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The didactic class is a pedagogical tool meant to increase classroom interactivity by encouraging student discussion of real-life cases in connection with theory. This paper evaluates the pedagogical impact of using a one-off didactic class where an external expert is brought in to discuss how to relate a cognitive psychology course's content to real-life problems. Using a mixed-methods approach, we measure the undergraduate students' sense of conceptual understanding, their perspective on applying cognitive sciences, their sense of belonging to the department, and their motivation to work. Students' sense of understanding and their perspective in applying cognitive sciences to real-world problems significantly increased after this class. However, we found no significant differences in their sense of belonging to the department or their motivation to study. This suggests didactic classes may further course-specific content but do not change broader aspects of motivation or belonging. The qualitative interviews support the quantitative results. Students reported that the didactic class made them think laterally about content from other modules and how they could apply theoretical insights to real-world problems, which boosted confidence. Students reported great satisfaction with the didactic class. Of course, the speaker must be relevant to the course content, and students should feel empowered and able to speak in class. However, these are practical concerns that should not discourage lecturers from exploring didactic classes as a fun and instructive tool that has significant pedagogical benefits.

Background and Context: Since the surge of grounded cognition (GC) theories in cognitive psychology, many studies have focused on demonstrating the importance of embodiment and sensorimotor activities on students' conceptual development. In computing education, however, there is not yet a conceptual framework for developing age-appropriate. Objective: This paper brings these sets of work together, showing how the wider grounded cognition literature can be of value to computing education. The main objective of the paper is to suggest and set the theoretical foundations of a model for conceptual development in the early years of computing education. Method: The paper is a conceptual paper and thus, it is based on an extensive account of relevant cognitive psychology and education literature. Findings: The paper presents a model for conceptual development (EIFFEL -Enacted Instrumented Formal Framework for Early Learning in Computing). The general premise underlying the model is that programming concepts are first realised as actions performed on objects; as such, it aims to describe children's conceptual development in computing from their first actions on concrete objects to entirely abstract forms of action representation epitomised by a program. Implications: The model constitutes the first attempt to theorise conceptual development in the early years of computing education; as such it is expected to be used for the design of learning trajectories that progressively advance children's conceptualisations from concrete, situated and multi-modal to formal and more abstract representations.

Purpose: Learning how to identify and avoid inaccurate information, especially disinformation, is essential for any informational consumer. Many information literacy tools specify criteria that can help users evaluate information more efficiently and effectively. However, the authors of these tools do not always agree on which criteria should be emphasized, what they mean or why they should be included in the tool. This study aims to clarify two such criteria (source credibility and soundness of content), which evolutionary cognitive psychology research emphasize. This paper uses them as a basis for building a question-based evaluation tool and draws implications for information literacy programs. Design/methodology/approach: This paper draws on cross-disciplinary scholarship (in library and information science, evolutionary cognitive psychology and rhetoric studies) to explore 15 approaches to information evaluation which conceptualizes source credibility and content soundness, two markers of information accuracy. This paper clarifies these two concepts, builds two sets of questions meant to elicit empirical indicators of information accuracy and deploys them against a recent piece of journalism which embeds a conspiracy theory about the origins of the COVID-19 pandemic. This paper shows how the two standards can help us determine that the article is misleading. This paper draws implications for information literacy programs. Findings: The meanings of and relationships between source credibility and content soundness often diverge across the 15 approaches to information evaluation this paper analyzed. Conceptual analysis allowed the authors to articulate source credibility in terms of authority and trustworthiness, and content soundness in terms of plausibility and evidential support. These conceptualizations allow the authors to formulate two respective sets of appropriate questions, the answers to which are meant to function as empirical indicators for the two standards. Deploying this instrument provides us with the opportunity to understand why a certain article discussing COVID-19 is misleading. Originality/value: By articulating source credibility and content soundness as the two key criteria for evaluating information, together with guiding questions meant to elicit empirical indicators for them, this paper streamlines the process through which information users can judge the likelihood that a piece of information they encounter is accurate.

