@article{55400, abstract = {{This study contributes to the evolving field of robot learning in interaction with humans, examining the impact of diverse input modalities on learning outcomes. It introduces the concept of "meta-modalities" which encapsulate additional forms of feedback beyond the traditional preference and scalar feedback mechanisms. Unlike prior research that focused on individual meta-modalities, this work evaluates their combined effect on learning outcomes. Through a study with human participants, we explore user preferences for these modalities and their impact on robot learning performance. Our findings reveal that while individual modalities are perceived differently, their combination significantly improves learning behavior and usability. This research not only provides valuable insights into the optimization of human-robot interactive task learning but also opens new avenues for enhancing the interactive freedom and scaffolding capabilities provided to users in such settings.}}, author = {{Beierling, Helen and Beierling, Robin and Vollmer, Anna-Lisa}}, journal = {{Frontiers in Robotics and AI}}, keywords = {{human-robot interaction, human-in-the-loop learning, reinforcement learning, interactive robot learning, multi-modal feedback, learning from demonstration, preference-based learning, scaffolding in robot learning}}, publisher = {{Frontiers }}, title = {{{The power of combined modalities in interactive robot learning}}}, volume = {{12}}, year = {{2025}}, } @inproceedings{56277, abstract = {{What is learner-sensitive feedback to argumentative learner texts when it is to be issued computer- based? Learning stages are difficult to quantify. The paper provides insight into the history of research since the 1980s and a preview of what this automated feedback might look like. These questions are embedded in a research project at the Universities of Paderborn and Hannover, Germany, from which a software (project name ArgSchool) emerges that will provide such feedback.}}, author = {{Kilsbach, Sebastian and Michel, Nadine}}, booktitle = {{Proceedings of the Tenth Conference of the International Society for the Study of Argumentation}}, keywords = {{AI, argumentation mining, discourse history, (automated, learner-sensitive) feedback}}, location = {{Leiden}}, title = {{{Computer-Based Generation of Learner-Sensitive Feedback to Argumentative Learner Texts}}}, year = {{2024}}, } @article{23891, abstract = {{Within a pre-post-design, we scrutinized the effects of normative augmented feedback with positive and negative valence on learning motor accuracy, consistency as well as automaticity by means of a dual-task paradigm. Forty-two healthy physical education students were instructed to produce an arm-movement sequence as precisely as possible with regard to three spatial reversal points within a time limit of 1200 ms. Twenty-eight practiced an elbow-extension-flexion-sequence (690 trials) and 14 participants were tested as a control group without feedback practice. Valence of normative feedback was systematically manipulated by means of reference lines in a visual feedback display. The reference lines indicated performance of a putative peer-group either to be superior (negative valence, Normative-Negative-Group) or inferior (positive valence, Normative-Positive-Group) to participants’ actual performance. As a result, dual-task costs (n-back error) significantly decreased solely in the Normative-Positive-Group, p = .003, η2p = .51, but in no other group. Surprisingly, the mean absolute error for the motor task significantly decreased (i.e., precision increased) only in the Normative-Negative-Group with a large effect size, but in none of the other groups. Motor consistency was not significantly affected by the valence of normative feedback. According to the hypotheses of error-provoked attentional control, positive feedback-valence appears to enhance skill automatization, while – unexpectedly – only negative feedback-valence seems to enhance movement precision, which may be explained by effects of feedback valence on the learners aspiration level.