Behaviour Sequence Analysis Research Articles

Advancing a Practical Inquiry Model with Multi-Perspective Role-Playing to Foster Critical Thinking Behavior in e-book Reading

In the digital age, where media proliferation challenges traditional reading habits, this study investigated the impact of digital platforms on critical thinking (CT) and reading practices. Some conventional e-books may not sufficiently encourage reflective thinking or foster CT skills due to their linear nature and lack of engaging elements. Employing the Practical Inquiry Model (PIM) within the Community of Inquiry (CoI) framework, this study highlights the integration of multimedia elements and the use of students' selfies to boost engagement and social presence in a digital learning environment. This study introduced selfie role-playing reading, along with group discussions from various perspectives as an innovative pedagogy to enhance cognitive presence within the CoI, ultimately enhancing learners’ CT performance. Using a quasi-experimental design, 63 participants were grouped into single-perspective or multiple-perspective categories by narrative perspective exposure, and then engaged in online story discussions with worksheets. Reading performance was measured through a detailed examination of their CT patterns via behavioral sequential analysis. Results revealed that students in the multi-perspective groups demonstrated superior CT and reflective thinking levels, underscoring the potential of innovative e-book designs in enhancing CT. This study not only validates the importance of diverse narratives and role-playing in CT development, but also pioneers a method for analyzing such skills through behavioral sequence analysis. It signifies a leap in applying the PIM to multimedia e-book reading, offering insights for future educational strategies and CT assessment in the digital era.

The prince of insiders: a multiple pathway approach to understanding IP theft insider attacks

Purpose Intellectual property (IP) theft is an increasing threat that can lead to large financial losses and reputational harm. These attacks are typically noticed only after the IP is stolen, which is usually too late. This paper aims to investigate the psychological profile and the socio-technical events that statistically predict the likelihood of an IP threat. Design/methodology/approach This paper analyses 86 IP theft cases found in court documents. Two novel analyses are conducted. The research uses LLMs to analyse the personality of these insiders, which is followed by an investigation of the pathways to the attack using behaviour sequence analysis (BSA). Findings These IP theft insiders scored significantly higher on measures of Machiavellianism compared to the normal population. Socio-technical variables, including IP theft via photographs, travelling overseas, approaching multiple organisations and delivering presentations, were identified. Contrary to previous assumptions that there is a single pathway to an attack, the authors found that multiple, complex pathways lead to an attack (sometimes multiple attacks). This work, therefore, provides a new framework for considering critical pathways to insider attacks. Practical implications These findings reveal that IP theft insiders may come across as charming, star employees rather than the stereotype of disgruntled employees. Moreover, organisations’ policies may need to consider that IP theft occurs via non-linear and multiple pathways. This means that sequences of events need to be considered in detecting these attacks instead of anomalies outright. The authors also argue that there may be a case for “continuous evaluation” to detect insider activity. Originality/value This paper offers a new framework for understanding and studying insider threats. Instead of a single critical pathway, this work demonstrates the need to consider multiple interconnected pathways. It elucidates the importance of a multidisciplinary approach and provides opportunities to reconsider current practices in detection and prevention.

A Comparative Study driven by Spatial Performance and VR toward Wayfinding in Architectural Space: Healthcare Buildings as a Case Study

Healthcare buildings can be complicated to navigate, causing patients to experience stress and lose time if not adequately planned. This study aims to identify the relationship between the spatial layout in healthcare buildings and wayfinding for users, by utilizing Behavioral Sequence Analysis (BSA) and Space Syntax through Immersive Virtual Reality (iVR). The methodology is based on behavioral and spatial data and was tested by using the experimental setups in VR environments. Space syntax analysis is applied to collect spatial data. Experiments were conducted by assigning wayfinding tasks in virtual hospitals with various plan configurations. Behavioral data obtained from BSA was associated with the spatial data driven by the space syntax analysis to gain a comprehensive understanding of the participants’ wayfinding behavior. The results indicate that the semi-centralized floor plan layout with high visibility levels performs better in wayfinding while the decentralized layout with low visibility values performs worse.

