@techreport{65789, author = {{Rohlfing, Katharina J. and Steinhardt, Isabel and Scharlau, Ingrid and Schaper, Niclas and Holtfreter, Susan and Biere, Lea and Grimminger, Angela and Schmidt, Rebecca and Festner, Dagmar Franziska and Schmidt, Rebekka and Buhl, Heike M. and Mindt, Ilka and Karsten, Andrea Ramona and Neiske, Iris and Luft, Sebastian}}, title = {{{(Nicht)Nutzung von KI-Werkzeugen in der Lehre: ein Reflexionspapier}}}, doi = {{10.17619/UNIPB/1-2576}}, year = {{2026}}, } @article{66854, abstract = {{Abstract Investigating the real-time interplay between language and vision has traditionally involved a trade-off between experimental control and interactive setups. To address this challenge, we present a methodological framework that embeds the visual world paradigm (VWP) within a continuous, goal-directed human–robot interaction (HRI) task. By augmenting VWP in an HRI setup to produce standardized yet responsive verbal and non-verbal behaviours, the framework makes it possible to selectively examine comprehension, production, actions and their relation to visual attention in real-time. We demonstrate the utility of the framework through a proof-of-concept manipulating action structure, specifically path and manner, as well as other-initiated repair formats, namely open and restricted requests. The findings show that the setup reliably captures time-locked referential gaze dynamics following comprehension and preceding production processes. They further indicate that differences in action history systematically influence speakers’ pre-verbal cognitive processes and their subsequent linguistic choices. These findings suggest that HRI can provide a useful methodological middle ground to investigate language processes online in a tightly controlled setup without disrupting the interaction. More broadly, the framework offers a test bed for examining whether established psycholinguistic findings extend to HRI setups. At the same time, it provides HRI researchers with an empirical basis for developing adaptive agents informed by online language-vision interaction theories.}}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, issn = {{0090-6905}}, journal = {{Journal of Psycholinguistic Research}}, number = {{5}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{A Methodological Framework for Studying Online Language–Vision Interplay in Human–Robot Interaction}}}, doi = {{10.1007/s10936-026-10296-z}}, volume = {{55}}, year = {{2026}}, } @inbook{66856, abstract = {{Abstract Goals are central to human actions: In fact, human actions are organized toward goals. Already early in human development, human perception becomes biased to goal-directed actions. A characteristic of social interaction is that goals can be shared among involved agents. This is a great benefit for designing sXAI as it allows explanation goals to be collaboratively negotiated. Even more, depending on the goal, users could be dynamically but minimalistically supported in their autonomous actions. Future sXAI developments can benefit from this chapter by recognizing how essential goals are and that they constitute an intersection of individual actions and social ecologies.}}, author = {{Rohlfing, Katharina J. and Singh, Amit and Groß, André and Wrede, Britta}}, booktitle = {{Social Explainable AI}}, isbn = {{9789819652891}}, publisher = {{Springer Nature Singapore}}, title = {{{Explanation Goals}}}, doi = {{10.1007/978-981-96-5290-7_6}}, year = {{2026}}, } @article{66855, author = {{Wildt, Eugenia and Singh, Amit and Rohlfing, Katharina J.}}, issn = {{0001-6918}}, journal = {{Acta Psychologica}}, publisher = {{Elsevier BV}}, title = {{{Infants' individual sensitivity to saliency shapes early word learning in social interaction}}}, doi = {{10.1016/j.actpsy.2026.106977}}, volume = {{266}}, year = {{2026}}, } @unpublished{59839, abstract = {{In many scientific approaches, especially in those that try to foster explainability of Artificial Intelligences, a narrow conception of explaining prevails. This narrow conception implies that explaining is a one-directional action in which knowledge is transferred from the explainer to an addressee. By studying the amount of agency in metaphors for explaining in scientific texts, we want to find out – or at least to contribute a partial answer to the question – why this narrow conception is so dominant. For our analysis, we use a linguistic conception of agency, transitivity. This concept allows to specify the degree of agency or effectiveness of the action in a verbalised event. It is defined by several component parts. We detail and discuss both the parameters of and global transitivity. Overall, transitivity of explaining metaphors has a rather common pattern across metaphors. Agency is not high and reduced in characteristic aspects: The metaphors imply that the object of explaining is static, i.e., is not changed within the explanation, and that explaining is the activity of one person only. This pattern may account for the narrow conception of explaining. It contrasts strongly with current co-constructive or sociotechnical approaches to explainability.}}, author = {{Scharlau, Ingrid and Rohlfing, Katharina J.