2012; Wolfe, Britt, and Butler 2009).”
An Interview With Philip H. Winne
Winne, P. H. (2022) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-64802-855-720251005
Self-citation
- Authors
- Raković, M., Winne, P. H., Marzouk, Z., & Chang, D.
- Affiliations
- Monash University (AU)
- Simon Fraser University (CA)
- Kwantlen Polytechnic University (CA)
- Corresponding author
- Raković, Mladen
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2021-02-15
- Volume
- 37
- Issue
- 4
- Pages
- 903-924
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W2997152227
- Cited by
- 26
- References
- 74
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 7 · 2023: 3 · 2022: 4 · 2021: 2 · 2013: 1
- FWCI
- 3.38
- Type
- journal article
- Language
- en
- Open access
- green
- summit.sfu.ca
- Licence
- Locations
- Journal of Computer Assisted Learning (publishedVersion)
- Summit (Simon Fraser University) (submittedVersion, other-oa)
- Summit (Simon Fraser University) (submittedVersion)
- Funders
- Simon Fraser University
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- knowledge transformation, argumentative essay, writing analytics, paraphrase, source integration, Bloom's taxonomy, automatic classification, undergraduate writing, machine learning classification, linguistic features
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-09-29.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-29.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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