Strategy Referents When Learning from Multiple Texts
The second strategy framework I consider in this chapter comes from the Integrated Framework of Multiple Texts (IF-MT; List & Alexander, 2018b). The IF-MT conceptualizes multiple text use as a three-stage process, including preparation, execution, and production. In the execution stage, List and Alexander (2018b) classified the strategies that students engage during multiple text use as behavioral, cognitive, or metacognitive in nature. They defined behavioral strategies, including information search, selection, and navigation, as intentional actions performed during the course of engaging with multiple texts. Cognitive strategies, then, are defined as the mental processes that students use when trying to learn from multiple texts. These are further distinguished as intra-textual or inter-textual in nature. Intra-textual processes refer to those strategies that are deployed in reference to only a single text; whereas, inter-textual processes refer to strategies that require the simultaneous consideration of more than one text at a time. Finally, metacognitive strategies are regulatory processes engaged based on students’ monitoring of their comprehension, epistemic standards, and task satisfaction. As such, our view of metacognitive strategy use is embedded in Schraw and Moshmans (1995) framework, which suggests that metacognition includes both (a) metacognitive knowledge (i.e., knowledge of cognition, such as strategy knowledge) and the (b) regulation of cognition (i.e., planning, monitoring, and evaluation). In this chapter, due to my focus specifically on strategy use during task completion, I am particularly concerned with students’ metacognitive monitoring (i.e., reflection and evaluation of their cognition during task completion) and any regulation (i.e., deliberate efforts to control cognition or affect during task completion) that may result.
The framework suggested by List and Alexander (2018b) may be said to adopt a directed view of strategy use. In other words, they classified the strategies that students engage according to the referents at which they are directed or the content they address (i.e., a single text, multiple texts, or learners’ knowledge and beliefs). The possible targets or referents for strategy use are reflected in each column of Table 8.1.
Comprehensive Strategy Framework
By overlapping the strategy functions and referents described by Cho et al. (2018) and List and Alexander (2018b), I introduce the Comprehensive Strategy Framework (CSF), presented in Table 8.1. Each row of the CSF (Table 8.1) identifies one of three
Table 8.1 Sample Strategies Corresponding to the Functions and Referents Identified in the Comprehensive Strategy Framework
general strategy functions, as specified by Cho et al. (2018). These functions include (a) constructive-integrative processing, (b) critical-analytic processing, and (c) metacog-nitive-reflective processing. Each column of the CSF corresponds to a strategy referent, as identified by List and Alexander (2018b). Referents include a single text, multiple texts, or learners themselves, including their prior knowledge and beliefs. Jointly, the rows and columns of the CSF introduce the idea that any strategy that students engage during multiple text use may be decomposed according to its function and referent, and that any strategic function that students carry out (e.g., identifying important information) may be executed in reference to a single text, to multiple text, or to students’ own knowledge and beliefs. In the sections that follow, I present examples of various strategic functions carried out across the variety of referents possible during students’ learning from multiple texts.
Constructive-Integrative Processing. As conceptualized by Cho et al. (2018), constructive-integrative processing involves students’ attempts to make meaning from multiple texts and includes strategies such as searching for and locating information, identifying and learning important ideas, and building new knowledge. Adopting List and Alexander’s (2018b) directional view of strategy use, the primary distinction in constructive-integrative processing may be whether students are trying to make sense of information presented only within a single text, occurring across multiple texts, or arising from students’ prior knowledge.
