Mapping and Drawing to Improve Students’ and Teachers’ Monitoring and Regulation of Students’ Learning from Text: Current Findings and Future Directions

van de Pol, Janneke; van Loon, Mariëtte; van Gog, Tamara; Braumann, Sophia; de Bruin, Anique (2020). Mapping and Drawing to Improve Students’ and Teachers’ Monitoring and Regulation of Students’ Learning from Text: Current Findings and Future Directions. Educational psychology review, 32(4), pp. 951-977. Springer 10.1007/s10648-020-09560-y

Preview

Text Van_de_Pol_et_al_2020.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (707kB) | Preview

For (facilitating) effective learning from texts, students and teachers need to accurately monitor students’ comprehension. Monitoring judgments are accurate when they correspond to students’ actual comprehension. Accurate monitoring enables accurate (self-)regulation of the learning process, i.e., making study decisions that are in line with monitoring judgments and/or students’ comprehension. Yet, (self-)monitoring accuracy is often poor as the information or cues used are not always diagnostic (i.e., predictive) for students’ actual comprehension. Having students engage in generative activities making diagnostic cues available improves monitoring and regulation accuracy. In this review, we focus on generative activities in which text is transformed into visual representations using mapping and drawing (i.e., making diagrams, concept maps, or drawings). This has been shown to improve monitoring and regulation accuracy and is suited for studying cue diagnosticity and cue utilization. First, we review and synthesize findings of studies regarding (1) students’ monitoring accuracy, regulation accuracy, learning, cue diagnosticity, and cue utilization; (2) teachers’ monitoring and regulation accuracy and cue utilization; and (3) how mapping and drawing affect using effort as a cue during monitoring and regulation, and how this affects monitoring and regulation accuracy. Then, we show how this research offers unique opportunities for future research on advancing measurements of cue diagnosticity and cue utilization and on how effort is used as a cue during monitoring and regulation. Improving measures of cue diagnosticity and cue utilization can provide us with more insight into how students and teachers monitor and regulate students’ learning, to help design effective interventions to foster these important skills.

Learning from texts is essential for most school subjects, further education, and working life (Biancarosa & Snow, 2004). To learn effectively from texts, students and teachers need to be able to accurately monitor and regulate students’ text learning (Dent & Koenka, 2016; Südkamp, Kaiser, & Möller, 2012). Accurate monitoring is important because it directly influences the learning actions students take to self-regulate their learning, such as selecting materials for restudy, allocating study time, seeking help, withdrawing erroneous responses, etc. (Dunlosky & Ariel, 2011; Ghetti, Hembacher, & Coughlin, 2013; Steiner, van Loon, Bayard, and Roebers, 2020). Students and teachers monitor students’ text learning well when their judgments about students’ text comprehension are accurate; that is, when their judgments are in line with students’ actual comprehension as evidenced by test performance (e.g., Griffin, Mielicki, & Wiley, 2019). When regulation decisions such as deciding which text(s) need to be restudied before taking a test are in line with one’s (accurate) monitoring judgments and/or text comprehension, regulation is considered accurate (i.e., fitting the students’ needs; e.g., Van Loon, De Bruin, Van Gog, Van Merriënboer, & Dunlosky, 2014). In turn, accurate regulation results in better learning outcomes (i.e., better comprehension test performance; Thiede, Anderson, & Therriault, 2003; Thiede, Oswalt, Brendefur, Carney, and Osguthorpe, 2019a; see also Dunlosky & Rawson, 2012). However, students and teachers have difficulties with accurately monitoring students’ comprehension, which makes subsequent regulation suboptimal (Thiede et al., 2003; Van de Pol, De Bruin, Van Loon, & Van Gog, 2019).

