Studies In Cognitive Psychology Research Articles

Research on Recognition Method of Social Robot Based on T-A-GCNIIT in the Metaverse

Social robots are used in intelligent customer service, intelligent chat, intelligent shopping guides, and more because of emotion recognition studies in cognitive psychology. However, determining the user's purpose quickly and precisely has proved challenging. Domestic researchers proposed the A-GCNII model to address missing feature information; however, it needs a lot of math. This research offers a social robot recognition approach using the T-A-GCNIIT model and cognitive psychology to optimize computing complexity and performance. The T-A-GCNIIT algorithm processes social network data, and the Viola–Jones algorithm improves social robot intelligence to represent social robots in the meta-universe. The model performs well in node classification, link prediction, community discovery, and other tasks, with enhanced accuracy, recall, F1 score value, and other metrics. The model can also better comprehend the user's emotional state using cognitive psychology to better recognize their purpose and propose a fresh notion for enhancing social robots' cognitive psychology.

The Role of Stimulus Uncertainty and Curiosity in Attention Control.

Most cognitive psychological studies assume that participants in lab-based tasks maintain a single goal based on task instructions. However, people can be motivated by other factors, such as curiosity. We examined if people attend to seemingly task-irrelevant information out of curiosity by manipulating stimulus uncertainty in a cueing paradigm. Participants were presented with an abrupt-onset cue followed by a letter target (E or H). Next, a mask either at the target location (low uncertainty) or at all four locations (high uncertainty) was shown. We expected high uncertainty to induce a state of curiosity that in turn influences the processing of the cue. Cueing effects were greater in the high-uncertainty condition compared to the low-uncertainty condition. In Experiment 2, we additionally elicited self-report ratings on curiosity. In sum, target-specific uncertainty leads to greater processing of task-irrelevant peripheral cues across two experiments. We tentatively conclude that uncertainty modulates attention control and further research is necessary to examine if this is indeed due to curiosity induced by uncertainty.

Examining How Contextual Cues Affect the Interpretation and Dissemination of Metaphors in Social Networks

This paper explores the intricate relationship between contextual cues and the interpretation and dissemination of metaphors in social networks. Utilizing a multi-disciplinary approach that combines insights from linguistics, cognitive psychology, and communication studies, we investigate how various contextual cues, such as visual elements, hashtags, and social signals, shape the way metaphors are understood and spread in digital environments. Through a comprehensive review of literature and analysis of case studies, we highlight the dynamic interplay between metaphor interpretation and dissemination, revealing how the same metaphor can evoke different interpretations and dissemination patterns depending on the surrounding context. Our findings underscore the complexity of metaphorical communication in social networks and its implications for online discourse. We discuss the theoretical and practical implications of our study, emphasizing the importance of considering contextual cues in the effective use of metaphors in social media communication. Finally, we suggest future research directions to further explore the role of contextual cues in metaphorical communication in social networks.

Reading for pleasure: scrutinising the evidence base – benefits, tensions and recommendations

Compelling international evidence illustrates the potential of reading for pleasure for enhancing student reading achievement along with other learning and wellbeing outcomes. Yet profound challenges exist for nations seeking to encompass attention to students’ volitional reading. In this paper we critically review the growing research evidence in this area by drawing systematically on cognitive psychological studies of reading attainment and motivation, educational studies of classroom practice, and the work of literary scholars and medical professionals. We consider and critique the methodologies deployed and read between the lines, exposing contradictions and complexities across this interdisciplinary field before considering the demands of operationalising this agenda in education. Through a dual focus on England and Australia, where, exemplifying international trends, young people’s voluntary reading continues to decline, we examine difficulties and dilemmas which play out in policy and practice contexts. Our points of commonality and comparison surface key issues for consideration in countries working to reconcile the push and pull of performativity and reading for pleasure agendas in order to nurture children’s volitional reading. To conclude, we examine ways forward for research, policy and practice which deserve increased global attention, and offer future-focused recommendations to advance this significant social justice agenda.

