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The attractiveness of dynamic systems perspectives for expanding thinking about motivation, more particularly interest, lies in the central proposition that the individual is a self-organizing system in which “novel forms emerge without predetermination and become increasingly complex with development” (Lewis, 2000, p. 36). As Lewis further points out, “self-organization is not a single theory or model. Rather it is an idea … that promises coherent explanation in the study of pattern, change and novelty” (Lewis, 2000, p. 42). Thelen and Smith (2006) have proposed that self-organization is a “fundamental property of living things” and “by self-organization we mean that pattern and order emerge from the interactions of the components of a complex system without explicit instructions, either in the organism itself or from the environment” (p. 259). They suggest that understanding change and development concerns “the elaborate causal web between active individuals and their continually changing environments” (p. 271) and refer to specific units of organization within the system as “patterns assembled for task-specific purposes whose form and stability depended on both the immediate and more distant history of the system” (p. 284). To date, dynamic systems perspectives have been applied to a wide range of psychological phenomena, for example, the development of perceptual, motor and cognitive systems in infancy and early childhood (see e.g., Thelen & Smith, 2006). Jörg, Davis, and Nickmans (2007) have argued for a similar approach for the learning sciences. They propose a new complexity paradigm suggesting that more attention needs to be given to understanding the dynamics of the complex systems that make up the science of education and teaching.

As educators seek ways to enhance student motivation and improve achievement, promising advances are being made in adaptive approaches to instruction. Learning technologies are emerging that promote a high level of personalization of the learning experience. One type of personalization is context personalization, in which instruction is presented in the context of learners’ individual interests in areas like sports, music, and video games. Personalized contexts may elicit situational interest, which can in turn spur motivational and metacognitive states like positive affect and focused attention. Personalized contexts may also allow for concepts to become grounded in prior knowledge by fostering connections to everyday activity. In this Chapter, we discuss the theoretical, design, and implementation issues to consider when creating interventions that utilize context personalization to enhance motivation.

First, we provide an overview of context personalization as an instructional principle and outline the emerging evidence that personalization can enhance motivation and improve achievement. We then discuss the theory hypothesized to account for the effectiveness of context personalization and discuss the approaches to personalization interventions. We close by discussing some of the practical issues to consider when bridging the design and implementation of personalization interventions. Throughout the paper, we anchor our discussion to our own research which focuses on the use of context personalization in middle and high school mathematics.

The theoretical mechanisms through which context personalization enhances learning may include (1) eliciting positive affective reactions to the instruction, (2) fostering feelings of value for the instructional content through connections to valued personal interests, or (3) drawing upon prior funds of knowledge of the topic. We provide hypotheses for the relatedness of context personalization to triggering and maintaining situational interest, and explore potential drawbacks of personalization, considering research on seductive details, desirable difficulties, and authenticity of connections to prior knowledge. We further examine four approaches to personalized learning – “fill-in-the-blank” personalization, matching instruction to individual topic interests, group-level personalization, and utility-value interventions. These approaches vary in terms of the depth of the personalization – whether simple, shallow connections are made to interest topics, or deep, meaningful connections are made to learners’ actual experiences. The consideration of depth also interacts with grain size – whether content is personalized based on the broader interests of a group, or the individual experiences of a particular learner. And finally, personalization interventions can have different levels of ownership – an instructor can generate the personalized connections, the connections can be made by the curriculum designers, or learners can take an active role in personalizing their own learning. Finally, we discuss the practical implementation issues when bringing context personalization interventions into K-12 classrooms. Personalization can be logistically difficult to implement, given that learners hold a diverse array of interests, and may experience each of those interests differently. In addition, particular types of instructional content may show greater sensitivity when personalization is implemented, and personalization may be most helpful for learners with certain background characteristics.

Realizing the promise of personalized learning is an unsolved problem in education whose solution becomes ever more critical as we confront a new digital age. Context personalization has the potential to bring together several well-established strands of research on improving student learning – research on the development of interest, funds of knowledge, and utility value – into one powerful intervention.