}}, publisher = {{Center for Open Science}}, title = {{{Agency in metaphors of explaining: An analysis of scientific texts}}}, year = {{2025}}, } @inproceedings{61432, abstract = {{This study investigated how action histories – unfolding sequences of actions with objects – provide a context for both attentional allocation and linguistic repair strategies. Building on theories of enactive cognition and sensorimotor contingency theory, we experimentally manipulated action sequences (action history) to create either simple or rich “situational models,” and investigated how these models interact with attention and reflect in linguistic processes during human–robot interaction. Participants (N = 30) engaged in a controlled object placement task with a humanoid robot, where the action (manner) information was either provided or omitted. The omission elicited repair behaviors in participants that were in focus of our investigation. For rich models (competing action possibilities) participants demonstrated: a) increased attentional reorientation, reflecting active engagement with the situational model b) preference for restricted repairs, targeting the specific source of trouble in action selection. Conversely, a simple situational model led to more generalized attention patterns and open repair strategies, suggesting weaker constraints on internal processing. These findings highlight how situational structures emerge externally to scaffold internal cognitive processes, with action histories serving as a crucial context for the interface between perception, action, and language. We discuss how to implement such a tight loop in the assistance of a system.}}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, booktitle = {{IEEE International Conference on Development and Learning (ICDL)}}, keywords = {{Attention, Action, Repairs, Task model, HRI, Eyemovement}}, location = {{Prague}}, title = {{{Manners Matter: Action history guides attention and repair choices during interaction}}}, doi = {{10.31234/osf.io/yn2we_v1}}, year = {{2025}}, } @inproceedings{61401, abstract = {{We introduce a method to study online language processes in human--robot interactive setup. In this interaction, language mediated eye movements can be studied as the dialogue unfolds between human and a robot. Traditionally, real-time linguistic processes are studied using visual world paradigms (VWP), where either the comprehension or the production tasks are implemented on screens for controlled investigations. Going beyond these traditional and unidirectional approach, we bring together production--comprehension loop with the help of a humanoid robot to preserve interactivity in an ecologically valid yet controlled setup. We discuss the potential of such setups for designing and evaluating findings from language--vision interplay in psycholinguistics. Our setup shows a potential to depart from traditional screen based experiments, balancing the dynamics of the interaction with control of the human behaviors. }}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, booktitle = {{6th Biannual Conference of the German Society for Cognitive Science, Bochum, Germany}}, location = {{Bochum}}, title = {{{Embedding Psycholinguistics: An Interactive Framework for Studying Language in Action}}}, doi = {{10.17605/OSF.IO/8PR23}}, year = {{2025}}, } @article{60935, abstract = {{Research suggests that presenting an action via multimodal stimulation (verbal and visual) enhances its perception. To highlight this, in most studies, assertive instructions are generally presented before the occurrence of the visual subevent(s). However, verbal instructions need not always be assertive; they can also include negation to contrast the present event with a prior one, thereby facilitating processing—a phenomenon known as contextual facilitation. In our study, we investigated whether using negation to guide an action sequence facilitates action perception, particularly when two consecutive subactions contrast with each other. Stimuli from previous studies on action demonstration were used to create (non)contrastive actions, that is, a ball following noncontrastive and identical (Over–Over or Under–Under) versus contrastive and opposite paths (Over–Under or Under–Over) before terminating at a goal location. In Experiment 1, either an assertive or a negative instruction was provided as verbal guidance before onset of each path. Analyzing data from 35 participants, we found that, whereas assertive instructions facilitate overall action recall, negating the later path for contrastive actions is equally facilitative. Given that action goal is the most salient aspect in event memory due to goal-path bias in attention, a second experiment was conducted to test the effect of multimodal synchrony on goal attention and action memory. Experiment 2 revealed that when instructions overlap with actions, they become more tailored—assertive instructions effectively guide noncontrastive actions, while assertive–negative instruction particularly guides contrastive actions. Both studies suggest that increased attention to the goal leads to coarser perception of midevents, with action-instruction synchrony modulating goal bias in real-time event apprehension to serve distinct purposes for action conceptualization. Whereas presenting instructions before subactions attenuates goal attention, overlapping instructions increase goal attention and reveal the selective roles of assertive and negative instructions in guiding contrastive and noncontrastive actions.