DRM LISTS CREATED WITH CHATGPT: ANALYSING RECOGNITION MEMORY WITH CLIMATE-CHANGE THEMED LISTS

Machine learning and natural language processing have led to the development of powerful language models such as ChatGPT, which can generate consistent and human-like responses to a wide range of queries. In many domains, ChatGPT provides appropriate responses to given commands. One of the aims of this study is to investigate the use of these association lists, such as the Deese-Roediger-McDermott (DRM) lists popular in cognitive psychology studies, by ChatGPT by giving the necessary instructions. The same method was then used to create association lists around a specific topic (climate change). The results of the first study showed that participants gave more false answers when discriminating whether critical words were presented during the test phase than when related and unrelated words were presented. This finding shows that DRM lists generated by ChatGPT can be used to search for memory errors. In line with the literature, false answers for critical words were predominantly rated as ‘remember’. The results of the second study, which was applied to the lists created on the topic of climate change and compared the responses of the groups with the climate denial scores, show that there is no significant difference in the emergence of false memories between the two groups. The level of climate change denial did not significantly affect the participants' responses to the critical words in the climate-related lists. The low level of climate denial in the sample is a limitation of this study. It is recommended that future studies compare memory performance across an appropriate sample.

Smartphone mobility assistants. A lever to guide route choice preferences in mass transit?

The regulation of passenger congestion in mass transit is a persistent issue that requires ingenious and cost-effective solutions to ensure that related operations run at optimum capacity. Mass transit operators may implement Public Transport Demand Management (PTDM) strategies like cognitive levers to tackle this issue by targeting passengers’ behaviour during the route planning that precedes travel in mass transit. In this regard, multiple experimental studies in cognitive psychology and sciences have shown that transit maps can be used to guide passengers’ route choice preferences in mass transit.A route choice experiment was conducted to examine the potential of smartphone mobility assistants as a tool to guide mass transit users’ away from the fastest options that tend to be predominantly preferred. 582 participants took part in an online study where they engaged in a route selection task by indicating their route choices in the Île-de-France mass transit system. We measured how participants’ preferences for the fastest route varied depending on the visual format in which routes were presented (on a transit map, on a timeline or listed briefly as per current trends), the presence of conflicting visuo-spatial information on the transit map (fastest choice = shortest vs. longest choice) and the level of comfort (availability of simple transfers and/or less congested routes).The main results suggest the existence of two levers than can be implemented in smartphone mobility assistants to manage passenger congestion in mass transit: (1) a perceptive heuristic whereby passengers presented with a transit map manifest a preference for the route presented as the shortest on the map and (2) the possibility to sway a proportion of passengers away from the choice of the fastest route by presenting information about the comfort levels of alternative options.

Symposium 12: Ebbinghaus’ Legacy: Neuropsychological Studies of Long-Term Forgetting

Summary Abstract:Most clinical and research investigations of memory focus on consolidation of information over relatively brief intervals of time (i.e., minutes, hours). However, in everyday life we are most interested in retaining experiences for much longer periods of time (days, weeks, years). Studies in cognitive psychology demonstrate that the survival of an engram is influenced by a variety of factors including contextual aspects at time of initial learning, the age of an event, frequency and distribution of exposure to the memory over time and, of course, the amnestic capacity of the learner. In the current symposium we examine the durability of new memories as well those from the past. Presentations focus on medical factors, such as epilepsy and stroke, that result in acceleration of memory loss. The longevity of old memories is examined in relation to age-related decline and the onset of dementia. Findings from these studies enhance our understanding of the cognitive and neural underpinnings of consolidation and, hence, they inform our ability to remember our past.