The study aims to contribute to the literature on board behavior and performance in public sector organizations, by investigating conflicts as a fundamental and inevitable part of interactions between board members. Despite impressive advances in studying the behavioral dimensions of governing bodies, several gaps still remain in our knowledge, especially for public sector boards. These face specific challenges related to multiple, conflicting, and ambiguous goals.

Earlier studies identified four different types of conflict (affective, cognitive, interest, and authority conflicts). These were used to guide a systematic literature review considering the source and the nature of conflicts to classify and describe the state of knowledge on the topic.

Most academic contributions emphasized cognitive and interest conflicts, suggesting that solving them was essential to improve board performance and enable boards to create value. The results suggest the utility of broadening the perspective of the governing board role, moving beyond agency and institutional theory, taking into consideration resource dependence theory as an alternative perspective to investigate board roles and task expectations.

Understanding conflicts within public boards is an interesting challenge from several perspectives. First, it provides a deep look inside board decision-making processes using a behavioral perspective. Second, analyzing the nature and sources of conflict places boards in a better position to address complex political issues. Finally, resolving conflicts may lead boards to channel their energies into collaborative activities that stimulate best practices, facilitate mutual awareness, and generate commitment to cooperation inside and outside the boardroom.

Each of the four objectives can be applied within the military training environment. Military training often requires that soldiers achieve specific levels of performance or proficiency in each phase of training. For example, training courses impose entrance and graduation criteria, and awards are given for excellence in military performance. Frequently, training devices, training media, and training evaluators or observers also directly support the need to diagnose performance strengths and weaknesses. Training measures may be used as indices of performance, and to indicate the need for additional or remedial training.

This chapter provides a contemporary view of state-of-the science research and thinking done in the areas of selection and classification. It takes as a starting point the observation that the world of work is undergoing important changes that are likely to result in different occupational and organizational structures. In this context, we review recent research on criteria, especially models of job performance, followed by sections on predictors, including ability, personality, vocational interests, biodata, and situational judgment tests. The paper also discusses person-organization fit models, as alternatives or complements to the traditional person-job fit paradigm.

Evaluation of research is a core function of academic work, yet there has been very little theoretical development about what it means to ‘know’ in relation to judgements made in examination of doctoral research. This chapter addresses the issue by reflecting on findings from three projects aimed at enhancing understanding of doctoral examination. In order to progress understanding about knowledge judgements in the doctoral research context, the chapter draws on two key contributions in the field of knowledge and knowing, namely, Habermas’ cognitive interests and Chinn, Buckland and Samarapungavan’s notion of epistemic cognition. It examines the common ground between the two bodies of theory, drawing illustratively on empirical work in the field of doctoral examination. The comparison of the Habermasian theory of cognitive interests with Chinn et al.’s notion of epistemic cognition led to the conclusion that there were areas of overlap between the two conceptual schemas that could be utilised to advance research into doctoral examination in higher education. Habermas’ cognitive interests (which underpin his ways of knowing theory) offer a conceptual lens that facilitates analysis of the interaction of ontological and epistemic components of knowledge production. Chinn et al.’s notion of epistemic cognition allows for finer grained analysis of aspects of the cognitive work involved in knowledge rendition. This work is particularly pertinent in an era that sees the boundaries of the disciplines being challenged by the need for new perspectives and cross-disciplinary approaches to solving complex problems.

Cognitive literary criticism is introduced as a bridge between cognitive approaches to the study of persuasion, and literary traditions in consumer research. As a successor to reader-response theory, cognitive literary theory focuses on the cognitive processes of interpretation, while keeping an eye on the aesthetic properties of the text. Paradigmatically cautious researchers might shy away from attempts to marry positivist cognitive constructs to interpretivist cultural theory, but this chapter argues that these qualms also conceal missed opportunities for the study of persuasion.

Insights from cognitive literary criticism are demonstrated at the hand of a LEGO ad.

Theory of mind and conceptual blending are crucial cognitive skills involved in the interpretation of persuasive texts.

Most research to date has kept literary and cognitive approaches to persuasion separate, black-boxing the processes of persuasion. This chapter argues for a revitalization of interest in aesthetic detail, informed by insights from cognitive science.