@article{ref1,
title="A field assessment of child abuse investigators' engagement with a child-avatar to develop interviewing skills",
journal="Child abuse and neglect",
year="2023",
author="Røed, Ragnhild Klingenberg and Powell, Martine B. and Riegler, Michael A. and Baugerud, Gunn Astrid",
volume="143",
number="",
pages="e106324-e106324",
abstract="BACKGROUND: Child investigative interviewing is a complex skill requiring specialised training. A critical training element is practice. Simulations with digital avatars are cost-effective options for delivering training. This study of real-world data provides novel insights evaluating a large number of trainees' engagement with LiveSimulation (LiveSim), an online child-avatar that involves a trainee selecting a question (i.e., an option-tree) and the avatar responding with the level of detail appropriate for the question type. While LiveSim has been shown to facilitate learning of open-ended questions, its utility (from a user engagement perspective) remains to be examined. <br><br>OBJECTIVE: We evaluated trainees' engagement with LiveSim, focusing on patterns of interaction (e.g., amount), appropriateness of the prompt structure, and the programme's technical compatibility. PARTICIPANTS AND SETTING: Professionals (N = 606, mainly child protection workers and police) being offered the avatar as part of an intensive course on how to interview a child conducted between 2009 and 2018. <br><br>METHODS: For descriptive analysis, Visual Basic for Applications coding in Excel was applied to evaluate engagement and internal attributes of LiveSim. A compatibility study of the programme was run testing different hardware focusing on access and function. <br><br>RESULTS: The trainees demonstrated good engagement with the programme across a variety of measures, including number and timing of activity completions. Overall, knowing the utility of avatars, our results provide strong support for the notion that a technically simple avatar like LiveSim awake user engagement. This is important knowledge in further development of learning simulations using next-generation technology.<p /> <p>Language: en</p>",
language="en",
issn="0145-2134",
doi="10.1016/j.chiabu.2023.106324",
url="http://dx.doi.org/10.1016/j.chiabu.2023.106324"
}