HUMAN-COMPUTER INTERACTION: ENHANCING USER EXPERIENCE IN INTERACTIVE SYSTEMS

In this research, we investigate how human-computer interaction (HCI) can be used to improve the user experience (UX) of interactive systems. Studies in cognitive psychology, information processing, and human factors are examined as they relate to the development of HCI. It highlights how HCI has shifted its focus from functionality to user-friendliness, teaching ability, efficiency, enjoyment, and emotion. To better understand the current state of HCI and UX research, practice, and theory, a systematic literature study is performed. Focusing on users' goals wants, and characteristics at every stage of the design process is central to user-centered design (UCD) ideas and approaches, which are discussed at length in this article. We investigate usability testing as a crucial technique for bettering HCI, focusing on its advantages in pinpointing usability problems, boosting system efficacy, and boosting user pleasure. Methods for creating tests, finding participants, collecting data, and analyzing results are discussed. The importance of prototype methods in HCI and user-centric design is also emphasized in the study. This article delves into the practice of creating prototypes to collect user feedback, iterate designs, and perfect interactive systems. Techniques covered include paper prototyping, interactive wireframes, and high-fidelity prototypes. We propose interaction design frameworks like the User-Centered Design Process (UCDP) and the Double Diamond model to help designers prioritize users when developing interactive systems. The study also delves into how technologies like augmented reality, virtual reality, natural language processing, machine learning, and gesture-based interfaces have revolutionized HCI in recent years. The paper defends user-centric design's place in HCI, pointing out how UX affects user happiness, participation, and output. Researchers and practitioners in HCI and software engineering can greatly benefit from this paper's findings.

The storage capacity of a directed graph and nodewise autonomous, ubiquitous learning.

The brain, an exceedingly intricate information processing system, poses a constant challenge to memory research, particularly in comprehending how it encodes, stores, and retrieves information. Cognitive psychology studies memory mechanism from behavioral experiment level and fMRI level, and neurobiology studies memory mechanism from anatomy and electrophysiology level. Current research findings are insufficient to provide a comprehensive, detailed explanation of memory processes within the brain. Numerous unknown details must be addressed to establish a complete information processing mechanism connecting micro molecular cellular levels with macro cognitive behavioral levels. Key issues include characterizing and distributing content within biological neural networks, coexisting information with varying content, and sharing limited resources and storage capacity. Compared with the hard disk of computer mass storage, it is very clear from the polarity of magnetic particles in the bottom layer, the division of tracks and sectors in the middle layer, to the directory tree and file management system in the high layer, but the understanding of memory is not sufficient. Biological neural networks are abstracted as directed graphs, and the encoding, storage, and retrieval of information within directed graphs at the cellular level are explored. A memory computational model based on active directed graphs and node-adaptive learning is proposed. First, based on neuronal local perspectives, autonomous initiative, limited resource competition, and other neurobiological characteristics, a resource-based adaptive learning algorithm for directed graph nodes is designed. To minimize resource consumption of memory content in directed graphs, two resource-occupancy optimization strategies-lateral inhibition and path pruning-are proposed. Second, this paper introduces a novel memory mechanism grounded in graph theory, which considers connected subgraphs as the physical manifestation of memory content in directed graphs. The encoding, storage, consolidation, and retrieval of the brain's memory system correspond to specific operations such as forming subgraphs, accommodating multiple subgraphs, strengthening connections and connectivity of subgraphs, and activating subgraphs. Lastly, a series of experiments were designed to simulate cognitive processes and evaluate the performance of the directed graph model. Experimental results reveal that the proposed adaptive connectivity learning algorithm for directed graphs in this paper possesses the following four features: (1) Demonstrating distributed, self-organizing, and self-adaptive properties, the algorithm achieves global-level functions through local node interactions; (2) Enabling incremental storage and supporting continuous learning capabilities; (3) Displaying stable memory performance, it surpasses the Hopfield network in memory accuracy, capacity, and diversity, as demonstrated in experimental comparisons. Moreover, it maintains high memory performance with large-scale datasets; (4) Exhibiting a degree of generalization ability, the algorithm's macroscopic performance remains unaffected by the topological structure of the directed graph. Large-scale, decentralized, and node-autonomous directed graphs are suitable simulation methods. Examining storage problems within directed graphs can reveal the essence of phenomena and uncover fundamental storage rules hidden within complex neuronal mechanisms, such as synaptic plasticity, ion channels, neurotransmitters, and electrochemical activities.

