In this chapter we examine measures and methods that have come to prominence over the last two decades exploring how they build on, and are shaped by, relevant theory. In addition, we identify how contemporary measures and methods have expanded as researchers investigate interactive influences of person and context. First, the importance of distinguishing levels of generality and specificity in definitions of motivation constructs is explored. Second, we examine attempts to define the type of relation between motivation constructs and learning, for example, mediation relations and reciprocal relations. As specific research is considered we direct attention to the types of analytic procedures that have been used to test hypotheses and assess models of the relations between motivation and learning. In particular we highlight the development of research methods that go beyond the range of insights into motivation and learning that can be achieved using only self-report questionnaires.

While research on neuroscience posits that intrinsic and extrinsic incentives involve a single, common psychological process based on a reinforcement learning model (forming a “commonality view” on motivation), research in psychology has made a strong distinction between these two types of incentives (forming a “multifaceted view” on motivation), often even viewing them as competitive. Although they are not necessarily contradictory, I argue that these two meta-theoretical views have biased and prevented our comprehensive understanding of motivation and its relation to learning. I suggest ways that these different perspectives can inform each other, contributing to our broader understanding of human motivation and learning. These examples include the effects of reward on learning, the way people can transform one type of motivation to another, and a rewarding view for effort, challenge, and negative feedback. The arguments presented in this chapter underscore the vital importance of cross-disciplinary work on motivation and learning in future studies.

Developing interest is a powerful support for deeper learning. The presence of even some interest beneficially affects individuals’ attention and memory, as well as their motivation and meaningful engagement. In this chapter, we expand on previous descriptions of the relation between interest and its development as conceptualized in the Four-Phase Model of Interest Development (Hidi & Renninger, 2006; Renninger & Hidi, 2016). We explain that interest has a physiological basis, and therefore is universal – meaning that all persons, regardless of age or context, can be supported to develop at least some interest in topics to be learned. We describe how and when interest is likely to develop. We review findings which provide evidence that the structure of tasks and activities, as well as interactions with other people, may be helpful to interest development, and also that when these supports are mismatched with the learner's phase of interest, they may constrain or impede interest development. We point to interest as a determinant of learners’ understanding, effort, and feedback preferences, and the coordination of their phase of interest development with their abilities to set and realize goals, feel self-efficacy, and self-regulate. We conclude by identifying some open questions concerning the process of interest development and learning.

In this chapter, we describe psychological and neuroscientific research that demonstrates the unique characteristics of self-related information processing. These characteristics have been shown to produce beneficial effects on basic functions (such as perception, attention, and actions), as well as on higher-order cognitive activities (including memory). The findings are explained by their correspondence to the neurocorrelates of self-related information processing. Northoff's (2016) basic model of the self, which describes self-specificity to be a fundamental aspect of the brain's spontaneous (resting) activity, provides further clarification of these results. After considering the unique characteristics of self-related information processing, we describe the potential benefits of considering findings from neuroscience for educational practice by pointing to the positive outcomes of utility value interventions. More specifically, these types of interventions, which are grounded in the expectancy-value theory of student motivation, are examples of how self-related information processing can have educational benefits by increasing motivation and learning.

Developing interest is a powerful support for deeper learning. The presence of even some interest beneficially affects individuals’ attention and memory, as well as their motivation and meaningful engagement. In this chapter, we expand on previous descriptions of the relation between interest and its development as conceptualized in the Four-Phase Model of Interest Development (Hidi & Renninger, 2006; Renninger & Hidi, 2016). We explain that interest has a physiological basis, and therefore is universal – meaning that all persons, regardless of age or context, can be supported to develop at least some interest in topics to be learned. We describe how and when interest is likely to develop. We review findings which provide evidence that the structure of tasks and activities, as well as interactions with other people, may be helpful to interest development, and also that when these supports are mismatched with the learner's phase of interest, they may constrain or impede interest development. We point to interest as a determinant of learners’ understanding, effort, and feedback preferences, and the coordination of their phase of interest development with their abilities to set and realize goals, feel self-efficacy, and self-regulate. We conclude by identifying some open questions concerning the process of interest development and learning.

A growing body of literature indicates that motivation can critically shape long-term memory formation in the service of adaptive behavior. In the present chapter, we review recent cognitive neuroscience evidence of motivational influences on memory, with a focus on anatomical pathways by which neuromodulatory networks support encoding-related activity in distinct subregions of the medial temporal lobe. We argue that engagement of distinct neural circuits as a function of motivational context at encoding leads to formation of different memory representations, supporting different patterns of adaptive behavior. We present a novel neurocognitive model, the Interrogative/Imperative model of information-seeking, to account for pursuit of learning goals. Interrogative or imperative modes of information-seeking are often, but not necessarily, associated with approach or avoidance motivation, respectively. We also discuss additional influences on motivated memory encoding, including intrinsic motivation, curiosity, choice, and cognitive control processes. Taken together, this body of research suggests that the nature of memory representations depends on an individual's neurophysiological response to, rather than extrinsic qualities of, a given motivational manipulation or context at the time of encoding. Finally, we discuss potential applications of these research findings to real-life educational settings and directions for future research.

Curiosity – the intrinsic desire to acquire new information – is a key factor for learning and memory in everyday life. To date, there has been very little research on curiosity and, therefore, our understanding of how curiosity impacts learning is relatively poor. In this chapter, we give an overview of psychological theories of curiosity and how initial research has focused on curiosity as a specific personality characteristic (i.e. trait curiosity). We then review recent findings on curiosity emerging in experimental psychology and cognitive neuroscience. Rather than examining trait curiosity, this recent line of research explores how temporary states of curiosity affect cognitive processes. Recent findings suggest that curiosity states elicit activity in the brain's dopaminergic circuit and thereby enhance hippocampus-dependent learning for information associated with high curiosity but also for incidental information encountered during high-curiosity states. We speculate how this new line of curiosity research could help to better understand the mechanisms underlying curiosity-related learning and potentially lead to a fruitful avenue of translating laboratory-based findings on curiosity into educational settings.

In this chapter, we describe psychological and neuroscientific research that demonstrates the unique characteristics of self-related information processing. These characteristics have been shown to produce beneficial effects on basic functions (such as perception, attention, and actions), as well as on higher-order cognitive activities (including memory). The findings are explained by their correspondence to the neurocorrelates of self-related information processing. Northoff's (2016) basic model of the self, which describes self-specificity to be a fundamental aspect of the brain's spontaneous (resting) activity, provides further clarification of these results. After considering the unique characteristics of self-related information processing, we describe the potential benefits of considering findings from neuroscience for educational practice by pointing to the positive outcomes of utility value interventions. More specifically, these types of interventions, which are grounded in the expectancy-value theory of student motivation, are examples of how self-related information processing can have educational benefits by increasing motivation and learning.