Investigating the Cognitive Affective Engagement Model of Learning From Multiple Texts: A Structural Equation Modeling Approach

Abstract

Given limited work modeling the role of individual difference factors and processing variables in students’ learning from multiple texts, the author evaluates such a model. In particular, the model analyzed examines the relation between cognitive (i.e., habits with regard to information evaluation) and affective (i.e., interest) individual difference factors and multiple‐text outcomes (i.e., integrated mental model development and intertext model development, as facets of multiple‐text integration), as mediated by students’ processing of multiple texts (i.e., time on texts, engagement in cross‐textual elaboration). Interest and time devoted to text access were found to have a direct effect on integrated mental model formation, whereas time and students’ engagement in cross‐textual elaboration had a direct effect on intertext model development. Additionally, time on texts mediated the relation between both individual difference factors and the integration‐related outcomes examined. Implications for theory development and research on learning from multiple texts are discussed.

Predictors and outcomes of behavioral engagement in the context of text comprehension: when quantity means quality

“…For example, Bråten et al (2014) found that both prior topic knowledge and interest in the topic were positively related to students' time use, with time use also mediating the effect of interest on their comprehension performance. Likewise, List (2020) found that behavioral engagement as indicated by time on task was affected by topic interest and thus mediated the effects of topic interest on comprehension performance, and List et al (2019) found that the time students devoted to text use mediated the effects of situational (i.e., text-based) interest on the written comprehension products. Moreover, List (2020) found that a cognitive factor based on students' scores on a general, decontextualized measure of perceived strategy use predicted the time devoted to text use and, in turn, their comprehension performance.…”

“…Likewise, List (2020) found that behavioral engagement as indicated by time on task was affected by topic interest and thus mediated the effects of topic interest on comprehension performance, and List et al (2019) found that the time students devoted to text use mediated the effects of situational (i.e., text-based) interest on the written comprehension products. Moreover, List (2020) found that a cognitive factor based on students' scores on a general, decontextualized measure of perceived strategy use predicted the time devoted to text use and, in turn, their comprehension performance. Both prior knowledge and topic interest were also positively related to indicators of behavioral engagement (e.g., number of unique websites visited and revisited) in the Kammerer et al (2021) study.…”

“…Both these studies used a multidimensional measure of student engagement based on teacher ratings. Other work has linked both prior topic knowledge and interest, which is a construct closely related to intrinsic motivation (Schiefele et al, 2012), to comprehension performance via behavioral engagement, in particular (e.g., Bråten et al, 2014;Kammerer et al, 2021;List, 2020;List et al, 2019). For example, Bråten et al (2014) found that both prior topic knowledge and interest in the topic were positively related to students' time use, with time use also mediating the effect of interest on their comprehension performance.…”

“…Regarding direct effects of behavioral engagement on comprehension performance, several researchers have found that the time students invest in reading and comprehension tasks uniquely predicts their comprehension performance (Bråten et al, 2014(Bråten et al, , 2018Du & List, 2020;List, 2020;List et al, 2019). For example, Bråten et al (2014), in a path analytic study with upper-secondary students, found that reading time predicted comprehension performance even when several individual differences (e.g., prior topic knowledge) and the use of deeper level comprehension strategies were controlled for.…”

“…These findings were corroborated by List et al (2019), who also used hierarchical multiple regression analysis to demonstrate that behavioral engagement in terms of the time undergraduate students devoted to text use uniquely predicted the quality of their post-reading written products. Moreover, List (2020), who performed structural equation modeling with undergraduate students, found that time on texts directly affected memory for textual information and integrated understanding when cognitive and motivational differences as well as deeper level strategy use were controlled for. Finally, Du and List (2020) found that both total reading time and total writing time were positively correlated with undergraduate students' comprehension performance as reflected in their post-reading written products.…”