Cognitive impairment analysis of public health emergencies from cognitive psychology perspective

BackgroundPublic health emergencies (such as epidemics, natural disasters and chemical accidents) have aroused widespread concern in society, threatening physical health and affecting mental health and cognitive function. Despite concerns about these effects, the cognitive impairment of the masses during such events remains unclear. Cognitive psychology studies individual thinking, perception, learning, etc., and provides a useful framework for analyzing the impact of emergencies on mass cognitive function.Subjects and MethodsThe Stanford Acute Stress Response Questionnaire (SASRQ) and 3-minute Disorder Assessment Scale (3D-CAM) were used to study the effects of emergency events on cognitive function. 500 participants were randomly selected and divided into an exposed group and a non-exposed group. The exposed group received cognitive tests after the event, while the non-exposed group was tested at the same time as the control group.ResultsThe SASRQ scores of the emergency exposure group showed a significant increase in cognitive stress (P<0.05). The cognitive confusion in the exposed group was significantly higher than that in the non-exposed group (P<0.01). SPSS23.0 statistical analysis confirmed the significance of these differences.ConclusionsStudies have shown that public health emergencies can negatively impact cognitive function in the population, including increased cognitive stress and confusion. This highlights the importance of cognitive psychology in understanding and responding to the impact of unexpected events on individual cognition. In the future, more attention should be paid to the psychological cognitive state of the masses to better meet the challenges of public health emergencies.

How to Run Behavioural Experiments Online: Best Practice Suggestions for Cognitive Psychology and Neuroscience

The combination of a replication crisis, the global COVID-19 pandemic in 2020, and recent technological advances, have accelerated the on-going transition of research in cognitive psychology and neuroscience to the online realm. When participants cannot be tested in-person, data of acceptable quality can still be collected online. While online research offers many advantages, numerous pitfalls may hinder researchers in addressing their questions appropriately, potentially resulting in unusable data and misleading conclusions. Here, we present an overview of the costs and benefits of conducting online studies in cognitive psychology and neuroscience, coupled with detailed best practice suggestions that span the range from initial study design to the final interpretation of data. These suggestions offer a critical look at issues regarding recruitment of typical and (sub)clinical samples, their comparison, and the importance of context-dependency in each part of a study. We illustrate our suggestions by means of a fictional online study, applicable to traditional paradigms such as research on working memory with a control and treatment group.

Humanitarian crises in Sadat Hassan Mantos works

This article examines at how memories and the humanitarian situation are connected in the context of the 1947 India-Pakistan Partition as it is portrayed in Sadat Hassan Manto’s short stories. It will look at the ways in which Manto’s fiction captures the anguish of physical and existential displacement brought on by the birth of two states following a campaign of political and epistemological violence and remapping. The study will pay particular attention to the relationship between memory and insanity in addition to the more general concerns of nation-formation, alienation, and loss. The Partition trauma of 1947 will be examined as a psychological and existential crisis that commonly showed up as insanity, aphasia, and forgetfulness. By referencing trauma studies, phenomenology, and cognitive psychological studies in episodic memory, unreliable narration, and cognition, the paper will explore the human condition of shock and loss with an emphasis on the formal aspects of Manto’s short fiction.

PARA UMA APROXIMAÇÃO ENTRE A SOCIOLOGIA DO CONHECIMENTO E A PSICOLOGIA COGNITIVA

Abstract This social theory essay prospects for pathways for bringing together two seemingly unrelated traditions of thought: the sociology of knowledge and cognitive psychology. Such an endeavor is pursued at two different levels. First, I lay out three general assumptions underlying the sociology of knowledge, as conceived by several authors from Karl Mannheim onwards, examining whether and to what extent they are compatible with contemporary cognitive psychology studies, especially in heuristics and biases research program. Second, I bring under the same roof some of Georg Simmel’s ideas about the cognitive assumptions that render social life possible and some contemporary findings on heuristics and biases by connecting a thought experiment built upon Simmel’s ideas to a set of real-life experiments conducted in cognitive psychology.

