We agree with Murayama and Jach's (M&J) claims that unpacking the mental black box underlying motivated behavior and paying greater attention to the emerging properties of key latent constructs is critical precisely “because … it would provide a new landscape of understanding these concepts.” We think we have spent considerable time over the last 50 years on these goals. Contrary to M&J's claim that “Expectancy-value theory does not specify how value is incorporated and represented into the existing knowledge structure,” our model of subjective task value and ability self-concepts/expectations for success is based on: (1) Social cognitive theories including attribution theory of achievement behavior and its links to mentally stored emotional responses and causal inferences regarding the nature of the self and reality; self-schema and identity-development theories; and the cognitive integration over time of one's experiences in the creation of concepts and cognitive algorithms; as well as cognitive developmental theories potentially underlying age-related changes in the kinds of cognitive algorithms one might use to make “wise” behavioral choices; and (2) several of the major classic reward theories including classical, operant, and observational learning, and mental rewards for successful enactment of new behaviors. We have articulated a wide array of mental processes linked to the formation and storage of value-related information that are linked to both reward systems and the self-systems in the medial prefrontal and posterior parietal cortex. Like M&J, we agree that seeking information is likely to be rewarded by the brain; we also believe that using cognitive algorithms to make short- and long-term behavioral choices is rewarding.
It is important to note that Eccles trained under Weiner – an achievement motivational theorist who explicitly replaced needs-based theories of motivation in favor of more mentally informed information processing and achievement-related problem solving. Building on his socio-emotional cognitive perspective on motivation, we focus specifically on those mental calculations related to the formation of relative expectancy and subjective task value beliefs and then the use of this information in making behavioral decisions. To the extent that such decisions have a direct influence on survival and reproduction, it is likely that the mental processes associated with such choices have developed and are inherently rewarding. The existence of specific brain regions linked to self-related mental processes supports this hypothesis.
Furthermore, although we do not fully understand these mental processes, we have specifically proposed some, such as those listed above, and have discussed the importance of uncovering others such as the varying algorithms used by people of different histories and ages in aggregating various pieces of information relative to subjective task value across different situations (i.e., Eccles & Wigfield, Reference Eccles and Wigfield2020). Right now, we are interested in individual differences in the mental computational mechanisms underlying the various subjective task values people place on the array of options available in making high-level behavioral plans related to long-term motivated behavioral choices, for example, occupational, and recreational choices. We also have discussed how different kinds of comparison processes, for example, temporal, social comparative, or dimensional across different activity domains, influence the development of both expectancies and subjective task values (Wigfield, Eccles, & Möller, Reference Wigfield, Eccles and Möller2020).
Moving beyond our own theory we turn to some broader comments regarding M&J's article. We were somewhat surprised by their choice of need for competence as the exemplar construct on which to focus. There are constellations of “higher-level” constructs having to do with competence and competence perception, for example, expectancies, self-efficacy, self-concept of ability, and perceived control. Obviously, need for competence is related, but Ryan and Deci's (Reference Ryan and Deci2017) notion that there is a need to be competent is different than having beliefs about one's competences and engaging in behaviors to improve competence. Needs imply something more basic and fundamental, whereas beliefs are formed through experience, and therefore more likely to be determined by the mental computational processes proposed by M&J.
We also think it is important to expand on M&J's focus on “reward-learning models of information seeking behavior.” What other reward systems might be operative in motivated behavior? We mentioned several earlier. Additionally, we think it is important to consider the processes linked to seeking specific kinds of information. It seems likely that the mental processes involved in forming expectancies for success are different than those involved in forming one's subjective task values. Both the kinds of information used and the associated affective experiences pertaining to each of these constructs are likely to differ. It is also likely that the kinds of information used to make specific behavioral decisions vary across different contextual settings and developmental ages. Thus, we need to explore the nature of such processes behind different “higher-order” motivation constructs in different contextual settings and time frames.
Finally, it will be important to understand the development of the relevant mental computation processes. Cognitive maturation is undoubtedly involved in the developmental changes we see across the life span in the responses people make to information related in making “wise” motivated-behavioral choices. For example, young children (up to about 8) continue to have very high success expectations despite repeated failure in lab studies (e.g., Parsons & Ruble, Reference Parsons and Ruble1977); after 8 children show a very linear decline in expectations for success following such failure information. Similarly, children's theory of mind changes over childhood. Finally, according to Baltes’ (Reference Baltes1997) SOC model, people of different ages should weight opportunities to “select, optimize, and compensate” differently as they manage their motivated behaviors differently due to age-related changes in their cognitive and physical resources. Research is needed to understand age differences in such motivated behavioral choices.
We thank M&J for helping us to think harder about unpacking the black box.
