Creating an Online Social Learning Platform: A Model Approach for Open Development, Open Access and Open Education

The importance of online learning platforms in the face of the challenges of the 21st century cannot be stressed enough. Multiple approaches based on different didactic concepts and software have already been discussed. At Karlsruhe Institute of Technology, our team supports the development of an innovative digital infrastructure in creating a virtual campus that provides a portfolio of digital skills and key qualifications for students of all disciplines. The following paper presents this open source-based social online learning platform called hocampus: it aims to function as a model approach for future learning platforms connecting unsupervised learning, peer communication and tutoring as well as teaching. However, our platform is not a mere technical architecture that employs online learning and communication possibilities: it is characterized by a strong correlation of structure and content. For this, we advance a didactic concept focused on empowering students to strengthen their cross-disciplinary key competences and 21st century skills. We also depict the digital infrastructure and tools being used in the creating and operation of hocampus. Lastly, the general design principles for digital platforms are put forward. This paper also presents a firsthand account of how to implement such a learning platform by showing what hindrances need to be overcome, how students benefit from a social online learning platform and how digital learning can develop and change in the coming years. Thus, it can function as a manual portraying the necessary steps for the realization of concrete didactic concepts in a digital space

When Anthropomorphism Backfires: The Effects of Power and Brand Role amid Product Wrongdoings

Anthropomorphism is the attribution of human features to nonhuman entities. Brand anthropomorphization, as a popular marketing strategy, has only recently begun to spur interests of researchers. However, its potential negative repercussions have so far received scarce attention. Consisting of two studies, this thesis seeks to look into that gap. Specifically, study 1 examines the effects of brand anthropomorphismand power on brand attitudes amid product wrongdoings. Study 2 investigates the influence of power and two specific types of anthropomorphization (brand as a partner or as a servant) in the same setting. Power is manipulated as a contextually malleable status. In both studies, we explored the moderating effects of two dimensions of Hofstede’scultural orientations: power distance and uncertainty avoidance. As inherent traits, they are measured at an individual level. The findings suggestthat marketers should be aware of consumers’ power status, cultural orientations and their combined implications when imbuing anthropomorphic features to their brand. For example, consumers in high-power positions (compared to those in low-power positions) are more sensitive towards product wrongdoings involving a human-like brand. Also, high-power-people possibly favor less a servant brand (compared to a partner brand) when it has done wrong. On the one hand, in the short term, the manipulation of power balance might help with the brand crisis. But on the other, ethics and social responsibilities should not be omitted when long-term consumer-brand relationship is considered, especially when an anthropomorphized positioning is concerned

A Cross-Case Analysis of Disciplinary Identities Communicated Through Design Reviews

In post-secondary educational settings, discourse is a mechanism by which students develop occupational identities as they engage in a particular community that communicates attributes of their prospective profession. This study focuses on revealing disciplinary identities and how they are conveyed and negotiated during interactions between design students and project reviewers. We draw upon Gee’s identity framework and focus on the enactments of disciplinary identity in three different disciplinary settings: choreography, industrial design, and mechanical engineering. A cross-case analysis indicated differences that were epistemological (e.g., subjectivity of reviews) and similarities in ways instructors modeled institutional identities. The results have implications for interdisciplinary activities and suggest that disciplines that engage in design have much to learn from one another

Negative Consequences of Anthropomorphized Technology: A Bias-Threat-Illusion Model

Attributing human-like traits to information technology (IT) — leading to what is called anthropomorphized technology (AT)—is increasingly common by users of IT. Previous IS research has offered varying perspectives on AT, although it primarily focuses on the positive consequences. This paper aims to clarify the construct of AT and proposes a “bias–threat–illusion” model to classify the negative consequences of AT. Drawing on “three-factor theory of anthropomorphism” from social psychology and integrating self-regulation theory, we propose that failing to regulate the use of elicited agent knowledge and to control the intensified psychological needs (i.e., sociality and effectance) when interacting with AT leads to negative consequences: “transferring human bias,” “inducing threat to human agency,” and “creating illusionary relationship.” Based on this bias–threat–illusion model, we propose theory-driven remedies to attenuate negative consequences. We conclude with implications for IS theories and practice

