The construct of working memory (WM), as described by Baddeley and Hitch (1974), has had a far-reaching impact on theories of cognition. For years, Baddeley's model was the predominant theory of WM, and it remained relatively unchanged, with its two storage components for visuospatial and phonological information and a central executive component for coordinating storage and various processing functions. 1 A defining feature of all three of these subcomponents has been their attention-driven nature. In fact, at one point, Baddeley (1993) reflected that it may have been more appropriate to use the term working attention, rather than working memory. The term attention is used by Baddeley, as well as by many other authors within the WM literature, to refer broadly to effortful processes that range from rehearsal procedures to executive functions, such as planning, organizing, and controlling cognitive actions. In this article, we rely on the broad distinction between deliberate, attention-driven processes of WM that operate within the awareness of the individual and processes that operate outside of conscious awareness, such as implicit memory processes that underlie various forms of priming.Various theorists have noted that relatively smallcapacity, attention-driven storage components of WM fail to explain complex cognitive activities such as language comprehension, in which a great deal of information needs to be temporarily available for processing (e.g., Anderson, 1983;Cowan, 1999;Ericsson & Kintsch, 1995;Just & Carpenter, 1992;Kintsch, Patel, & Ericsson, 1999). Corresponding to this criticism, alternative conceptualizations of WM have been proposed that allow for more information to be available for processing at any given moment. Most define this greater availability in terms of long-term memory (LTM) activation, or the temporary increase in retrieval strength of existing memory representations. These models differ in important respects, but of interest here is their common inclusion of long-term memory structures that are temporarily available for processing but that are not in the current focus of attention. Most of these alternative models postulate that both attentiondriven WM processes and automatic LTM activation or retrieval processes effectively define capacity limits that constrain complex processing activities. Furthermore, some suggest that the LTM activation processes are capacity limited in a different manner than the attention-driven processes. However, direct empirical evidence regarding these issues is limited. LTM Processes in WM ModelsA variety of WM models that represent alternatives to Baddeley's model have been proposed within different theoretical contexts (see Miyake & Shah, 1999). We will describe only a few of these that are most prominent in their inclusion of active-but-unattended LTM elements in WM. Virtually all WM theorists acknowledge the contribution of LTM knowledge structures to WM performance, but some have proposed models in which LTM processes are central to the definition...

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In 2 experiments, the authors investigated available but unattended information following working memory task demands. The experimental task presented a memory set containing exemplars from 2 conceptual categories. Following instructions to focus attention on only 1 category, priming of both categories was assessed with category comparisons of exemplar pairs. Priming was greatest for the focused category and for exemplars from the memory set (direct priming). Priming also extended to new exemplars of both categories (indirect priming) and showed little decline over more than 1 min of intervening processes. Finally, changing between category exemplars and features across memory set and comparison phases eliminated the indirect priming. These results support a persistent, operation-specific, procedural account of available but unattended conceptual information in working memory.

The purpose of this study was to illustrate the relationship between self-efficacy, task value, goal orientations, metacognitive self-regulation, self-regulation and learning strategies and to investigate the unique contribution of each on the variability in students' total scores of 12 exams. Our study revealed that students' self-efficacy, task-value, self-regulation, and elaboration are significantly positively correlated with total scores. Path analysis demonstrated that self-efficacy was the strongest predictor of total score and positively predicted mastery goals, but negatively predicted avoidant goals. The study reveals positive direct effect of mastery goals on metacognitive self-regulation. In addition, positive direct effects of metacognitive self-regulation on deep learning strategies and on self-regulatory strategies are found. However, some expected direct effects were not represented with significant parameters in the model. Performance-approach goals were not a significant predictor of other variables in the model. Also, there were no significant direct effects of mastery goals nor metacognitive self-regulation and deep learning strategies on total scores which were discussed here.