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Systematic Effects of Levels of Processing on Performance

Given the issues regarding conceptualization and operationalization mentioned previously, deriving clear links between levels of processing and performance is difficult. However, across these reviews different conclusions were reached. ‘Hattie and Donoghue’s (2016) meta-analysis and ‘Vermunt and Donche’s (2017) review offered perhaps the most targeted interpretation of this relation. Hattie and Donoghue suggest a subset of strategies that are more effective depending on the phase of learning that individuals are in (i.e., acquiring, consolidating, and transferring). Given the data in ‘Vermunt and Donche’s (2017) review, they made an argument that the ILS could be an effective tool to predict processing over a course or semester, which would in turn predict future performance. However, with the issues of retrospective self-report discussed previously in the chapter, there is some doubt whether these claims are justified. If patterns of processing and strategy use are indeed rather stable over time, this could be the case. On the other hand, if processing and strategy use are more attuned to the conditions of the task and change rapidly, this argument may not hold for those particular instances.

Most of the reviews, however, were rather tenuous in speaking about the relation between levels of processing and performance. These reviews often attempted to qualify the relations between levels of processing and performance further than *Hattie and Donoghue (2016). For instance, ^Dinsmore (2017) reported that the relations between levels of processing and performance were higher when quality and conditional use of the strategies were measured rather than simply the quantity of that strategy use. *Asikainen and Gijbels (2017) took a dimmer view of the efficacy of self-report instruments used in the SAL framework to predict performance, noting there was little relation between the learning patterns identified using the SAL perspective and learning performance.

In addition to these views, there is also a third perspective of individuals who do not necessarily believe that a direct link to performance is necessary, which comes predominately from the SRL framework (e.g., Pintrich, 1999). The idea that self-regulatory strategy use is a goal in its own right has been a point of major discussion lately, for example at the European Association for Research on Learning and Instruction (EARLI; Molenaar, 2017). Some of these researchers contend that improved self-regulation, even without being linked to performance, should be emphasized. This position subsumes within it the idea that all strategies are self-regulatory - one that needs further investigation. As Alexander pointed out in her expositions of the MDL (e.g., Alexander, 1997; 2004), strategies become increasingly metacognitive as one progresses toward higher levels of expertise. Especially in the stage of acclimation (the first stage on the path toward expertise) there is no expectation that the strategies employed are entirely self-regulatory. While we agree that enacting these cognitive strategies (whether surface or deep level) will probably be more successful when enacted alongside self-regulatory strategies, one can certainly employ a reading strategy without being self-regulatory. The degree to which this enaction with, without, or with limited self-regulation is more or less successful for different learners at different stages of expertise needs to be better fleshed out.

Discussion. With regard to the last point - that the link between levels of processing (and strategies more generally) and performance are not of tantamount importance -we disagree. Although we do agree that the ability to engage in self-regulatory strategies is important, this importance is limited if it does not lead to better performance or learning gains. For example, in studies of reading comprehension, there are readers who are termed effortful (Alexander, 2005; Dinsmore, Parkinson, Fox & Bilgili, 2019) who employ many strategies and do quite well in terms of performance outcomes. However, they are very inefficient - their reading times a quite a bit higher than readers in other categories, even those that were deemed to be highly competent readers. Thus, the relation between regulatory competence - which the highly competent readers possess - and reading outcomes is not so straightforward.

Fortunately, evidence supports that strategies - self-regulatory included - should improve performance for a wide range of tasks. Indeed, the MDL in particular proposes that metacognitive and self-regulatory strategies - along with a mix of surface-level and deep-level strategies - are necessary for performance in a domain except for someone who has advanced beyond the novice stage (i.e., in competence or expertise in the MDL). However, we also acknowledge that for some tasks, such as those that are routine or quite straightforward, the degree to which self-regulatory strategies are utilized or required are of much lower import.

Additionally, as a result of these reviews, empirical work that we have conducted, and our practical experience in classrooms with children, adolescents, and adults, we are skeptical of the more targeted view of ‘Hattie and Donoghue (2016) and *Vermunt and Donche (2017). In the previously mentioned reviews, contextual and individual factors play a key role. We certainly agree with Hattie and Donoghue that some strategies are better than others, but we would posit that the degree to which these strategies are better or worse is far more conditional than they state in their meta-analysis. We dissect this issue now as we turn to the contextual and individual factors that might mediate or moderate the relation between levels of strategy use and performance.

