A reality of conducting motivation research in educational settings is that there are tensions between technical standards of research and practical constraints of a given situation. Although adherence to standards for high-quality measurement is critical for good-quality data to be collected, measurement also requires substantial resources to ensure quality. In the current chapter, we discuss several examples of real data collected in different educational settings using a pragmatic measurement framework. Based on contemporary measurement perspectives, the pragmatic measurement framework emphasizes building evidence-based arguments to support the use and interpretation of a measure. Example 1 explores college students’ attitudes toward general education classes. Example 2 tracks students’ classroom motivation over several time points. Example 3 assesses experimental differences from an online motivation intervention. Together the three examples cover a range of possible research questions that researchers may encounter. As a whole, this chapter demonstrates that important and meaningful insights can be gained using pragmatic approaches to measurement. Importantly, we discuss the trade-offs that researchers or other measure users must consider when adopting a pragmatic approach to measurement.

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 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.

Curiosity and situational interest are powerful driving forces in learning and motivation that lead students to learn more effectively. In this chapter, we elucidate curiosity and situational interest by focusing on (1) conceptual definitions and characteristics, (2) antecedents, (3) cognitive and behavioral outcomes, and (4) strategies to foster them in school. Curiosity is a short-lasting, aversive state that desires an acquisition of specific information. Its properties contrast with those of situational interest, which is an overall positive affect and a general preference for a topic. Whereas curiosity and situational interest are stimulated by similar contextual features (such as collative variables), triggering curiosity requires one to perceive an information gap between what one knows and what one wants to know. Despite these differences, ample evidence displays that both curiosity and situational interest positively impact students’ learning, motivation, creativity, and well-being once triggered. Thus, in closing, integrative and specific pedagogical guidelines to enhance students’ curiosity and situational interest in education practice are suggested.

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.

In this chapter, we describe the principles of a person-oriented approach to studying individual differences (and similarities), and how it can be applied to the study of students’ achievement goal orientations. First, we briefly illustrate the approach, which provides a way of looking at the relative emphasis of different achievement goal orientations, thereby explicitly addressing the issue of multiple goals and their associations with important outcomes. Second, we give a comprehensive review of studies that have applied such an approach to investigating students’ achievement goals. The diversity in conceptualizations, methods, and study samples in the studies complicates the interpretation of the findings, but some generalizations can nevertheless be made. Based on the review, we conclude that students with qualitatively different achievement goal orientation profiles can clearly be identified, and that the extracted profiles are rather similar across studies. Further, it seems that such profiles are relatively stable over time and meaningfully associated with learning and various educational outcomes (e.g., academic achievement, self-perceptions, well-being, task-related motivation, and performance). The review also contributes to the debate concerning the advantages of endorsing different goals. Finally, we raise some methodological concerns, discuss implications for learning, and provide suggestions for future research.

Curiosity has been a popular subject of inquiry by psychological scientists for over a century. Nevertheless, its nature, dimensionality, and determinants all remain surprisingly poorly understood. While there is general agreement on a “broad strokes” understanding of curiosity as a desire for new knowledge, the precise character of that desire and the specific behaviors it may motivate continue to spark considerable disagreement and debate. In this chapter, I discuss both previous and contemporary theory and research on curiosity as a psychological construct. I describe curiosity in terms of two types: D-type and I-type. D-type curiosity is theorized to reflect an uncomfortable “need to know” that becomes increasingly bothersome until satisfied by obtaining the desired specific pieces of missing information. I-type curiosity is theorized to be a more relaxed “take it or leave it” attitude towards the discovery of new information, in which the aim is simply to have fun while learning. Qualitative differences between I-type and D-type curiosity experiences – being motivated either to induce situational interest or reduce situational uncertainty, respectively – are hypothesized to translate into significant quantifiable differences in the extent to which each type of curiosity energizes behavior. Specifically, D-type curiosity is hypothesized to be associated with both more intense levels of state-curiosity and greater persistence in subsequent information-seeking behavior as compared to I-type curiosity. Finally, future directions for research are discussed.

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.