}}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, journal = {{Cognitive Science}}, number = {{8}}, publisher = {{Wiley}}, title = {{{Contrastive Verbal Guidance: A Beneficial Context for Attention To Events and Their Memory?}}}, doi = {{10.1111/cogs.70096}}, volume = {{49}}, year = {{2025}}, } @inproceedings{56660, abstract = {{In a successful dialogue in general and a successful explanation in specific, partners need to account for both, the task model (what is relevant for the task) and the partner model (what one can con- tribute). The phenomenon of coupling between task and the partner model becomes especially interesting in the context of Human– Robot Interaction where humans have to deal with unknown ca- pabilities of the robot, which can momentarily be perceived when the robot is unable to contribute to the task. Following research on the path over manner prominence in an action [31–33], a robot ex- plained actions to a human by emphasizing two aspects – the path ("where" component) and the manner ("how" component). On criti- cal trials, the robot occasionally omitted one of these components where participants sought missing information for the path or the manner. Participants’ information-seeking and gaze behaviour were analysed. Analysis confirms the initial predictions for, a) task model (path over manner prominence), i.e., earlier information-seeking for path-missing than manner-missing trials, and b) partner model, i.e., while information-seeking is predominantly tied to the attention on the robot’s face, when robot fails to provide resolution, attention shifts more often towards its torso – a behavior likely to indicate an exploration of the robot’s capabilities. An individual-level anal- ysis further confirms that the intra-individual variation in the task model is partly influenced by the perceived capability of the robot.}}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, booktitle = {{Proceedings of 26th ACM International Conference on Multimodal Interaction (ICMI 2024)}}, keywords = {{Explanation, Scaffolding, Eyetracking, Partner Model, HRI}}, location = {{San Jose, Costa Rica}}, title = {{{Coupling of Task and Partner Model: Investigating the Intra-Individual Variability in Gaze during Human–Robot Explanatory Dialogue}}}, doi = {{10.1145/3686215.3689202}}, year = {{2024}}, } @article{56264, author = {{Buhl, Heike M. and Fisher, Josephine Beryl and Rohlfing, Katharina}}, journal = {{Proceedings of the Annual Meeting of the Cognitive Science Society}}, title = {{{Changes in partner models – Effects of adaptivity in the course of explanations}}}, volume = {{46}}, year = {{2024}}, } @article{58708, abstract = {{Research about explanation processes is gaining relevance because of the increased popularity of artificial systems required to explain their function or outcome. Following an interactive approach, not only explainers, but also explainees contribute to successful interactions. However, little is known about how explainees actively guide explanation processes and how their involvement relates to learning. We explored the occurrence and type of explainees’ questions in 20 adult — adult explanation dialogues about unknown present and absent objects. Crucially, we related the question types to the explainees’ subsequent recall of the unknown object labels. We found that explainees asked different types of questions, especially about the object’s label and facts. Questions about the object’s function were asked more when objects were present. In addition, requests for labelling were linked to better recall. The results contribute to designing explainable AI that aims to provide relevant and adaptive explanations and to further experimental approaches to study explanations.}}, author = {{Fisher, Josephine Beryl and Rohlfing, Katharina J. and Donnellan, Ed and Grimminger, Angela and Gu, Yan and Vigliocco, Gabriella}}, journal = {{Interaction Studies}}, number = {{2}}, pages = {{244--255}}, publisher = {{John Benjamins}}, title = {{{ Explain with, rather than explain to: How explainees shape their own learning}}}, doi = {{doi.org/10.1075/is.23019.fis}}, volume = {{25}}, year = {{2024}}, } @article{48543, abstract = {{Explanation has been identified as an important capability for AI-based systems, but research on systematic strategies for achieving understanding in interaction with such systems is still sparse. Negation is a linguistic strategy that is often used in explanations. It creates a contrast space between the affirmed and the negated item that enriches explaining processes with additional contextual information. While negation in human speech has been shown to lead to higher processing costs and worse task performance in terms of recall or action execution when used in isolation, it can decrease processing costs when used in context. So far, it has not been considered as a guiding strategy for explanations in human-robot interaction. We conducted an empirical study to