{"abstract":[{"text":"Understanding how scaffolding strategies influence human understanding in\nhuman-robot interaction is important for developing effective assistive\nsystems. This empirical study investigates linguistic scaffolding strategies\nbased on negation as an important means that de-biases the user from potential\nerrors but increases processing costs and hesitations as a means to ameliorate\nprocessing costs. In an adaptive strategy, the user state with respect to the\ncurrent state of understanding and processing capacity was estimated via a\nscoring scheme based on task performance, prior scaffolding strategy, and\ncurrent eye gaze behavior. In the study, the adaptive strategy of providing\nnegations and hesitations was compared with a non-adaptive strategy of\nproviding only affirmations. The adaptive scaffolding strategy was generated\nusing the computational model SHIFT. Our findings indicate that using adaptive\nscaffolding strategies with SHIFT tends to (1) increased processing costs, as\nreflected in longer reaction times, but (2) improved task understanding,\nevidenced by a lower error rate of almost 23%. We assessed the efficiency of\nSHIFT's selected scaffolding strategies across different cognitive states,\nfinding that in three out of five states, the error rate was lower compared to\nthe baseline condition. We discuss how these results align with the assumptions\nof the SHIFT model and highlight areas for refinement. Moreover, we demonstrate\nhow scaffolding strategies, such as negation and hesitation, contribute to more\neffective human-robot explanatory dialogues.","lang":"eng"}],"status":"public","author":[{"full_name":"Groß, André","last_name":"Groß","first_name":"André"},{"full_name":"Richter, Birte","last_name":"Richter","first_name":"Birte"},{"first_name":"Bjarne","full_name":"Thomzik, Bjarne","last_name":"Thomzik"},{"first_name":"Britta","full_name":"Wrede, Britta","last_name":"Wrede"}],"type":"preprint","date_created":"2025-09-11T10:28:03Z","date_updated":"2025-09-11T10:32:16Z","year":"2025","citation":{"ieee":"A. Groß, B. Richter, B. Thomzik, and B. Wrede, “Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI,” <i>arXiv:2503.19692</i>. 2025.","mla":"Groß, André, et al. “Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI.” <i>ArXiv:2503.19692</i>, 2025.","bibtex":"@article{Groß_Richter_Thomzik_Wrede_2025, title={Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI}, journal={arXiv:2503.19692}, author={Groß, André and Richter, Birte and Thomzik, Bjarne and Wrede, Britta}, year={2025} }","ama":"Groß A, Richter B, Thomzik B, Wrede B. Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI. <i>arXiv:250319692</i>. Published online 2025.","short":"A. Groß, B. Richter, B. Thomzik, B. Wrede, ArXiv:2503.19692 (2025).","apa":"Groß, A., Richter, B., Thomzik, B., &#38; Wrede, B. (2025). Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI. In <i>arXiv:2503.19692</i>.","chicago":"Groß, André, Birte Richter, Bjarne Thomzik, and Britta Wrede. “Leveraging Cognitive States for Adaptive Scaffolding of Understanding in   Explanatory Tasks in HRI.” <i>ArXiv:2503.19692</i>, 2025."},"title":"Leveraging Cognitive States for Adaptive Scaffolding of Understanding in\n  Explanatory Tasks in HRI","_id":"61213","user_id":"93405","publication":"arXiv:2503.19692","external_id":{"arxiv":["2503.19692"]}}