collaborative behavior
Recently Published Documents


TOTAL DOCUMENTS

125
(FIVE YEARS 45)

H-INDEX

12
(FIVE YEARS 3)

2022 ◽  
pp. 073563312110622
Author(s):  
Sinan Hopcan ◽  
Elif Polat ◽  
Ebru Albayrak

The pair programming approach is used to overcome the difficulties of the programming process in education environments. In this study, the interaction sequences during the paired programming of preservice teachers was investigated. Lag sequential analysis were used to explore students’ behavioral patterns in pair programming. The participants of the study consist of 14 students, seven pairs enrolled in a Programming Languages course. The findings indicate that there are significant behavioral learning sequences. During the program development process, students hesitated to create an algorithm and to improve an existing one while proposing the next step. In addition, they constantly waited for approval. Collaborative behaviors such as giving and receiving feedback and helping other partners were less observed in females. In addition, significant sequential driver and navigator behaviors were presented. The findings of the study have important implications for instructors and designers when using a pair programming approach in teaching programming. In the future, programming instruction environments can be designed by considering the learner behaviors that are presented in this study.


Author(s):  
Ting-Chia Hsu ◽  
Hal Abelson ◽  
Evan Patton ◽  
Shih-Chu Chen ◽  
Hsuan-Ning Chang

AbstractIn order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software development. An empirical study probed into the differential impact on self-efficacy and collaborative behavior of learners in the environment depending upon their disciplinary background. The study serves as an example of the use of learning analytics to explore the frequent behavior patterns of adult learners, in this case specifically while performing BBP in MAI integrated with RTC. This study compares behavior patterns that are collaborative or individual that occurred on the platform, and investigates the effects of collaboration on learners working within the RTC depending on whether they were CS-majors or not. We highlight advantages of the new MAI design during multi-user programming in the online RTC based on the connections between the interface design and BBP as illustrated by two significant behavior patterns found in this instructional experiment. First, the multi-user programming in the RTC allowed multiple tasks to happen at the same time, which promoted engagement in joint behavior. For example, one user arranged components in the interface design while another dragged blocks to complete the program. Second, this study confirmed that the Computer Programming Self-Efficacy (CPSE) was similar for individual and multi-user programming overall. The CPSE of the homogeneous CS-major groups engaged in programming within the RTC was higher than that of the homogeneous non-CS-major groups and heterogeneous groups. There was no significant difference between the CPSE of the homogenous non-CS group and the CPSE of the heterogeneous groups, regardless of whether they were engaged in individual programming or collaborative programming within their groups. The results of the study support the value of engaging with MAI collaboratively, especially for CS-majors, and suggest directions for future work in RTC design.


SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110582
Author(s):  
Shu-Rong Zhao ◽  
Hong Li

In flipped learning (FL), the pre-class section plays an important role and determines whether meaningful and deep-level learning can take place in the following in-class section. However, previous studies focus on in-class learning and research little on the pre-class section. In order to explore an interactive mode which can ensure the effect of pre-class learning, a production-oriented peer collaboration FL framework was proposed and applied to the Business English course. Mixed research methods including questionnaire and focus group interview were used to test the effectiveness of the framework and explore effective forms of interaction. Data analysis shows that the FL framework improved significantly social interaction self-efficacy, help-seeking, and self-evaluation in self-regulated learning, thus ensured quality pre-class learning. As to interaction, eight collaboration forms were found through thematic analysis, namely comparison, correction, reaching agreement, supervision, inspiration, complementation, negotiation, and emotional support. Among them, comparison is the most beneficial and frequently mentioned collaborative behavior. This research provides an empirical case for peer interaction based on online learning tasks. It helps enrich interactive research in FL and provides teaching reference for practitioner teachers by offering a feasible framework.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257734
Author(s):  
Patricia Raab ◽  
Franz X. Bogner