This difference in foci as the referents for processing is highlighted in Wolfe and Goldman (2005) think-aloud study of adolescents reading conflicting texts about the fall of the Roman Empire. Specifically, Wolfe and Goldman coded students’ think-aloud utterances both for the type of processing evidenced (i.e., referred to as a think-aloud event) and for the information source(s) targeted, with four information sources examined (i.e., information from the same text; information from a previous text; prior knowledge; and information from a previous think-aloud comment). In total, 58% of students’ utterances reflected elaborations, or attempts to make meaning from information in texts. These included strategies aimed at developing: (a) causal (25.24%) or comparative (8.61%) (i.e., connections that enriched the meaning of texts) selfexplanations, (b) surface associations (45% ) (i.e., prior knowledge-based connections that did not contribute to textual understanding); (c) predictions (2%) (i.e., expectations), and (d) surface-text connections (12%) (i.e., superficial connections based on semantic overlap). These various elaborative functions were able to be carried out in reference to a single text, to multiple texts, or to students’ prior knowledge. Specifically, 49% of elaborations referred to students’ prior knowledge, 16% of elaborations focused on a single text, while 18% of elaborations were focused on a previously read text. As such, only a minority of the elaborative utterances that students produced referred to multiple texts. Moreover, few identified causal, comparative relations of any kind, making the intersection of these, or the number of utterances identifying relations across multiple texts, all the more limited.
Wolfe and Goldman (2005) further found that the nature of the connections that students formed differed by referent. In particular, when elaborations referred to a single text, 75% of the connections formed were causal in nature, while 15% were comparative. As a contrast, when elaborations were developed across texts, 46% were causal, while 40% were comparative. In part, this reflects an increase in comparative relations formed when students reason about multiple texts. This differential pattern in think-aloud utterances points to the need to examine not only the function of students’ strategic engagement (i.e., formation of causal or comparative connections) but also its referent (e.g., a single text or multiple texts).
Anmarkrud, Brâten, and Stroms© (2014) adopted a similar approach to coding undergraduate students’ think-aloud utterances reported during multiple text use. Specifically, in addition to coding for the strategy clusters specified by Afflerbach and Cho (2008), they coded for linking strategies, capturing students’ consideration of more than one text at a time, rather than a single text. All told, Anmarkrud et al. (2014) found 31.29% of students’ strategic processing involved cross-textual linking. When considering more than one text at a time, they found 47.1% of strategies to be aimed at learning important information, 16.7% of strategies to be aimed at monitoring, and 36.3% of strategies to be focused on evaluation (i.e., critical analytic processing). In this case, the majority of strategies executed across multiple texts focused on connecting ideas across texts to improve comprehension. In examining the nature of cross-textual linking, they further found the majority of such linking to be backward, rather than forward, directed, drawing connections to previously read texts. Moreover, they found linking to identify conflicts between texts, rather than points of concurrence or corroboration. Both different types of strategies (i.e., identifying and learning important information strategies vis-à-vis evaluation strategies) and linking strategies, in particular, were found to have distinct associations with multiple text task performance. In keeping with the differential strategy use, both in function and in referent, documented by Wolfe and Goldman (2005) and Anmarkrud et al., 2014), Table 8.1 includes descriptions of the constructive-integrative strategies that may be engaged in reference to a single text, to multiple texts, or to learners’ prior knowledge and beliefs.
Integrative Processing Across Multiple Texts. As strategies that may be used to construct meaning from a single text have been much more extensively examined in prior work (Afflerbach & Cho, 2008; McNamara, 2004; McNamara & Magliano, 2009), here I provide a more detailed discussion of how students may make meaning across multiple texts or engage in cross-textual integration. Cho et al. (2018) and List and Alexander (2018b) recognized that multiple text integration involves the connecting and cognitive representation of texts that are both consistent with and in conflict with one another. For texts that are consistent, providing corroborative (e.g., redundant) or complementary information, the cross-textual strategies engaged may be described as synthesis. These are strategies focused on additively connecting texts and organizing such connections. To make sense of texts that are conflicting, reconciliation-focused strategies are required. Reconciliation is the umbrella term applied to the processes involved in the representation of discordant texts as in conflict with one another, and associated efforts to understand and possibly resolve such conflicts. The joining and organization of the mental representations that arise through synthesis and reconciliation results in integration, or students’ holistic conceptualization of multiple texts (Britt et al., 1999; Goldman, Lawless, & Manning, 2013; Perfetti et al., 1999).
