Typical Interaction Patterns Research Articles

A double-edged sword: diverse interactions in hypergraphs

Abstract Interaction diversity and interaction identity, as two classic interaction patterns in real-world systems, are frequently employed to probe into the cooperative dilemmas among participants with diverse interaction identities within groups. Considering the influence of factors such as hyperlink configurations on the evolution of cooperation within complex networks, this study particularly focuses on the organic integration of hypergraphs and diverse interaction modes. Employing the public goods game model in uniformly stochastic hypergraphs, we explore the effects of synergy factors and diverse interacting individuals on the cooperation rate and strategy consistency within hyperlinks. We emphasize that the diverse interacting individuals are a double-edged sword, and the controlled number of such individuals is conducive to the evolution of cooperation. The findings of this study reveal the significance of these two typical interaction patterns and provide valuable insights for coordinating them to achieve social optimality in cooperation.

The role of multidisciplinary collaborations in publishing innovation

Product innovation is crucial for the future of the publishing industry, and the objective of this study was to understand the role of multi-disciplinarity in publishing innovation teams, typical patterns of interaction between team members, and similarities and differences in multidisciplinary innovation teams across national boundaries (US, Canada, and Germany). This is an exploratory study from Portland State University, Stuttgart Media University and Toronto Metropolitan University based on twenty-one qualitative in-depth interviews with publishing employees involved in the innovation process. The study reveals that multidisciplinary innovation teams are common in all three countries. Using an input-process-output (IPO) model, researchers found three main things: 1) input from outside the company is helpful; 2) corporate culture, familiarity and psychological safety foster creativity during the innovation process; and 3) innovation output is often evaluated by low-cost prototypes presented to the target audience.

EFL Classroom Interaction through Contextual Teaching and Learning: A Qualitative Study

Contextual teaching and learning (CTL) and classroom interaction are closely intertwined and have a significant influence on each other. The latter enables students to ask questions, seek clarifications, and receive immediate feedback. This qualitative research aimed to explore classroom interaction and the various patterns of interaction among students in an English as a Foreign Language (EFL) class using CTL as the teaching approach. Data were collected through observations, video recordings, and questionnaires, which were then analyzed using a series of stages, namely data reduction, data display, categorization, and drawing conclusion. The findings revealed that classroom interaction occurred in three phases: pre, whilst, and post-activities. The study also unveiled three types of interaction patterns, namely clarification requests, mime, and confirmation checks. The percentage of interaction between the teacher and students was 94.28%; between students and the teacher was 82.85%; and between students themselves was 88.57%. The most common interaction patterns were clarification requests (80%), mime (71.42%), and confirmation checks (65.71%). These results indicate that the teacher effectively implemented CTL in the EFL teaching and learning process, fostering active and communicative engagement between the teacher and students. Future researchers are encouraged to explore the implementation of CTL components in classroom interactions within English language teaching activities

An Exploratory Analysis of Transactive Interaction Patterns in Cooperative Learning Using Sequential Analysis

For cooperative learning to be effective, the quality of student–student interaction is crucial. Interactions, which are transactive in nature, are positively related to students’ learning success during cooperative learning. However, little is known about typical interaction patterns during transactive interaction in face-to-face cooperative learning. Therefore, the current study aims to analyze typical interaction patterns of transactive interaction in cooperative learning. Sixty-eight students from seventh to tenth grade were randomly assigned to a total of 23 groups in their classes. The groups were videotaped while solving the same open-ended mathematical modelling task. The interaction behavior was coded, and interaction patterns were analyzed using sequential analysis with first- and second-order Markov chains. The results indicate that the likelihood that students confirm and pick up correct proposals is relatively high, indicating transactive interaction. However, it is almost equally likely that incorrect proposals are confirmed erroneously, as students barely correct them. Still, students do frequently engage in transactive interaction by discussing incorrect proposals, even though these discussions rarely lead to correct solution approaches. Limitations of these results, as well as the practical implications for cooperative learning in classroom settings, are discussed.