Analysis of the Construction and Course Effectiveness of the Online Course Platform for College Piano in the Background of the Internet

Abstract Internet technology continues to develop and deepen, course learning methods present diversity, and piano courses are an important way for colleges and universities to carry out students’ musical quality training. In this paper, we first propose a behavioral sequence analysis method for predicting students’ online course performance in the context of the Internet for college piano online courses. The sequence-based prediction task is divided into two stages in total. In the first stage, the sequence characteristics of students’ online course learning behaviors are predicted by mining the potential expressions of the implicit layer through deep RNN. In the second stage, the support vector machine is used to create an optimal segmentation hyperplane. The SPC two-stage classifier is able to predict student course grades in order to identify students with learning crises in time. Then a layered MVC model is used to design the university piano online course platform system. Finally, the performance of the platform and the effectiveness of the course were tested. When the number of concurrent users reached 150, the success rate of the server in processing transactions remained at about 96%, and the pre-test and post-test of students’ piano scores showed that the mean value of score-reading skills was 34.32 in the pre-test and 45.63 in the post-test, with a mean value improvement of 11.31. The study showed that the online course client had high operational performance and the online course could effectively the study shows that the online lesson client has high performance and the online lessons is effective in improving the students’ piano performance.

Sequencing statements: using behaviour sequence analysis with statement analysis to indicate deception

PurposeUnderstanding when an individual is being deceptive is an important part of police and criminal investigations. While investigators have developed multiple methods, the research literature has yet to fully explore some of the newer applied techniques. This study aims to investigate statement analysis, a recent approach in forensic linguistic analysis that has been applied to criminal investigations.Design/methodology/approachReal-world statements of individuals exposed as deceptive or truthful were used in the analyses. A behaviour sequence analysis approach is used to provide a timeline analysis of the individuals’ statements.FindingsResults indicate that sequential patterns are different in deceptive statements compared to truthful statements. For example, deceptive statements were more likely to include vague words and temporal lacunas, to convince investigators into believing that the suspect was not present when the crime occurred. The sample in this research did not use one deceptive indicator, instead, electing to frequently change the order of deceptive indicators. Gaps in deception were also noted, and there was common repetition found in both the deceptive and truthful statements. While gaps are predicted to occur in truthful statements to reflect an absence of deception, gaps occurring in the deceptive statements are likely due to cognitive load.Originality/valueThe current research provides more support for using statement analysis in real-world criminal cases.

Describing Behavior Sequences of Fattening Pigs Using Process Mining on Video Data and Automated Pig Behavior Recognition

This study aimed to demonstrate the application of process mining on video data of pigs, facilitating the analysis of behavioral patterns. Video data were collected over a period of 5 days from a pig pen in a mechanically ventilated barn and used for analysis. The approach in this study relies on a series of individual steps to allow process mining on this data set. These steps include object detection and tracking, spatiotemporal activity recognition in video data, and process model analysis. Each step gives insights into pig behavior at different time points and locations within the pen, offering increasing levels of detail to describe typical pig behavior up to process models reflecting different behavior sequences for clustered datasets. Our data-driven approach proves suitable for the comprehensive analysis of behavioral sequences in conventional pig farming.

Prevalence scores: an addition to behaviour sequence analysis

PurposeBehaviours occur across complex, dynamic timelines. Research methods to analyse these complex timelines have repeatedly used behaviour sequence analysis (BSA) as a primary method. Traditional BSA outputs, however, are limited in that they do not show how prevalent a behaviour sequence is throughout a sample or group. Until now, how many people in a sample showed the sequence was not analysed and reported. This paper aims to provide a new metric to calculate prevalence scores in BSA data sets.Design/methodology/approachOpen access recorded responses including nonverbal communication of deceptive and truthful individuals were analysed initially with a standard BSA approach and then the prevalence scores of transitions were calculated.FindingsPrevalence scores offered new insights into the distribution of sequences across groups. The prevalence score showed differences in which transitions were seen across the truthful and guilty samples. This offers new approaches to analysing nonverbal communication.Originality/valueThis is the first paper to provide a prevalence score for BSA research and show how it can be used in applied research. The current prevalence score metric is provided and suggested for all future research into sequences.

Using Behavior Sequence Analysis to Study Teams During Long- Duration Isolation and Confinement

Using Behavior Sequence Analysis to Study Teams During Long- Duration Isolation and Confinement

A Behavioral Sequence Analysis of Mass School Shooters Examining Stressors, Antisocial Behaviors, Mental Health Issues, and Planning and Preparation Activities

ABSTRACT This study examines all completed mass school shooting offenders (1966–2021) using a behavioral sequence analysis of their stressors, antisocial behaviors, mental health issues, and planning/preparation activities. We also conduct isolated analyses of K-12 and college shooters. Findings illustrate a multitude of factors along the sequence from birth to attack for all offenders, with several differences between K-12 and college shooters. We highlight key behaviors and experiences that may warrant increased vigilance by bystanders and offer potential points of intervention for authorities. Ultimately, this study’s findings enable an understanding of the culmination of lived experiences that contribute to the decision to engage in an attack, and we point to directions for future research examining mass school shooters’ pathways to violence.

Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication

Over the last 40-50 years, ethology has become increasingly quantitative and computational. However, when analysing animal behavioural sequences, researchers often need help finding an adequate model to assess certain characteristics of these sequences while using a relatively small number of parameters. In this review, I demonstrate that the information theory approaches based on Shannon entropy and Kolmogorov complexity can furnish effective tools to analyse and compare animal natural behaviours. In addition to a comparative analysis of stereotypic behavioural sequences, information theory can provide ideas for particular experiments on sophisticated animal communications. In particular, it has made it possible to discover the existence of a developed symbolic "language" in leader-scouting ant species based on the ability of these ants to transfer abstract information about remote events.

Finding the missing: using statement analysis to assist in missing persons cases

PurposeThe purpose of this paper is to address the complexity of missing persons cases and highlight the linguistic differences that arise in this type of crime. Missing persons cases are typically very complex investigations. Without a body, crime scene forensics is not possible, and police are often left only with witness and suspect statements. Forensic linguistics methods may help investigators to prioritise or remove suspects. There are many competing approaches in forensic linguistic analysis; however, there is limited empirical research available on emerging methods.Design/methodology/approachThis research investigates Statement Analysis, a recent development in linguistic analysis that has practical applications in criminal investigations. Real-world statements of individuals convicted of or found to be not guilty of their involvement in missing persons cases were used in the analyses. In addition, Behaviour Sequence Analysis was used to map the progressions of language in the suspects' statements.FindingsResults indicated differences between the guilty and innocent individuals based on their language choices, for example, guilty suspects in missing [alive] cases were found more likely to use passive language and vague words because of high levels of cognitive load associated with the several types of guilty knowledge suspects in missing persons cases possess. Of particular interest is the use of untruthful words in the innocent suspects’ statements in missing [murdered] cases. While typically seen in deceptive statements, untruthful words in innocent statements may result because of false acquittals.Originality/valueThis research provides some support for Statement Analysis as a suitable approach to analysing linguistic statements in missing persons cases.

Pathways to truth: using criteria-based content analysis in missing person cases

PurposeWhen investigating missing persons cases, witness and suspect statements are often the only available evidence to investigators. As such, forensic linguistics can be useful to police when seeking information from individuals during investigative interviews. The presumption of innocence must be maintained in an investigation, and therefore this study aims to use a method focused on veracity detection, rather than the majority of studies using deception detection approaches.Design/methodology/approachThe current research uses criteria-based content analysis (CBCA), a method that has been applied to a variety of criminal cases. Real-world statements of individuals convicted or found innocent of their involvement in missing persons cases were used in the analyses. Additionally, behaviour sequence analysis (BSA) was used to map language patterns within individuals’ statements.FindingsResults indicated that two individual markers occurred at a high frequency across all four groups (the guilty and innocent statements of both case types); however, differences were noted in the sequences based on an individual’s ability to provide experiential details.Research limitations/implicationsThe current research contributes to the growing literature that aims to test CBCA in adult samples across crimes that do not pertain to sexual abuse, in addition to aiding researchers and practitioners to understand better the linguistic differences that occur in missing persons cases.Originality/valueTo the best of the authors’ knowledge, this type of research, using CBCA to assist with missing person's cases with a temporal method (BSA), has never before been tested. BSA has previously been used in forensic linguistics, and shown support for the method. The current research builds on this in terms of missing persons cases.

Prediction of College Students' Classroom Learning Effect Considering Positive Learning Emotion

Exploring the influence of positive learning emotion on college students' classroom learning effect facilitates fully understanding college students' online learning effect and emotional state, and is beneficial to improving students' learning quality and teachers' teaching quality. At present, few scholars have summative evaluation of students' classroom learning effect from the perspective of students' learning emotions and prove from the perspective of theory and practice that good emotional state is an important influencing factor to improve college students' classroom learning effect. Therefore, this article fully considers the positive learning emotion, and makes a research on the prediction of college students' classroom learning effect. Firstly, this article defines the behavior data of students in the online learning process based on learning emotions, and studies the correlation between college students' classroom learning behaviors based on Hawkes process. Then, based on the learning participation under the influence of different learning emotions, the online learning effect of students is quantified, and the prediction model of students' classroom learning is constructed by combining the learning behavior sequence analysis results represented by Hawkes process and the characteristic information of students themselves and courses. The experimental results verify the effectiveness of the model, and the significance test results confirm the positive effect of positive emotion on learning effect.