}}, author = {{Zobe, Christina and Krause, Daniel and Blischke, Klaus}}, journal = {{Human Movement Science}}, keywords = {{Augmented feedback Automaticity Dual task Motor learning}}, pages = {{529--540}}, publisher = {{Elsevier}}, title = {{{Dissociative effects of normative feedback on motor automaticity and motor accuracy in learning an arm movement sequence}}}, doi = {{https://doi.org/10.1016/j.humov.2019.06.004}}, volume = {{66}}, year = {{2019}}, } @book{21817, author = {{Goller, Michael}}, isbn = {{978-3-946023-04-3}}, keywords = {{Bahnhofsmission, Survey Feedback, Monitoring}}, pages = {{200}}, publisher = {{IN VIA Verlag}}, title = {{{Monitoring für die Bahnhofsmissionen: Ein datengestütztes Instrument zur Organisationsentwicklung. Projektbeschreibung und Ergebnisdarstellung}}}, year = {{2018}}, } @article{17199, abstract = {{Research of tutoring in parent-infant interaction has shown that tutors - when presenting some action - modify both their verbal and manual performance for the learner (‘motherese’, ‘motionese’). Investigating the sources and effects of the tutors’ action modifications, we suggest an interactional account of ‘motionese’. Using video-data from a semi-experimental study in which parents taught their 8 to 11 month old infants how to nest a set of differently sized cups, we found that the tutors’ action modifications (in particular: high arches) functioned as an orienting device to guide the infant’s visual attention (gaze). Action modification and the recipient’s gaze can be seen to have a reciprocal sequential relationship and to constitute a constant loop of mutual adjustments. Implications are discussed for developmental research and for robotic ‘Social Learning’. We argue that a robot system could use on-line feedback strategies (e.g. gaze) to pro-actively shape a tutor’s action presentation as it emerges.}}, author = {{Pitsch, Karola and Vollmer, Anna-Lisa and Rohlfing, Katharina and Fritsch, Jannik and Wrede, Britta}}, issn = {{1572-0381}}, journal = {{Interaction Studies}}, keywords = {{conversation analysis, interactional coordination, adult-child-interaction, feedback, gaze, quantification, social learning, motionese, tutoring}}, number = {{1}}, pages = {{55--98}}, publisher = {{John Benjamins Publishing Company}}, title = {{{Tutoring in adult-child-interaction: On the loop of the tutor's action modification and the recipient's gaze}}}, doi = {{10.1075/is.15.1.03pit}}, volume = {{15}}, year = {{2014}}, } @article{5716, abstract = {{The tendency of managers to focus on short-term results rather than on sustained company success is of particular importance to retail marketing managers, because marketing activities involve expenditures which may only pay off in the longer term. To address the issue of myopic management, our study shows how the complexity of the service profit chain (SPC) can cause managers to make suboptimal decisions. Hence, our paper departs from past research by recognizing that understanding the temporal interplay between operational investments, employee satisfaction, customer satisfaction, and operating profit is essential to achieving sustained success. In particular, we intend to improve understanding of the functioning of the SPC with respect to time lags and feedback loops. Results of our large-scale longitudinal study set in a multi-outlet retail chain reveal time-lag effects between operational investments and employee satisfaction, as well as between customer satisfaction and performance. These findings, along with evidence of a negative interaction effect of employee satisfaction on the relationship between current performance and future investments, show the substantial risk of mismanaging the SPC. We identify specific situations in which the dynamic approach leads to superior marketing investment decisions, when compared to the conventional static view of the SCP. These insights provide valuable managerial guidance for effectively managing the SPC over time.}}, author = {{Evanschitzky, Heiner and Wangenheim, Florian v and Wünderlich, Nancy}}, journal = {{Journal of Retailing}}, keywords = {{Employee satisfaction, Customer satisfaction, Performance, Service profit chain, Feedback loops, Time lags, Myopic marketing management}}, number = {{3}}, pages = {{356--366}}, publisher = {{Elsevier}}, title = {{{Perils of Managing the Service Profit Chain: The Role of Time Lags and Feedback Loops.}}}, volume = {{88}}, year = {{2012}}, } @inproceedings{17244, abstract = {{Robots interacting with humans need to understand actions and make use of language in social interactions. Research on infant development has shown that language helps the learner to structure visual observations of action. This acoustic information typically in the form of narration overlaps with action sequences and provides infants with a bottom-up guide to find structure within them. This concept has been introduced as acoustic packaging by Hirsh-Pasek and Golinkoff. We developed and integrated a prominence detection module in our acoustic packaging system to detect semantically relevant information linguistically highlighted by the tutor. Evaluation results on speech data from adult-infant interactions show a significant agreement with human raters. Furthermore a first approach based on acoustic packages which uses the prominence detection results to generate acoustic feedback is presented. Index Terms: prominence, multimodal action segmentation, human robot interaction, feedback}}, author = {{Schillingmann, Lars and Wagner, Petra and Munier, Christian and Wrede, Britta and Rohlfing, Katharina}}, booktitle = {{Interspeech 2011 (12th Annual Conference of the International Speech Communication Association)}}, keywords = {{Feedback, Human Robot Interaction, Prominence, Multimodal Action Segmentation}}, pages = {{3105--3108}}, title = {{{Using Prominence Detection to Generate Acoustic Feedback in Tutoring Scenarios}}}, year = {{2011}}, } @inproceedings{17245, author = {{Schillingmann, Lars and Wagner, Petra and Munier, Christian and Wrede, Britta and Rohlfing, Katharina}}, issn = {{1662-5188}}, keywords = {{Prominence, Multimodal Action Segmentation, Feedback, Color Saliency, Human Robot Interaction}}, title = {{{Acoustic Packaging and the Learning of Words}}}, doi = {{10.3389/conf.fncom.2011.52.00020}}, year = {{2011}}, } @inproceedings{17253, author = {{Vollmer, Anna-Lisa and Pitsch, Karola and Lohan, Katrin Solveig and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Development and Learning (ICDL), 2010 IEEE 9th International Conference on Development and Learning}}, keywords = {{tutoring interaction, social interaction, video signal processing, robot systems, paediatrics, neurophysiology, Learning, infant, feedback, biology computing, cognitive capabilities, cognition, children}}, pages = {{76--81}}, title = {{{Developing feedback: How children of different age contribute to a tutoring interaction with adults}}}, year = {{2010}}, } @article{11937, abstract = {{In automatic speech recognition, hidden Markov models (HMMs) are commonly used for speech decoding, while switching linear dynamic models (SLDMs) can be employed for a preceding model-based speech feature enhancement. In this paper, these model types are combined in order to obtain a novel iterative speech feature enhancement and recognition architecture. It is shown that speech feature enhancement with SLDMs can be improved by feeding back information from the HMM to the enhancement stage. Two different feedback structures are derived. In the first, the posteriors of the HMM states are used to control the model probabilities of the SLDMs, while in the second they are employed to directly influence the estimate of the speech feature distribution. Both approaches lead to improvements in recognition accuracy both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature enhancement with SLDMs. It is also shown that a combination with uncertainty decoding further enhances performance.}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{AURORA2 databases, AURORA4 databases, automatic speech recognition, feedback structures, hidden Markov models, HMM, iterative methods, iterative speech feature enhancement, model probabilities, speech decoding, speech enhancement, speech feature distribution, speech recognition, switching linear dynamic models}}, number = {{5}}, pages = {{974--984}}, title = {{{Approaches to Iterative Speech Feature Enhancement and Recognition}}}, doi = {{10.1109/TASL.2009.2014894}}, volume = {{17}}, year = {{2009}}, } @inproceedings{17272, abstract = {{In developmental research, tutoring behavior has been identified as scaffolding infants' learning processes. It has been defined in terms of child-directed speech (Motherese), child-directed motion (Motionese), and contingency. In the field of developmental robotics, research often assumes that in human-robot interaction (HRI), robots are treated similar to infants, because their immature cognitive capabilities benefit from this behavior. However, according to our knowledge, it has barely been studied whether this is true and how exactly humans alter their behavior towards a robotic interaction partner. In this paper, we present results concerning the acceptance of a robotic agent in a social learning scenario obtained via comparison to adults and 8-11 months old infants in equal conditions. These results constitute an important empirical basis for making use of tutoring behavior in social robotics. In our study, we performed a detailed multimodal analysis of HRI in a tutoring situation using the example of a robot simulation equipped with a bottom-up saliency-based attention model. Our results reveal significant differences in hand movement velocity, motion pauses, range of motion, and eye gaze suggesting that for example adults decrease their hand movement velocity in an Adult-Child Interaction (ACI), opposed to an Adult-Adult Interaction (AAI) and this decrease is even higher in the Adult-Robot Interaction (ARI). We also found important differences between ACI and ARI in how the behavior is modified over time as the interaction unfolds. These findings indicate the necessity of integrating top-down feedback structures into a bottom-up system for robots to be fully accepted as interaction partners.