Measuring the Perceived Boundary between Consumers and Brands

This study develops and validates a measure that captures the perceived psychological boundary between consumers and brands, which is defined as consumers’ perceived demarcation between themselves and a brand. This construct captures both consumers’ separateness from and relatedness to a brand. A seven-point Venn diagram, which has been proved effective and valid in interpersonal relationship and other self-expansion studies, is applied to measure consumers’ perceived boundary with various brands. The reliability and validity of the boundary measure are assessed with 44 brands. This study finds that consumers’ boundary with brands is significantly correlated with brand-related consumer responses. The discriminant validity and convergent validity between the boundary and self-brand connection, self-brand attachment, and BESC scales are validated. Masculinity incongruence and femininity incongruence between consumers and brands are shown to have a significantly negative relationship with boundary, thus supporting the concurrent validity. In a nomological network, a significant mediation effect of boundary on the relationship between brand-consumer gender identity incongruence and brand-related consumer responses is observed

Become a Lifesaver - How to Design Conversational Agents to Increase Users’ Intention to Donate Blood

Donating blood is a selfless act that impacts public welfare, potentially saving human lives. However, blood shortage is a rising worldwide issue due to increased demand. Thus, finding ways to animate and motivate potential donors to donate blood is para-mount. In this context, conversational agents (CAs) offer a promising approach to edu-cating, promoting, and achieving desired behaviors. In this paper, we conducted an online experimental study (N=303) and investigated the effect of a human-like designed CA and fear-inducing communication on users’ intention to donate. Our results show that users’ intention is driven by perceived persuasiveness rather than perceived human-ness and that fear-inducing communication does not significantly affect the intention to donate. Against this background, we provide numerous theoretical and practical impli-cations, contributing to information system literature by enhancing our understanding of how fear-inducing communication is used in CA interactions

THE EFFECT OF CHATBOTS RESPONSE LATENCY ON USERS’ TRUST

Chatbots are widely used as conversational agents and being designed using anthropomorphic design guidelines. However, response latency (response latency is the time it takes for a chatbot/person to provide a response immediately after receiving a message) as an anthropomorphic design cue in a conversational user interface has not been the subject of many studies. Even though the system's response latency has an undeniable effect on users' satisfaction and performance, the connection between users' trust and chatbots' response time is not addressed. A critical reason that executives are reluctant to implement chatbots for their businesses is the user adoption hesitancy. Customers and users are unwilling to engage with a chatbot because they do not trust chatbot. Therefore, this study used empirical data collected from chatbot users to investigate the effect of chatbots response latency on users’ trust – cognitive and affective trust. The results of this study suggest that dynamically delaying chatbot response increases users’ cognitive trust but has no significant impact on users’ affective trust. General sentiment analysis on chatbot users’ responses to an open-ended question that describes their experiences interacting with chatbots suggests that dynamically delaying chatbot response produces higher positive sentiment and trust sentiment than near-instant chatbot response. Other findings are discussed and some ideas for future research are also presented in this paper

“Smart home system is like a mother”: The potential and risks of using product metaphors to influence consumers’ comprehension of really new products

Driven by innovative technology, really new products (RNPs) incorporate new functions that provide significant benefits for consumers. But consumers often experience difficulty understanding RNPs, which hinders consumers’ further adoption. To facilitate consumers’ comprehension, the use of product metaphors in RNPs is a promising strategy because it relates a target RNP to a source product/concept familiar to consumers. By using knowledge from the familiar source, consumers could gain better comprehension of the RNP. However, product metaphors can also carry risks that hinder consumers’ comprehension of RNPs, such as consumers’ misidentification of the source and consumer’ inability to use the relevant knowledge to comprehend RNPs. This research investigates the potential and risks of using product metaphors in RNPs through a mixed-methods approach. Specifically, an experiment and in-depth interviews were conducted to examine the effects of product metaphors on consumers’ comprehension. Results revealed that consumers encounter difficulty in detecting the similarities between source concepts/products and target RNPs due to which product metaphors may not necessarily enhance consumers’ comprehension. Accompanying a product metaphor with a textual clue can help consumers to detect the similarities between source concepts/products and target RNPs, leading to enhanced consumers’ comprehension. Implications for theory and practice are discussed. <br

Human vs. machine as message source in advertising: examining the persuasiveness of brand influencer type and the mediating role of source credibility for advertising effectiveness in social media advertising