Exploring the relationship between interaction patterns and social capital accumulation in connectivist learning

ABSTRACT To inform the relationships among interaction patterns, social capital accumulation, and learning benefits, based on 29,056 log data from a cMOOC (Connectivist Massive Open Online Course) in China, this study examined the difference in social capital accumulation and content production among different interaction patterns using cluster analysis, lag sequence analysis, social network analysis, and the Kruskal–Wallis test. Five types of interaction patterns in connectivist learning were identified: “creative connected participants”, “active connected participants”, “poorly engaged social participants”, “poorly engaged moderate participants”, and “resource investigating participants”. The results demonstrated that participants’ interaction patterns influence their social capital accumulation and content production and that positive interaction engagement would compensate for the disadvantage of participants’ initial position in social capital accumulation. Furthermore, resource access, social interaction, and content release had different roles in the accumulation of social capital. The pattern with higher engagement in all three kinds of interaction activities was associated with better content production because learners accumulated more bonding capital and bridging capital, which would bring them more returns in content creation. This study highlights the connectivist learning mechanism and effectiveness from the social capital perspective and provides valuable insights into the design and support of connectivist learning.

Development of a student engagement score for online undergraduate engineering courses using learning management system interaction data

AbstractAlthough researchers agree that student engagement in online courses is a function of time dedicated to course‐related activities, there is little consensus about the best way to quantify the construct. This study introduces a measure for undergraduate engineering students' engagement in online courses using their interactions with their online course learning management system (LMS). Data from 81 courses offered by three fully online, undergraduate engineering degree programs generated a total of 3848 unique student–course combinations (approximately 2.7 million rows of LMS interaction data), to which we applied a five‐step process to calculate a single score representing student LMS engagement. First, we converted the students' LMS interaction data into a set of natural features representing the time they spent per 3‐day period on various course elements, such as quizzes, assignments, discussion forums, and so forth, and how these times changed across the duration of the course. We then used the natural features to derive 216 relative features describing deviations from typical interaction patterns among students in the same course. Next, we conducted association rule mining on a training portion of the data set to generate rules separately describing the behavior of students who completed the course (completers) and those who chose to drop early (leavers). The rules generated were applied to students from the testing portion of the data set to compute the percentage of unique rules met by completers and leavers. Finally, the mathematical difference between the percentages of completer and leaver rules met by each student was found to be the best measure of student engagement.

Understanding interactions between Automated Road Transport Systems and other road users: A video analysis

If automated vehicles (AVs) are to move efficiently through the traffic environment, there is a need for them to interact and communicate with other road users in a comprehensible and predictable manner. For this reason, an understanding of the interaction requirements of other road users is needed. The current study investigated these requirements through an analysis of 22 h of video footage of the CityMobil2 AV demonstrations in La Rochelle (France) and Trikala (Greece). Manual and automated video-analysis techniques were used to identify typical interaction patterns between AVs and other road users. Results indicate that road infrastructure and road user factors had a major impact on the type of interactions that arose between AVs and other road users. Road infrastructure features such as road width, and the presence or absence of zebra crossings had an impact on road users’ trajectory decisions while approaching an AV. Where possible, pedestrians and cyclists appeared to leave as much space as possible between their trajectories and that of the AV. However, in situations where the infrastructure did not allow for the separation of traffic, risky behaviours were more likely to emerge, with cyclists, in particular, travelling closely alongside the AVs on narrow parts of the road, rather than waiting for the AV to pass. In addition, the types of interaction varied considerably across socio-demographic groups, with females and older users more likely to show cautionary behaviour around the AVs than males, or younger road users. Overall, the results highlight the importance of implementing the correct infrastructure to support the safe introduction of AVs, while also ensuring that the behaviour of the AV matches other road users’ expectations as closely as possible in order to avoid traffic conflicts.

Extending Mixed Embeddedness: Entrepreneurial Figurations of Entrepreneurs with Migrant Origins in Germany

»Eine Erweiterung des Mixed Embeddedness Ansatzes: Unternehmerische Figurationen von Migrantenunternehmen in Deutschland«. Focusing on entrepreneurs with migrant origins, this contribution introduces the concept of entrepreneurial figurations as a theoretical complement to mixed embeddedness. After introducing Elias’ concept of figuration, I explain how figurations can be used to understand migrant entrepreneurship. Using a dataset of 584 entrepreneurs with migrant origins, I show to what extent entrepreneurs of migrant origin build their businesses on co-ethnic interaction and how coethnic economic relations are combined into different figurations. The analysis shows that a majority of entrepreneurs with migrant origins in Germany do not make use of any co-ethnic resources. The discussion points out crucial differences between branches of economic activity and I propose that figurations, understood as typical interaction patterns, could foster the understanding of different types of migrant entrepreneurship. Furthermore, the analysis shows that the figurational approach is a useful complement to mixed embeddedness, which helps to deal with the plethora of phenomena in migrant entrepreneurship.

