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  • × author_ss:"Xu, H."
  1. Erickson, L.B.; Wisniewski, P.; Xu, H.; Carroll, J.M.; Rosson, M.B.; Perkins, D.F.: ¬The boundaries between : parental involvement in a teen's online world (2016) 0.04 
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    Abstract
    The increasing popularity of the Internet and social media is creating new and unique challenges for parents and adolescents regarding the boundaries between parental control and adolescent autonomy in virtual spaces. Drawing on developmental psychology and Communication Privacy Management (CPM) theory, we conduct a qualitative study to examine the challenge between parental concern for adolescent online safety and teens' desire to independently regulate their own online experiences. Analysis of 12 parent-teen pairs revealed five distinct challenges: (a) increased teen autonomy and decreased parental control resulting from teens' direct and unmediated access to virtual spaces, (b) the shift in power to teens who are often more knowledgeable about online spaces and technology, (c) the use of physical boundaries by parents as a means to control virtual spaces, (d) an increase in indirect boundary control strategies such as covert monitoring, and (e) the blurring of lines in virtual spaces between parents' teens and teens' friends.
    Date
    7. 5.2016 20:05:22
  2. Xu, H.; Bu, Y.; Liu, M.; Zhang, C.; Sun, M.; Zhang, Y.; Meyer, E.; Salas, E.; Ding, Y.: Team power dynamics and team impact : new perspectives on scientific collaboration using career age as a proxy for team power (2022) 0.01 
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  3. Wu, D.; Xu, H.; Sun, Y.; Lv, S.: What should we teach? : A human-centered data science graduate curriculum model design for iField schools (2023) 0.01 
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    Abstract
    The information schools, also referred to as iField schools, are leaders in data science education. This study aims to develop a data science graduate curriculum model from an information science perspective to support iField schools in developing data science graduate education. In June 2020, information about 96 data science graduate programs from iField schools worldwide was collected and analyzed using a mixed research method based on inductive content analysis. A wide range of data science competencies and skills development and 12 knowledge topics covered by the curriculum were obtained. The humanistic model is further taken as the theoretical and methodological basis for course model construction, and 12 course knowledge topics are reconstructed into 4 course modules, including (a) data-driven methods and techniques; (b) domain knowledge; (c) legal, moral, and ethical aspects of data; and (d) shaping and developing personal traits, and human-centered data science graduate curriculum model is formed. At the end of the study, the wide application prospect of this model is discussed.

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