Influences of Contextual and Individuals Factors that Mediate or Moderate the Relation between Levels of Processing and Performance

The last of our three guiding questions examines how each of the reviews in the pool did or did not examine individual and contextual factors during strategy use.

Individual Factors. Eleven of the reviews in the pool specifically discussed individual factors that might influence the relation between level of processing and performance. The largest category of individual differences discussed across these reviews was motivation. Six of these reviews discussed some facet or multiple facets of motivation. For example, ‘Vermunt & Donche (2017) discussed goal orientations, attributions, effort, and self-efficacy, while Pintrich (1999) discussed self-efficacy, task value, and goal orientation. In general, across both of these reviews, autonomous motivation and positive conceptions of learning (e.g., higher self-efficacy) are more likely to lead to deeper-level strategies employed.

The next largest category was the discussion of prior knowledge or prior performance. Four reviews specifically addressed the importance of prior knowledge on the use of strategies: ‘Alexander and Judy (1988), ‘Alexander et al. (1998), ‘Dinsmore et al. (2018), and Paris et al. (1983). ‘Asikainen and Gijbels (2017), ‘Paris (1988), and ‘Vermunt and Donche (2017) discussed the role of prior performance - or patterns of performance in the case of Asikainen and Gijbels - in the use of strategies and how that influenced performance. As indicated previously, all these reviews support the notion that higher levels of prior knowledge lead to better deep-level processing.

The next set of factors that were mentioned in a few reviews were of epistemic beliefs and emotions. Two studies, ‘Alexander Grossnickle, Dumas, and Hattan (2018) and ‘Vermunt and Donche (2017), both discussed how more sophisticated epistemic beliefs might lead to advantageous differences in strategic processing - particularly the use of deeper-level strategies. ‘Hattie and Donoghue (2016) focused on a related construct, understanding criteria for success in their review. Finally, ‘Alexander et al. (2018) discussed learner emotions, while ‘Vermunt and Donche (2017) also addressed personality, age, and gender in his discussion. For Alexander et al. regulation of learner emotions was considered to be beneficial for strategy use, while for Vermunt and Donche they found that the personality factors of openness and conscientiousness were related to patterns of learning they describe as deep or analytic.

Contextual Factors. The scope of the reviews with regard to contextual factors was also wide ranging. Some of the reviews focused on specific domains such as reading (‘Aftlerbach et al., 2008; Paris et al., 1983), mathematics (‘Ashcraft, 1990), and business (‘Najmaei & Sadeghinejad, 2016). Other reviews, however, focused on how domain-general versus domain-specific investigations of strategic processing influenced performance (‘Dinsmore, 2017; ‘Dinsmore & Alexander, 2012; ‘Dinsmore et al., 2018; ‘Vermunt & Donche, 2017). Overall, there seems to be consensus among these reviews that while there are some strategies that can be considered domain general, there is certainly quite a bit of evidence to suggest that being conscious of domain when examining strategic processing is important (e.g., Deekens et al., 2018).

Other reviews focused more on the setting in which these investigations of levels of processing took place. For example, ‘Asikainen and Gijbels (2017) focused solely on students enrolled in higher education, while ‘Alexander et al. (2018) addressed strategies that students might employ in online versus face-to-face courses. ‘Alexander et al. (1998) and ‘Vermunt and Donche (2017) addressed the role of conducive learning environments regarding levels of processing, which is a major area of research in its own right (cf. Gijbels & Loyens, 2008).

Discussion. For us, the discussion in these reviews of the individual and contextual factors that influence the levels of strategic processing and its relation to performance provide additional evidence that a less sophisticated model that posits more deep processing will lead to better performance should indeed be a historical notion. The degree to which there are interrelated constructs such as motivation and epistemic beliefs underscore the interconnected relations between levels of strategic processing and performance. Although many of the individual difference factors have been extensively systematically reviewed, the degree to which contextual factors have been reviewed in this regard is much less extensive.

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