Data science is a new field of research that has attracted growing interest in recent years as it focuses on turning raw data into understanding, insight, knowledge, and value. New data science education programs, which are being launched at an increasing rate, are designed for multiple education levels and populations. Machine learning (ML) is an essential element of data science that requires an extensive background in mathematics. Whereas it is possible to teach the principles of ML only as a black box, novice learners might find it difficult to improve an algorithm's performance without a white box understanding of the underlying ML algorithms. In this paper, we suggest a pedagogical method, based on hands-on pen-and-paper tasks, to support white box understanding of ML algorithms for learners who lack the level of mathematics knowledge required for this purpose. Data were collected using a comprehension questionnaire and analyzed according to the process-object theory borrowed from mathematics education research. We present evidence of the effectiveness of this method based on data collected in an introduction-level data science course for graduate psychology students. This population had extensive psychology domain knowledge, as well as an established background in statistics, but had gaps in mathematical and computer science knowledge compared with data science majors. The research contribution is both practical and theoretical. Practically, we present a learning module that supports non-major data science students' white box understanding of ML. Theoretically, we propose a data analysis method to evaluate students' conceptions of ML algorithms.

Purpose: The application of leadership theory to training and development in international leadership contexts is burdened by the idealistic, western-centric, prescriptive nature of many leadership theories. Consequently, theories are needed that are culturally neutral, descriptive and practically applicable to the culturally diverse contexts in which leadership interaction takes place. To this end, the cognitive process model of (Denis "et al.," 2012) leadership was developed to facilitate leadership development study in a variety of cultural contexts. The model is based on how the human brain functions at its most basic level in leadership situations across cultures and outlines basic principles of leadership associated with these functions. These principles include awareness, decision-making, attention, relationship building, communication and action. This study aims to discuss this model and how it can be used as a framework for doing leadership training and development study in international settings. Design/methodology/approach: This paper is conceptual in nature and uses psychological studies on brain function as a foundation for developing a process model of leadership. Findings: In contrast the cognitive process model of leadership provides a foundation for understanding what is truly universal when it comes to leadership activities by examining what happens in the brain in any given leadership moment. It then provides a framework for promoting the development of leadership competencies that are essential to practicing the principles and competencies and applying them as one takes action in specific leadership moments at the self, interpersonal, group and team, organizational and social and political community levels. Research limitations/implications: The paper has implications for the content, structure and process of leadership development study in relation to training and coaching. Practical implications: This model makes it possible to identify how to provide training and education in relation to leadership competencies by identifying which aspects of the competencies are universal and which are situational or culture dependent. Originality/value: This study is an original paper exploring the application of this model in the context of global leadership training and development.

This document is an editorial from the Counselling Psychology Review, written by Miltos Hadjiosif and May Lene Karlsen. The authors discuss their anthology of seven stories that aim to provoke and inspire therapists to reflect on their own journeys. They challenge the dominant narrative of the "wounded healer" and seek to highlight the diverse experiences and perspectives within the profession. The authors also emphasize the importance of storytelling and narrative in the field of counselling psychology, calling for a balance between skills-based knowledge and the rich, non-linear life-histories of therapists. [Extracted from the article]

Conventional statistics methods in most psychological research, such as null-hypothesis significance tests (NHSTs), use aggregated values (i.e., the sample means) of group behaviours to make inferences about individuals. Such inferences are possibly erroneous because groups of humans rarely, if ever, constitute an ergodic system. To assume ergodicity without checking is to commit the 'ergodic fallacy'. The aim of the current study was to examine the prevalence of this error in contemporary psychological research. We analysed three highly cited 'Q1' journals in the fields of clinical, educational and cognitive psychology for statements that indicated this error. As hypothesized, the ergodic fallacy was found in the vast majority of the papers investigated here. We also hypothesised that the prevalence of this error would be highest in cognitive psychology papers because this field typically assesses theoretical claims about universal cognitive mechanisms, whereas clinical and educational psychology are more concerned with empirically supported interventions. This hypothesis was also supported by our results. Nonetheless, the prevalence of the ergodic fallacy was still high in all fields. Implications are discussed with respect to the reporting of research findings and the validity of theories in psychology. [ABSTRACT FROM AUTHOR]

The 1980s and 1990s saw a robust connection between computer science education and cognitive psychology as researchers worked to understand how students learn to program. More recently, academic disciplines such as science and engineering have begun drawing on cognitive psychology research and theories of learning to create instructional materials and teacher professional development materials based on theories of learning, to some success. In this paper, we follow a similar approach by highlighting common areas of interest between computer science education and cognitive psychology--specifically theories of analogical transfer--and discuss how cross-pollination of theoretical constructs between disciplines can support research on the teaching and learning of multiple programming languages. We will also discuss areas where computing education research can adapt the existing theories from cognitive psychology to develop domain-specific theories of knowledge transfer in computing and feed back into cognitive psychology research to inform larger debates about the nature of cognition and learning.