[EMBARGOED UNTIL 5/31/2023] Message source effects on persuasion of target audiences have been examined for decades by scholars in advertising, consumer behavior, communication, and psychology, among others. Myriads of studies are available on the subject, but in nearly every instance "source" is defined as a human and rarely is source defined as non-human, or machine. The rise of artificial intelligence (AI) as a message source urges scientific inquiry of the validity of those established theories in a new technology context. The focus of this dissertation is on that of the machine as source. By "machine" this study refers broadly to AI agents, defined to mean digitally created artificial beings that can think and perform tasks like a human. The specific AI agent examined here is that of SMIs, defined as AI agents who are associated with fame and perform human tasks using software and algorithms. The context of the study is social media, defined as "digital networked tools or technologies that enable communication, collaboration, and creative expression across social networks" (McMillan and Childers, 2017, p. 52). Influencer marketing is a crucial component of social media marketing, which is projected to become a $10 billion market by 2023 (Tan, 2019). The primary contribution of this study is, therefore, to understand SMIs' effectiveness in social media advertising. Considering that 95 percent of consumer interaction is projected to be powered by AI by the year of 2025 (Finance Digest, 2020), research to understand the impact of this transformation of message source (from human to machine) is urgently needed but rarely conducted to date. The most apparent machine sources, SMIs, are already being put to use in practice without fully understanding their effectiveness and risk, to replace human influencers. Human influencers, here, specifically refer to social media influencers (SMIs) "who have built a sizable social network of people following them and are seen as self-made microcelebrities" (Shan et al., 2020, p. 2). Indeed, this very notion is reflected in the warnings of the infamous physicist Stephen Hawking who predicted that, someday, machines may even replace humans. As much as this may sound like a futuristic movie, machines are beginning to replace humans in fields as far and wide as medicine, engineering, and transportation. For example, AI is cleaning floors at airports, taking people's temperatures, and even making salad in hospital dining-halls in response to the coronavirus pandemic (Semuels, 2020). In advertising, AI is taking over the work humans have traditionally done, from content matching to advertising creation (Rodgers, 2021). An SMI, Lil Miquela, even takes the spot that is usually reserved for a human and is named as one of Time's 25 most influential people on the internet in 2018 (Time, 2018). The proposed research is supported by survey results from consumers worldwide that paint a mixed picture --some consumers embrace AI for its potential benefits, whereas others fear that AI will hurt their privacy and ability to control their jobs, lives, and futures (Zhang and Dafoe, 2019), suggesting potential drawbacks of AI technology. This suggests that SMIs could trigger various perceptions among consumers that may lead to different outcomes. The challenge is to know the underlying psychological mechanisms to explain potential positive/negative outcomes, yet studies on the subject are rare but urgently needed. This dissertation investigates this phenomenon, specifically, potential benefits and drawbacks of using SMIs compared to (human) SMIs in social media advertising. Based on established theories of persuasion on advertising and brand endorsers, this dissertation identifies a crucial processing mechanism - source credibility - that is used to explain instances under which influencer type (i.e., AI vs. human) differentially influences advertising outcomes (i.e., attitude toward the advertisement, attitude toward brand, and purchase intentions). Source credibility is the source's truthfulness and believability perceived by the consumers (Roy et al., 2017). The treatment of source credibility as a mediating factor is a unique aspect of the research and that diverges from prior approaches that treat it as a predictor of persuasion. Rather, this research conceptualizes source credibility as dynamic, constantly changing, and not related in a simple way to the persuasiveness of an influencer type. Three dimensions of source credibility - expertise, trustworthiness, and physical attractiveness - are proposed to explain how an AI influencer may perform better/worse than a (human) SMI on advertising outcomes. A review of five decades' of source credibility studies noted several discrepancies regarding three dimensions of source credibility, suggesting gaps or unresolved issues in source credibility that deserve attention (see Pornpitakpan, 2004). Additionally, initial negative/positive dispositions toward the brand influencers, which has hardly been examined (see Pornpitakpan, 2004), will be measured in an effort to assess how much, if any, of a shift is detected in source credibility perceptions. To summarize, this research examines effectiveness of influencer type (artificial intelligence influencer vs. SMI) on persuasion of social media advertising (attitude toward the ad, attitude toward the brand, and purchase intentions). One mediator, source credibility, is proposed to explain the results. This is accomplished with a pilot study and an experimental study conducted in an online setting.Includes bibliographical references