Information Landscape
In CORE, we systematically investigate the online information landscape (IL), which includes all sources and content accessible on the World Wide Web that students use for their university studies as well as for solving COR tasks in online assessments. An unrestricted Internet search on a domain-specific or generic topic is recorded in real-time to gather data on how an Internet search is carried out. Data is also collected on which Web sources are accessed during the search, such as domain, modality, genre, quality, as well as other characteristics. Students need to apply specific skills in order to acquire applicable knowledge from Web-based information and provide a credible solution during the critical online reasoning tasks. Various skills can be crucial for accessing some parts of the IL and attaining particular learning goals (e.g., only experts may be able to detect errors in data), while, in other cases, use of online information varies less according to skill than to the presence of specific cues. While research suggests an interdependence between students’ skills and the (online) IL they assess and use for learning, the online IL has rarely been examined for educational purposes. To address this research desideratum, the IL framework is based on the integration of several theories to analyze the central characteristics of online sources and their influences on COR. This includes the analyses of
- the correctness and comprehensibility of content based on the evaluation criteria of established theories, such as media bias (see B04);
- linguistic features of the sources based on the theories of text and cognitive linguistics (see B05);
- narrative framings and latent meaning structures based on theories of narratology and reconstructive hermeneutics (see B06).
Critical Online Reasoning
CORE research is based on a newly developed, integrated theoretical-conceptual framework of a key skillset deemed crucial for acquiring accurate information online and using it for learning that we refer to as critical online reasoning (COR). COR consists of three overarching and overlapping cognitive facets:
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(1) online information acquisition (OIA) skills, e.g., selecting search engines or databases, specifying search queries; (2) critical information evaluation (CIE) skills, e.g., evaluating website credibility based on cues; and argumentative skills, e.g., using evidence to generate and justify a valid argument based on the (3) synthesis of information accessed (REAS), including accounting for common errors and biases and considering and weighting (contradictory) arguments and (covert) perspectives of (partly conflicting) information sources. |
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In addition, metacognitive skills regulate the state- and situation-specific activation, continuation, and conclusion of COR processes (MCA) within the encompassing information acquisition context, e.g., recognizing the need to use COR in learning contexts.
The COR concept leans heavily on previously developed process and phase models of (online) information search, selection, and evaluation, especially the Information problem-solving on the Internet (IPS-I) model (Brand-Gruwel et al., 2009), and it includes insights e.g., into cues of sources from related research on ‘Web credibility’ (e.g., Wierzbicki, 2018) and multiple-source comprehension (MSU, Braasch et al., 2018), where COR-related skills have been investigated.
Based on a research review (Zlatkin-Troitschanskaia, Hartig et al., 2021), we also developed a taxonomy for online student learning, created with a focus on knowledge acquisition from Internet sources. The taxonomy describes the typical situations in which students use the Internet. Two broad areas have become evident: One is Internet use in specific study and practice-related tasks within one study domain, such as creating a diagnostic plan in medicine. The other is the cross-domain area, which covers broad topics such as discussion forums on climate change. Therefore, we distinguish between two typical application contexts of COR: Everyday situations in the study without reference to a specific domain as well as domain-specific situations. Since students face domain-specific as well as cross-domain requirements in their studies, we focus on both COR contexts. We refer to COR in the generic context as GEN-COR and COR in the domain-specific context as DOM-COR. Accordingly, we differentiate between GEN- and DOM-COR processes and performance. For instance, while a successful GEN-COR student faces everyday critical information problems and may need to primarily identify suitable information and honest, competent experts to trust, a successful DOM-COR student may need to act as said (budding) domain expert and research on specialist platforms, consult studies, interpret (reported) domain facts and data, and draw more nuanced conclusions (or display conducive online behaviors). To examine both application contexts, students were presented with corresponding tasks based on real Internet or Internet-like simulations.