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Jörg Cassens, Rebekah Wegener, Lorenz Habenicht, and Julian Blohm discuss the dialogic form of explanations. Explanations are a long established research topic in a wide variety of disciplines, ranging from philosophy (van Fraassen, 1980; Achinstein, 1983) over the cognitive sciences and psychology (Lalljee et al., 1983; Keil and Wilson, 2000; Lombrozo, 2006) to computer science in general and artificial intelligence in particular (Schank, 1986; Leake, 1992; Leake (1995); Sørmo et al., 2005). However, while there is compelling research supporting the value, structure and function of explanation, as Edwards et al. (2019) argue, “accounts of explanation typically define explanation (the product) rather than explaining (the process)”. By contrast, we aim at an understanding of explanation as a functional variety of language behaviour that treats explanations as being:

The answers people give when asked to “think of theunexpected” for everyday event scenarios appear to be moreexpected than unexpected. There are expected unexpectedoutcomes that closely adhere to the given information in ascenario, based on familiar disruptions and common plan-failures. There are also unexpected unexpected outcomes thatare more inventive, that depart from given information, addingnew concepts/actions. However, people seem to tend toconceive of the unexpected as the former more than the latter.Study 1 tests these proposals by analysing the object-conceptspeople mention in their reports of the unexpected and theagreement between their answers. Study 2 shows that object-choices are weakly influenced by recency, that is, the order ofsentences in the scenario. The implications of these results forideas in philosophy, psychology and computing are discussed.

Objective: This article reviews research on computerized and computer‐assisted psychological assessment and psychotherapy for college and university students. Method: Published reviews of outcome research on the topic are reviewed, along with individual clinical trials and other relevant studies not covered by reviews, as well as reviews of closely‐related research. Results: Computer‐assisted assessment and psychotherapy have proven effective with collegians across samples, nations, and presenting concerns. Conclusions: Currently‐available digital technologies can address these mental health service delivery challenges: cost, limited human resources, failure of students to seek help, stigmatization of collegians seeking help, premature termination, inadequate process and outcome data to assess and improve treatment effectiveness, and lack of real‐time data‐based treatment selection. [ABSTRACT FROM AUTHOR]