Personal values influence goals and motivate actions. The case study reported in this paper explored whether an understanding of values would provide a useful framework to guide the co-creation of the undergraduate cognitive psychology curriculum at a UK University. A design team composed of staff and students ran two co-creation workshops to explore underlying values. These values were translated into curriculum ideas which were then shared via an online survey to students and staff for feedback. The activities revealed a set of values that were salient when imagining future curriculum designs: feeling stimulated, choice and autonomy, developing competence, feeling safe and secure, community and fairness. In addition, a deeper value layer was visible which reflected participants' orientations to learning and education. We describe our process for eliciting values and the intertwined and iterative relationship between value elicitation and a co-created curriculum. We also reflect on the position of co-creation within the value landscape of higher education and the social dynamics of staff-student partnerships. We argue that whilst using values to frame co-creation allows for deeper insight into how to embed curriculum re-innovation, it is important to attend to the value system of co-creation and those who do not participate.

The European Journal of Psychology of Education (EJPE) will now be publishing a new format called "Special Section" to encourage collaboration among researchers in the field of psychology of education. A Special Section consists of 4 to 6 papers focused on a specific area of research proposed by a group of researchers, the editorial team, or the editorial board. The papers go through the same peer review process as regular papers and are published in the journal as a collection. The goal of this format is to promote visibility for European collaborative research projects, foster collaboration, and explore new ideas and approaches in psychology of education. Several Special Sections are already planned for publication between 2024 and 2025. [Extracted from the article]

This paper will use two examples from human cognition-theory of mind and concept representation-to compare human and artificial intelligence. One problem in comparing humans to AI is that performance does not entail competence, meaning that even if two systems can carry out a particular task, the two systems do not necessarily share the same underlying cognitive capacity. However, researchers have begun testing AI on psychological measures to compare human and AI cognition. For example, researchers have investigated the artificial theory of mind, which is the ability to attribute mental states to oneself and others. Additionally, researchers have investigated artificial concept representation, which is the ability to represent categories abstractly. This paper argues that although empirical evidence is key to exploring AI, it is possible that data alone cannot capture the challenge of human-artificial comparison. [ABSTRACT FROM AUTHOR]

Were you able to read and understand what that foreign word means? If not, it is never too late to start learning a new language. However, is it possible to become fluent in a foreign language despite the age at which you start? To answer this question this paper delves into the critical periods in language acquisition and their importance. This paper highlights infants' gradual acquisition of different aspects of language, such as phonemes, words, and grammar. To conclude the importance of critical periods, I compare different strategies for infants and adults learning a language, referring to the example of German word order acquisition. Furthermore, this paper focuses on second language learning. It gives some successful examples of perfectly acquired language by foreigners beyond childhood and highlights the phenomenon of exposure to a native-speaking environment. Additionally, I will discuss the degree of plasticity after the critical period ends and some challenges learners might experience when acquiring a second language. In conclusion, this paper offers a comprehensive review that contributes to our understanding of language development and its implications for language learning beyond childhood. [ABSTRACT FROM AUTHOR]

Inconsistency in real-world judgments can cause random unfairness, injustice and misallocation of resources. In their recent monograph Kahneman, Sibony, and Sunstein (2021) analyse judgment inconsistency or "Noise," examine its sources and propose remedies. In this commentary on Kahneman et al., we reflect on the major concepts (such as "judgment," "noise," "error," and "bias") used in analysing inconsistency. We place this work in the broader context of applied cognitive psychology, relating it to error typologies and to dual-systems views of thinking. We also compare Kahneman et al.'s heuristics based approach to the linear combination of attributes based approach of Social Judgment Theory (SJT), with particular reference to judgment noise. We conclude that the main contributions of Kahneman et al.'s book are: (1) to raise awareness of the pervasiveness of judgment noise across a range of important real-world areas; (2) to provide a taxonomy of types of noise in terms of system noise versus occasion noise, and level noise versus pattern noise; and (3) to outline useful ways of reducing noise, and thus overall levels of error.