List and colleagues (List, 2019; List & Alexander, 2018b) specified four steps involved in both students’ synthesis and reconciliation of multiple texts. Specifically, students connect multiple complementary and conflicting texts through: (a) identification,
(b) separate representation, (c) simultaneous relation, and (d) relational elaboration. Identification involves students’ initial search for possible corroborative or related information across texts or attendance to potential conflict. Separate representation involves students’ separate mapping or elaboration of related information within each text. Simultaneous relation involves students conceptually linking information from separate texts via a single statement, typically using a relational modifier (i.e., a linking term such as and, but, or therefore). Finally, relational elaboration involves students classifying the type of cross-textual connections formed, and elaborating these to various extents. This may include students generally specifying that texts agree or conflict with one another or determining a more specific point of comparison across texts (e.g., texts disagree with one another in their estimate of projected causalities as a result of overpopulation).
When texts are classified as being in conflict with one another, Stadtler and Bromme (2014) outlined at least three strategies that students may use to not only represent conflicting information but also to resolve conflicts as well. These included (a) ignoring the conflict, by dismissing one of the texts that conflicts, (b) inferring an (often incorrect) resolution to the conflict based on prior knowledge or other information in texts, or (c) deliberately choosing a side of a conflict to defer to by evaluating and comparing either author (i.e., whom to believe?) or information (i.e., what to believe?) quality. Of course, when students are presented with conflicting information from similarly expert or trustworthy sources, they are left unable to easily determine whom to believe. In such instances, other strategies, including relying on their prior attitudes, making plausibility judgments based on world knowledge, or searching for additional information, may be required (Hepfer, List, & Du, 2019; Lombardi, Seyranian, & Sinatra, 2014). Nevertheless, the comparison and evaluation of discrepant sources remains a key mechanism that students can use to resolve conflicts when these are identified across texts (Braasch et al., 2012). The processes used to evaluate texts’ sources (e.g., author) and content were termed critical analytic strategies by Cho et al. (2018).
Critical-Analytic Strategies. Cho et al. (2018) described critical analytic strategies as focused on the evaluation of information and its source(s). The leading evaluation strategy examined within the context of multiple text use has been sourcing. As Stadtler and Bromme (2014) explained, sourcing is key because when trying to understand a complex and unfamiliar topic by reading multiple texts, students often do not have the requisite knowledge, resources, and skills necessary to directly evaluate the knowledge claims introduced (i.e., to decide what is true). Rather, students are left to make second-order sourcing judgments or assumptions about information quality based on source characteristics, including author benevolence (i.e., intention to provide accurate and quality information) and expertise (i.e., authoritativeness). Making such judgments is, nevertheless, a complex process. Brante and Stroms© (2018), in a review of sourcing interventions, found sourcing to include students’ (a) attendance to and identification of document information, including author, publisher, date of publication, (b) recall of document information (i.e., its storage in memory or in an external representation, like students’ notes), (c) use of document information to predict and interpret content in texts, and (d) evaluation of source credibility.
Beyond sourcing, the other strategies identified by Wineburg (1991) may also serve evaluative functions, albeit less frequently considered in prior work. Rouet et al. (1997) examined the sourcing, corroboration, and contextualization of graduate students classified as either experts or novices in the domain of history. Sourcing included specific references to study documents reflected in students’ essays, but was not found to differ across expert and novice graduate students in the domain of history. Corroboration, or comparing information across texts, was classified in one of four ways. Specifically, students developed (a) argument models (i.e., recognizing different texts as forwarding conflicting interpretations), (b) positive connections (i.e., grouping similar texts), (c) negative connections (i.e., identifying conflicting texts), and (d) general references (i.e., identifying a group of consistent sources) across texts. Corroboration was limited, with less than one corroborative instance occurring in students’ essays, but uniformly so across expert and novice graduate students. Finally, students’ engagement in contextualization was classified according to the type of knowledge implicated. Specifically, students made (a) problem context statements, drawing on topic-specific prior knowledge; (b) historical context statements, using prior knowledge at the domain level; and (c) general context statements, reflecting the contribution of general, world knowledge to multiple text evaluation. It was in the engagement in contextualization that expert-novice differences emerged, with expert students including more contextual information overall and more historical contextual statements in their essays, in particular. Elsewhere, the use of sourcing, corroboration, and contextualization by high school history students has been found to be quite limited, with the engagement of the latter two strategies found to be especially rare (Nokes et al., 2007; Stahl, Hynd, Britton, McNish, & Bosquet, 1996).