Interaction patterns of trauma providers are associated with length of stay.

Trauma-related hospitalizations drive a high percentage of health care expenditure and inpatient resource consumption, which is directly related to length of stay (LOS). Robust and reliable interactions among health care employees can reduce LOS. However, there is little known about whether certain patterns of interactions exist and how they relate to LOS and its variability. The objective of this study is to learn interaction patterns and quantify the relationship to LOS within a mature trauma system and long-standing electronic medical record (EMR). We adapted a spectral co-clustering methodology to infer the interaction patterns of health care employees based on the EMR of 5588 hospitalized adult trauma survivors. The relationship between interaction patterns and LOS was assessed via a negative binomial regression model. We further assessed the influence of potential confounders by age, number of health care encounters to date, number of access action types care providers committed to patient EMRs, month of admission, phenome-wide association study codes, procedure codes, and insurance status. Three types of interaction patterns were discovered. The first pattern exhibited the most collaboration between employees and was associated with the shortest LOS. Compared to this pattern, LOS for the second and third patterns was 0.61 days (P = 0.014) and 0.43 days (P = 0.037) longer, respectively. Although the 3 interaction patterns dealt with different numbers of patients in each admission month, our results suggest that care was provided for similar patients. The results of this study indicate there is an association between LOS and the extent to which health care employees interact in the care of an injured patient. The findings further suggest that there is merit in ascertaining the content of these interactions and the factors that induce these differences in interaction patterns within a trauma system.

Evolution of cooperation with interactive identity and diversity

Interactive identity and interactive diversity are generally regarded as two typical interaction patterns in living systems. The former describes that in each generation every individual behaves identically to all of its opponents, and the latter allows each individual to behave diversely to its distinct opponents. Most traditional research on the evolution of cooperation, however, has been confined to populations with a uniform interaction pattern. Here we study the cooperation conundrum in a diverse population comprising players with interactive identity and with interactive diversity. We find that in homogeneous networks a small fraction of players taking interactive diversity are enough to stabilize cooperation for a wide range of payoff values even in a noisy environment. When assigned to heterogeneous networks, players in high-degree nodes taking interactive diversity significantly strengthen systems’ resilience against the shifty environment and enlarge the survival region of cooperation. However, they fail to establish a homogeneous strategy ‘cloud’ in the neighborhood and thus can not coordinate players in low-degree nodes to reach a socially optimal cooperation level. The most favorable outcome emerges when players in high-degree nodes take interactive identity and meanwhile others adopt interactive diversity. Our findings reveal the significance of the two typical interaction patterns and could be a good heuristic in coordinating them to achieve the social optimum in cooperation.

A Hybrid Approach Combining the Multi-Temporal Scale Spatio-Temporal Network with the Continuous Triangular Model for Exploring Dynamic Interactions in Movement Data: A Case Study of Football

Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN) and the continuous triangular model (CTM) for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC) is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness) are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1) exploring the interaction intensities between any two individuals; (2) exploring the interaction intensities among multiple individuals, and (3) exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

A Machine Learning Approach to Leverage Individual Keyboard and Mouse Interaction Behavior From Multiple Users in Real-World Learning Scenarios

There is strong evidence that emotions influence the learning process. For this reason, we explore the relevance of individual and general mouse and keyboard interaction patterns in real-world settings while learners perform free text tasks. To this end, we have modeled users’ mouse movements and keystroke dynamics with data mining techniques, building on previous related research and extending it in terms of some critical modeling issues that may have an impact on detection results. Inspired by practice in affective computing where physiological sensors are used, we argue for the creation of an interaction baseline model, as a reference point in the way how learners interact with the keyboard and mouse. To make the proposed affective model feasible, we have adopted a simplified 2-D self-labeling approach for labeling the users’ affective state. Our approach to affect detection improves results when there is a small amount of data instances available and does not require additional affect-oriented tasks from the learners. Specifically, learners are only asked to self-reflect their emotional state after finishing the tasks and immediately selecting two values in the affect scale. The approach we have followed aims to distill two types of interaction patterns: 1) within-subject patterns (from a single participant) and 2) between-subject patterns (across all participants). Doing this, we aim to combine both the approaches as modeling factors, thus taking advantage of individual and general interaction patterns to predict affect.