Purpose: This paper aims to provide a wide picture of studies on heuristics for international decision-making with a focus on foreign market entry. This paper systematically reviews studies published in the international business and international marketing domain to examine heuristically based decisions for foreign market entry. Design/methodology/approach: This paper proposes a systematic literature review and an in-depth analysis of 32 papers published between 1997 and 2021 dealing with foreign market entry and the use of heuristics for international decision-making. Findings: Even if the marketing and management literature is in many ways permeable to the debate around heuristics developed in experimental psychology and cognitive science, international business and international marketing studies on the one hand recognize that international decision-making, especially when dealing with foreign market entry, is strongly characterized by uncertainty, on the other hand, there isn't a developed and systematized literature about it. This paper shows key topics and areas fundamental to foreign market entry in which heuristics are applied by decision makers and their effectiveness. Originality/value: A systematic review of the use of heuristics for foreign market entry decision-making can represent a useful step for a more organic development of knowledge about the more general use of heuristics for international decision-making. Understanding the decision-making process on the modes of entry in foreign markets is a key topic for international marketing and international business scholars and practitioners. [ABSTRACT FROM AUTHOR]

Enterprise innovation ecology plays a vital role in the operation and development of enterprises. It can enable enterprises to have benign and sustainable progress space in action. At the same time, it can also make the innovation ability of enterprises grow unprecedentedly, which is a crucial factor related to the survival and lifeline of enterprises. However, enterprise managers are often too immersed in concept innovation and structural optimization in the actual innovation and ecological construction of enterprises. Still, they do not pay attention to the problems in actual construction. This would cause the actual operation of the system to be restricted by key influencing factors such as environmental protection policies, making it difficult to achieve effective progress. In this regard, the purpose of this paper is to analyze and discuss the enterprise innovation ecological philosophy based on the human–computer interaction mental model. Therefore, this paper comprehensively considers four key factors that affect the construction of enterprise innovation ecology, namely, the promotion of enterprise technology, the competitiveness of enterprise market, the innovation characteristics of enterprises, and the environmental constraints of innovation ecology, and improves and perfects the innovation ecosystem from these factors. Finally, an efficient ecological model of enterprise innovation was designed, and the scientific construction was carried out through the human–computer interaction mental model combining human–computer interaction technology and cognitive psychology. At the same time, the model is applied to the actual enterprise operation, and the naive Bayesian algorithm is adopted to optimize the relevant performance of the algorithm model. The experimental results showed that the highest sample accuracy of the algorithm reaches 92.9%, which greatly improved the operation efficiency of enterprise innovation ecological construction. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear teaching approach, based on learning theories in cognitive psychology, with a special focus on large-cohort economics modules. The fundamental rationale is to match the features of teaching with the nature of learning. This approach was implemented in an undergraduate economics module, which received qualitative feedback and quantitative evaluation. Formal econometric models with both binary and continuous treatment effects were developed and estimated to quantify the effects of the proposed approach. Evidence shows that the nonlinear teaching approach significantly improves the effectiveness and efficiency of the learning-teaching process but does not promote student attendance. [ABSTRACT FROM AUTHOR]

Our faces provide information about our emotions, personal identity, trustworthiness, attractiveness, age, and sex. However, because of the COVID-19 pandemic, mask-wearing, which occludes 60% of the face, has become pervasive. Consequently, some clinicians and educators have expressed concern about the effect of masks on social, emotional, and cognitive health in adults and during child and adolescent development. This paper investigates the impact of mask-wearing on the ability of children, adolescents, and adults to identify emotions. In particular, this paper explores the typical development of emotion)reading abilities, emotion reading through masks, and emotion reading in specific populations such as those with disabilities and those from various cultural backgrounds. The paper ends with a framework for improving communication through masks. [ABSTRACT FROM AUTHOR]

The article discusses the history and development of the journal Social Cognitive & Affective Neuroscience (SCAN). The author, Matthew D. Lieberman, reflects on the early years of the journal and the challenges faced in establishing a dedicated platform for social and affective neuroscience research. Lieberman announces that he will be stepping down as the Editor-in-Chief in January 2025, marking the end of his tenure. He also outlines some upcoming changes for the journal, including the acceptance of non-neuroscience papers and the publication of a "Tools of the Trade" piece to support the growth of social and affective neuroscience in academic institutions. [Extracted from the article]

Paul Schwartz In the introductory section of his commentary, Paul Schwartz says that Freud's notions of free and bound energy are based only loosely on Helmholtzian physics, "which as near as can be determined, Freud himself never formally acknowledged" (p. 1158). Like most neuropsychoanalysts, I am a dual-aspect monist, which means I take the view that the functional dynamics of what Freud called the "mental apparatus" can be studied from two different I observational i perspectives: the outer, objective one (seeing a brain) and the inner, subjective one (being a brain). Anyone who shares Sugarman's view that "neuroscientific concepts are relevant only in explaining brain functioning, not mental functioning" (p. 1142), should carefully reread the quotations from Freud that I provided in those opening paragraphs. Alan Sugarman In the introductory section of his commentary, Alan Sugarman expresses disappointment that I did not outline a general psychology in my paper. [Extracted from the article]