DeepEmotionNet: Emotion mining for corporate performance analysis and prediction

Since previous studies in cognitive psychology show that individuals’ affective states can help analyze and predict their future behaviors, researchers have explored emotion mining for predicting online activities, firm profitability, and so on. Existing emotion mining methods are divided into two categories: feature-based approaches that rely on handcrafted annotations and deep learning-based methods that thrive on computational resources and big data. However, neither category can effectively detect emotional expressions captured in text (e.g., social media postings). In addition, the utilization of these methods in downstream explanatory and predictive applications is also rare. To fill the aforementioned research gaps, we develop a novel deep learning-based emotion detector named DeepEmotionNet that can simultaneously leverage contextual, syntactic, semantic, and document-level features and lexicon-based linguistic knowledge to bootstrap the overall emotion detection performance. Based on three emotion detection benchmark corpora, our experimental results confirm that DeepEmotionNet outperforms state-of-the-art baseline methods by 4.9% to 29.8% in macro-averaged F-score. For the downstream application of DeepEmotionNet to a real-world financial application, our econometric analysis highlights that top executives’ emotions of fear and anger embedded in their social media postings are significantly associated with corporate financial performance. Furthermore, these two emotions can significantly improve the predictive power of corporate financial performance when compared to sentiments. To the best of our knowledge, this is the first study to develop a deep learning-based emotion detection method and successfully apply it to enhance corporate performance prediction.

Analysis of group behavior based on sharing heterogeneous roles in a triad using a coordinated drawing task.

Humans often share roles and aim to achieve a group goal based on sociality, which is the tendency to spontaneously involve oneself with others. Cognitive science, psychology, and neuroscience studies suggest that in such planned coordination, adjusting one's own actions based on other roles is crucial for high task performance. However, the mechanisms of complex and dynamically planned coordination, such as non-verbal group behavior with three or more members, remain to be fully investigated. This study introduced a coordinated drawing task in a triad, quantitatively analyzed non-verbal group behavior based on sharing heterogeneous roles, and investigated an important role. Participant triads engaged in the task repeatedly by operating reels to change thread tensions and moving a pen connected to the three threads to draw an equilateral triangle. Then, the three roles (pulling, relaxing, and adjusting) had to be shared. The pulling and relaxing roles served to move the pen as if an operator pulled it closer to the hand and to support the pen's movement, respectively. However, these roles alone could not draw a side considering the task specification. The adjusting role needed to change the tension flexibly and maintain an overall balance. In the experiment, we measured the pen positions and tensions, and established statistical models to fit the analyzed data. The results estimated that the action in the adjusting role was related to the improved performance of faster drawing on a side. This role may moderately intervene in the actions by the other roles and fine-tune without disturbing the pen's smooth movement while avoiding great pen deviation. Our findings may suggest the crucial role as a facilitator that handles resiliently in non-verbal coordinated behavior of a triad, and contribute to our understanding of social interactions.

Взаимосвязь предикторов иррационального поведения с индивидуально-типологическими и личностными особенностями

A number of studies in cognitive psychology indicate that human behavior is largely governed by irrational factors (heuristics, cognitive biases, attitudes). These factors influence vital decisions, which can subsequently affect a person’s life and behavior in a broad temporal perspective. There is a lack of research on identifying the individual-typological and personal characteristics that make the irrational behavior more likely to occur. Our research is aimed at revealing the interrelation of predictors of irrational behavior (superstitiousness, “prelogical” defense, unconstructive, categorical, personally superstitious and esoteric thinking, naive optimism), individual-typological and personality characteristics of respondents. We used I. R. Abitov’s questionnaire, J. Tobacyk’s Paranormal Belief Scale adapted by D. S. Grigoriev, I. Y. Stoyanova’s Beliefs and Superstitions Questionnaire, and S. Epstein’s Constructive Thinking Inventory (adapted by S. N. Enikolopov and S. V. Lebedev) to reveal the expression of irrational behavior predictors. The individual-typological characteristics were identified using the Temperament Accentuation Test and the Individual-Typological Questionnaire, while the personal characteristics were identified using the G. V. Zalewski Psychological Rigidity Questionnaire and the C. Scheyer and M. Carver Test for Optimism. It was found that a decrease in the constructive thinking is associated with the expression of such characteristics as shyness, aggression, neuroticism (anxiety), sensitivity to external influences, various manifestations of rigidity, emotional instability and pessimism. It was also found that the expression of these characteristics, as well as pessimism and aversion to changes in self-esteem and personal position, is associated with a tendency to show categorical (“black and white”) thinking. Naive optimism is more often shown by respondents with such characteristics as hyperthymia and increased social activity. The relationship of personality-superstitious thinking with pessimism, fear of new situations, shyness, neuroticism (anxiety), and a tendency to exaggerate one’s difficulties were found. The novelty of our study lies in the discovery of complexes of characteristics that can increase the likelihood of irrational behavior. Reviewing the literature on the topic of the research, we did not find any works made in the mainstream of such an approach. The complexes of individual-typological and personal characteristics revealed in the given research can be considered as “targets” of psychological correction and prevention to decrease the risk of socially dangerous behavior.