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We agree with Murayama and Jach's (M&J) claims that unpacking the mental black box underlying motivated behavior and paying greater attention to the emerging properties of key latent constructs is critical precisely “because … it would provide a new landscape of understanding these concepts.” We think we have spent considerable time over the last 50 years on these goals. Contrary to M&J's claim that “Expectancy-value theory does not specify how value is incorporated and represented into the existing knowledge structure,” our model of subjective task value and ability self-concepts/expectations for success is based on: (1) Social cognitive theories including attribution theory of achievement behavior and its links to mentally stored emotional responses and causal inferences regarding the nature of the self and reality; self-schema and identity-development theories; and the cognitive integration over time of one's experiences in the creation of concepts and cognitive algorithms; as well as cognitive developmental theories potentially underlying age-related changes in the kinds of cognitive algorithms one might use to make “wise” behavioral choices; and (2) several of the major classic reward theories including classical, operant, and observational learning, and mental rewards for successful enactment of new behaviors. We have articulated a wide array of mental processes linked to the formation and storage of value-related information that are linked to both reward systems and the self-systems in the medial prefrontal and posterior parietal cortex. Like M&J, we agree that seeking information is likely to be rewarded by the brain; we also believe that using cognitive algorithms to make short- and long-term behavioral choices is rewarding.
It is important to note that Eccles trained under Weiner – an achievement motivational theorist who explicitly replaced needs-based theories of motivation in favor of more mentally informed information processing and achievement-related problem solving. Building on his socio-emotional cognitive perspective on motivation, we focus specifically on those mental calculations related to the formation of relative expectancy and subjective task value beliefs and then the use of this information in making behavioral decisions. To the extent that such decisions have a direct influence on survival and reproduction, it is likely that the mental processes associated with such choices have developed and are inherently rewarding. The existence of specific brain regions linked to self-related mental processes supports this hypothesis.
Furthermore, although we do not fully understand these mental processes, we have specifically proposed some, such as those listed above, and have discussed the importance of uncovering others such as the varying algorithms used by people of different histories and ages in aggregating various pieces of information relative to subjective task value across different situations (i.e., Eccles & Wigfield, Reference Eccles and Wigfield2020). Right now, we are interested in individual differences in the mental computational mechanisms underlying the various subjective task values people place on the array of options available in making high-level behavioral plans related to long-term motivated behavioral choices, for example, occupational, and recreational choices. We also have discussed how different kinds of comparison processes, for example, temporal, social comparative, or dimensional across different activity domains, influence the development of both expectancies and subjective task values (Wigfield, Eccles, & Möller, Reference Wigfield, Eccles and Möller2020).
Moving beyond our own theory we turn to some broader comments regarding M&J's article. We were somewhat surprised by their choice of need for competence as the exemplar construct on which to focus. There are constellations of “higher-level” constructs having to do with competence and competence perception, for example, expectancies, self-efficacy, self-concept of ability, and perceived control. Obviously, need for competence is related, but Ryan and Deci's (Reference Ryan and Deci2017) notion that there is a need to be competent is different than having beliefs about one's competences and engaging in behaviors to improve competence. Needs imply something more basic and fundamental, whereas beliefs are formed through experience, and therefore more likely to be determined by the mental computational processes proposed by M&J.
We also think it is important to expand on M&J's focus on “reward-learning models of information seeking behavior.” What other reward systems might be operative in motivated behavior? We mentioned several earlier. Additionally, we think it is important to consider the processes linked to seeking specific kinds of information. It seems likely that the mental processes involved in forming expectancies for success are different than those involved in forming one's subjective task values. Both the kinds of information used and the associated affective experiences pertaining to each of these constructs are likely to differ. It is also likely that the kinds of information used to make specific behavioral decisions vary across different contextual settings and developmental ages. Thus, we need to explore the nature of such processes behind different “higher-order” motivation constructs in different contextual settings and time frames.
Finally, it will be important to understand the development of the relevant mental computation processes. Cognitive maturation is undoubtedly involved in the developmental changes we see across the life span in the responses people make to information related in making “wise” motivated-behavioral choices. For example, young children (up to about 8) continue to have very high success expectations despite repeated failure in lab studies (e.g., Parsons & Ruble, Reference Parsons and Ruble1977); after 8 children show a very linear decline in expectations for success following such failure information. Similarly, children's theory of mind changes over childhood. Finally, according to Baltes’ (Reference Baltes1997) SOC model, people of different ages should weight opportunities to “select, optimize, and compensate” differently as they manage their motivated behaviors differently due to age-related changes in their cognitive and physical resources. Research is needed to understand age differences in such motivated behavioral choices.
We thank M&J for helping us to think harder about unpacking the black box.
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Competing interests
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