In order to improve the efficiency of information acquisition and task selection in Virtual Reality (VR) systems, enhance the interactive experience, and reduce cognitive load for users, it is crucial to effectively organize and leverage user cognitive psychology and design elements during the VR scene design phase. This paper focuses on analyzing the low cognitive load requirements of users and the need for a satisfactory user perceptual experience based on the cognitive resource theory. We propose a method for optimizing the design of VR system scenario tasks under low cognitive load requirements. By utilizing human-computer hybrid intelligent assistance for predicting user cognitive load and incorporating intelligent optimization genetic algorithms into the optimization of VR system design elements, we aim to minimize cognitive load as the objective function based on the principle of low cognitive load. Important knowledge granularity nodes are used as fitness functions in the optimization process of VR system design resource elements. An application study is conducted, combining the multi-channel cognition in a smart city VR system task information interface, to optimize the system resource features. The study validates and compares the solutions obtained through traditional design processes and the solutions optimized by the method proposed in this paper, using virtual reality eye-tracking experiments for the same design task requirements in VR systems. The results demonstrate that users experience lower cognitive load and better task operation experience when interacting with the optimized solutions proposed in this paper. Therefore, the optimization method studied in this paper can serve as a reference for the construction of virtual reality systems. [ABSTRACT FROM AUTHOR]

This paper proposes the complex dynamics of collective behavior through an interdisciplinary approach that integrates individual cognition with potential fields. Firstly, the interaction between individual cognition and external potential fields in complex social systems is explored, integrating perspectives from physics, cognitive psychology, and social science. Subsequently, a new modeling method for the multidimensional potential field mechanism is proposed, aiming to reduce individual behavioral errors and cognitive dissonance, thereby improving system efficiency and accuracy. The approach uses cooperative control and distributed learning algorithms to simulate collective behavior, allowing individuals to iteratively adapt based on local information and collective intelligence. Simulations highlight the impact of factors such as individual density, noise intensity, communication radius, and negative potential fields on collective dynamics. For instance, in a high-density environment with 180 individuals, increased social friction and competition for resources significantly decrease collective search efficiency. Validation is achieved by comparing simulation results with existing research, showing consistency and improvements over traditional models. In noisy environments, simulations maintain higher accuracy and group cohesion compared to standard methods. Additionally, without communication, the Mean Squared Error (MSE) initially drops rapidly as individuals adapt but stabilizes over time, emphasizing the importance of communication in maintaining collective efficiency. The study concludes that collective behavior emerges from complex nonlinear interactions between individual cognition and potential fields, rather than being merely the sum of individual actions. These insights enhance the understanding of complex system dynamics, providing a foundation for future applications in adaptive urban environments and the design of autonomous robots and AI systems. [ABSTRACT FROM AUTHOR]

At the end of the last century, there was a debate about whether cognitive psychology had superseded behavioral psychology and psychoanalysis, and the question was raised of whether the latter two might even be dead. The aim of this study was to investigate how these sub-disciplines have developed since then. The citation count, Journal Impact Factor (JIF), and Immediacy Index of four leading journals from each sub-discipline were abstracted for the years 1998, 2008, and 2018. Trends were analyzed using joinpoint regression analysis. The average number of times each sub-discipline's journals were cited increased between 1988 and 2018. The cognitive journals' JIF increased slightly, the behavioral journals' doubled, and the psychoanalytic journals' remained at the same level. The average annual percentage change for citations to the International Journal of Psychoanalysis showed that the number of citations statistically significantly increased over the years. This was also the case for the Journal of Applied Behavior Analysis. Its JIF trend changed at one point: it decreased up through 2006, after which it increased. Citations to Cognitive Psychology also increased over time, while there was no evidence that its JIF changed. This shows that all three sub-disciplines are still alive and relevant. [ABSTRACT FROM AUTHOR]