}}, author = {{Vollmer, Anna-Lisa and Lohan, Katrin Solveig and Fischer, Kerstin and Nagai, Yukie and Pitsch, Karola and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on Development and Learning}}, keywords = {{robot simulation, hand movement velocity, robotic interaction partner, robotic agent, robot-directed interaction, multimodal analysis, Motionese, Motherese, intelligent tutoring systems, immature cognitive capability, human computer interaction, eye gaze, child-directed speech, child-directed motion, bottom-up system, bottom-up saliency-based attention model, adult-robot interaction, adult-child interaction, adult-adult interaction, human-robot interaction, action learning, social learning scenario, social robotics, software agents, top-down feedback structures, tutoring behavior}}, pages = {{1--6}}, publisher = {{IEEE}}, title = {{{People modify their tutoring behavior in robot-directed interaction for action learning}}}, doi = {{10.1109/DEVLRN.2009.5175516}}, year = {{2009}}, } @inproceedings{17278, abstract = {{This paper investigates the influence of feedback provided by an autonomous robot (BIRON) on users’ discursive behavior. A user study is described during which users show objects to the robot. The results of the experiment indicate, that the robot’s verbal feedback utterances cause the humans to adapt their own way of speaking. The changes in users’ verbal behavior are due to their beliefs about the robots knowledge and abilities. In this paper they are identified and grouped. Moreover, the data implies variations in user behavior regarding gestures. Unlike speech, the robot was not able to give feedback with gestures. Due to the lack of feedback, users did not seem to have a consistent mental representation of the robot’s abilities to recognize gestures. As a result, changes between different gestures are interpreted to be unconscious variations accompanying speech.}}, author = {{Lohse, Manja and Rohlfing, Katharina and Wrede, Britta and Sagerer, Gerhard}}, isbn = {{1050-4729}}, keywords = {{discursive behavior, autonomous robot, BIRON, man-machine systems, robot abilities, robot knowledge, user gestures, robot verbal feedback utterance, speech processing, user verbal behavior, service robots, human-robot interaction, human computer interaction, gesture recognition}}, pages = {{3481--3486}}, title = {{{“Try something else!” — When users change their discursive behavior in human-robot interaction}}}, doi = {{10.1109/ROBOT.2008.4543743}}, year = {{2008}}, } @inproceedings{39411, abstract = {{Rapid prototyping based on 3D models is well accepted for several applications. This article addresses the application of animated virtual 3D prototypes for the development of computer-based systems supporting early collaboration of the system designer with the external customer. Our methodology seamlessly integrates illustration through 3D animation with the main tasks of computer-based real-time systems development, i.e., implementation and verification. The approach is outlined by the example of the design of a flexible manufacturing system.}}, author = {{Flake, Stephan and Geiger, Christian and Müller, Wolfgang and Ruf, Jürgen}}, booktitle = {{Proceedings of IEEE KMN 2001}}, isbn = {{0-7695-1269-0}}, keywords = {{Virtual prototyping, Animation, Collaboration, System analysis and design, Feedback, Application software, Power system modeling, Handicapped aids, Process design, Contracts}}, title = {{{Customer-Oriented Systems Design through Virtual Prototyps}}}, doi = {{10.1109/ENABL.2001.953425}}, year = {{2001}}, } @inproceedings{39487, abstract = {{This article introduces and discusses different innovative means for visual specification and animation of complex concurrent systems. It introduces the completely visual programming language Pictorial Janus (PJ) and its application in the customer-oriented design process. PJ implements a completely visual programming language with inherent animation facilities. The article outlines the transformation of purely visual PJ programs into textual imperative programming languages. The second part of the article investigates animated 3D-presentations and introduces a novel approach to an animated 3D programming language for interactive customer-oriented illustrations.}}, author = {{Geiger, Christian and Lehrenfeld, G. and Müller, Wolfgang}}, booktitle = {{Proceedings of HICSS-32}}, isbn = {{0-7695-0001-3}}, keywords = {{Animation, Computer languages, Object oriented modeling, Collaboration, Process design, Graphical user interfaces, Jacobian matrices, Standardization, Feedback, Software prototyping}}, location = {{Maui, Hawaii}}, title = {{{Visual Specification, Modeling, and Illustrations of Complex Systems}}}, doi = {{10.1109/HICSS.1999.772621}}, year = {{1999}}, }