Effects of Physical Properties of Konjac Glucomannan on Appetite Response of Rats

Dietary fiber has been widely used in designing foods with a high satiating capacity, as the use of satiety-enhancing food is considered to be a promising strategy for combating obesity and the overweight condition. In the present study, partially degraded konjac glucomannan (DKGM) diets with different water-holding capacities, swelling capacities, and viscosities were used to feed rats to investigate the effects of the fiber's physical properties in regulating the appetite response of the animals. The results showed that the mass and water content of the gastrointestinal chyme increased as the diet's physical properties were enhanced by the DKGM, which increased the stomach distention of the rats and promoted satiation. Besides, the hydrated DKGM elevated the chyme's viscosity, and the retention time of the digesta in the small intestine was prolonged significantly, which resulted in an increased concentration of cholecystokinin-8, glucagon-like peptide 1, and peptide tyrosine-tyrosine in the plasma, thus helping to maintain the satiety of rats. Furthermore, the results of the behavioral satiety sequence and meal pattern analysis showed that DKGM in the diets is more likely to reduce the food intake of rats by enhancing satiety rather than satiation, and will finally inhibit excessive weight gain. In conclusion, the physical properties of dietary fiber are highly related to the appetite response, which is a powerful tool in designing food with a high satiating capacity.

Theoretical Development of Connectivism through Innovative Application in China

As a learning theory that reveals a new learning in the Internet environment, connectivism has become a popular academic topic at the forefront of online learning. The MOOC Research Team at the Distance Education Research Centre at Beijing Normal University designed and developed the first massive open online course, adapting a connectivist (cMOOC) approach in China. Using the data collected from six offerings of the cMOOC over 3 years, the big data paradigm was used for data analysis including complex network analysis, content analysis, text mining, behaviour sequence analysis, epistemic network analysis, and statistical and econometric models. This paper summarizes the findings of the patterns of connectivist learning, including a) the basic characteristics and evolutional patterns of complex networks, b) the characteristics and modes of knowledge production, c) the patterns of instructional interactions, and d) the relationships between pipe and content and between facilitators and learners. It is expected that the outcome of this study could make contributions to understanding the changes of online learning in depth and further promote the theoretical development and practical application of a connectivist approach.

The influence of pups on aggressive interactions between smooth-coated otters and water monitor lizards in Singapore.

Smooth-coated otters (Lutrogale perspicillata) and Malayan water monitor lizards (Varanus salvator) occupy similar habitats and interact regularly in Singapore's waterways. These interactions have a range of potential outcomes and are sometimes lethal. Few formal behavioral studies exist for either species. We analyzed interactions between otters and monitor lizards by gleaning data from publicly available videos from citizen scientists to examine what factors influence aggressive and defensive behaviors and what influences vigilance in otters. Behavioral sequence analysis revealed no obvious monitor lizard behavior that predicted otter aggression toward monitors. We found that the presence and number of otter pups are positively associated with otter aggression. Otters also tended to be more vigilant in groups with more pups and more vigilant on land than water. Monitor lizards almost always displayed aggressive and defensive behaviors, regardless of whether otters were aggressive toward the lizards. These observations suggest that otters vary their aggression and vigilance levels depending on their group composition and the physical environment of their interactions with monitor lizards.

Risk factors for momentary loss of control and subsequent abandonment of self-devised dietary restraint plans in adults with weight-loss goals: a behaviour sequence analysis approach

Objective The current study aims to improve understanding of events leading to lapses of dietary restraint, and to identify pathways to perseverance or abandonment of weight loss efforts in response to lapses. In addition, Behaviour Sequence Analysis (BSA) was also evaluated as an analytical tool in dietary behaviour. Design A sample of 176 adults who were engaging in self-imposed dietary restraint for weight loss were recruited to participate. Main outcome measures Participants were instructed to provide a detailed written timeline of an episode where they lapsed in their dietary restraint plan. They were instructed to report their preceding behaviours and internal states, and social and environmental contexts, leading up to and after their lapse in dietary restraint. Results Lapses in dietary restraint were precipitated by negative internal states in the presence of cues for highly palatable foods. In addition, abandonment of weight loss efforts after lapsing was preceded by dichotomous thinking, whereas perseverance was preceded by a more neutral, flexible interpretation of the lapse in self-control. Conclusion BSA has identified that neutral evaluation of inevitable lapses in dietary restraint are predictive of continuation with weight loss efforts, highlighting the importance of individual tolerance of lapses in self-regulation.