Spatial reasoning is ingrained in daily life, such as when locating our keys or parking our car. At a broad level, spatial reasoning describes the ability to mentally represent and transform objects and their relations. Spatial reasoning is comprised of distinct, yet related, spatial skills, most of which have strong links with mathematics achievement. Subsequently, understanding the ways spatial reasoning connects with mathematics has the potential to support achievement in school. However, current research practices have failed to translate into practical outcomes for students. To date, research has often focused on decontextualized spatial skills, measured by psychometric tests, to generalize about broader models of spatial reasoning. However, spatial reasoning goes beyond test performance. In this theoretical review, I have sought to find the points of connection between the fields of cognitive psychology, often based in the lab, and mathematics education, situated within classrooms, and discussed ways to connect this currently siloed work for greater impact on classroom practice. The paper addresses the emergence of spatial research from its historical roots in intelligence testing and the influence these conceptualizations have had on contemporary methodologies. It goes on to discuss how these research traditions may be limiting our ability to understand the mechanisms linking spatial reasoning and mathematics. The paper argues for a broader view of research problems and methodologies in spatial cognition research to facilitate the translation of research to meaningful contexts in pedagogy and learning. [ABSTRACT FROM AUTHOR]

Intangible cultural heritage (ICH) terms are unique expressions of cultural knowledge and practices that are deeply rooted in a particular region or community. Accurately translating ICH terms is crucial for sharing this knowledge and promoting cross-cultural understanding. However, the complex nature of ICH terms, including their regional and cultural specificity, means that mistranslations can easily occur during the translation process. In addition to linguistic and cultural barriers, psychological factors can also impact the accuracy of translations. Translation psychology, a new discipline that examines the psychological process of bilingual conversion and its cognitive mechanisms, can provide insights into the translation of ICH terms. This paper proposes an information processing model of translating ICH terms based on translation psychology, which examines the psychological processes of translators during the translation of Chinese ICH terms into English. Through questionnaires and translation exercises, the study compares and analyzes the psychological activity process of the translators, verifies the expression of translation psychology in the translation of ICH terms, and identifies the characteristics of students' translations. The study's subjects were non-English major sophomores with diverse academic backgrounds, randomly sampled from a representative polytechnic university in Guangdong. The findings of this study are significant for improving the quality of translations and promoting cross-cultural understanding of ICH terms. By understanding the psychological factors involved in the translation of ICH terms, we can overcome language and cultural barriers and accurately convey the rich cultural heritage embodied in these terms. [ABSTRACT FROM AUTHOR]

Recently, the spread of fake images on social media platforms has become a significant concern for individuals, organizations, and governments. These images are often created using sophisticated techniques to spread misinformation, influence public opinion, and threaten national security. This paper begins by defining fake images and their potential impact on society, including the spread of misinformation and the erosion of trust in digital media. This paper also examines the different types of fake images and their challenges for detection. We then review the recent approaches proposed for detecting fake images, including digital forensics, machine learning, and deep learning. These approaches are evaluated in terms of their strengths and limitations, highlighting the need for further research. This paper also highlights the need for multimodal approaches that combine multiple sources of information, such as text, images, and videos. Furthermore, we present an overview of existing datasets, evaluation metrics, and benchmarking tools for fake image detection. This paper concludes by discussing future directions for fake image detection research, such as developing more robust and explainable methods, cross-modal fake detection, and the integration of social context. It also emphasizes the need for interdisciplinary research that combines computer science, digital forensics, and cognitive psychology experts to tackle the complex problem of fake images. This survey paper will be a valuable resource for researchers and practitioners working on fake image detection on social media platforms. [ABSTRACT FROM AUTHOR]

This paper conjectures and validates a framework that allows for action during inference in supervised neural networks. Supervised neural networks are constructed with the objective to maximize their performance metric in any given task. This is done by reducing free energy and its associated surprisal during training. However, the bottom-up inference nature of supervised networks is a passive process that renders them fallible to noise. In this paper, we provide a thorough background of supervised neural networks, both generative and discriminative, and discuss their functionality from the perspective of free energy principle. We then provide a framework for introducing action during inference. We introduce a new measurement called stochastic surprisal that is a function of the network, the input, and any possible action. This action can be any one of the outputs that the neural network has learnt, thereby lending stochasticity to the measurement. Stochastic surprisal is validated on two applications: Image Quality Assessment and Recognition under noisy conditions. We show that, while noise characteristics are ignored to make robust recognition, they are analyzed to estimate image quality scores. We apply stochastic surprisal on two applications, three datasets, and as a plug-in on 12 networks. In all, it provides a statistically significant increase among all measures. We conclude by discussing the implications of the proposed stochastic surprisal in other areas of cognitive psychology including expectancy-mismatch and abductive reasoning. [ABSTRACT FROM AUTHOR]