Microplastics are a global challenge and a frequently studied environmental issue. Hence, the knowledge body about microplastics within the scientific community is growing fast and challenges an elaborated knowledge transfer from science to the general public. Just as well-informed people are the basis for reducing microplastics’ impact on the environment, knowledge of the audience’s conceptions is the basis for an accurate and successful dissemination of scientific findings. However, insights into the publics’ perceptions of microplastics are still rare. The present study aimed to capture students’ conceptions about microplastics based on their individual experiences following qualitative inductive, exploratory research. Therefore, 267 students of a state university in Germany responded to a paper-and-pencil questionnaire containing open and closed questions on microplastic-related conceptual understanding, risk perception, information behavior, sources, and sinks. The inductive classifying of all responses by a qualitative content analysis revealed six basic concepts: 1) Microplastics are mainly understood as small plastic particles. 2) Microplastics are closely associated with its negative consequences. 3) The most labeled source in households is plastic packaging. 4) Compared to other water bodies, microplastics are rarely suspected in groundwater. 5) A high threat awareness exists in classifying microplastics as very dangerous and dangerous. 6) Media such as TV or the Internet are the most crucial information sources while the school has less importance in acquiring information. It is precisely this pattern that indicates the need for profound science communication to establish a joint and scientifically sound knowledge base in society. Knowledge about conceptions of potential “customers” allows tailor-made scientific knowledge transfers to shape public awareness, initiate changes in thoughts and prepare the field for collaborative behavior.


Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1235
Author(s):  
Shaojuan Lei ◽  
Xiaodong Zhang ◽  
Suhui Liu

A large amount of semantic content is generated during designer collaboration in open-source projects (OSPs). Based on the characteristics of knowledge collaboration behavior in OSPs, we constructed a directed, weighted, semantic-based knowledge collaborative network. Four social network analysis indexes were created to identify the key opinion leader nodes in the network using the entropy weight and TOPSIS method. Further, three degradation modes were designed for (1) the collaborative behavior of opinion leaders, (2) main knowledge dissemination behavior, and (3) main knowledge contribution behavior. Regarding the degradation model of the collaborative behavior of opinion leaders, we considered the propagation characteristics of opinion leaders to other nodes, and we created a susceptible–infected–removed (SIR) propagation model of the influence of opinion leaders’ behaviors. Finally, based on empirical data from the Local Motors open-source vehicle design community, a dynamic robustness analysis experiment was carried out. The results showed that the robustness of our constructed network varied for different degradation modes: the degradation of the opinion leaders’ collaborative behavior had the lowest robustness; this was followed by the main knowledge dissemination behavior and the main knowledge contribution behavior; the degradation of random behavior had the highest robustness. Our method revealed the influence of the degradation of collaborative behavior of different types of nodes on the robustness of the network. This could be used to formulate the management strategy of the open-source design community, thus promoting the stable development of OSPs.


Author(s):  
Peizhuo Sheng ◽  
Xuelin Zhu ◽  
Chunmei Wang

Neither every dramatic change in ways of production and living, nor the renovation of cognition and culture in human history are not the result of science and technology revolution. Private law culture, important part of human organizational culture and legal culture, is based on humanity, freedom and equality, justice, order and harmony. Present Artifi cial intelligent revolution will not only change human way of living and developing, but also affect private law culture dramatically and destructively, which will affect human beings as a whole and may lead to devastating destroy to humans. Firstly, individuals become digital persons under two-tier space structure, under which self will not be an end, but a device and means to be used by humans. Humans and machines coexist, which promotes artifi cial machines to become subjects, to a great extent. The modern somatic technology may create somatic, emotional or intelligent supermen, furthermore, an inequality between supermen and normal humans will result in reifi cation and objectifi cation of the latter. Secondly, data hegemony may arise from the algorithms and data which are becoming resources, which will make natural persons lose privacy, personal lives, personal space and critical abilities, in the end, natural persons will become transparent ones, furthermore, freedom of the private law will be fading away. Thirdly, data decision-making replaces human decision-making, and algorithm equality replaces formal equality. However, the algorithm black box, the value deviation of built-in program code and deep learning of intelligent machines may lead to permanent prejudice and discrimination against subjects, giving rise to overused algorithm, completely challenge and deviate from fairness and justice that private law seeks for. Therefore, it is necessary to prevent the theories systems and rules the private law from losing cultural values so as to develop high technology, live up to the expectation of humans for a better life, and produce an orderly and harmonious society, which is an important goal of developing an intelligent society: First of all, humans are the main users of technology. The negative effect of technology application is based on perception and morality of human beings. The loss of private law cultural values, caused by the development and change of precaution technology, forces people to consider related perception and ethics, absorb various cultural values, maintain, uphold and advocate technological humanism, guide the development and practical application of artifi cial intelligence technology with ethical goodness, construct scientifi c humanism, and integrate science -technology and humanity. Secondly, the value of justice is relative and developing, which requires integrating the concept of data justice, code justice and algorithm justice into the value and basic principles, providing a new standard of justice for the freedom and equality of the private law, weakening and eliminating data hegemony and algorithm discrimination so that free value and equality of the private law will be recovered. Finally, Related concepts and principles must be included in systems and rules so that the private law subject system is reshaped, the private law subject status of intelligent robots is accepted completely or partly, and the subject-object confusion caused by human-computer symbiosis is removed. Moreover, the legal behavior system must be changed so that the civil subject’s online and offl ine behavior and man-machine collaborative behavior are integrated and standardized, and the potential risks of the harmonious private law order are eliminated. Furthermore, legal right systems are updated and restructured, so that legal attributes and uses of data and information are redefi ned or reorganized reasonably, and the protection of data, information and privacy are strengthened. Last but not the least, the basic imputation principle and causality of civil liability must be renewed so that the liability risks caused by human-machine coordination and the independent behavior of intelligent machines are distributed reasonably, and compensation systems are improved.