Application of Visitor Eye Movement Information to Museum Exhibit Analysis

The motivation of this study is that after the COVID-19 epidemic, museum exhibition visits have also been significantly affected. The purpose of this research is to better understand the visual cognition of visitors, so as to improve the application of physical field or online exhibitions. Currently, no research is available on the differences in the visitor’s viewing and cognitive process with eye movements sequence analysis that stem from the exhibition planning and design of different museums. This study tracks and analyzes the eye movement trajectories of visitors and studies its relation to learning and cognition and finds the key to influencing cognition through behavioral sequence analysis of displayed content. The results show that those interested in the displayed content have better cognitive performance, are immersed in reading text, and have a substantial shift in eye movement. Contrarily, those not interested in the displayed content are distracted and often turn their attention back to the title of the content. In this study, eye movement and fixation are indicators that can be used as a reference for the future design of displays to improve the effectiveness of presenting information to a visitor. Furthermore, this research can also provide future applications in integrating the virtual world and cognitive information, in the application of AR, VR, or metaverse environment, to provide people’s cognition of rapid information in the virtual environment.

Studies of the Behavioral Sequences: The Neuroethological Morphology Concept Crossing Ethology and Functional Morphology.

Simple SummaryBehavioral sequences analysis is a relevant method for quantifying the behavioral repertoire of animals to respond to the classical Tinbergen’s four questions. Research in ethology and functional morphology intercepts at the level of analysis of behaviors through the recording and interpretation of data from of movement sequence studies with various types of imaging and sensor systems. We propose the concept of Neuroethological morphology to build a holistic framework for understanding animal behavior. This concept integrates ethology (including behavioral ecology and neuroethology) with functional morphology (including biomechanics and physics) to provide a heuristic approach in behavioral biology.Postures and movements have been one of the major modes of human expression for understanding and depicting organisms in their environment. In ethology, behavioral sequence analysis is a relevant method to describe animal behavior and to answer Tinbergen’s four questions testing the causes of development, mechanism, adaptation, and evolution of behaviors. In functional morphology (and in biomechanics), the analysis of behavioral sequences establishes the motor pattern and opens the discussion on the links between “form” and “function”. We propose here the concept of neuroethological morphology in order to build a holistic framework for understanding animal behavior. This concept integrates ethology with functional morphology, and physics. Over the past hundred years, parallel developments in both disciplines have been rooted in the study of the sequential organization of animal behavior. This concept allows for testing genetic, epigenetic, and evo-devo predictions of phenotypic traits between structures, performances, behavior, and fitness in response to environmental constraints. Based on a review of the literature, we illustrate this concept with two behavioral cases: (i) capture behavior in squamates, and (ii) the ritualistic throat display in lizards.

The influence of social network prestige on in-service teachers’ learning outcomes in online peer assessment

• Social network prestige is used to measure the participation gap, a detailed description and impact analysis was conducted. • Prestige has a significant effect on learning performance, social network structure and learning behavior. • Differences in social network structure and learning behavior were important reasons for the differences in learning performance. • Effective suggestions for reducing the participation gap are proposed. Online peer assessment has been widely applied in online teacher training. However, not all learners participate equally, detailed characterization and impact analysis of peer assessment is required. This study draws on a sociological term, social network prestige, to evaluate the participation gap of learners in online peer assessment. A teacher training course was offered to in-service primary and secondary school teachers, and 457 participants were ranked according to their prestige. Then, the top 30% of learners were considered the high-prestige group (142 participants) and the bottom 30% as the low-prestige group (128 participants). Social network analysis and behavioral sequence analysis were used to explore the differences in the learning outcomes of these two groups. The results showed significant differences in learning performance, social network structure and learning behaviors among learners with different prestige. High-prestige learners have better learning performance and are affected by their prior knowledge. Learners with different levels of prestige differ in social network structure and learning behavior. Based on these findings, this study suggests improvements to reduce the participation gap.