investigate the use of negation as a guiding strategy in explanatory human-robot dialogue, in which a virtual robot explains tasks and possible actions to a human explainee to solve them in terms of gestures on a touchscreen. Our results show that negation vs. affirmation 1) increases processing costs measured as reaction time and 2) increases several aspects of task performance. While there was no significant effect of negation on the number of initially correctly executed gestures, we found a significantly lower number of attempts—measured as breaks in the finger movement data before the correct gesture was carried out—when being instructed through a negation. We further found that the gestures significantly resembled the presented prototype gesture more following an instruction with a negation as opposed to an affirmation. Also, the participants rated the benefit of contrastive vs. affirmative explanations significantly higher. Repeating the instructions decreased the effects of negation, yielding similar processing costs and task performance measures for negation and affirmation after several iterations. We discuss our results with respect to possible effects of negation on linguistic processing of explanations and limitations of our study.}}, author = {{Groß, A. and Singh, Amit and Banh, Ngoc Chi and Richter, B. and Scharlau, Ingrid and Rohlfing, Katharina J. and Wrede, B.}}, journal = {{Frontiers in Robotics and AI}}, keywords = {{HRI, XAI, negation, understanding, explaining, touch interaction, gesture}}, title = {{{Scaffolding the human partner by contrastive guidance in an explanatory human-robot dialogue}}}, doi = {{10.3389/frobt.2023.1236184}}, volume = {{10}}, year = {{2023}}, } @inproceedings{46067, abstract = {{

The study investigates two different ways of guiding the addressee of an explanation - an explainee, through action demonstration: contrastive and non-contrastive. Their effect was tested on attention to specific action elements (goal) as well as on event memory. In an eye-tracking experiment, participants were shown different motion videos that were either contrastive or non-contrastive with respect to the segments of movement presentation. Given that everyday action demonstration is often multimodal, the stimuli were created with re- spect to their visual and verbal presentation. For visual presentation, a video combined two movements in a contrastive (e.g., Up-motion following a Down-motion) or non-contrastive way (e.g., two Up-motions following each other). For verbal presentation, each video was combined with a sequence of instruction descriptions in the form of negative (i.e., contrastive) or assertive (i.e., non-contrastive) guidance. It was found that a) attention to the event goal increased for this condition in the later time window, and b) participants’ recall of the event was facilitated when a visually contrastive motion was combined with a verbal contrast.

}}, author = {{Singh, Amit and Rohlfing, Katharina J.}}, booktitle = {{Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45)}}, keywords = {{Attention, negation, contrastive guidance, eye-movements, action understanding, event representation}}, location = {{Sydney}}, publisher = {{Cognitive Science Society}}, title = {{{Contrastiveness in the context of action demonstration: an eye-tracking study on its effects on action perception and action recall}}}, year = {{2023}}, } @article{37074, abstract = {{Pointing is one of the first conventional means of communication and infants have various motives for engaging in it such as imperative, declarative, or informative. Little is known about the developmental paths of producing and understanding these different motives. In our longitudinal study (N = 58) during the second year of life, we experimentally elicited infants’ pointing production and comprehension in various settings and under pragmatically valid conditions. We followed two steps in our analyses and assessed the occurrence of canonical index-finger pointing for different motives and the engagement in an ongoing interaction in pursuit of a joint goal revealed by frequency and multimodal utterances. For understanding the developmental paths, we compared two groups: typically developing infants (TD) and infants who have been assessed as having delayed language development (LD). Results showed that the developmental paths differed according to the various motives. When comparing the two groups, for all motives, LD infants produced index-finger pointing 2 months later than TD infants. For the engagement, although the pattern was less consistent across settings, the frequency of pointing was comparable in both groups, but infants with LD used less canonical forms of pointing and made fewer multimodal contributions than TD children.