인간의 인지 체계를 기반으로 한 문장 이해

This study attempted to clarify what sentences are based on an understanding of the human cognitive system. Until now, there has been a widespread understanding of whether sentences represent events in the real world or propositions that have truth-value. However, based on recent studies of cognitive psychology, brain science, and consciousness science, Sentence(utterance) is neither an event nor a proposition. An organism compares, analyzes and judges real-time sensory data input or declarative memory in the prefrontal lobe, the working memory area. Sentence is an output of such a process of speculation, inference, prediction and evaluation on the world. In order to derive these results, this paper theoretically reviewed and synthesized the achievements of brain science, consciousness science, and cognitive science so far to establish a cognitive model, and explained what sentences are based on this cognitive model.

Information source and content: articulating two key concepts for information evaluation

PurposeLearning 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/approachThis 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.FindingsThe 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/valueBy 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.

From embodiment to emplacement: Toward understanding occupation as body-mind-environment

ABSTRACT Participation in occupation is an integrated and holistic mind/body experience. However, research and theory development on human action and occupational participation tend to be limited by mind/body dualisms which separate the mind from the body when studying and conceptualizing human action. The ontological supremacy of the mind over the body has led to obfuscation of the body’s role in occupation. The purpose of this paper is to provide a broad overview of contemporary research on embodiment and to highlight the importance of the body in the performance of meaningful occupation. We present various perspectives and conceptual framings of embodiment using research from disciplines such as occupational science, cognitive psychology, anthropology, neuroscience, social psychology, developmental psychology, humanistic geography, and performance studies. Due to the expansive and varied literature on embodiment, we do not attempt to summarize or synthesize disciplinary perspectives; rather, we aim to highlight different perspectives within and across different disciplines. We also present examples of various research methods for studying embodiment and occupation. Additionally, we discuss implications for how sensory processing has been conceptualized in occupational science and occupational therapy and its relation to embodiment. Our aim is to encourage occupational scientists to further incorporate research methods that attend to the body’s role in studies on occupation and to encourage scientists and practitioners to re-think widely accepted assumptions regarding sensory processing and mind/body dualisms.

Results of studies in cognitive neuroscience, psycholo-gy, and medicine. A proposal to verify the robustness of the analysis, and hypotheses

El p-value es el análisis estadístico más utilizado para comprobar hipótesis en áreas de la salud, sin embargo, su uso único presenta desventajas que afectan los estudios por depender del tamaño de la muestra y necesitar una distribución normal. Esto obliga a buscar formas más flexibles y válidas para comprobar hipótesis. Por ello nuestro objetivo fue recopilar procedimientos estadísticos complementarios sensibles para muestras típicamente clínicas. Elegimos el tamaño del efecto y la inferencia bayesiana. Ambos presentan una correlación entre ellas y con el p-value, permitiendo disminuir la incertidumbre al comprobar supuestos. El primero es un método cuantitativo para entender el grado en que un fenómeno está presente en un grupo de estudio, donde se deben observar los valores específicos de cada rama científica, sus características y la estabilidad de variables. Cuenta también con maneras de mejorar su interpretación y cálculos para medidas no paramétricas. El segundo utiliza valores ? para una mayor precisión interpretativa y toma de decisiones, sustentando la H0 con un ? a priori y a posteriori. Proponemos que el grado de certidumbre del FB se base en literatura previa y valores ? reportados, añadiendo el apartado de intervalos de credibilidad en la tabla de mediciones generales, así como incluirse las hipótesis sometidas a prueba y mostrar las evidencias a favor de H0 y H1. Concluimos que la implementación las propuestas presentadas como complemento de la estadística frecuentista apoyará la interpretación de hipótesis, con mayor fuerza estadística y mejor toma de decisiones. Sugerimos integrarlas en la revisión académica o de cursos, la realización convenciones para su uso adecuado y la revisión de previos estudios donde puedan ser integradas dando una mejor interpretación de resultados.