Aesthetic Adaptation as a Culture Strategy in Preserving the Local Creative Potentials

This study aims to understand and explain the problems of aesthetic adaptation through the development of ceramic art design in Mayong Lor Village as a cultural strategy in facing market competition to maintain the local characteristics. The research data was through by participant observation technique, in-depth interview, and document data tracking. The results show the following: First, the type of ceramic products can be classified into four categories, namely: 1) celengan (piggy banks), (2) children›s toys/remitance (keg, jars, cups, glasses, plates, paso, teapots, earrings, angklo, kekep) , (3) glassware for household purposes, such as jugs, kendil, padasan, and cowek, (4) decorative items (vases, jars, pots, wuwungan tiles, pencil pot, souvenirs, and carving. Aesthetically, the expression on ceramic pottery of Mayong Lor Village is simple and non-complicated as well as prioritizes the aspect of physical function which is oriented to economic value. Second, the social and cultural environment of Mayong Lor society creates typical patterns of interaction and lifestyle (with the support of its natural resources) resulting in the process of skill transfer of ceramic pottery traditionally from generation to generation and produces a unique and simple ceramic product. Third, in the midst of the strong influence of modern industrial pressures, the craftsmen struggle in the process of creativity by performing an aesthetic adaptation to develop new design with new artistic and economical values as the embodiment of a cultural strategy to maintain the creative potential of their local arts.

Mapping Asynchronous Forum-based Interaction Patterns between Second Language Educational Researchers and Practitioners

This paper presents a detailed mapping of the interaction patterns and level of cognitive processing that characterised online communication between educational researchers and L2 teachers during six weeks of asynchronous forum-based discussions of six research articles. The project was designed to investigate and ultimately bridge the linkage gap between researchers and practitioners, following the Graham et al (2006) knowledge to action framework. We used NodeXL to map the different types of interaction patterns (user-to-user and user-to-thread) and adapted the Hara et al (2000) framework to identify and describe the level of social cues used and cognitive processing mechanisms evident in the participants’ texts. The findings showed little direct interaction between the two groups as evidenced by the low use of social clues and reluctance of practitioners to respond directly to the researchers. On the other hand, the mapping of the user-to-thread patterns showed clustering around some discussion topics that were raised by both researchers and practitioners, which suggests that the discussion was meaningful and co-constructed by members of both groups. The exchange of ideas in the forum space seemed to transcend issues of identity and conventional roles as it allowed both groups to be equal contributors to the dialogue. Moreover, there was clear evidence of in-depth cognitive processing in the messages of both groups. We propose that, in spite of the seeming guarded distance and practitioners’ reluctance to address researchers directly, the forum facilitated knowledge exchange and meaningful discussion of issues of interest to both groups.

Music therapy interaction patterns in relation to borderline personality disorder (BPD) patients

Music therapy for patients suffering from borderline personality disorder (BPD) has been a standard treatment option for many years in in-patient psychiatric work. The BPD symptoms, such as identity disturbance, emotional regulation and unstable relationships, lead to challenging and stormy therapy sessions for all therapists of all disciplines. In music therapy, difficulties in treatment include, for example, the patient’s refusal to play, extreme loud music or withdrawal from the process. This article presents the method and results of a systematic qualitative research of 20 BPD female patients undergoing individual psychoanalytical music therapy in an acute psychiatric context. The aim of the research was to identify typical interaction patterns, arising from the relationship between patient and therapist and also from the significance of music. The method “forming types by understanding” is based on the well-known sociological research method of “ideal types”. ed results are generated by contrasting cases, and the research process is validated through communicative validation. In total, it was possible to identify 10 typical interaction patterns within music therapy, reflecting typical BPD themes such as regulation of proximity and distance, splitting phenomena, trauma genesis, aggression and mentalization. The 10 typical interaction patterns of BPD patients have provided a way of accessing individual music therapy cases and making them much easier to understand. The interaction patterns help to maintain and reconstruct the therapist’s capacity to play, improvise and to mentalize.

