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In today’s social online world there is a variety of interaction and participatory possibilities which enable web users to actively produce content themselves.
This user-generated content is omnipresent in the web and there is growing evidence that it is used to select or evaluate professionally created online information.
The present study investigated how this surrounding content affects online advertising by drawing from social influence theory. Specifically, it was assumed that
web users sharing an interpersonal relationship (interpersonal influence) and/or a group membership (collective influence) with authors of user-generated content
which appears next to advertising on the web page are more strongly influenced in their response to the advertising than unrelated users. These assumptions were
tested in a 2 × 2 between-subject experiment with 118 students who were exposed to four different Facebook profiles that differed in terms of interpersonal
connection to the source (existent/non-existent) and collective connection to the source (existent/non-existent). The results show a significant impact in the case
of collective influence, but not in the case of interpersonal influence. The underlying mechanisms of this effect and implications of the results for online advertising
are discussed.
According to research examining self‐regulated learning (SRL), we regard individual regulation as a specific sequence of regulatory activities. Ideally, students perform various learning activities, such as analyzing, monitoring, and evaluating cognitive and motivational aspects during learning. Metacognitive prompts can foster SRL by inducing regulatory activities, which, in turn, improve the learning outcome. However, the specific effects of metacognitive support on the dynamic characteristics of SRL are not understood. Therefore, the aim of our study was to analyze the effects of metacognitive prompts on learning processes and outcomes during a computer‐based learning task. Participants of the experimental group (EG, n=35) were supported by metacognitive prompts, whereas participants of the control group (CG, n=35) received no support. Data regarding learning processes were obtained by concurrent think‐aloud protocols. The EG exhibited significantly more metacognitive learning events than did the CG. Furthermore, these regulatory activities correspond positively with learning outcomes. Process mining techniques were used to analyze sequential patterns. Our findings indicate differences in the process models of the EG and CG and demonstrate the added value of taking the order of learning activities into account by discovering regulatory patterns.