}}, author = {{Rohlfing, Katharina J. and Lüke, Carina and Liszkowski, Ulf and Ritterfeld, Ute and Grimminger, Angela}}, issn = {{1660-4601}}, journal = {{International Journal of Environmental Research and Public Health}}, keywords = {{Health, Toxicology and Mutagenesis, Public Health, Environmental and Occupational Health}}, number = {{9}}, publisher = {{MDPI AG}}, title = {{{Developmental Paths of Pointing for Various Motives in Infants with and without Language Delay}}}, doi = {{10.3390/ijerph19094982}}, volume = {{19}}, year = {{2022}}, } @article{34703, abstract = {{One of the many purposes for which social robots are designed is education, and there have been many attempts to systematize their potential in this field. What these attempts have in common is the recognition that learning can be supported in a variety of ways because a learner can be engaged in different activities that foster learning. Up to now, three roles have been proposed when designing these activities for robots: as a teacher or tutor, a learning peer, or a novice. Current research proposes that deciding in favor of one role over another depends on the content or preferred pedagogical form. However, the design of activities changes not only the content of learning, but also the nature of a human–robot social relationship. This is particularly important in language acquisition, which has been recognized as a social endeavor. The following review aims to specify the differences in human–robot social relationships when children learn language through interacting with a social robot. After proposing categories for comparing these different relationships, we review established and more specific, innovative roles that a robot can play in language-learning scenarios. This follows Mead’s (1946) theoretical approach proposing that social roles are performed in interactive acts. These acts are crucial for learning, because not only can they shape the social environment of learning but also engage the learner to different degrees. We specify the degree of engagement by referring to Chi’s (2009) progression of learning activities that range from active, constructive, toward interactive with the latter fostering deeper learning. Taken together, this approach enables us to compare and evaluate different human–robot social relationships that arise when applying a robot in a particular social role.}}, author = {{Rohlfing, Katharina and Altvater-Mackensen, Nicole and Caruana, Nathan and van den Berghe, Rianne and Bruno, Barbara and Tolksdorf, Nils Frederik and Hanulíková, Adriana}}, issn = {{2296-9144}}, journal = {{Frontiers in Robotics and AI}}, keywords = {{Artificial Intelligence, Computer Science Applications}}, publisher = {{Frontiers Media SA}}, title = {{{Social/dialogical roles of social robots in supporting children’s learning of language and literacy—A review and analysis of innovative roles}}}, doi = {{10.3389/frobt.2022.971749}}, volume = {{9}}, year = {{2022}}, } @inproceedings{30952, abstract = {{In child-robot interaction research, many studies pursue the goal to support children's language development. While research in human-human interaction suggests that changing human partners during children's language learning can reduce their recall performance of the learning content, little is known whether a change in social robots as interaction partners influence children's learning in the same way. In this paper, we present findings from a word learning study, in which we changed the robotic partner for one group of children while the other group interacted with the same robot. Contrary to work with human social partners, we found that children did not retrieve words differently when interacting with different humanoid robots as their social interaction partners.}}, author = {{Tolksdorf, Nils Frederik and Hönemann, Dirk and Viertel, Franziska E. and Rohlfing, Katharina}}, booktitle = {{Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction}}, location = {{Sapporo Hokkaido, Japan}}, pages = {{1069--1074}}, title = {{{Who is that?! Does Changing the Robot as a Learning Companion Impact Preschoolers’Language Learning?}}}, doi = {{10.5555/3523760.3523937}}, year = {{2022}}, } @article{24456, abstract = {{One objective of current research in explainable intelligent systems is to implement social aspects in order to increase the relevance of explanations. In this paper, we argue that a novel conceptual framework is needed to overcome shortcomings of existing AI systems with little attention to processes of interaction and learning. Drawing from research in interaction and development, we first outline the novel conceptual framework that pushes the design of AI systems toward true interactivity with an emphasis on the role of the partner and social relevance. We propose that AI systems will be able to provide a meaningful and relevant explanation only if the process of explaining is extended to active contribution of both partners that brings about dynamics that is modulated by different levels of analysis. Accordingly, our conceptual framework comprises monitoring and scaffolding as key concepts and claims that the process of explaining is not only modulated by the interaction between explainee and explainer but is embedded into a larger social context in which conventionalized and routinized behaviors are established. We discuss our conceptual framework in relation to the established objectives of transparency and autonomy that are raised for the design of explainable AI systems currently.