Mining Statistically Significant Co-location and Segregation Patterns

In spatial domains, interaction between features gives rise to two types of interaction patterns: co-location and segregation patterns. Existing approaches to finding co-location patterns have several shortcomings: (1) They depend on user specified thresholds for prevalence measures; (2) they do not take spatial auto-correlation into account; and (3) they may report co-locations even if the features are randomly distributed. Segregation patterns have yet to receive much attention. In this paper, we propose a method for finding both types of interaction patterns, based on a statistical test. We introduce a new definition of co-location and segregation pattern, we propose a model for the null distribution of features so spatial auto-correlation is taken into account, and we design an algorithm for finding both co-location and segregation patterns. We also develop two strategies to reduce the computational cost compared to a naive approach based on simulations of the data distribution, and we propose an approach to reduce the runtime of our algorithm even further by using an approximation of the neighborhood of features. We evaluate our method empirically using synthetic and real data sets and demonstrate its advantages over a state-of-the-art co-location mining algorithm.

Problems and challenges in teaching and learning speaking at advanced level

The article deals with the problems of teaching and learning speaking, in particular those which are most relevant in the context of developing oral skills at the advanced level of foreign language proficiency. The complex nature of spoken discourse must be taken into account and reflected at each stage of the learning process. Thus, the article examines the difficulties connected with choosing the appropriate framework and approach and discusses the typical patterns of interaction in the foreign language classroom. It also examines forms of control and evaluation and suggests some speaking activities which seem most suitable for advanced language learners in the light of the above theoretical considerations.

A synthetic coiled-coil interactome provides heterospecific modules for molecular engineering.

The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pairwise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein "interactome" includes 27 pairs of interacting peptides that preferentially heteroassociate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of special interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications.

An Investigation of Relationships between Seventh-Grade Students' Beliefs and Their Participation during Mathematics Discussions in Two Classrooms

As mathematics teachers attempt to promote classroom discourse that emphasizes reasoning about mathematical concepts and supports students' development of mathematical autonomy, not all students will participate similarly. For the purposes of this research report, I examined how 15 seventh-grade students participated during whole-class discussions in two mathematics classrooms. Additionally, I interpreted the nature of students' participation in relation to their beliefs about participating in whole-class discussions, extending results reported previously (Jansen, 2006) about a wider range of students' beliefs and goals in discussion-oriented mathematics classrooms. Students who believed mathematics discussions were threatening avoided talking about mathematics conceptually across both classrooms, yet these students participated by talking about mathematics procedurally. In addition, students' beliefs about appropriate behavior during mathematics class appeared to constrain whether they critiqued solutions of their classmates in both classrooms. Results suggest that coordinating analyses of students' beliefs and participation, particularly focusing on students who participate outside of typical interaction patterns in a classroom, can provide insights for engaging more students in mathematics classroom discussions.

Remarkable Synergistic Effects in Antifouling Chemicals against Vibrio fischeri in a Bioluminescent Assay

A bioluminescent assay using Vibrio fischeri Deutsche Sammlung von Mikroorganismen (DSM) 7151 was applied to evaluate the toxicities of some new antifouling chemicals. First, the efficient concentration, led to 50% inhibition of bioluminescence (EC50) values of the single antifouling chemicals zinc 2-pyridinethiol-1-oxide (Zn-pt), copper 2-pyridinethiol-1-oxide (Cu-pt), CuSO4, zinc bis(N,N′-dimethyl)-dithiocarbamate (Ziram), 4,5-dichloro-2-(n-octyl)-3(2H)-isothiazolone (SeaNine 211), pyridine triphenylboron (PTPB), 3-iodo-2-propynyl butylcarbamate (IPBC), 3-(3,4-dichlorophenyl)-1,1-dimethylurea (Diuron), dichlofluanid (N-dichlorofluoromthylthio-N′,N′-dimethyl-N-phynylsulfamide) (DCF), and 2-methylthio-4-tert-butylamino-6-cyclopropylamino-s-triazine (Irgarol 1051) were determined to be 0.08, 0.12, 0.22, 0.31, 0.35, 0.75, 8.49, 12.74, 39 and > 40 mg/l at 30 min of incubation, respectively. Then, 45 different combinations composed of two antifoulants each were evaluated. Based on the EC50 values at 30 min of incubation, typical patterns of interaction for the combinations were classified into three groups based on the comparison of inhibition difference between single chemicals and their mixtures. Mixture toxicity indices were also introduced to examine the interaction effect of each combination. The results showed that most combinations were partially additive, and there was no antagonistic effect among the present combinations of chemicals. Additive effects were observed in the case of Diuron, PTPB, or SeaNine 211 when mixed with IPBC. Marked synergistic effects were observed for Irgarol 1051, Ziram, Zn-pt, and Cu-pt when mixed with Cu2+, which will make these chemicals more toxic against organisms in marine environments.