2021 ◽  
pp. 101056
Author(s):  
J. Jobu Babin ◽  
Marine Foray ◽  
Andrew Hussey

2021 ◽  
Vol 12 ◽  
Author(s):  
Noah R. Fram ◽  
Visda Goudarzi ◽  
Hiroko Terasawa ◽  
Jonathan Berger

The Covid-19 pandemic severely limited collaboration among musicians in rehearsal and ensemble performance, and demanded radical shifts in collaborative practices. Understanding the nature of these changes in music creators' patterns of collaboration, as well as how musicians shifted prioritizations and adapted their use of the available technologies, can offer invaluable insights into the resilience and importance of different aspects of musical collaboration. In addition, assessing changes in the collaboration networks among music creators can improve the current understanding of genre and style formation and evolution. We used an internet survey distributed to music creators, including performers, composers, producers, and engineers, all active before and during the pandemic, to assess their perceptions of how their music, collaborative practice, and use of technology were impacted by shelter-in-place orders associated with Covid-19, as well as how they adapted over the course of the pandemic. This survey was followed by Zoom interviews with a subset of participants. Along with confirming previous results showing increased reliance on nostalgia for musical inspiration, we found that participants' collaborative behaviors were surprisingly resilient to pandemic-related changes. In addition, participant responses appeared to be driven by a relatively small number of underlying factors, representing approaches to musical collaboration such as musical extroversion or musical introversion, inspiration clusters such as activist musicking, and style or genre clusters.


Author(s):  
Mustafa Al-Bazoon

This article investigates the use of Harris Hawks Optimization (HHO) to solve planar and spatial trusses with design variables that are discrete. The original HHO has been used to solve continuous design variables problems. However, HHO is formulated to solve optimization problems with discrete variables in this research. HHO is a population-based metaheuristic algorithm that simulates the chasing style and the collaborative behavior of predatory birds Harris hawks. The mathematical model of HHO uses a straightforward formulation and does not require tuning of algorithmic parameters and it is a robust algorithm in exploitation. The performance of HHO is evaluated using five benchmark structural problems and the final designs are compared with ten state-of-the-art algorithms. The statistical outcomes (average and standard deviation of final designs) show that HHO is quite consistent and robust in solving truss structure optimization problems. This is an important characteristic that leads to better confidence in the final solution from a single run of the algorithm for an optimization problem.


2021 ◽  
Vol 5 (GROUP) ◽  
pp. 1-25
Author(s):  
Leticia S. Machado ◽  
Ricardo Rodrigo M. Melo ◽  
Cleidson R. B. de Souza ◽  
Rafael Prikladnicki

Software Crowdsourcing (SW CS) allows a requester to increase the speed of its software development efforts by submitting a task to be performed by the crowd. SW CS is usually structured around software platforms, which are used by crowd members to identify a task suited for them, gather information about this task, and finally, submit a solution for it. In competitive software crowdsourcing, members of the crowd independently create solutions while competing against each other by monetary rewards for task completion. While competition usually reduces collaboration, in this paper, we investigated how crowd members create a collaborative behavior during programming challenges using online forums to help each other, share useful information, and discuss important documents and artifacts. We also investigated different collaborative behaviours by crowd members and and how this collaboration is associated with crowd members' improved outcome in the challenges. These results are based on analysis of the online forums from Topcoder, one of the largest competitive SW CS platforms


Sign in / Sign up

Export Citation Format

Share Document