In this chapter, we present an overview of the literature addressing the neuroscience of attention, information-seeking, and active sampling, and we discuss its potential significance for learning and learning progress. First, we review the emerging hypothesis that attention is an active mechanism for information sampling and exploration in the environment. We then turn to a discussion of how reward motivates attention and how attention can be employed to reduce uncertainty about knowledge of one's current state. We further consider the way rewards interact with other factors (including novelty, surprise, and task relevance). Throughout the review, we particularly focus on the distinction between extrinsic and intrinsic motivation, highlighting curiosity as a key example of the latter in motivating the search for intrinsically desirable information that benefits learning on both long and short timescales. Finally, we discuss the role of cognitive control in directing attention during learning, as well as the way neural systems underlying cognition and motivation have implications for informing techniques for teaching and learning in wider educational contexts.

This chapter describes different approaches to the concept of goals in different theoretical explanations of motivation and engagement, considers their limitations, and points out tensions among explanations. Approaches to understanding goals and motivation have varied considerably. Psychological theories, focusing on individual differences or on the effects of context on individuals, aim to predict the relationship of goals to actions and beliefs across settings. More situated approaches have taken the position that individuals are always in context and that the focus of research should be the activity system or the individual-in-context. Research from this perspective investigates how goals arise within activity systems as individuals interact with people and objects over time. Different approaches have led to differences in research questions and methods. The chapter is organized around metatheoretical questions common to the study of goals across theoretical perspectives, including which goals should be studied and promoted in educational settings, the nature of the relationship between individual and context, and the relation of goals to the meaning of activity.

Self-efficacy is a popular construct among researchers interested in student learning and performance. It has been used successfully to explain and predict a variety of cognitive, affective, and behavioral outcomes in diverse academic settings. Evidence has accumulated that unanimously points to the functional advantage of having strong self-efficacy beliefs. While so much has been documented on this important construct during the past several decades, it is our judgment that the time has come to reflect on past research findings and revisit some of the unresolved issues that have held up further development in academic self-efficacy research. In this chapter, we summarize existing research on self-efficacy beliefs in academic settings and suggest directions for future research in this area. Specifically, we present a brief overview of self-efficacy theory, along with relevant empirical findings, paying particular attention to the development of self-efficacy beliefs and their relationships with academic outcomes and other motivation constructs. We then turn to unresolved issues in self-efficacy theory and research, such as the growth trajectories of self-efficacy beliefs across time and academic domains, the benefits of modeling, and cross-cultural issues.

In recent years, web-enabled credentials for learning have emerged, primarily in the form of Open Badges. These new credentials can contain specific claims about competency, evidence supporting those claims, links to student work, and traces of engagement. Moreover, these credentials can be annotated, curated, shared, discussed, and endorsed over digital networks, which can provide additional meaning. However, digital badges have also reignited the simmering debate over rewards for learning. This is because they have been used by some and characterized by many as inherently “extrinsic” motivators. Our chapter considers this debate in light of a study that traced the development and evolution of 30 new Open Badge systems. Seven arguments are articulated: (1) digital badges are inherently more meaningful than grades and other credentials; (2) circulation in digital networks makes Open Badges particularly meaningful; (3) Open Badges are particularly consequential credentials; (4) the negative consequences of extrinsic rewards are overstated; (5) consideration of motivation and badges should focus primarily on social activity and secondarily on individual behavior and cognition; (6) situative models of engagement are ideal for studying digital credentials; and (7) the motivational impact of digital credentials should be studied across increasingly formal “levels.”

In the behavioral sciences, it is common to explain behavior in terms of what was learned in a task, as if any subsequent change in performance had to denote a change in learning. However, learning alone cannot account for variability in performance. Instead, incentive motivation plays a direct role (and is more effective) in controlling moment-to-moment changes in an individual's responses than the learning process. After briefly introducing the history of the study of incentive motivation, we explain that incentive motivation consists of a dopamine-dependent process that does not require consciousness to influence responding to a task. We analyze two Pavlovian situations in which incentive motivation can modulate performance, irrespective of additional learning: the instant transformation of disgust into attraction for salt and the invigoration of responses under reward uncertainty. Finally, we consider drug addiction as an example of motivational dysregulation rather than as a consequence of the habit to consume substances of abuse.