}}, author = {{Rohlfing, Katharina J. and Cimiano, Philipp and Scharlau, Ingrid and Matzner, Tobias and Buhl, Heike M. and Buschmeier, Hendrik and Esposito, Elena and Grimminger, Angela and Hammer, Barbara and Haeb-Umbach, Reinhold and Horwath, Ilona and Hüllermeier, Eyke and Kern, Friederike and Kopp, Stefan and Thommes, Kirsten and Ngonga Ngomo, Axel-Cyrille and Schulte, Carsten and Wachsmuth, Henning and Wagner, Petra and Wrede, Britta}}, issn = {{2379-8920}}, journal = {{IEEE Transactions on Cognitive and Developmental Systems}}, keywords = {{Explainability, process ofexplaining andunderstanding, explainable artificial systems}}, number = {{3}}, pages = {{717--728}}, title = {{{Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems}}}, doi = {{10.1109/tcds.2020.3044366}}, volume = {{13}}, year = {{2021}}, } @article{28696, abstract = {{The aim of the present study is to bring new momentum into research on students’ understanding of academic writing. Drawing on the idea that metaphors give insight into implicit conceptions of abstract entities and processes, we developed a detailed and differentiated set of conceptual metaphors that can be used to study student ideas about writing in research, teaching, and interventions. A large sample of undergraduates produced their everyday understanding of writing in short texts beginning with a self-generated metaphor. Based on theories from cognitive linguistics, the conceptual metaphors in their texts were analyzed in terms of their action quality (transitivity) and spatiality (spatial primitives). The undergraduates’ conceptualizations were very heterogeneous. Most metaphors depart strongly from scientific approaches to academic writing within cognitive psychology and sociocultural theory. Roughly half of the metaphors could be collated to one of four metaphor systems. Depending on the desired degree of abstraction or concreteness, conceptual metaphors or metaphor systems can be employed in further studies to illuminate thinking about writing.}}, author = {{Scharlau, Ingrid and Karsten, Andrea and Rohlfing, Katharina}}, issn = {{2030-1006}}, journal = {{Journal of Writing Research}}, keywords = {{metaphor analysis, academic writing, transitivity, spatial primitives}}, number = {{3}}, pages = {{493--529}}, title = {{{Building, emptying out, or dreaming? Action structures and space in undergraduates’ metaphors of academic writing}}}, doi = {{10.17239/jowr-2021.12.03.01}}, volume = {{12}}, year = {{2021}}, } @article{31680, author = {{Scharlau, Ingrid and Karsten, A. and Rohlfing, Katharina J.}}, issn = {{2030-1006}}, journal = {{Journal of Writing Research}}, keywords = {{Literature and Literary Theory, Linguistics and Language, Language and Linguistics, Education}}, number = {{vol. 12 issue 3}}, pages = {{493--529}}, publisher = {{ARLE (International Association for Research in L1 Education)}}, title = {{{Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing}}}, doi = {{10.17239/jowr-2021.12.03.01}}, volume = {{12}}, year = {{2021}}, } @article{37185, abstract = {{Social robots have emerged as a new digital technology that is increasingly being implemented in the educational landscape. While social robots could be deployed to assist young children with their learning in a variety of different ways, the typical approach in educational practices is to supplement the learning process rather than to replace the human caregiver, e.g., the teacher, parent, educator or therapist. When functioning in the role of an educational assistant, social robots will likely constitute a part of a triadic interaction with the child and the human caregiver. Surprisingly, there is little research that systematically investigates the role of the caregiver by examining the ways in which children involve or check in with them during their interaction with another partner—a phenomenon that is known as social referencing. In the present study, we investigated social referencing in the context of a dyadic child–robot interaction. Over the course of four sessions within our longitudinal language-learning study, we observed how 20 pre-school children aged 4–5 years checked in with their accompanying caregivers who were not actively involved in the language-learning procedure. The children participating in the study were randomly assigned to either an interaction with a social robot or a human partner. Our results revealed that all children across both conditions utilized social referencing behaviors to address their caregiver. However, we found that the children who interacted with the social robot did so significantly more frequently in each of the four sessions than those who interacted with the human partner. Further analyses showed that no significant change in their behavior over the course of the sessions could be observed. Findings are discussed with regard to the caregiver's role during children's interactions with social robots and the implications for future interaction design.}}, author = {{Tolksdorf, Nils F. and Crawshaw, Camilla E. and Rohlfing, Katharina}}, issn = {{2504-284X}}, journal = {{Frontiers in Education}}, keywords = {{Education}}, publisher = {{Frontiers Media SA}}, title = {{{Comparing the Effects of a Different Social Partner (Social Robot vs. Human) on Children's Social Referencing in Interaction}}}, doi = {{10.3389/feduc.2020.569615}}, volume = {{5}}, year = {{2021}}, }