Nevertheless, all three of these critical-analytic strategies are presented in the second row of Table 8.1. As demonstrated in Table 8.1, critical-analytic strategies may be intra-textually, inter-textually, or personally directed. For instance, students engaging in sourcing may consider the document information in one text (i.e., an intra-textually directed strategy) or can compare author credentials across texts (i.e., an inter-textually directed strategy). Likewise, students may apply prior knowledge to contextualize a particular text (i.e., a personally directed strategy) or may use information in one text to contextualize or situate another (i.e., an inter-textually directed strategy). An exception to this may be the corroborative strategy for text evaluation, which necessarily requires the simultaneous consideration of more than one text and is therefore a strategy that is inter-textual in nature. At the same time, even this strategy may be engaged to compare information in a text with students’ prior knowledge, thereby evaluating its content. The intra-textual, inter-textual, and personal-directedness of various critical-analytic strategies is reflected in Table 8.1.
Metacognitive-Reflective Strategies. The final strategy cluster defined by Cho et al. (2018) is termed metacognitive-reflective and includes students’ regulation of their own sense-making of multiple texts and monitoring, or self-assessments of comprehension. Although Cho et al. (2018) identified metacognitive-reflective strategy use as necessary for the deployment of the constructive-integrative and critical-analytic strategies necessary for learning from multiple texts, this strategy cluster has, nevertheless, received the least attention in the literature on learning from multiple texts. Wolfe and Goldman (2005) found evidence of metacognitive monitoring among students’ think-aloud utterances. These were coded as either reports of comprehension success or comprehension problems; however, each of these accounted for only 3% of all reported think-aloud utterances. Likewise, Anmarkrud, Braten, and Stromso (2014) found strategies belonging to the metacognitive-reflective cluster to be the least commonly reported (16.56%), as compared to constructive-integrative (34.36%) and critical-analytic strategies (49.08%). As demonstrated in Table 8.1, these strategies can nevertheless be executed in reference to a single text (e.g., detecting a comprehension problem with a particular text), to multiple texts (e.g., trying to solve a detected comprehension problem ...by searching for clarifying information in other available texts, Anmarkrud et al., 2014, p. 70), or to students’ prior knowledge (e.g., if students are conscious of knowledge revision or belief change; Richter & Maier, 2017).
Other work has sought to explicitly elicit metacognition and comprehension monitoring, in particular, during the course of students’ learning from multiple texts. For instance, Stadtler and Bromme (2007, 2008) developed met. a. ware as a platform to prompt students’ metacognitive monitoring and source evaluation. To spur monitoring, students were asked to rate: how well do you comprehend the information, how much do you know about the topic right now, and how much information do you still need on the topic, after accessing each text. At post-test, students assigned to the monitoring condition were found to have higher factual knowledge as compared to a control group.
Maier and Richter (2014) examined an expanded set of three metacognitive monitoring strategies that students could use when learning from multiple texts. The first involved students monitoring the biasing influence of their prior beliefs on their processing of multiple texts. The second involved students identifying inconsistencies across texts, violating standards for internal coherence among information sources (i.e., internal consistency standard). Finally, the third standard involved students evaluating information in texts relative to their prior knowledge (i.e., external consistency standard). Although not specifically examining the differential effects of these various metacognitive monitoring strategies, instruction on these various strategies and the provision of feedback were found to result in improved situation model construction, corresponding to a more accurate cognitive representation of information presented across texts, and improved text recall. Noteworthy for the development of the CSF is that Maier and Richter (2014) specify monitoring strategies that use both multiple texts and learners’ prior knowledge and beliefs as strategy referents. Indeed, as was the case with evaluative strategy use, metacognitive monitoring and regulatory strategies may be deployed in reference to a single text, to multiple texts, or to learners’ prior knowledge and beliefs.