According to the cue utilization framework (Koriat, 1997), monitoring accuracyFootnote 1 depends on the information or cues people use when making judgments (see also Fig. 1). Cues are defined as “bits of information that might potentially be drawn upon or referred to […] to inform a judgment” (Snow, as cited in Cooksey, Freebody, & Wyatt-Smith, 2007, p. 431). As stated in the cue utilization framework, those cues that are most diagnostic of students’ text comprehension should be used (and non-diagnostic cues should be ignored) to arrive at accurate judgments (Koriat, 1997). A cue is diagnostic when it is related to the judged outcome; in this case, students’ text comprehension. Yet, students and teachers tend to use cues with low diagnosticity levels (e.g., Van de Pol et al., 2019; Thiede, Griffin, Wiley, & Anderson, 2010). For example, students often use surface cues (e.g., text length) or experiential cues originating from one’s subjective experience in performing tasks (e.g., the effort needed to read a text). However, text length or whether a text is read effortlessly does not necessarily predict one’s text comprehension and is thus not necessarily diagnostic (Thiede et al., 2010). Thus, using this information does not necessarily help students to arrive at accurate monitoring judgments.
An effective way to improve students’ monitoring accuracy is asking students to complete the so-called generative activities such as completing diagrams or concept maps about causal relations in texts (e.g., Thiede et al., 2010; Van Loon et al., 2014). To improve teachers’ monitoring accuracy, it appears effective to ask them to inspect the results of those completed activities before making judgments about students’ understanding (e.g., Van de Pol et al., 2019). Having students perform and teachers inspect the results of generative activities focuses their attention on diagnostic cues. When those diagnostic cues are used to make monitoring judgments, these tend to be more accurate than when these cues are not used (e.g., Van de Pol et al., 2019; Thiede et al., 2010). In this review, we synthesize research that has tested this premise in education with complex text comprehension tasks. We focus on generative activities that require students to transfer text into a visual representation of a that text. Mapping and drawing are appropriate for learning materials that contain several key concepts and (causal or spatial) relations between these concepts. Mapping refers to “a collection of techniques in which a learner converts printed or spoken text into a spatial arrangement of words and links among them” (Fiorella & Mayer, 2016, p. 722). We focus on two mapping techniques: concept mapping and diagramming. Concept mapping refers to creating or completing maps that represent relations between key concepts from a text. Diagramming refers to creating or completing diagrams about causal relations in a text. Drawings are pictorial representations of the text content. These generative activities provide unique opportunities for studying cue diagnosticity and cue utilization, given that the products of these generative activities (e.g., diagram, drawing) can be reliably coded with regard to several cues, for example, the number of correct elements that a product contains (e.g., Van Loon et al., 2014). These coded cues can be related to students’ or teachers’ judgments to make inferences about presumed cue utilization, and to students’ test performance to determine cue diagnosticity (cf. Van Loon et al., 2014). Therefore, we focus on mapping and drawing in this review. Effects of a wider array of generative activities on students’ relative monitoring accuracy (excluding cue utilization and cue diagnosticity) can be found in Prinz, Golke, and Wittwer (this special issue).

The first aim of this review is to synthesize research on mapping and drawing that focuses on students’ monitoring, regulation, learning, cue utilization, and/or the diagnosticity of cues. The second aim is to discuss whether having access to students’ maps and drawings improves teachers’ monitoring and regulation accuracy, and cue utilization. The third aim is to explore how the effort involved in mapping and drawing affects students’ monitoring and regulation. The effort with which texts are read seems to be used as a cue by students (e.g., Schleinschok, Eitel, & Scheiter, 2017), whereby students generally give higher judgments when having completed the learning task effortlessly (Koriat & Ma’ayan, 2005). However, whereas effort invested in reading texts tends to be a low-diagnostic cue that should be avoided (Thiede et al., 2010), the effort invested in generative activities after reading texts, could potentially be a diagnostic cue that could improve students’ monitoring accuracy. According to the Effort Monitoring and Regulation (EMR) Framework (De Bruin et al., n.d., this special issue), which synthesizes theory on self-regulation of learning and cognitive load theory, it is important to increase our understanding how effort cues—by itself and in combination with other cues—affect monitoring and regulation of learning. This will help to optimize cue utilization activities and promote monitoring and regulation of text learning. For this third aim, we focus on students, as teachers often do not have insight into students’ effort.

Finally, we describe three major future directions in research on mapping and drawing: improving measurements of (a) cue diagnosticity and (b) cue utilization, and (c) discussing how the use of effort as a cue is potentially affected during mapping and drawing and how this cue can be best measured. Future research on these central topics can help in gaining a better understanding of the monitoring and regulation process and how to improve this. Before we address our aims, we first discuss measures of monitoring and regulation accuracy.

Interest & Impact

Downloads

60 since deposited on 09 Feb 2021
30 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item